fix(gpu): refactor crypto params in backend

Bumps [zizmorcore/zizmor-action](https://github.com/zizmorcore/zizmor-action) from 0.5.2 to 0.5.3.
- [Release notes](https://github.com/zizmorcore/zizmor-action/releases)
- [Commits](71321a20a9...b1d7e1fb5d)

---
updated-dependencies:
- dependency-name: zizmorcore/zizmor-action
  dependency-version: 0.5.3
  dependency-type: direct:production
  update-type: version-update:semver-patch
...

Signed-off-by: dependabot[bot] <support@github.com>

.github/workflows/aws_data_tests.yml

@@ -54,7 +54,7 @@ jobs:
 
       - name: Retrieve data from cache
         id: retrieve-data-cache
-        uses: actions/cache/restore@cdf6c1fa76f9f475f3d7449005a359c84ca0f306 #v5.0.3
+        uses: actions/cache/restore@668228422ae6a00e4ad889ee87cd7109ec5666a7 #v5.0.4
         with:
           path: |
             utils/tfhe-backward-compat-data/**/*.cbor
@@ -89,7 +89,7 @@ jobs:
       - name: Store data in cache
         if: steps.retrieve-data-cache.outputs.cache-hit != 'true'
         continue-on-error: true
-        uses: actions/cache/save@cdf6c1fa76f9f475f3d7449005a359c84ca0f306 #v5.0.3
+        uses: actions/cache/save@668228422ae6a00e4ad889ee87cd7109ec5666a7 #v5.0.4
         with:
           path: |
             utils/tfhe-backward-compat-data/**/*.cbor

.github/workflows/aws_tfhe_fast_tests.yml

@@ -16,7 +16,6 @@ env:
   PULL_REQUEST_MD_LINK: ""
   CHECKOUT_TOKEN: ${{ secrets.REPO_CHECKOUT_TOKEN || secrets.GITHUB_TOKEN }}
 
-
 on:
   # Allows you to run this workflow manually from the Actions tab as an alternative.
   workflow_dispatch:
@@ -37,6 +36,7 @@ jobs:
       csprng_test: ${{ env.IS_PULL_REQUEST == 'false' || steps.changed-files.outputs.csprng_any_changed }}
       zk_pok_test: ${{ env.IS_PULL_REQUEST == 'false' || steps.changed-files.outputs.zk_pok_any_changed }}
       versionable_test: ${{ env.IS_PULL_REQUEST == 'false' || steps.changed-files.outputs.versionable_any_changed }}
+      safe_serialize_test: ${{ env.IS_PULL_REQUEST == 'false' || steps.changed-files.outputs.safe_serialize_any_changed }}
       core_crypto_test: ${{ env.IS_PULL_REQUEST == 'false' ||
         steps.changed-files.outputs.core_crypto_any_changed ||
         steps.changed-files.outputs.dependencies_any_changed }}
@@ -64,7 +64,7 @@ jobs:
         uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd
         with:
           fetch-depth: 0
-          persist-credentials: 'false'
+          persist-credentials: "false"
           token: ${{ env.CHECKOUT_TOKEN }}
 
       - name: Check for file changes
@@ -79,6 +79,7 @@ jobs:
               - tfhe-zk-pok/**
               - utils/tfhe-versionable/**
               - utils/tfhe-versionable-derive/**
+              - utils/tfhe-safe-serialize/**
             csprng:
               - tfhe-csprng/**
             zk_pok:
@@ -86,6 +87,8 @@ jobs:
             versionable:
               - utils/tfhe-versionable/**
               - utils/tfhe-versionable-derive/**
+            safe_serialize:
+              - utils/tfhe-safe-serialize/**
             core_crypto:
               - tfhe/src/core_crypto/**
             boolean:
@@ -122,6 +125,7 @@ jobs:
           steps.changed-files.outputs.csprng_any_changed == 'true' ||
           steps.changed-files.outputs.zk_pok_any_changed == 'true' ||
           steps.changed-files.outputs.versionable_any_changed == 'true' ||
+          steps.changed-files.outputs.safe_serialize_any_changed == 'true' ||
           steps.changed-files.outputs.core_crypto_any_changed == 'true' ||
           steps.changed-files.outputs.boolean_any_changed == 'true' ||
           steps.changed-files.outputs.shortint_any_changed == 'true' ||
@@ -145,7 +149,7 @@ jobs:
       - name: Checkout tfhe-rs
         uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd
         with:
-          persist-credentials: 'false'
+          persist-credentials: "false"
           token: ${{ env.CHECKOUT_TOKEN }}
 
       - name: Install latest stable
@@ -170,6 +174,11 @@ jobs:
         run: |
           make test_versionable
 
+      - name: Run tfhe-safe-serialize tests
+        if: needs.should-run.outputs.safe_serialize_test == 'true'
+        run: |
+          make test_safe_serialize
+
       - name: Run core tests
         if: needs.should-run.outputs.core_crypto_test == 'true'
         run: |
@@ -191,7 +200,7 @@ jobs:
 
       - name: Node cache restoration
         id: node-cache
-        uses: actions/cache/restore@cdf6c1fa76f9f475f3d7449005a359c84ca0f306 #v5.0.3
+        uses: actions/cache/restore@668228422ae6a00e4ad889ee87cd7109ec5666a7 #v5.0.4
         with:
           path: |
             ~/.nvm
@@ -204,7 +213,7 @@ jobs:
           make install_node
 
       - name: Node cache save
-        uses: actions/cache/save@cdf6c1fa76f9f475f3d7449005a359c84ca0f306 #v5.0.3
+        uses: actions/cache/save@668228422ae6a00e4ad889ee87cd7109ec5666a7 #v5.0.4
         if: steps.node-cache.outputs.cache-hit != 'true'
         with:
           path: |

.github/workflows/aws_tfhe_noise_checks.yml

@@ -34,7 +34,7 @@ jobs:
       - name: Start remote instance
         id: start-remote-instance
         if: env.SECRETS_AVAILABLE == 'true'
-        uses: zama-ai/slab-github-runner@0a812986560d3f10dc65728b1ccb9ae4c48a8a16 # v1.5.1
+        uses: zama-ai/slab-github-runner@5aee5d157f4a0201e5eaefc9cc648e5f9f5472a5 # v1.6.0
         with:
           mode: start
           github-token: ${{ secrets.SLAB_ACTION_TOKEN }}
@@ -99,7 +99,7 @@ jobs:
       - name: Stop remote instance
         id: stop-instance
         if: env.SECRETS_AVAILABLE == 'true'
-        uses: zama-ai/slab-github-runner@0a812986560d3f10dc65728b1ccb9ae4c48a8a16 # v1.5.1
+        uses: zama-ai/slab-github-runner@5aee5d157f4a0201e5eaefc9cc648e5f9f5472a5 # v1.6.0
         with:
           mode: stop
           github-token: ${{ secrets.SLAB_ACTION_TOKEN }}

.github/workflows/aws_tfhe_wasm_tests.yml

@@ -14,12 +14,11 @@ env:
   PULL_REQUEST_MD_LINK: ""
   CHECKOUT_TOKEN: ${{ secrets.REPO_CHECKOUT_TOKEN || secrets.GITHUB_TOKEN }}
 
-
 on:
   # Allows you to run this workflow manually from the Actions tab as an alternative.
   workflow_dispatch:
   pull_request:
-    types: [ labeled ]
+    types: [labeled]
 
 permissions:
   contents: read
@@ -32,16 +31,16 @@ jobs:
     if: github.event_name == 'workflow_dispatch' || contains(github.event.label.name, 'approved')
     runs-on: ubuntu-latest
     permissions:
-      pull-requests: read  # Needed to check for file change
+      pull-requests: read # Needed to check for file change
     outputs:
       wasm_test: ${{ github.event_name == 'workflow_dispatch' ||
-          steps.changed-files.outputs.wasm_any_changed }}
+        steps.changed-files.outputs.wasm_any_changed }}
     steps:
       - name: Checkout tfhe-rs
         uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd
         with:
           fetch-depth: 0
-          persist-credentials: 'false'
+          persist-credentials: "false"
           token: ${{ env.CHECKOUT_TOKEN }}
 
       - name: Check for file changes
@@ -63,6 +62,7 @@ jobs:
                 - tfhe/js_on_wasm_tests/**
                 - tfhe/web_wasm_parallel_tests/**
                 - utils/tfhe-versionable/**
+                - utils/tfhe-safe-serialize/**
                 - .github/workflows/aws_tfhe_wasm_tests.yml
 
   wasm-tests:
@@ -78,7 +78,7 @@ jobs:
       - name: Checkout tfhe-rs
         uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd
         with:
-          persist-credentials: 'false'
+          persist-credentials: "false"
           token: ${{ env.CHECKOUT_TOKEN }}
 
       - name: Install latest stable
@@ -92,7 +92,7 @@ jobs:
 
       - name: Node cache restoration
         id: node-cache
-        uses: actions/cache/restore@cdf6c1fa76f9f475f3d7449005a359c84ca0f306 #v5.0.3
+        uses: actions/cache/restore@668228422ae6a00e4ad889ee87cd7109ec5666a7 #v5.0.4
         with:
           path: |
             ~/.nvm
@@ -105,7 +105,7 @@ jobs:
           make install_node
 
       - name: Node cache save
-        uses: actions/cache/save@cdf6c1fa76f9f475f3d7449005a359c84ca0f306 #v5.0.3
+        uses: actions/cache/save@668228422ae6a00e4ad889ee87cd7109ec5666a7 #v5.0.4
         if: steps.node-cache.outputs.cache-hit != 'true'
         with:
           path: |

.github/workflows/backward_compat_pr_change_report.yml

@@ -6,6 +6,9 @@ name: backward_compat_pr_change_report
 on:
   pull_request:
 
+env:
+  CHECKOUT_TOKEN: ${{ secrets.REPO_CHECKOUT_TOKEN || secrets.GITHUB_TOKEN }}
+
 permissions:
   contents: read
 
@@ -14,9 +17,35 @@ concurrency:
   cancel-in-progress: true
 
 jobs:
+  should-run:
+    name: backward_compat_pr_change_report/should-run
+    runs-on: ubuntu-latest
+    permissions:
+      pull-requests: read  # Needed to check for file change
+    outputs:
+      backward_report: ${{ steps.changed-files.outputs.backward_any_changed }}
+    steps:
+      - name: Checkout tfhe-rs
+        uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd
+        with:
+          fetch-depth: 0
+          persist-credentials: 'false'
+          token: ${{ env.CHECKOUT_TOKEN }}
+
+      - name: Check for file changes
+        id: changed-files
+        uses: tj-actions/changed-files@22103cc46bda19c2b464ffe86db46df6922fd323 # v47.0.5
+        with:
+          files_yaml: |
+            backward:
+              - utils/tfhe-lints/snapshots/*.json
+
   change-report:
     name: backward_compat_pr_change_report/change-report (bpr)
     runs-on: ubuntu-latest
+    needs: should-run
+    if:
+      needs.should-run.outputs.backward_report == 'true'
     permissions:
       pull-requests: write # To send and modify message in the PR
     steps:
@@ -50,19 +79,11 @@ jobs:
             exit 1
           fi
 
-      - name: Find existing comment
+      - name: Post/refresh backward-compat report
         if: steps.report.outputs.has_report == 'true'
-        id: find-comment
-        uses: peter-evans/find-comment@b30e6a3c0ed37e7c023ccd3f1db5c6c0b0c23aad # v4.0.0
+        uses: marocchino/sticky-pull-request-comment@0ea0beb66eb9baf113663a64ec522f60e49231c0
         with:
-          issue-number: ${{ github.event.pull_request.number }}
-          body-includes: '**Backward-compat snapshot:'
-
-      - name: Comment on PR
-        if: steps.report.outputs.has_report == 'true'
-        uses: peter-evans/create-or-update-comment@e8674b075228eee787fea43ef493e45ece1004c9 # v5.0.0
-        with:
-          comment-id: ${{ steps.find-comment.outputs.comment-id }}
-          issue-number: ${{ github.event.pull_request.number }}
-          body-path: report.md
-          edit-mode: replace
+          header: backward-compat-snapshot
+          hide_and_recreate: true
+          hide_classify: OUTDATED
+          path: report.md

.github/workflows/benchmark_cpu.yml

@@ -19,7 +19,7 @@ on:
           - shortint_oprf
           - hlapi_unsigned
           - hlapi_signed
-          - hlapi_erc20
+          - hlapi_erc7984
           - hlapi_dex
           - hlapi_noise_squash
           - hlapi_kvstore
@@ -93,8 +93,8 @@ jobs:
 
           if inputs_command == "integer_zk":
             files_to_parse.append("pke_zk_crs_sizes.csv")
-          elif inputs_command == "hlapi_erc20":
-            files_to_parse.append("erc20_pbs_count.csv")
+          elif inputs_command == "hlapi_erc7984":
+            files_to_parse.append("erc7984_pbs_count.csv")
           elif inputs_command == "hlapi_dex":
             files_to_parse.extend(
               [

.github/workflows/benchmark_cpu_common.yml

@@ -126,7 +126,7 @@ jobs:
     steps:
       - name: Start instance
         id: start-instance
-        uses: zama-ai/slab-github-runner@0a812986560d3f10dc65728b1ccb9ae4c48a8a16 # v1.5.1
+        uses: zama-ai/slab-github-runner@5aee5d157f4a0201e5eaefc9cc648e5f9f5472a5 # v1.6.0
         with:
           mode: start
           github-token: ${{ secrets.SLAB_ACTION_TOKEN }}
@@ -223,7 +223,7 @@ jobs:
           results_type: ${{ inputs.additional_results_type }}
 
       - name: Upload parsed results artifact
-        uses: actions/upload-artifact@bbbca2ddaa5d8feaa63e36b76fdaad77386f024f
+        uses: actions/upload-artifact@043fb46d1a93c77aae656e7c1c64a875d1fc6a0a
         with:
           name: ${{ github.sha }}_${{ matrix.command }}_${{ matrix.op_flavor }}_${{ matrix.bench_type }}_${{ matrix.params_type }}
           path: ${{ env.RESULTS_FILENAME }}
@@ -261,7 +261,7 @@ jobs:
     steps:
       - name: Stop instance
         id: stop-instance
-        uses: zama-ai/slab-github-runner@0a812986560d3f10dc65728b1ccb9ae4c48a8a16 # v1.5.1
+        uses: zama-ai/slab-github-runner@5aee5d157f4a0201e5eaefc9cc648e5f9f5472a5 # v1.6.0
         with:
           mode: stop
           github-token: ${{ secrets.SLAB_ACTION_TOKEN }}

.github/workflows/benchmark_cpu_weekly.yml

@@ -108,14 +108,14 @@ jobs:
       SLAB_URL: ${{ secrets.SLAB_URL }}
       SLAB_BASE_URL: ${{ secrets.SLAB_BASE_URL }}
 
-  run-benchmarks-hlapi-erc20:
-    name: benchmark_cpu_weekly/run-benchmarks-hlapi-erc20
+  run-benchmarks-hlapi-erc7984:
+    name: benchmark_cpu_weekly/run-benchmarks-hlapi-erc7984
     if: needs.prepare-inputs.outputs.is_weekly_bench_group_2 == 'true'
     needs: prepare-inputs
     uses: ./.github/workflows/benchmark_cpu_common.yml
     with:
-      command: hlapi_erc20
-      additional_file_to_parse: erc20_pbs_count.csv
+      command: hlapi_erc7984
+      additional_file_to_parse: erc7984_pbs_count.csv
     secrets:
       BOT_USERNAME: ${{ secrets.BOT_USERNAME }}
       SLACK_CHANNEL: ${{ secrets.SLACK_CHANNEL }}

.github/workflows/benchmark_ct_key_sizes.yml

@@ -33,7 +33,7 @@ jobs:
     steps:
       - name: Start instance
         id: start-instance
-        uses: zama-ai/slab-github-runner@0a812986560d3f10dc65728b1ccb9ae4c48a8a16 # v1.5.1
+        uses: zama-ai/slab-github-runner@5aee5d157f4a0201e5eaefc9cc648e5f9f5472a5 # v1.6.0
         with:
           mode: start
           github-token: ${{ secrets.SLAB_ACTION_TOKEN }}
@@ -99,7 +99,7 @@ jobs:
           --append-results
 
       - name: Upload parsed results artifact
-        uses: actions/upload-artifact@bbbca2ddaa5d8feaa63e36b76fdaad77386f024f
+        uses: actions/upload-artifact@043fb46d1a93c77aae656e7c1c64a875d1fc6a0a
         with:
           name: ${{ github.sha }}_ct_key_sizes
           path: ${{ env.RESULTS_FILENAME }}
@@ -137,7 +137,7 @@ jobs:
     steps:
       - name: Stop instance
         id: stop-instance
-        uses: zama-ai/slab-github-runner@0a812986560d3f10dc65728b1ccb9ae4c48a8a16 # v1.5.1
+        uses: zama-ai/slab-github-runner@5aee5d157f4a0201e5eaefc9cc648e5f9f5472a5 # v1.6.0
         with:
           mode: stop
           github-token: ${{ secrets.SLAB_ACTION_TOKEN }}

.github/workflows/benchmark_documentation.yml

@@ -17,6 +17,10 @@ on:
         description: "Run GPU core-crypto benchmarks"
         type: boolean
         default: true
+      run-gpu-zk-benchmarks:
+        description: "Run GPU ZK benchmarks"
+        type: boolean
+        default: true
       run-hpu-benchmarks:
         description: "Run HPU benchmarks"
         type: boolean
@@ -36,7 +40,7 @@ jobs:
     uses: ./.github/workflows/benchmark_cpu_common.yml
     if: inputs.run-cpu-benchmarks
     with:
-      command: integer,hlapi_erc20
+      command: integer,hlapi_erc7984
       op_flavor: fast_default
       bench_type: both
       precisions_set: documentation
@@ -91,7 +95,7 @@ jobs:
     with:
       profile: multi-h100-sxm5
       hardware_name: n3-H100-SXM5x8
-      command: integer_multi_bit,hlapi_erc20
+      command: integer_multi_bit,hlapi_erc7984
       op_flavor: fast_default
       bench_type: both
       precisions_set: documentation
@@ -110,7 +114,7 @@ jobs:
     uses: ./.github/workflows/benchmark_hpu_common.yml
     if: inputs.run-hpu-benchmarks
     with:
-      command: integer,hlapi_erc20
+      command: integer,hlapi_erc7984
       op_flavor: default
       bench_type: both
       precisions_set: documentation
@@ -165,21 +169,42 @@ jobs:
       SLAB_URL: ${{ secrets.SLAB_URL }}
       SLAB_BASE_URL: ${{ secrets.SLAB_BASE_URL }}
 
+  run-benchmarks-gpu-zk-server:
+    name: benchmark_documentation/run-benchmarks-gpu-zk-server
+    uses: ./.github/workflows/benchmark_gpu_common.yml
+    if: inputs.run-gpu-zk-benchmarks
+    with:
+      profile: multi-h100-sxm5
+      hardware_name: n3-H100-SXM5x8
+      command: integer_zk
+      op_flavor: default
+      bench_type: both
+    secrets:
+      BOT_USERNAME: ${{ secrets.BOT_USERNAME }}
+      SLACK_CHANNEL: ${{ secrets.SLACK_CHANNEL }}
+      SLACK_WEBHOOK: ${{ secrets.SLACK_WEBHOOK }}
+      REPO_CHECKOUT_TOKEN: ${{ secrets.REPO_CHECKOUT_TOKEN }}
+      JOB_SECRET: ${{ secrets.JOB_SECRET }}
+      SLAB_ACTION_TOKEN: ${{ secrets.SLAB_ACTION_TOKEN }}
+      SLAB_URL: ${{ secrets.SLAB_URL }}
+      SLAB_BASE_URL: ${{ secrets.SLAB_BASE_URL }}
+
   generate-svgs-with-benchmarks-run:
     name: benchmark-documentation/generate-svgs-with-benchmarks-run
     if: ${{ always() &&
-      (inputs.run-cpu-benchmarks || inputs.run-gpu-integer-benchmarks || inputs.run-gpu-core-crypto-benchmarks ||inputs.run-hpu-benchmarks) &&
+      (inputs.run-cpu-benchmarks || inputs.run-gpu-integer-benchmarks || inputs.run-gpu-core-crypto-benchmarks || inputs.run-gpu-zk-benchmarks || inputs.run-hpu-benchmarks) &&
       inputs.generate-svgs }}
     needs: [
       run-benchmarks-cpu-integer, run-benchmarks-gpu-integer, run-benchmarks-hpu-integer,
       run-benchmarks-cpu-zk-server, run-benchmarks-cpu-zk-client,
-      run-benchmarks-cpu-core-crypto, run-benchmarks-gpu-core-crypto
+      run-benchmarks-cpu-core-crypto, run-benchmarks-gpu-core-crypto,
+      run-benchmarks-gpu-zk-server
     ]
     uses: ./.github/workflows/generate_svgs.yml
     with:
       time_span_days: 5
       generate-cpu-svgs: ${{ inputs.run-cpu-benchmarks }}
-      generate-gpu-svgs: ${{ inputs.run-gpu-integer-benchmarks || inputs.run-gpu-core-crypto-benchmarks }}
+      generate-gpu-svgs: ${{ inputs.run-gpu-integer-benchmarks || inputs.run-gpu-core-crypto-benchmarks || inputs.run-gpu-zk-benchmarks }}
       generate-hpu-svgs: ${{ inputs.run-hpu-benchmarks }}
     secrets:
       DATA_EXTRACTOR_DATABASE_USER: ${{ secrets.DATA_EXTRACTOR_DATABASE_USER }}
@@ -188,7 +213,7 @@ jobs:
 
   generate-svgs-without-benchmarks-run:
     name: benchmark-documentation/generate-svgs-without-benchmarks-run
-    if: ${{ !(inputs.run-cpu-benchmarks || inputs.run-gpu-integer-benchmarks || inputs.run-gpu-core-crypto-benchmarks || inputs.run-hpu-benchmarks) &&
+    if: ${{ !(inputs.run-cpu-benchmarks || inputs.run-gpu-integer-benchmarks || inputs.run-gpu-core-crypto-benchmarks || inputs.run-gpu-zk-benchmarks || inputs.run-hpu-benchmarks) &&
       inputs.generate-svgs }}
     uses: ./.github/workflows/generate_svgs.yml
     with:

.github/workflows/benchmark_gpu.yml

@@ -37,7 +37,7 @@ on:
           - integer_zk_experimental
           - integer_aes
           - integer_aes256
-          - hlapi_erc20
+          - hlapi_erc7984
           - hlapi_dex
           - hlapi_noise_squash
       op_flavor:
@@ -123,8 +123,8 @@ jobs:
 
           if inputs_command == "integer_zk":
             files_to_parse.append("pke_zk_crs_sizes.csv")
-          elif inputs_command == "hlapi_erc20":
-            files_to_parse.append("erc20_pbs_count.csv")
+          elif inputs_command == "hlapi_erc7984":
+            files_to_parse.append("erc7984_pbs_count.csv")
           elif inputs_command == "hlapi_dex":
             files_to_parse.extend(
               [

.github/workflows/benchmark_gpu_4090.yml

@@ -89,7 +89,7 @@ jobs:
           REF_NAME: ${{ github.ref_name }}
 
       - name: Upload parsed results artifact
-        uses: actions/upload-artifact@bbbca2ddaa5d8feaa63e36b76fdaad77386f024f
+        uses: actions/upload-artifact@043fb46d1a93c77aae656e7c1c64a875d1fc6a0a
         with:
           name: ${{ github.sha }}_integer_multi_bit_gpu_default
           path: ${{ env.RESULTS_FILENAME }}
@@ -173,7 +173,7 @@ jobs:
           REF_NAME: ${{ github.ref_name }}
 
       - name: Upload parsed results artifact
-        uses: actions/upload-artifact@bbbca2ddaa5d8feaa63e36b76fdaad77386f024f
+        uses: actions/upload-artifact@043fb46d1a93c77aae656e7c1c64a875d1fc6a0a
         with:
           name: ${{ github.sha }}_core_crypto
           path: ${{ env.RESULTS_FILENAME }}

.github/workflows/benchmark_gpu_common.yml

@@ -126,17 +126,11 @@ jobs:
     needs: prepare-matrix
     runs-on: ubuntu-latest
     outputs:
-      # Use permanent remote instance label first as on-demand remote instance label output is set before the end of start-remote-instance step.
-      # If the latter fails due to a failed GitHub action runner set up, we have to fallback on the permanent instance.
-      # Since the on-demand remote label is set before failure, we have to do the logical OR in this order,
-      # otherwise we'll try to run the next job on a non-existing on-demand instance.
-      runner-name: ${{ steps.use-permanent-instance.outputs.runner_group || steps.start-remote-instance.outputs.label }}
-      remote-instance-outcome: ${{ steps.start-remote-instance.outcome }}
+      runner-name: ${{ steps.start-instance.outputs.label }}
     steps:
-      - name: Start remote instance
-        id: start-remote-instance
-        continue-on-error: true
-        uses: zama-ai/slab-github-runner@0a812986560d3f10dc65728b1ccb9ae4c48a8a16 # v1.5.1
+      - name: Start instance
+        id: start-instance
+        uses: zama-ai/slab-github-runner@5aee5d157f4a0201e5eaefc9cc648e5f9f5472a5 # v1.6.0
         with:
           mode: start
           github-token: ${{ secrets.SLAB_ACTION_TOKEN }}
@@ -145,25 +139,6 @@ jobs:
           backend: ${{ inputs.backend }}
           profile: ${{ inputs.profile }}
 
-      - name: Acknowledge remote instance failure
-        if: steps.start-remote-instance.outcome == 'failure' &&
-          inputs.profile != 'single-h100'
-        run: |
-          echo "Remote instance instance has failed to start (profile provided: '${INPUTS_PROFILE}')"
-          echo "Permanent instance instance cannot be used as a substitute (profile needed: 'single-h100')"
-          exit 1
-        env:
-          INPUTS_PROFILE: ${{ inputs.profile }}
-
-      # This will allow to fallback on permanent instances running on Hyperstack.
-      - name: Use permanent remote instance
-        id: use-permanent-instance
-        if: env.SECRETS_AVAILABLE == 'true' &&
-          steps.start-remote-instance.outcome == 'failure' &&
-          inputs.profile == 'single-h100'
-        run: |
-          echo "runner_group=h100x1" >> "$GITHUB_OUTPUT"
-
   # Install dependencies only once since cuda-benchmarks uses a matrix strategy, thus running multiple times.
   install-dependencies:
     name: benchmark_gpu_common/install-dependencies
@@ -184,7 +159,6 @@ jobs:
           token: ${{ secrets.REPO_CHECKOUT_TOKEN }}
 
       - name: Setup Hyperstack dependencies
-        if: needs.setup-instance.outputs.remote-instance-outcome == 'success'
         uses: ./.github/actions/gpu_setup
         with:
           cuda-version: ${{ matrix.cuda }}
@@ -296,7 +270,7 @@ jobs:
           filenames: ${{ inputs.additional_file_to_parse }}
 
       - name: Upload parsed results artifact
-        uses: actions/upload-artifact@bbbca2ddaa5d8feaa63e36b76fdaad77386f024f
+        uses: actions/upload-artifact@043fb46d1a93c77aae656e7c1c64a875d1fc6a0a
         with:
           name: ${{ github.sha }}_${{ matrix.command }}_${{ matrix.op_flavor }}_${{ inputs.profile }}_${{ matrix.bench_type }}_${{ matrix.params_type }}
           path: ${{ env.RESULTS_FILENAME }}
@@ -333,13 +307,13 @@ jobs:
 
   teardown-instance:
     name: benchmark_gpu_common/teardown-instance
-    if: ${{ always() && needs.setup-instance.outputs.remote-instance-outcome == 'success' }}
+    if: ${{ always() && needs.setup-instance.result == 'success' }}
     needs: [ setup-instance, cuda-benchmarks, slack-notify ]
     runs-on: ubuntu-latest
     steps:
       - name: Stop instance
         id: stop-instance
-        uses: zama-ai/slab-github-runner@0a812986560d3f10dc65728b1ccb9ae4c48a8a16 # v1.5.1
+        uses: zama-ai/slab-github-runner@5aee5d157f4a0201e5eaefc9cc648e5f9f5472a5 # v1.6.0
         with:
           mode: stop
           github-token: ${{ secrets.SLAB_ACTION_TOKEN }}

.github/workflows/benchmark_gpu_coprocessor.yml

@@ -42,7 +42,7 @@ env:
   OPTIMIZATION_TARGET: "throughput"
   BATCH_SIZE: "5000"
   SCHEDULING_POLICY: "MAX_PARALLELISM"
-  BENCHMARKS: "erc20"
+  BENCHMARKS: "erc7984"
   BRANCH_NAME: ${{ github.ref_name }}
   COMMIT_SHA: ${{ github.sha }}
   SLAB_SECRET: ${{ secrets.JOB_SECRET }}
@@ -94,7 +94,7 @@ jobs:
     steps:
       - name: Start remote instance
         id: start-remote-instance
-        uses: zama-ai/slab-github-runner@0a812986560d3f10dc65728b1ccb9ae4c48a8a16 # v1.5.1
+        uses: zama-ai/slab-github-runner@5aee5d157f4a0201e5eaefc9cc648e5f9f5472a5 # v1.6.0
         with:
           mode: start
           github-token: ${{ secrets.SLAB_ACTION_TOKEN }}
@@ -204,7 +204,7 @@ jobs:
         uses: foundry-rs/foundry-toolchain@8789b3e21e6c11b2697f5eb56eddae542f746c10
 
       - name: Cache cargo
-        uses: actions/cache@cdf6c1fa76f9f475f3d7449005a359c84ca0f306 # v5.0.3
+        uses: actions/cache@668228422ae6a00e4ad889ee87cd7109ec5666a7 # v5.0.4
         with:
           path: |
             ~/.cargo/registry
@@ -214,14 +214,14 @@ jobs:
           restore-keys: ${{ runner.os }}-cargo-
 
       - name: Login to GitHub Container Registry
-        uses: docker/login-action@b45d80f862d83dbcd57f89517bcf500b2ab88fb2 # v4.0.0
+        uses: docker/login-action@4907a6ddec9925e35a0a9e82d7399ccc52663121 # v4.1.0
         with:
           registry: ghcr.io
           username: ${{ github.actor }}
           password: ${{ secrets.GITHUB_TOKEN }}
 
       - name: Login to Chainguard Registry
-        uses: docker/login-action@b45d80f862d83dbcd57f89517bcf500b2ab88fb2 # v4.0.0
+        uses: docker/login-action@4907a6ddec9925e35a0a9e82d7399ccc52663121 # v4.1.0
         with:
           registry: cgr.dev
           username: ${{ secrets.CGR_USERNAME }}
@@ -232,7 +232,7 @@ jobs:
         working-directory: fhevm/coprocessor/fhevm-engine/tfhe-worker
 
       - name: Use Node.js
-        uses: actions/setup-node@53b83947a5a98c8d113130e565377fae1a50d02f # v6.3.0
+        uses: actions/setup-node@48b55a011bda9f5d6aeb4c2d9c7362e8dae4041e # v6.4.0
         with:
           node-version: 20.x
 
@@ -248,13 +248,13 @@ jobs:
           npm install && npm run deploy:emptyProxies && npx hardhat compile
         working-directory: fhevm/
 
-      - name: Profile erc20 no-cmux benchmark on GPU
+      - name: Profile erc7984 no-cmux benchmark on GPU
         run: |
           BENCHMARK_BATCH_SIZE="${BATCH_SIZE}" \
           FHEVM_DF_SCHEDULE="${SCHEDULING_POLICY}" \
           BENCHMARK_TYPE="THROUGHPUT_200" \
           OPTIMIZATION_TARGET="${OPTIMIZATION_TARGET}" \
-          make -e "profile_erc20_gpu"
+          make -e "profile_erc7984_gpu"
         working-directory: fhevm/coprocessor/fhevm-engine/tfhe-worker
 
       - name: Get nsys profile name
@@ -271,7 +271,7 @@ jobs:
       - name: Upload profile artifact
         env:
           REPORT_NAME: ${{ steps.nsys_profile_name.outputs.profile }}
-        uses: actions/upload-artifact@bbbca2ddaa5d8feaa63e36b76fdaad77386f024f
+        uses: actions/upload-artifact@043fb46d1a93c77aae656e7c1c64a875d1fc6a0a
         with:
           name: ${{ env.REPORT_NAME }}
           path: fhevm/coprocessor/fhevm-engine/tfhe-worker/${{ env.REPORT_NAME }}
@@ -302,7 +302,7 @@ jobs:
         working-directory: fhevm/
 
       - name: Upload parsed results artifact
-        uses: actions/upload-artifact@bbbca2ddaa5d8feaa63e36b76fdaad77386f024f
+        uses: actions/upload-artifact@043fb46d1a93c77aae656e7c1c64a875d1fc6a0a
         with:
           name: ${COMMIT_SHA}_${BENCHMARKS}_${{ needs.parse-inputs.outputs.profile }}
           path: fhevm/$${{ env.RESULTS_FILENAME }}
@@ -333,7 +333,7 @@ jobs:
     steps:
       - name: Stop remote instance
         id: stop-instance
-        uses: zama-ai/slab-github-runner@0a812986560d3f10dc65728b1ccb9ae4c48a8a16 # v1.5.1
+        uses: zama-ai/slab-github-runner@5aee5d157f4a0201e5eaefc9cc648e5f9f5472a5 # v1.6.0
         with:
           mode: stop
           github-token: ${{ secrets.SLAB_ACTION_TOKEN }}

.github/workflows/benchmark_hpu.yml

@@ -14,7 +14,7 @@ on:
           - integer
           - hlapi_unsigned
           - hlapi_signed
-          - hlapi_erc20
+          - hlapi_erc7984
       op_flavor:
         description: "Operations set to run"
         type: choice

.github/workflows/benchmark_hpu_common.yml

@@ -185,7 +185,7 @@ jobs:
           BENCH_TYPE: ${{ matrix.bench_type }}
 
       - name: Upload parsed results artifact
-        uses: actions/upload-artifact@bbbca2ddaa5d8feaa63e36b76fdaad77386f024f
+        uses: actions/upload-artifact@043fb46d1a93c77aae656e7c1c64a875d1fc6a0a
         with:
           name: ${{ github.sha }}_${{ matrix.bench_type }}_${{ matrix.command }}_benchmarks
           path: ${{ env.RESULTS_FILENAME }}

.github/workflows/benchmark_perf_regression.yml

@@ -143,7 +143,7 @@ jobs:
     steps:
       - name: Start instance
         id: start-instance
-        uses: zama-ai/slab-github-runner@0a812986560d3f10dc65728b1ccb9ae4c48a8a16 # v1.5.1
+        uses: zama-ai/slab-github-runner@5aee5d157f4a0201e5eaefc9cc648e5f9f5472a5 # v1.6.0
         with:
           mode: start
           github-token: ${{ secrets.SLAB_ACTION_TOKEN }}
@@ -280,7 +280,7 @@ jobs:
           BENCH_TYPE: ${{ env.__TFHE_RS_BENCH_TYPE }}
 
       - name: Upload parsed results artifact
-        uses: actions/upload-artifact@bbbca2ddaa5d8feaa63e36b76fdaad77386f024f
+        uses: actions/upload-artifact@043fb46d1a93c77aae656e7c1c64a875d1fc6a0a
         with:
           name: ${{ github.sha }}_regression_${{ env.RESULTS_FILE_SHA }} # RESULT_FILE_SHA is needed to avoid collision between matrix.command runs
           path: ${{ env.RESULTS_FILENAME }}
@@ -387,7 +387,7 @@ jobs:
     steps:
       - name: Stop instance
         id: stop-instance
-        uses: zama-ai/slab-github-runner@0a812986560d3f10dc65728b1ccb9ae4c48a8a16 # v1.5.1
+        uses: zama-ai/slab-github-runner@5aee5d157f4a0201e5eaefc9cc648e5f9f5472a5 # v1.6.0
         with:
           mode: stop
           github-token: ${{ secrets.SLAB_ACTION_TOKEN }}

.github/workflows/benchmark_tfhe_fft.yml

@@ -40,7 +40,7 @@ jobs:
     steps:
       - name: Start instance
         id: start-instance
-        uses: zama-ai/slab-github-runner@0a812986560d3f10dc65728b1ccb9ae4c48a8a16 # v1.5.1
+        uses: zama-ai/slab-github-runner@5aee5d157f4a0201e5eaefc9cc648e5f9f5472a5 # v1.6.0
         with:
           mode: start
           github-token: ${{ secrets.SLAB_ACTION_TOKEN }}
@@ -99,7 +99,7 @@ jobs:
           REF_NAME: ${{ github.ref_name }}
 
       - name: Upload parsed results artifact
-        uses: actions/upload-artifact@bbbca2ddaa5d8feaa63e36b76fdaad77386f024f
+        uses: actions/upload-artifact@043fb46d1a93c77aae656e7c1c64a875d1fc6a0a
         with:
           name: ${{ github.sha }}_fft
           path: ${{ env.RESULTS_FILENAME }}
@@ -137,7 +137,7 @@ jobs:
     steps:
       - name: Stop instance
         id: stop-instance
-        uses: zama-ai/slab-github-runner@0a812986560d3f10dc65728b1ccb9ae4c48a8a16 # v1.5.1
+        uses: zama-ai/slab-github-runner@5aee5d157f4a0201e5eaefc9cc648e5f9f5472a5 # v1.6.0
         with:
           mode: stop
           github-token: ${{ secrets.SLAB_ACTION_TOKEN }}

.github/workflows/benchmark_tfhe_ntt.yml

@@ -40,7 +40,7 @@ jobs:
     steps:
       - name: Start instance
         id: start-instance
-        uses: zama-ai/slab-github-runner@0a812986560d3f10dc65728b1ccb9ae4c48a8a16 # v1.5.1
+        uses: zama-ai/slab-github-runner@5aee5d157f4a0201e5eaefc9cc648e5f9f5472a5 # v1.6.0
         with:
           mode: start
           github-token: ${{ secrets.SLAB_ACTION_TOKEN }}
@@ -99,7 +99,7 @@ jobs:
           REF_NAME: ${{ github.ref_name }}
 
       - name: Upload parsed results artifact
-        uses: actions/upload-artifact@bbbca2ddaa5d8feaa63e36b76fdaad77386f024f
+        uses: actions/upload-artifact@043fb46d1a93c77aae656e7c1c64a875d1fc6a0a
         with:
           name: ${{ github.sha }}_ntt
           path: ${{ env.RESULTS_FILENAME }}
@@ -137,7 +137,7 @@ jobs:
     steps:
       - name: Stop instance
         id: stop-instance
-        uses: zama-ai/slab-github-runner@0a812986560d3f10dc65728b1ccb9ae4c48a8a16 # v1.5.1
+        uses: zama-ai/slab-github-runner@5aee5d157f4a0201e5eaefc9cc648e5f9f5472a5 # v1.6.0
         with:
           mode: stop
           github-token: ${{ secrets.SLAB_ACTION_TOKEN }}

.github/workflows/benchmark_wasm_client_common.yml

@@ -77,7 +77,7 @@ jobs:
     steps:
       - name: Start instance
         id: start-instance
-        uses: zama-ai/slab-github-runner@0a812986560d3f10dc65728b1ccb9ae4c48a8a16 # v1.5.1
+        uses: zama-ai/slab-github-runner@5aee5d157f4a0201e5eaefc9cc648e5f9f5472a5 # v1.6.0
         with:
           mode: start
           github-token: ${{ secrets.SLAB_ACTION_TOKEN }}
@@ -124,7 +124,7 @@ jobs:
 
       - name: Node cache restoration
         id: node-cache
-        uses: actions/cache/restore@cdf6c1fa76f9f475f3d7449005a359c84ca0f306 #v5.0.3
+        uses: actions/cache/restore@668228422ae6a00e4ad889ee87cd7109ec5666a7 #v5.0.4
         with:
           path: |
             ~/.nvm
@@ -137,7 +137,7 @@ jobs:
           make install_node
 
       - name: Node cache save
-        uses: actions/cache/save@cdf6c1fa76f9f475f3d7449005a359c84ca0f306 #v5.0.3
+        uses: actions/cache/save@668228422ae6a00e4ad889ee87cd7109ec5666a7 #v5.0.4
         if: steps.node-cache.outputs.cache-hit != 'true'
         with:
           path: |
@@ -180,7 +180,7 @@ jobs:
           REF_NAME: ${{ github.ref_name }}
 
       - name: Upload parsed results artifact
-        uses: actions/upload-artifact@bbbca2ddaa5d8feaa63e36b76fdaad77386f024f
+        uses: actions/upload-artifact@043fb46d1a93c77aae656e7c1c64a875d1fc6a0a
         with:
           name: ${{ github.sha }}_wasm_${{ matrix.browser }}
           path: ${{ env.RESULTS_FILENAME }}
@@ -218,7 +218,7 @@ jobs:
     steps:
       - name: Stop instance
         id: stop-instance
-        uses: zama-ai/slab-github-runner@0a812986560d3f10dc65728b1ccb9ae4c48a8a16 # v1.5.1
+        uses: zama-ai/slab-github-runner@5aee5d157f4a0201e5eaefc9cc648e5f9f5472a5 # v1.6.0
         with:
           mode: stop
           github-token: ${{ secrets.SLAB_ACTION_TOKEN }}

.github/workflows/cargo_build_common.yml

@@ -138,7 +138,7 @@ jobs:
       - name: Node cache restoration
         if: inputs.run-pcc-cpu-batch == 'pcc_batch_2'
         id: node-cache
-        uses: actions/cache/restore@cdf6c1fa76f9f475f3d7449005a359c84ca0f306 #v5.0.3
+        uses: actions/cache/restore@668228422ae6a00e4ad889ee87cd7109ec5666a7 #v5.0.4
         with:
           path: |
             ~/.nvm
@@ -151,7 +151,7 @@ jobs:
           make install_node
 
       - name: Node cache save
-        uses: actions/cache/save@cdf6c1fa76f9f475f3d7449005a359c84ca0f306 #v5.0.3
+        uses: actions/cache/save@668228422ae6a00e4ad889ee87cd7109ec5666a7 #v5.0.4
         if: inputs.run-pcc-cpu-batch == 'pcc_batch_2' && steps.node-cache.outputs.cache-hit != 'true'
         with:
           path: |

.github/workflows/cargo_test_ntt.yml

@@ -63,7 +63,7 @@ jobs:
       - name: Start remote instance
         id: start-remote-instance
         if: env.SECRETS_AVAILABLE == 'true'
-        uses: zama-ai/slab-github-runner@0a812986560d3f10dc65728b1ccb9ae4c48a8a16 # v1.5.1
+        uses: zama-ai/slab-github-runner@5aee5d157f4a0201e5eaefc9cc648e5f9f5472a5 # v1.6.0
         with:
           mode: start
           github-token: ${{ secrets.SLAB_ACTION_TOKEN }}
@@ -146,7 +146,7 @@ jobs:
       - name: Stop remote instance
         id: stop-instance
         if: env.SECRETS_AVAILABLE == 'true'
-        uses: zama-ai/slab-github-runner@0a812986560d3f10dc65728b1ccb9ae4c48a8a16 # v1.5.1
+        uses: zama-ai/slab-github-runner@5aee5d157f4a0201e5eaefc9cc648e5f9f5472a5 # v1.6.0
         with:
           mode: stop
           github-token: ${{ secrets.SLAB_ACTION_TOKEN }}

.github/workflows/ci_lint.yml

@@ -43,14 +43,14 @@ jobs:
           echo "version=$(make zizmor_version)" >> "${GITHUB_OUTPUT}"
 
       - name: Check workflows security
-        uses: zizmorcore/zizmor-action@71321a20a9ded102f6e9ce5718a2fcec2c4f70d8 # v0.5.2
+        uses: zizmorcore/zizmor-action@b1d7e1fb5de872772f31590499237e7cce841e8e # v0.5.3
         with:
           advanced-security: 'false' # Print results directly in logs
           persona: pedantic
           version: ${{ steps.get_zizmor.outputs.version }}
 
       - name: Ensure SHA pinned actions
-        uses: zgosalvez/github-actions-ensure-sha-pinned-actions@70c4af2ed5282c51ba40566d026d6647852ffa3e # v5.0.1
+        uses: zgosalvez/github-actions-ensure-sha-pinned-actions@ca46236c6ce584ae24bc6283ba8dcf4b3ec8a066 # v5.0.4
         with:
           allowlist: |
             slsa-framework/slsa-github-generator

.github/workflows/code_coverage.yml

@@ -74,7 +74,7 @@ jobs:
           make test_shortint_cov
 
       - name: Upload tfhe coverage to Codecov
-        uses: codecov/codecov-action@671740ac38dd9b0130fbe1cec585b89eea48d3de
+        uses: codecov/codecov-action@57e3a136b779b570ffcdbf80b3bdc90e7fab3de2
         if: steps.changed-files.outputs.tfhe_any_changed == 'true'
         with:
           token: ${{ secrets.CODECOV_TOKEN }}
@@ -88,7 +88,7 @@ jobs:
           make test_integer_cov
 
       - name: Upload tfhe coverage to Codecov
-        uses: codecov/codecov-action@671740ac38dd9b0130fbe1cec585b89eea48d3de
+        uses: codecov/codecov-action@57e3a136b779b570ffcdbf80b3bdc90e7fab3de2
         if: steps.changed-files.outputs.tfhe_any_changed == 'true'
         with:
           token: ${{ secrets.CODECOV_TOKEN }}

.github/workflows/generate_svg_common.yml

@@ -87,7 +87,7 @@ jobs:
 
       - name: Upload tables
         if: inputs.backend_comparison == false
-        uses: actions/upload-artifact@bbbca2ddaa5d8feaa63e36b76fdaad77386f024f
+        uses: actions/upload-artifact@043fb46d1a93c77aae656e7c1c64a875d1fc6a0a
         with:
           name: ${{ github.sha }}_${{ inputs.backend }}_${{ inputs.layer }}_subset_${{inputs.bench_subset}}_${{ inputs.pbs_kind }}_${{ inputs.bench_type }}_tables
           # This will upload all the file generated
@@ -111,7 +111,7 @@ jobs:
 
       - name: Upload comparison tables
         if: inputs.backend_comparison == true
-        uses: actions/upload-artifact@bbbca2ddaa5d8feaa63e36b76fdaad77386f024f
+        uses: actions/upload-artifact@043fb46d1a93c77aae656e7c1c64a875d1fc6a0a
         with:
           name: ${{ github.sha }}_backends_comparison_tables
           # This will upload all the file generated

.github/workflows/generate_svgs.yml

@@ -209,60 +209,98 @@ jobs:
       DATA_EXTRACTOR_DATABASE_HOST: ${{ secrets.DATA_EXTRACTOR_DATABASE_HOST }}
       DATA_EXTRACTOR_DATABASE_PASSWORD: ${{ secrets.DATA_EXTRACTOR_DATABASE_PASSWORD }}
 
+  gpu-zk-server-latency-table:
+    name: generate_documentation_svgs/gpu-zk-server-latency-table
+    uses: ./.github/workflows/generate_svg_common.yml
+    if: inputs.generate-gpu-svgs
+    with:
+      backend: gpu
+      hardware_name: n3-H100-SXM5x8
+      layer: integer
+      bench_subset: zk
+      pbs_kind: multi_bit
+      grouping_factor: 4
+      bench_type: latency
+      time_span_days: ${{ inputs.time_span_days }}
+      output_filename: gpu-zk-benchmark-latency
+    secrets:
+      DATA_EXTRACTOR_DATABASE_USER: ${{ secrets.DATA_EXTRACTOR_DATABASE_USER }}
+      DATA_EXTRACTOR_DATABASE_HOST: ${{ secrets.DATA_EXTRACTOR_DATABASE_HOST }}
+      DATA_EXTRACTOR_DATABASE_PASSWORD: ${{ secrets.DATA_EXTRACTOR_DATABASE_PASSWORD }}
+
+  gpu-zk-server-throughput-table:
+    name: generate_documentation_svgs/gpu-zk-server-throughput-table
+    uses: ./.github/workflows/generate_svg_common.yml
+    if: inputs.generate-gpu-svgs
+    with:
+      backend: gpu
+      hardware_name: n3-H100-SXM5x8
+      layer: integer
+      bench_subset: zk
+      pbs_kind: multi_bit
+      grouping_factor: 4
+      bench_type: throughput
+      time_span_days: ${{ inputs.time_span_days }}
+      output_filename: gpu-zk-benchmark-throughput
+    secrets:
+      DATA_EXTRACTOR_DATABASE_USER: ${{ secrets.DATA_EXTRACTOR_DATABASE_USER }}
+      DATA_EXTRACTOR_DATABASE_HOST: ${{ secrets.DATA_EXTRACTOR_DATABASE_HOST }}
+      DATA_EXTRACTOR_DATABASE_PASSWORD: ${{ secrets.DATA_EXTRACTOR_DATABASE_PASSWORD }}
+
   # -----------------------------------------------------------
-  # ERC20 benchmarks tables
+  # ERC7984 benchmarks tables
   # -----------------------------------------------------------
 
-  cpu-erc20-latency-throughput-table:
-    name: generate_documentation_svgs/cpu-erc20-latency-throughput-table
+  cpu-erc7984-latency-throughput-table:
+    name: generate_documentation_svgs/cpu-erc7984-latency-throughput-table
     uses: ./.github/workflows/generate_svg_common.yml
     if: inputs.generate-cpu-svgs
     with:
       backend: cpu
       hardware_name: hpc7a.96xlarge
       layer: hlapi
-      bench_subset: erc20
+      bench_subset: erc7984
       pbs_kind: classical
       bench_type: both
       time_span_days: ${{ inputs.time_span_days }}
-      output_filename: cpu-hlapi-erc20-benchmark-latency-throughput
+      output_filename: cpu-hlapi-erc7984-benchmark-latency-throughput
     secrets:
       DATA_EXTRACTOR_DATABASE_USER: ${{ secrets.DATA_EXTRACTOR_DATABASE_USER }}
       DATA_EXTRACTOR_DATABASE_HOST: ${{ secrets.DATA_EXTRACTOR_DATABASE_HOST }}
       DATA_EXTRACTOR_DATABASE_PASSWORD: ${{ secrets.DATA_EXTRACTOR_DATABASE_PASSWORD }}
 
-  gpu-erc20-latency-throughput-table:
-    name: generate_documentation_svgs/gpu-erc20-latency-throughput-table
+  gpu-erc7984-latency-throughput-table:
+    name: generate_documentation_svgs/gpu-erc7984-latency-throughput-table
     uses: ./.github/workflows/generate_svg_common.yml
     if: inputs.generate-gpu-svgs
     with:
       backend: gpu
       hardware_name: n3-H100-SXM5x8
       layer: hlapi
-      bench_subset: erc20
+      bench_subset: erc7984
       pbs_kind: multi_bit
       grouping_factor: 4
       bench_type: both
       time_span_days: ${{ inputs.time_span_days }}
-      output_filename: gpu-hlapi-erc20-benchmark-h100x8-sxm5-latency-throughput
+      output_filename: gpu-hlapi-erc7984-benchmark-h100x8-sxm5-latency-throughput
     secrets:
       DATA_EXTRACTOR_DATABASE_USER: ${{ secrets.DATA_EXTRACTOR_DATABASE_USER }}
       DATA_EXTRACTOR_DATABASE_HOST: ${{ secrets.DATA_EXTRACTOR_DATABASE_HOST }}
       DATA_EXTRACTOR_DATABASE_PASSWORD: ${{ secrets.DATA_EXTRACTOR_DATABASE_PASSWORD }}
 
-  hpu-erc20-latency-throughput-table:
-    name: generate_documentation_svgs/hpu-erc20-latency-throughput-table
+  hpu-erc7984-latency-throughput-table:
+    name: generate_documentation_svgs/hpu-erc7984-latency-throughput-table
     uses: ./.github/workflows/generate_svg_common.yml
     if: inputs.generate-hpu-svgs
     with:
       backend: hpu
       hardware_name: hpu_x1
       layer: hlapi
-      bench_subset: erc20
+      bench_subset: erc7984
       pbs_kind: classical
       bench_type: both
       time_span_days: ${{ inputs.time_span_days }}
-      output_filename: hpu-hlapi-erc20-benchmark-hpux1-latency-throughput.svg
+      output_filename: hpu-hlapi-erc7984-benchmark-hpux1-latency-throughput.svg
     secrets:
       DATA_EXTRACTOR_DATABASE_USER: ${{ secrets.DATA_EXTRACTOR_DATABASE_USER }}
       DATA_EXTRACTOR_DATABASE_HOST: ${{ secrets.DATA_EXTRACTOR_DATABASE_HOST }}

.github/workflows/gpu_code_validation_tests.yml

@@ -43,7 +43,7 @@ jobs:
       - name: Start remote instance
         id: start-remote-instance
         if: env.SECRETS_AVAILABLE == 'true'
-        uses: zama-ai/slab-github-runner@0a812986560d3f10dc65728b1ccb9ae4c48a8a16 # v1.5.1
+        uses: zama-ai/slab-github-runner@5aee5d157f4a0201e5eaefc9cc648e5f9f5472a5 # v1.6.0
         with:
           mode: start
           github-token: ${{ secrets.SLAB_ACTION_TOKEN }}
@@ -149,7 +149,7 @@ jobs:
       - name: Stop remote instance
         id: stop-instance
         if: env.SECRETS_AVAILABLE == 'true'
-        uses: zama-ai/slab-github-runner@0a812986560d3f10dc65728b1ccb9ae4c48a8a16 # v1.5.1
+        uses: zama-ai/slab-github-runner@5aee5d157f4a0201e5eaefc9cc648e5f9f5472a5 # v1.6.0
         with:
           mode: stop
           github-token: ${{ secrets.SLAB_ACTION_TOKEN }}

.github/workflows/gpu_core_h100_tests.yml

@@ -23,7 +23,7 @@ on:
   # Allows you to run this workflow manually from the Actions tab as an alternative.
   workflow_dispatch:
   pull_request:
-    types: [ labeled ]
+    types: [ labeled, opened, synchronize ]
 
 permissions:
   contents: read
@@ -38,6 +38,7 @@ jobs:
       pull-requests: read  # Needed to check for file change
     outputs:
       gpu_test: ${{ env.IS_PULL_REQUEST == 'false' || steps.changed-files.outputs.gpu_any_changed }}
+      core_crypto_changed: ${{ steps.changed-files.outputs.core_crypto_any_changed }}
     steps:
       - name: Checkout tfhe-rs
         uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd
@@ -62,29 +63,24 @@ jobs:
               - tfhe/src/integer/server_key/radix_parallel/tests_cases_unsigned.rs
               - tfhe/src/shortint/parameters/**
               - tfhe/src/c_api/**
-              - 'tfhe/docs/**/**.md'
               - '.github/workflows/gpu_core_h100_tests.yml'
+            core_crypto:
+              - tfhe/src/core_crypto/gpu/**
 
   setup-instance:
     name: gpu_core_h100_tests/setup-instance
     needs: should-run
     if: github.event_name != 'pull_request' ||
-      (github.event.action != 'labeled' && needs.should-run.outputs.gpu_test == 'true') ||
-      (github.event.action == 'labeled' && github.event.label.name == 'approved' && needs.should-run.outputs.gpu_test == 'true')
+      (github.event.action == 'labeled' && github.event.label.name == 'approved' && needs.should-run.outputs.gpu_test == 'true') ||
+      (github.event.action != 'labeled' && needs.should-run.outputs.core_crypto_changed == 'true')
     runs-on: ubuntu-latest
     outputs:
-      # Use permanent remote instance label first as on-demand remote instance label output is set before the end of start-remote-instance step.
-      # If the latter fails due to a failed GitHub action runner set up, we have to fallback on the permanent instance.
-      # Since the on-demand remote label is set before failure, we have to do the logical OR in this order,
-      # otherwise we'll try to run the next job on a non-existing on-demand instance.
-      runner-name: ${{ steps.use-permanent-instance.outputs.runner_group || steps.start-remote-instance.outputs.label || steps.start-github-instance.outputs.runner_group }}
-      remote-instance-outcome: ${{ steps.start-remote-instance.outcome }}
+      runner-name: ${{ steps.start-remote-instance.outputs.label || steps.start-github-instance.outputs.runner_group }}
     steps:
       - name: Start remote instance
         id: start-remote-instance
         if: env.SECRETS_AVAILABLE == 'true'
-        continue-on-error: true
-        uses: zama-ai/slab-github-runner@0a812986560d3f10dc65728b1ccb9ae4c48a8a16 # v1.5.1
+        uses: zama-ai/slab-github-runner@5aee5d157f4a0201e5eaefc9cc648e5f9f5472a5 # v1.6.0
         with:
           mode: start
           github-token: ${{ secrets.SLAB_ACTION_TOKEN }}
@@ -93,13 +89,6 @@ jobs:
           backend: hyperstack
           profile: single-h100
 
-      # This will allow to fallback on permanent instances running on Hyperstack.
-      - name: Use permanent remote instance
-        id: use-permanent-instance
-        if: env.SECRETS_AVAILABLE == 'true' && steps.start-remote-instance.outcome == 'failure'
-        run: |
-          echo "runner_group=h100x1" >> "$GITHUB_OUTPUT"
-
       # This instance will be spawned especially for pull-request from forked repository
       - name: Start GitHub instance
         id: start-github-instance
@@ -132,7 +121,6 @@ jobs:
           token: ${{ env.CHECKOUT_TOKEN }}
 
       - name: Setup Hyperstack dependencies
-        if: needs.setup-instance.outputs.remote-instance-outcome == 'success'
         uses: ./.github/actions/gpu_setup
         with:
           cuda-version: ${{ matrix.cuda }}
@@ -176,14 +164,14 @@ jobs:
 
   teardown-instance:
     name: gpu_core_h100_tests/teardown-instance
-    if: ${{ always() && needs.setup-instance.outputs.remote-instance-outcome == 'success' }}
+    if: ${{ always() && needs.setup-instance.result == 'success' }}
     needs: [ setup-instance, cuda-tests-linux ]
     runs-on: ubuntu-latest
     steps:
       - name: Stop remote instance
         id: stop-instance
         if: env.SECRETS_AVAILABLE == 'true'
-        uses: zama-ai/slab-github-runner@0a812986560d3f10dc65728b1ccb9ae4c48a8a16 # v1.5.1
+        uses: zama-ai/slab-github-runner@5aee5d157f4a0201e5eaefc9cc648e5f9f5472a5 # v1.6.0
         with:
           mode: stop
           github-token: ${{ secrets.SLAB_ACTION_TOKEN }}

.github/workflows/gpu_fast_tests.yml

@@ -77,7 +77,7 @@ jobs:
       - name: Start remote instance
         id: start-remote-instance
         if: env.SECRETS_AVAILABLE == 'true'
-        uses: zama-ai/slab-github-runner@0a812986560d3f10dc65728b1ccb9ae4c48a8a16 # v1.5.1
+        uses: zama-ai/slab-github-runner@5aee5d157f4a0201e5eaefc9cc648e5f9f5472a5 # v1.6.0
         with:
           mode: start
           github-token: ${{ secrets.SLAB_ACTION_TOKEN }}
@@ -182,7 +182,7 @@ jobs:
       - name: Stop remote instance
         id: stop-instance
         if: env.SECRETS_AVAILABLE == 'true'
-        uses: zama-ai/slab-github-runner@0a812986560d3f10dc65728b1ccb9ae4c48a8a16 # v1.5.1
+        uses: zama-ai/slab-github-runner@5aee5d157f4a0201e5eaefc9cc648e5f9f5472a5 # v1.6.0
         with:
           mode: stop
           github-token: ${{ secrets.SLAB_ACTION_TOKEN }}

.github/workflows/gpu_full_h100_tests.yml

@@ -25,17 +25,11 @@ jobs:
     name: gpu_full_h100_tests/setup-instance
     runs-on: ubuntu-latest
     outputs:
-      # Use permanent remote instance label first as on-demand remote instance label output is set before the end of start-remote-instance step.
-      # If the latter fails due to a failed GitHub action runner set up, we have to fallback on the permanent instance.
-      # Since the on-demand remote label is set before failure, we have to do the logical OR in this order,
-      # otherwise we'll try to run the next job on a non-existing on-demand instance.
-      runner-name: ${{ steps.use-permanent-instance.outputs.runner_group || steps.start-remote-instance.outputs.label }}
-      remote-instance-outcome: ${{ steps.start-remote-instance.outcome }}
+      runner-name: ${{ steps.start-instance.outputs.label }}
     steps:
-      - name: Start remote instance
-        id: start-remote-instance
-        continue-on-error: true
-        uses: zama-ai/slab-github-runner@0a812986560d3f10dc65728b1ccb9ae4c48a8a16 # v1.5.1
+      - name: Start instance
+        id: start-instance
+        uses: zama-ai/slab-github-runner@5aee5d157f4a0201e5eaefc9cc648e5f9f5472a5 # v1.6.0
         with:
           mode: start
           github-token: ${{ secrets.SLAB_ACTION_TOKEN }}
@@ -44,13 +38,6 @@ jobs:
           backend: hyperstack
           profile: single-h100
 
-      # This will allow to fallback on permanent instances running on Hyperstack.
-      - name: Use permanent remote instance
-        id: use-permanent-instance
-        if: env.SECRETS_AVAILABLE == 'true' && steps.start-remote-instance.outcome == 'failure'
-        run: |
-          echo "runner_group=h100x1" >> "$GITHUB_OUTPUT"
-
   cuda-tests-linux:
     name: gpu_full_h100_tests/cuda-tests-linux
     needs: [ setup-instance ]
@@ -74,7 +61,6 @@ jobs:
           token: ${{ secrets.REPO_CHECKOUT_TOKEN }}
 
       - name: Setup Hyperstack dependencies
-        if: needs.setup-instance.outputs.remote-instance-outcome == 'success'
         uses: ./.github/actions/gpu_setup
         with:
           cuda-version: ${{ matrix.cuda }}
@@ -118,13 +104,13 @@ jobs:
 
   teardown-instance:
     name: gpu_full_h100_tests/teardown-instance
-    if: ${{ always() && needs.setup-instance.outputs.remote-instance-outcome == 'success' }}
+    if: ${{ always() && needs.setup-instance.result == 'success' }}
     needs: [ setup-instance, cuda-tests-linux ]
     runs-on: ubuntu-latest
     steps:
       - name: Stop instance
         id: stop-instance
-        uses: zama-ai/slab-github-runner@0a812986560d3f10dc65728b1ccb9ae4c48a8a16 # v1.5.1
+        uses: zama-ai/slab-github-runner@5aee5d157f4a0201e5eaefc9cc648e5f9f5472a5 # v1.6.0
         with:
           mode: stop
           github-token: ${{ secrets.SLAB_ACTION_TOKEN }}

.github/workflows/gpu_full_multi_gpu_tests.yml

@@ -80,7 +80,7 @@ jobs:
       - name: Start remote instance
         id: start-remote-instance
         if: env.SECRETS_AVAILABLE == 'true'
-        uses: zama-ai/slab-github-runner@0a812986560d3f10dc65728b1ccb9ae4c48a8a16 # v1.5.1
+        uses: zama-ai/slab-github-runner@5aee5d157f4a0201e5eaefc9cc648e5f9f5472a5 # v1.6.0
         with:
           mode: start
           github-token: ${{ secrets.SLAB_ACTION_TOKEN }}
@@ -186,7 +186,7 @@ jobs:
       - name: Stop remote instance
         id: stop-instance
         if: env.SECRETS_AVAILABLE == 'true'
-        uses: zama-ai/slab-github-runner@0a812986560d3f10dc65728b1ccb9ae4c48a8a16 # v1.5.1
+        uses: zama-ai/slab-github-runner@5aee5d157f4a0201e5eaefc9cc648e5f9f5472a5 # v1.6.0
         with:
           mode: stop
           github-token: ${{ secrets.SLAB_ACTION_TOKEN }}

.github/workflows/gpu_hlapi_h100_tests.yml

@@ -23,7 +23,7 @@ on:
   # Allows you to run this workflow manually from the Actions tab as an alternative.
   workflow_dispatch:
   pull_request:
-    types: [ labeled ]
+    types: [ labeled, opened, synchronize ]
 
 permissions:
   contents: read
@@ -38,6 +38,7 @@ jobs:
       pull-requests: read  # Needed to check for file change
     outputs:
       gpu_test: ${{ env.IS_PULL_REQUEST == 'false' || steps.changed-files.outputs.gpu_any_changed }}
+      core_crypto_changed: ${{ steps.changed-files.outputs.core_crypto_any_changed }}
     steps:
       - name: Checkout tfhe-rs
         uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd
@@ -65,27 +66,23 @@ jobs:
               - tfhe/src/c_api/**
               - 'tfhe/docs/**/**.md'
               - '.github/workflows/gpu_hlapi_h100_tests.yml'
+            core_crypto:
+              - tfhe/src/core_crypto/gpu/**
 
   setup-instance:
     name: gpu_hlapi_h100_tests/setup-instance
     needs: should-run
     if: github.event_name != 'pull_request' ||
-      (github.event.action != 'labeled' && needs.should-run.outputs.gpu_test == 'true') ||
-      (github.event.action == 'labeled' && github.event.label.name == 'approved' && needs.should-run.outputs.gpu_test == 'true')
+      (github.event.action == 'labeled' && github.event.label.name == 'approved' && needs.should-run.outputs.gpu_test == 'true') ||
+      (github.event.action != 'labeled' && needs.should-run.outputs.core_crypto_changed == 'true')
     runs-on: ubuntu-latest
     outputs:
-      # Use permanent remote instance label first as on-demand remote instance label output is set before the end of start-remote-instance step.
-      # If the latter fails due to a failed GitHub action runner set up, we have to fallback on the permanent instance.
-      # Since the on-demand remote label is set before failure, we have to do the logical OR in this order,
-      # otherwise we'll try to run the next job on a non-existing on-demand instance.
-      runner-name: ${{ steps.use-permanent-instance.outputs.runner_group || steps.start-remote-instance.outputs.label || steps.start-github-instance.outputs.runner_group }}
-      remote-instance-outcome: ${{ steps.start-remote-instance.outcome }}
+      runner-name: ${{ steps.start-remote-instance.outputs.label || steps.start-github-instance.outputs.runner_group }}
     steps:
       - name: Start remote instance
         id: start-remote-instance
         if: env.SECRETS_AVAILABLE == 'true'
-        continue-on-error: true
-        uses: zama-ai/slab-github-runner@0a812986560d3f10dc65728b1ccb9ae4c48a8a16 # v1.5.1
+        uses: zama-ai/slab-github-runner@5aee5d157f4a0201e5eaefc9cc648e5f9f5472a5 # v1.6.0
         with:
           mode: start
           github-token: ${{ secrets.SLAB_ACTION_TOKEN }}
@@ -94,13 +91,6 @@ jobs:
           backend: hyperstack
           profile: single-h100
 
-      # This will allow to fallback on permanent instances running on Hyperstack.
-      - name: Use permanent remote instance
-        id: use-permanent-instance
-        if: env.SECRETS_AVAILABLE == 'true' && steps.start-remote-instance.outcome == 'failure'
-        run: |
-          echo "runner_group=h100x1" >> "$GITHUB_OUTPUT"
-
       # This instance will be spawned especially for pull-request from forked repository
       - name: Start GitHub instance
         id: start-github-instance
@@ -133,7 +123,6 @@ jobs:
           token: ${{ env.CHECKOUT_TOKEN }}
 
       - name: Setup Hyperstack dependencies
-        if: needs.setup-instance.outputs.remote-instance-outcome == 'success'
         uses: ./.github/actions/gpu_setup
         with:
           cuda-version: ${{ matrix.cuda }}
@@ -184,14 +173,14 @@ jobs:
 
   teardown-instance:
     name: gpu_hlapi_h100_tests/teardown-instance
-    if: ${{ always() && needs.setup-instance.outputs.remote-instance-outcome == 'success' }}
+    if: ${{ always() && needs.setup-instance.result == 'success' }}
     needs: [ setup-instance, cuda-tests-linux ]
     runs-on: ubuntu-latest
     steps:
       - name: Stop remote instance
         id: stop-instance
         if: env.SECRETS_AVAILABLE == 'true'
-        uses: zama-ai/slab-github-runner@0a812986560d3f10dc65728b1ccb9ae4c48a8a16 # v1.5.1
+        uses: zama-ai/slab-github-runner@5aee5d157f4a0201e5eaefc9cc648e5f9f5472a5 # v1.6.0
         with:
           mode: stop
           github-token: ${{ secrets.SLAB_ACTION_TOKEN }}

.github/workflows/gpu_integer_long_run_tests.yml

@@ -17,8 +17,8 @@ on:
   # Allows you to run this workflow manually from the Actions tab as an alternative.
   workflow_dispatch:
   schedule:
-    # Nightly tests will be triggered each evening 8p.m.
-    - cron: "0 20 * * *"
+    # Weekly tests will be triggered every Monday at 8p.m.
+    - cron: "0 20 * * 1"
   pull_request:
 
 
@@ -28,17 +28,48 @@ permissions:
 # zizmor: ignore[concurrency-limits] concurrency is managed after instance setup to ensure safe provisioning
 
 jobs:
+  should-run:
+    name: gpu_integer_long_run_tests/should-run
+    runs-on: ubuntu-latest
+    permissions:
+      pull-requests: read  # Needed to check for file change
+    outputs:
+      is_needed_in_gpu_ci: ${{ env.IS_PR == 'false' || steps.changed-files.outputs.gpu_any_changed }}
+    steps:
+      - name: Checkout tfhe-rs
+        uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd
+        with:
+          fetch-depth: 0
+          persist-credentials: 'false'
+          token: ${{ env.CHECKOUT_TOKEN }}
+
+      - name: Check for file changes
+        id: changed-files
+        uses: tj-actions/changed-files@22103cc46bda19c2b464ffe86db46df6922fd323 # v47.0.5
+        with:
+          files_yaml: |
+            gpu:
+              - tfhe/Cargo.toml
+              - tfhe/build.rs
+              - backends/tfhe-cuda-backend/**
+              - tfhe/src/core_crypto/gpu/**
+              - tfhe/src/integer/gpu/**
+              - tfhe/src/shortint/parameters/**
+              - '.github/workflows/gpu_integer_long_run_tests.yml'
+
   setup-instance:
     name: gpu_integer_long_run_tests/setup-instance
-    if: github.event_name != 'schedule' ||
-      (github.event_name == 'schedule' && github.repository == 'zama-ai/tfhe-rs')
+    needs: [should-run]
+    if: github.event_name == 'workflow_dispatch' ||
+      (github.event_name == 'schedule' && github.repository == 'zama-ai/tfhe-rs') ||
+      needs.should-run.outputs.is_needed_in_gpu_ci == 'true'
     runs-on: ubuntu-latest
     outputs:
       runner-name: ${{ steps.start-instance.outputs.label }}
     steps:
       - name: Start instance
         id: start-instance
-        uses: zama-ai/slab-github-runner@0a812986560d3f10dc65728b1ccb9ae4c48a8a16 # v1.5.1
+        uses: zama-ai/slab-github-runner@5aee5d157f4a0201e5eaefc9cc648e5f9f5472a5 # v1.6.0
         with:
           mode: start
           github-token: ${{ secrets.SLAB_ACTION_TOKEN }}
@@ -112,7 +143,7 @@ jobs:
     steps:
       - name: Stop instance
         id: stop-instance
-        uses: zama-ai/slab-github-runner@0a812986560d3f10dc65728b1ccb9ae4c48a8a16 # v1.5.1
+        uses: zama-ai/slab-github-runner@5aee5d157f4a0201e5eaefc9cc648e5f9f5472a5 # v1.6.0
         with:
           mode: stop
           github-token: ${{ secrets.SLAB_ACTION_TOKEN }}

.github/workflows/gpu_memory_sanitizer.yml

@@ -74,7 +74,7 @@ jobs:
       - name: Start remote instance
         id: start-remote-instance
         if: env.SECRETS_AVAILABLE == 'true'
-        uses: zama-ai/slab-github-runner@0a812986560d3f10dc65728b1ccb9ae4c48a8a16 # v1.5.1
+        uses: zama-ai/slab-github-runner@5aee5d157f4a0201e5eaefc9cc648e5f9f5472a5 # v1.6.0
         with:
           mode: start
           github-token: ${{ secrets.SLAB_ACTION_TOKEN }}
@@ -166,7 +166,7 @@ jobs:
       - name: Stop remote instance
         id: stop-instance
         if: env.SECRETS_AVAILABLE == 'true'
-        uses: zama-ai/slab-github-runner@0a812986560d3f10dc65728b1ccb9ae4c48a8a16 # v1.5.1
+        uses: zama-ai/slab-github-runner@5aee5d157f4a0201e5eaefc9cc648e5f9f5472a5 # v1.6.0
         with:
           mode: stop
           github-token: ${{ secrets.SLAB_ACTION_TOKEN }}

.github/workflows/gpu_memory_sanitizer_h100.yml

@@ -74,7 +74,7 @@ jobs:
       - name: Start remote instance
         id: start-remote-instance
         if: env.SECRETS_AVAILABLE == 'true'
-        uses: zama-ai/slab-github-runner@0a812986560d3f10dc65728b1ccb9ae4c48a8a16 # v1.5.1
+        uses: zama-ai/slab-github-runner@5aee5d157f4a0201e5eaefc9cc648e5f9f5472a5 # v1.6.0
         with:
           mode: start
           github-token: ${{ secrets.SLAB_ACTION_TOKEN }}
@@ -166,7 +166,7 @@ jobs:
       - name: Stop remote instance
         id: stop-instance
         if: env.SECRETS_AVAILABLE == 'true'
-        uses: zama-ai/slab-github-runner@0a812986560d3f10dc65728b1ccb9ae4c48a8a16 # v1.5.1
+        uses: zama-ai/slab-github-runner@5aee5d157f4a0201e5eaefc9cc648e5f9f5472a5 # v1.6.0
         with:
           mode: stop
           github-token: ${{ secrets.SLAB_ACTION_TOKEN }}

.github/workflows/gpu_pcc.yml

@@ -38,7 +38,7 @@ jobs:
       - name: Start remote instance
         id: start-remote-instance
         if: env.SECRETS_AVAILABLE == 'true'
-        uses: zama-ai/slab-github-runner@0a812986560d3f10dc65728b1ccb9ae4c48a8a16 # v1.5.1
+        uses: zama-ai/slab-github-runner@5aee5d157f4a0201e5eaefc9cc648e5f9f5472a5 # v1.6.0
         with:
           mode: start
           github-token: ${{ secrets.SLAB_ACTION_TOKEN }}
@@ -131,6 +131,10 @@ jobs:
         env:
           GCC_VERSION: ${{ matrix.gcc }}
 
+      - name: Run semgrep and lint checks on CUDA code
+        run: |
+          make semgrep_and_lint_gpu_code
+
       - name: Run fmt checks
         run: |
           make check_fmt_gpu
@@ -139,10 +143,6 @@ jobs:
         run: |
           make pcc_gpu
 
-      - name: Run semgrep and lint checks on CUDA code
-        run: |
-          make semgrep_and_lint_gpu_code
-
       - name: Run semver checks on tfhe-cuda-backend
         run: |
           make semver_check_cuda_backend
@@ -176,7 +176,7 @@ jobs:
       - name: Stop remote instance
         id: stop-instance
         if: env.SECRETS_AVAILABLE == 'true'
-        uses: zama-ai/slab-github-runner@0a812986560d3f10dc65728b1ccb9ae4c48a8a16 # v1.5.1
+        uses: zama-ai/slab-github-runner@5aee5d157f4a0201e5eaefc9cc648e5f9f5472a5 # v1.6.0
         with:
           mode: stop
           github-token: ${{ secrets.SLAB_ACTION_TOKEN }}

.github/workflows/gpu_signed_integer_classic_tests.yml

@@ -63,7 +63,6 @@ jobs:
               - tfhe/src/shortint/parameters/**
               - tfhe/src/high_level_api/**
               - tfhe/src/c_api/**
-              - 'tfhe/docs/**/**.md'
               - '.github/workflows/gpu_signed_integer_classic_tests.yml'
               - scripts/integer-tests.sh
 
@@ -80,7 +79,7 @@ jobs:
       - name: Start remote instance
         id: start-remote-instance
         if: env.SECRETS_AVAILABLE == 'true'
-        uses: zama-ai/slab-github-runner@0a812986560d3f10dc65728b1ccb9ae4c48a8a16 # v1.5.1
+        uses: zama-ai/slab-github-runner@5aee5d157f4a0201e5eaefc9cc648e5f9f5472a5 # v1.6.0
         with:
           mode: start
           github-token: ${{ secrets.SLAB_ACTION_TOKEN }}
@@ -169,7 +168,7 @@ jobs:
       - name: Stop remote instance
         id: stop-instance
         if: env.SECRETS_AVAILABLE == 'true'
-        uses: zama-ai/slab-github-runner@0a812986560d3f10dc65728b1ccb9ae4c48a8a16 # v1.5.1
+        uses: zama-ai/slab-github-runner@5aee5d157f4a0201e5eaefc9cc648e5f9f5472a5 # v1.6.0
         with:
           mode: stop
           github-token: ${{ secrets.SLAB_ACTION_TOKEN }}

.github/workflows/gpu_signed_integer_h100_tests.yml

@@ -23,7 +23,7 @@ on:
   # Allows you to run this workflow manually from the Actions tab as an alternative.
   workflow_dispatch:
   pull_request:
-    types: [ labeled ]
+    types: [ labeled, opened, synchronize ]
 
 permissions:
   contents: read
@@ -38,6 +38,7 @@ jobs:
       pull-requests: read  # Needed to check for file change
     outputs:
       gpu_test: ${{ env.IS_PULL_REQUEST == 'false' || steps.changed-files.outputs.gpu_any_changed }}
+      core_crypto_changed: ${{ steps.changed-files.outputs.core_crypto_any_changed }}
     steps:
       - name: Checkout tfhe-rs
         uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd
@@ -63,30 +64,25 @@ jobs:
               - tfhe/src/shortint/parameters/**
               - tfhe/src/high_level_api/**
               - tfhe/src/c_api/**
-              - 'tfhe/docs/**/**.md'
               - '.github/workflows/gpu_signed_integer_h100_tests.yml'
               - scripts/integer-tests.sh
+            core_crypto:
+              - tfhe/src/core_crypto/gpu/**
 
   setup-instance:
     name: gpu_signed_integer_h100_tests/setup-instance
     needs: should-run
     if: github.event_name != 'pull_request' ||
-      (github.event.action != 'labeled' && needs.should-run.outputs.gpu_test == 'true') ||
-      (github.event.action == 'labeled' && github.event.label.name == 'approved' && needs.should-run.outputs.gpu_test == 'true')
+      (github.event.action == 'labeled' && github.event.label.name == 'approved' && needs.should-run.outputs.gpu_test == 'true') ||
+      (github.event.action != 'labeled' && needs.should-run.outputs.core_crypto_changed == 'true')
     runs-on: ubuntu-latest
     outputs:
-      # Use permanent remote instance label first as on-demand remote instance label output is set before the end of start-remote-instance step.
-      # If the latter fails due to a failed GitHub action runner set up, we have to fallback on the permanent instance.
-      # Since the on-demand remote label is set before failure, we have to do the logical OR in this order,
-      # otherwise we'll try to run the next job on a non-existing on-demand instance.
-      runner-name: ${{ steps.use-permanent-instance.outputs.runner_group || steps.start-remote-instance.outputs.label || steps.start-github-instance.outputs.runner_group }}
-      remote-instance-outcome: ${{ steps.start-remote-instance.outcome }}
+      runner-name: ${{ steps.start-remote-instance.outputs.label || steps.start-github-instance.outputs.runner_group }}
     steps:
       - name: Start remote instance
         id: start-remote-instance
         if: env.SECRETS_AVAILABLE == 'true'
-        continue-on-error: true
-        uses: zama-ai/slab-github-runner@0a812986560d3f10dc65728b1ccb9ae4c48a8a16 # v1.5.1
+        uses: zama-ai/slab-github-runner@5aee5d157f4a0201e5eaefc9cc648e5f9f5472a5 # v1.6.0
         with:
           mode: start
           github-token: ${{ secrets.SLAB_ACTION_TOKEN }}
@@ -95,13 +91,6 @@ jobs:
           backend: hyperstack
           profile: single-h100
 
-      # This will allow to fallback on permanent instances running on Hyperstack.
-      - name: Use permanent remote instance
-        id: use-permanent-instance
-        if: env.SECRETS_AVAILABLE == 'true' && steps.start-remote-instance.outcome == 'failure'
-        run: |
-          echo "runner_group=h100x1" >> "$GITHUB_OUTPUT"
-
       # This instance will be spawned especially for pull-request from forked repository
       - name: Start GitHub instance
         id: start-github-instance
@@ -134,7 +123,6 @@ jobs:
           token: ${{ env.CHECKOUT_TOKEN }}
 
       - name: Setup Hyperstack dependencies
-        if: needs.setup-instance.outputs.remote-instance-outcome == 'success'
         uses: ./.github/actions/gpu_setup
         with:
           cuda-version: ${{ matrix.cuda }}
@@ -176,14 +164,14 @@ jobs:
 
   teardown-instance:
     name: gpu_signed_integer_h100_tests/teardown-instance
-    if: ${{ always() && needs.setup-instance.outputs.remote-instance-outcome == 'success' }}
+    if: ${{ always() && needs.setup-instance.result == 'success' }}
     needs: [ setup-instance, cuda-tests-linux ]
     runs-on: ubuntu-latest
     steps:
       - name: Stop remote instance
         id: stop-instance
         if: env.SECRETS_AVAILABLE == 'true'
-        uses: zama-ai/slab-github-runner@0a812986560d3f10dc65728b1ccb9ae4c48a8a16 # v1.5.1
+        uses: zama-ai/slab-github-runner@5aee5d157f4a0201e5eaefc9cc648e5f9f5472a5 # v1.6.0
         with:
           mode: stop
           github-token: ${{ secrets.SLAB_ACTION_TOKEN }}

.github/workflows/gpu_signed_integer_tests.yml

@@ -64,7 +64,6 @@ jobs:
               - tfhe/src/shortint/parameters/**
               - tfhe/src/high_level_api/**
               - tfhe/src/c_api/**
-              - 'tfhe/docs/**/**.md'
               - '.github/workflows/gpu_signed_integer_tests.yml'
               - scripts/integer-tests.sh
 
@@ -81,7 +80,7 @@ jobs:
       - name: Start remote instance
         id: start-remote-instance
         if: env.SECRETS_AVAILABLE == 'true'
-        uses: zama-ai/slab-github-runner@0a812986560d3f10dc65728b1ccb9ae4c48a8a16 # v1.5.1
+        uses: zama-ai/slab-github-runner@5aee5d157f4a0201e5eaefc9cc648e5f9f5472a5 # v1.6.0
         with:
           mode: start
           github-token: ${{ secrets.SLAB_ACTION_TOKEN }}
@@ -178,7 +177,7 @@ jobs:
       - name: Stop remote instance
         id: stop-instance
         if: env.SECRETS_AVAILABLE == 'true'
-        uses: zama-ai/slab-github-runner@0a812986560d3f10dc65728b1ccb9ae4c48a8a16 # v1.5.1
+        uses: zama-ai/slab-github-runner@5aee5d157f4a0201e5eaefc9cc648e5f9f5472a5 # v1.6.0
         with:
           mode: stop
           github-token: ${{ secrets.SLAB_ACTION_TOKEN }}

.github/workflows/gpu_unsigned_integer_classic_tests.yml

@@ -63,7 +63,6 @@ jobs:
               - tfhe/src/shortint/parameters/**
               - tfhe/src/high_level_api/**
               - tfhe/src/c_api/**
-              - 'tfhe/docs/**/**.md'
               - '.github/workflows/gpu_unsigned_integer_classic_tests.yml'
               - scripts/integer-tests.sh
 
@@ -80,7 +79,7 @@ jobs:
       - name: Start remote instance
         id: start-remote-instance
         if: env.SECRETS_AVAILABLE == 'true'
-        uses: zama-ai/slab-github-runner@0a812986560d3f10dc65728b1ccb9ae4c48a8a16 # v1.5.1
+        uses: zama-ai/slab-github-runner@5aee5d157f4a0201e5eaefc9cc648e5f9f5472a5 # v1.6.0
         with:
           mode: start
           github-token: ${{ secrets.SLAB_ACTION_TOKEN }}
@@ -169,7 +168,7 @@ jobs:
       - name: Stop remote instance
         id: stop-instance
         if: env.SECRETS_AVAILABLE == 'true'
-        uses: zama-ai/slab-github-runner@0a812986560d3f10dc65728b1ccb9ae4c48a8a16 # v1.5.1
+        uses: zama-ai/slab-github-runner@5aee5d157f4a0201e5eaefc9cc648e5f9f5472a5 # v1.6.0
         with:
           mode: stop
           github-token: ${{ secrets.SLAB_ACTION_TOKEN }}

.github/workflows/gpu_unsigned_integer_h100_tests.yml

@@ -23,7 +23,7 @@ on:
   # Allows you to run this workflow manually from the Actions tab as an alternative.
   workflow_dispatch:
   pull_request:
-    types: [ labeled ]
+    types: [ labeled, opened, synchronize ]
 
 permissions:
   contents: read
@@ -38,6 +38,7 @@ jobs:
       pull-requests: read  # Needed to check for file change
     outputs:
       gpu_test: ${{ env.IS_PULL_REQUEST == 'false' || steps.changed-files.outputs.gpu_any_changed }}
+      core_crypto_changed: ${{ steps.changed-files.outputs.core_crypto_any_changed }}
     steps:
       - name: Checkout tfhe-rs
         uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd
@@ -63,30 +64,25 @@ jobs:
               - tfhe/src/shortint/parameters/**
               - tfhe/src/high_level_api/**
               - tfhe/src/c_api/**
-              - 'tfhe/docs/**/**.md'
               - '.github/workflows/gpu_unsigned_integer_h100_tests.yml'
               - scripts/integer-tests.sh
+            core_crypto:
+              - tfhe/src/core_crypto/gpu/**
 
   setup-instance:
     name: gpu_unsigned_integer_h100_tests/setup-instance
     needs: should-run
     if: github.event_name == 'workflow_dispatch' ||
-      (github.event.action != 'labeled' && needs.should-run.outputs.gpu_test == 'true') ||
-      (github.event.action == 'labeled' && github.event.label.name == 'approved' && needs.should-run.outputs.gpu_test == 'true')
+      (github.event.action == 'labeled' && github.event.label.name == 'approved' && needs.should-run.outputs.gpu_test == 'true') ||
+      (github.event.action != 'labeled' && needs.should-run.outputs.core_crypto_changed == 'true')
     runs-on: ubuntu-latest
     outputs:
-      # Use permanent remote instance label first as on-demand remote instance label output is set before the end of start-remote-instance step.
-      # If the latter fails due to a failed GitHub action runner set up, we have to fallback on the permanent instance.
-      # Since the on-demand remote label is set before failure, we have to do the logical OR in this order,
-      # otherwise we'll try to run the next job on a non-existing on-demand instance.
-      runner-name: ${{ steps.use-permanent-instance.outputs.runner_group || steps.start-remote-instance.outputs.label || steps.start-github-instance.outputs.runner_group }}
-      remote-instance-outcome: ${{ steps.start-remote-instance.outcome }}
+      runner-name: ${{ steps.start-remote-instance.outputs.label || steps.start-github-instance.outputs.runner_group }}
     steps:
       - name: Start remote instance
         id: start-remote-instance
         if: env.SECRETS_AVAILABLE == 'true'
-        continue-on-error: true
-        uses: zama-ai/slab-github-runner@0a812986560d3f10dc65728b1ccb9ae4c48a8a16 # v1.5.1
+        uses: zama-ai/slab-github-runner@5aee5d157f4a0201e5eaefc9cc648e5f9f5472a5 # v1.6.0
         with:
           mode: start
           github-token: ${{ secrets.SLAB_ACTION_TOKEN }}
@@ -95,13 +91,6 @@ jobs:
           backend: hyperstack
           profile: single-h100
 
-      # This will allow to fallback on permanent instances running on Hyperstack.
-      - name: Use permanent remote instance
-        id: use-permanent-instance
-        if: env.SECRETS_AVAILABLE == 'true' && steps.start-remote-instance.outcome == 'failure'
-        run: |
-          echo "runner_group=h100x1" >> "$GITHUB_OUTPUT"
-
       # This instance will be spawned especially for pull-request from forked repository
       - name: Start GitHub instance
         id: start-github-instance
@@ -134,7 +123,6 @@ jobs:
           token: ${{ env.CHECKOUT_TOKEN }}
 
       - name: Setup Hyperstack dependencies
-        if: needs.setup-instance.outputs.remote-instance-outcome == 'success'
         uses: ./.github/actions/gpu_setup
         with:
           cuda-version: ${{ matrix.cuda }}
@@ -176,14 +164,14 @@ jobs:
 
   teardown-instance:
     name: gpu_unsigned_integer_h100_tests/teardown-instance
-    if: ${{ always() && needs.setup-instance.outputs.remote-instance-outcome == 'success' }}
+    if: ${{ always() && needs.setup-instance.result == 'success' }}
     needs: [ setup-instance, cuda-tests-linux ]
     runs-on: ubuntu-latest
     steps:
       - name: Stop remote instance
         id: stop-instance
         if: env.SECRETS_AVAILABLE == 'true'
-        uses: zama-ai/slab-github-runner@0a812986560d3f10dc65728b1ccb9ae4c48a8a16 # v1.5.1
+        uses: zama-ai/slab-github-runner@5aee5d157f4a0201e5eaefc9cc648e5f9f5472a5 # v1.6.0
         with:
           mode: stop
           github-token: ${{ secrets.SLAB_ACTION_TOKEN }}

.github/workflows/gpu_unsigned_integer_tests.yml

@@ -64,7 +64,6 @@ jobs:
               - tfhe/src/shortint/parameters/**
               - tfhe/src/high_level_api/**
               - tfhe/src/c_api/**
-              - 'tfhe/docs/**/**.md'
               - '.github/workflows/gpu_unsigned_integer_tests.yml'
               - scripts/integer-tests.sh
 
@@ -81,7 +80,7 @@ jobs:
       - name: Start remote instance
         id: start-remote-instance
         if: env.SECRETS_AVAILABLE == 'true'
-        uses: zama-ai/slab-github-runner@0a812986560d3f10dc65728b1ccb9ae4c48a8a16 # v1.5.1
+        uses: zama-ai/slab-github-runner@5aee5d157f4a0201e5eaefc9cc648e5f9f5472a5 # v1.6.0
         with:
           mode: start
           github-token: ${{ secrets.SLAB_ACTION_TOKEN }}
@@ -178,7 +177,7 @@ jobs:
       - name: Stop instance
         id: stop-instance
         if: env.SECRETS_AVAILABLE == 'true'
-        uses: zama-ai/slab-github-runner@0a812986560d3f10dc65728b1ccb9ae4c48a8a16 # v1.5.1
+        uses: zama-ai/slab-github-runner@5aee5d157f4a0201e5eaefc9cc648e5f9f5472a5 # v1.6.0
         with:
           mode: stop
           github-token: ${{ secrets.SLAB_ACTION_TOKEN }}

.github/workflows/gpu_zk_tests.yml

@@ -55,12 +55,9 @@ jobs:
               - tfhe/build.rs
               - backends/tfhe-cuda-backend/**
               - backends/zk-cuda-backend/**
-              - tfhe/src/core_crypto/gpu/**
-              - tfhe/src/integer/gpu/**
               - tfhe/src/shortint/parameters/**
               - tfhe/src/zk/**
               - tfhe-zk-pok/**
-              - 'tfhe/docs/**/**.md'
               - '.github/workflows/gpu_zk_tests.yml'
               - ci/slab.toml
 
@@ -76,7 +73,7 @@ jobs:
       - name: Start remote instance
         id: start-remote-instance
         if: env.SECRETS_AVAILABLE == 'true'
-        uses: zama-ai/slab-github-runner@0a812986560d3f10dc65728b1ccb9ae4c48a8a16 # v1.5.1
+        uses: zama-ai/slab-github-runner@5aee5d157f4a0201e5eaefc9cc648e5f9f5472a5 # v1.6.0
         with:
           mode: start
           github-token: ${{ secrets.SLAB_ACTION_TOKEN }}
@@ -170,7 +167,7 @@ jobs:
       - name: Stop remote instance
         id: stop-instance
         if: env.SECRETS_AVAILABLE == 'true'
-        uses: zama-ai/slab-github-runner@0a812986560d3f10dc65728b1ccb9ae4c48a8a16 # v1.5.1
+        uses: zama-ai/slab-github-runner@5aee5d157f4a0201e5eaefc9cc648e5f9f5472a5 # v1.6.0
         with:
           mode: stop
           github-token: ${{ secrets.SLAB_ACTION_TOKEN }}

.github/workflows/make_release_common.yml

@@ -62,7 +62,7 @@ jobs:
           PACKAGE: ${{ inputs.package-name }}
         run: |
           cargo package -p "${PACKAGE}"
-      - uses: actions/upload-artifact@bbbca2ddaa5d8feaa63e36b76fdaad77386f024f # v7.0.0
+      - uses: actions/upload-artifact@043fb46d1a93c77aae656e7c1c64a875d1fc6a0a # v7.0.1
         with:
           name: crate-${{ inputs.package-name }}
           path: target/package/*.crate
@@ -107,7 +107,7 @@ jobs:
           path: target/package
 
       - name: Authenticate on registry
-        uses: rust-lang/crates-io-auth-action@b7e9a28eded4986ec6b1fa40eeee8f8f165559ec # v1.0.3
+        uses: rust-lang/crates-io-auth-action@bbd81622f20ce9e2dd9622e3218b975523e45bbe # v1.0.4
         id: auth
 
       - name: Publish crate.io package

.github/workflows/make_release_common_cuda.yml

@@ -1,12 +1,36 @@
-name: make_release_cuda
+# Common workflow to make crate release for CUDA backend
+name: make_release_common_cuda
 
 on:
-  workflow_dispatch:
+  workflow_call:
     inputs:
-      dry_run:
-        description: "Dry-run"
+      package-name:
+        type: string
+        required: true
+      dry-run:
         type: boolean
         default: true
+    secrets:
+      REPO_CHECKOUT_TOKEN:
+        required: true
+      SLAB_ACTION_TOKEN:
+        required: true
+      SLAB_BASE_URL:
+        required: true
+      SLAB_URL:
+        required: true
+      JOB_SECRET:
+        required: true
+      SLACK_CHANNEL:
+        required: true
+      BOT_USERNAME:
+        required: true
+      SLACK_WEBHOOK:
+        required: true
+      ALLOWED_TEAM:
+        required: true
+      READ_ORG_TOKEN:
+        required: true
 
 env:
   ACTION_RUN_URL: ${{ github.server_url }}/${{ github.repository }}/actions/runs/${{ github.run_id }}
@@ -21,15 +45,15 @@ permissions: {}
 
 jobs:
   verify-triggering-actor:
-    name: make_release_cuda/verify-triggering-actor
+    name: make_release_common_cuda/verify-triggering-actor
     if: startsWith(github.ref, 'refs/tags/')
     uses: ./.github/workflows/verify_triggering_actor.yml
     secrets:
-      ALLOWED_TEAM: ${{ secrets.RELEASE_TEAM }}
+      ALLOWED_TEAM: ${{ secrets.ALLOWED_TEAM }}
       READ_ORG_TOKEN: ${{ secrets.READ_ORG_TOKEN }}
 
   setup-instance:
-    name: make_release_cuda/setup-instance
+    name: make_release_common_cuda/setup-instance
     needs: verify-triggering-actor
     runs-on: ubuntu-latest
     outputs:
@@ -37,7 +61,7 @@ jobs:
     steps:
       - name: Start instance
         id: start-instance
-        uses: zama-ai/slab-github-runner@0a812986560d3f10dc65728b1ccb9ae4c48a8a16 # v1.5.1
+        uses: zama-ai/slab-github-runner@5aee5d157f4a0201e5eaefc9cc648e5f9f5472a5 # v1.6.0
         with:
           mode: start
           github-token: ${{ secrets.SLAB_ACTION_TOKEN }}
@@ -47,7 +71,7 @@ jobs:
           profile: gpu-build
 
   package:
-    name: make_release_cuda/package
+    name: make_release_common_cuda/package
     needs: setup-instance
     runs-on: ${{ needs.setup-instance.outputs.runner-name }}
     outputs:
@@ -76,7 +100,6 @@ jobs:
           toolchain: stable
 
       - name: Export CUDA variables
-        if: ${{ !cancelled() }}
         run: |
           echo "$CUDA_PATH/bin" >> "${GITHUB_PATH}"
           {
@@ -89,7 +112,6 @@ jobs:
 
       # Specify the correct host compilers
       - name: Export gcc and g++ variables
-        if: ${{ !cancelled() }}
         run: |
           {
             echo "CC=/usr/bin/gcc-${GCC_VERSION}";
@@ -101,12 +123,14 @@ jobs:
           GCC_VERSION: ${{ matrix.gcc }}
 
       - name: Prepare package
+        env:
+          PACKAGE: ${{ inputs.package-name }}
         run: |
-          cargo package -p tfhe-cuda-backend
+          cargo package -p "${PACKAGE}"
 
-      - uses: actions/upload-artifact@bbbca2ddaa5d8feaa63e36b76fdaad77386f024f # v7.0.0
+      - uses: actions/upload-artifact@043fb46d1a93c77aae656e7c1c64a875d1fc6a0a # v7.0.1
         with:
-          name: crate-tfhe-cuda-backend
+          name: crate-${{ inputs.package-name }}
           path: target/package/*.crate
 
       - name: generate hash
@@ -114,8 +138,8 @@ jobs:
         run: cd target/package && echo "hash=$(sha256sum ./*.crate | base64 -w0)" >> "${GITHUB_OUTPUT}"
 
   provenance:
-    name: make_release_cuda/provenance
-    if: ${{ !inputs.dry_run  }}
+    name: make_release_common_cuda/provenance
+    if: ${{ !inputs.dry-run  }}
     needs: [package]
     # This action cannot be pinned to a specific commit (see https://github.com/slsa-framework/slsa-github-generator/blob/main/README.md#referencing-slsa-builders-and-generators)
     uses: slsa-framework/slsa-github-generator/.github/workflows/generator_generic_slsa3.yml@v2.1.0 # zizmor: ignore[unpinned-uses] as said above SLSA cannot be pinned by tag today
@@ -128,7 +152,7 @@ jobs:
       base64-subjects: ${{ needs.package.outputs.hash }}
 
   publish-cuda-release:
-    name: make_release_cuda/publish-cuda-release
+    name: make_release_common_cuda/publish-cuda-release
     needs: [setup-instance, package] # for comparing hashes
     runs-on: ${{ needs.setup-instance.outputs.runner-name }}
     permissions:
@@ -150,7 +174,6 @@ jobs:
           toolchain: stable
 
       - name: Export CUDA variables
-        if: ${{ !cancelled() }}
         run: |
           echo "$CUDA_PATH/bin" >> "${GITHUB_PATH}"
           {
@@ -163,7 +186,6 @@ jobs:
 
       # Specify the correct host compilers
       - name: Export gcc and g++ variables
-        if: ${{ !cancelled() }}
         run: |
           {
             echo "CC=/usr/bin/gcc-${GCC_VERSION}";
@@ -174,25 +196,33 @@ jobs:
         env:
           GCC_VERSION: ${{ matrix.gcc }}
 
+      - name: Checkout
+        uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
+        with:
+          fetch-depth: 0
+          persist-credentials: "false"
+          token: ${{ secrets.REPO_CHECKOUT_TOKEN }}
+
       - name: Download artifact
         uses: actions/download-artifact@3e5f45b2cfb9172054b4087a40e8e0b5a5461e7c # v8.0.1
         with:
-          name: crate-tfhe-cuda-backend
+          name: crate-${{ inputs.package-name }}
           path: target/package
 
       - name: Authenticate on registry
-        uses: rust-lang/crates-io-auth-action@b7e9a28eded4986ec6b1fa40eeee8f8f165559ec # v1.0.3
+        uses: rust-lang/crates-io-auth-action@bbd81622f20ce9e2dd9622e3218b975523e45bbe # v1.0.4
         id: auth
 
       - name: Publish crate.io package
         env:
           CARGO_REGISTRY_TOKEN: ${{ steps.auth.outputs.token }}
-          DRY_RUN: ${{ inputs.dry_run && '--dry-run' || '' }}
+          PACKAGE: ${{ inputs.package-name }}
+          DRY_RUN: ${{ inputs.dry-run && '--dry-run' || '' }}
         run: |
-          # DRY_RUN expansion cannot be double quoted when variable contains empty string otherwise cargo publish 
+          # DRY_RUN expansion cannot be double quoted when variable contains empty string otherwise cargo publish
           # would fail. This is safe since DRY_RUN is handled in the env section above.
           # shellcheck disable=SC2086
-          cargo publish -p tfhe-cuda-backend ${DRY_RUN}
+          cargo publish -p "${PACKAGE}" ${DRY_RUN}
 
       - name: Generate hash
         id: published_hash
@@ -204,7 +234,7 @@ jobs:
         uses: rtCamp/action-slack-notify@e31e87e03dd19038e411e38ae27cbad084a90661 # v2.3.3
         env:
           SLACK_COLOR: failure
-          SLACK_MESSAGE: "SLSA tfhe-cuda-backend crate - hash comparison failure: (${{ env.ACTION_RUN_URL }})"
+          SLACK_MESSAGE: "SLSA ${{ inputs.package-name }} crate - hash comparison failure: (${{ env.ACTION_RUN_URL }})"
 
       - name: Slack Notification
         if: ${{ failure() || (cancelled() && github.event_name != 'pull_request') }}
@@ -212,17 +242,17 @@ jobs:
         uses: rtCamp/action-slack-notify@e31e87e03dd19038e411e38ae27cbad084a90661 # v2.3.3
         env:
           SLACK_COLOR: ${{ job.status }}
-          SLACK_MESSAGE: "tfhe-cuda-backend release finished with status: ${{ job.status }}. (${{ env.ACTION_RUN_URL }})"
+          SLACK_MESSAGE: "${{ inputs.package-name }} release finished with status: ${{ job.status }}. (${{ env.ACTION_RUN_URL }})"
 
   teardown-instance:
-    name: make_release_cuda/teardown-instance
+    name: make_release_common_cuda/teardown-instance
     if: ${{ always() && needs.setup-instance.result == 'success' }}
     needs: [setup-instance, publish-cuda-release]
     runs-on: ubuntu-latest
     steps:
       - name: Stop instance
         id: stop-instance
-        uses: zama-ai/slab-github-runner@0a812986560d3f10dc65728b1ccb9ae4c48a8a16 # v1.5.1
+        uses: zama-ai/slab-github-runner@5aee5d157f4a0201e5eaefc9cc648e5f9f5472a5 # v1.6.0
         with:
           mode: stop
           github-token: ${{ secrets.SLAB_ACTION_TOKEN }}
@@ -232,7 +262,7 @@ jobs:
 
       - name: Slack Notification
         if: ${{ failure() }}
-        uses: rtCamp/action-slack-notify@e31e87e03dd19038e411e38ae27cbad084a90661
+        uses: rtCamp/action-slack-notify@e31e87e03dd19038e411e38ae27cbad084a90661 # v2.3.3
         env:
           SLACK_COLOR: ${{ job.status }}
-          SLACK_MESSAGE: "Instance teardown (publish-cuda-release) finished with status: ${{ job.status }}. (${{ env.ACTION_RUN_URL }})"
+          SLACK_MESSAGE: "Instance teardown (${{ inputs.package-name }} release) finished with status: ${{ job.status }}. (${{ env.ACTION_RUN_URL }})"

.github/workflows/make_release_tfhe.yml

@@ -16,6 +16,10 @@ on:
         description: "Push web js package"
         type: boolean
         default: true
+      push_web_compat_package:
+        description: "Push web compat (cross-origin) js package"
+        type: boolean
+        default: true
       push_node_package:
         description: "Push node js package"
         type: boolean
@@ -85,7 +89,7 @@ jobs:
           make build_web_js_api_parallel
 
       - name: Authenticate on NPM
-        uses: actions/setup-node@53b83947a5a98c8d113130e565377fae1a50d02f # v6.3.0
+        uses: actions/setup-node@48b55a011bda9f5d6aeb4c2d9c7362e8dae4041e # v6.4.0
         with:
           node-version: '24'
           registry-url: 'https://registry.npmjs.org'
@@ -99,6 +103,23 @@ jobs:
           tag: ${{ env.NPM_TAG }}
           provenance: true
 
+      - name: Build web compat (cross-origin) package
+        if: ${{ inputs.push_web_compat_package }}
+        run: |
+          rm -rf tfhe/pkg
+
+          make build_web_js_api
+          sed -i 's/"tfhe"/"tfhe-compat"/g' tfhe/pkg/package.json
+
+      - name: Publish web compat (cross-origin) package
+        if: ${{ inputs.push_web_compat_package }}
+        uses: JS-DevTools/npm-publish@0fd2f4369c5d6bcfcde6091a7c527d810b9b5c3f
+        with:
+          package: tfhe/pkg/package.json
+          dry-run: ${{ inputs.dry_run }}
+          tag: ${{ env.NPM_TAG }}
+          provenance: true
+
       - name: Build Node package
         if: ${{ inputs.push_node_package }}
         run: |

.github/workflows/make_release_tfhe_cuda.yml

@@ -0,0 +1,44 @@
+# Publish new release of tfhe-rs CUDA backend on crates.io.
+name: make_release_tfhe_cuda
+
+on:
+  workflow_dispatch:
+    inputs:
+      dry_run:
+        description: "Dry-run"
+        type: boolean
+        default: true
+
+env:
+  ACTION_RUN_URL: ${{ github.server_url }}/${{ github.repository }}/actions/runs/${{ github.run_id }}
+  SLACK_CHANNEL: ${{ secrets.SLACK_CHANNEL }}
+  SLACK_ICON: https://pbs.twimg.com/profile_images/1274014582265298945/OjBKP9kn_400x400.png
+  SLACK_USERNAME: ${{ secrets.BOT_USERNAME }}
+  SLACK_WEBHOOK: ${{ secrets.SLACK_WEBHOOK }}
+
+permissions: {}
+
+# zizmor: ignore[concurrency-limits] only Zama organization members can trigger this workflow
+
+jobs:
+  make-release:
+    name: make_release_tfhe_cuda/make-release
+    uses: ./.github/workflows/make_release_common_cuda.yml
+    with:
+      package-name: "tfhe-cuda-backend"
+      dry-run: ${{ inputs.dry_run }}
+    permissions:
+      actions: read # Needed to detect the GitHub Actions environment
+      id-token: write # Needed to create the provenance via GitHub OIDC
+      contents: write # Needed to upload assets/artifacts
+    secrets:
+      BOT_USERNAME: ${{ secrets.BOT_USERNAME }}
+      SLACK_CHANNEL: ${{ secrets.SLACK_CHANNEL }}
+      SLACK_WEBHOOK: ${{ secrets.SLACK_WEBHOOK }}
+      REPO_CHECKOUT_TOKEN: ${{ secrets.REPO_CHECKOUT_TOKEN }}
+      ALLOWED_TEAM: ${{ secrets.RELEASE_TEAM }}
+      READ_ORG_TOKEN: ${{ secrets.READ_ORG_TOKEN }}
+      SLAB_ACTION_TOKEN: ${{ secrets.SLAB_ACTION_TOKEN }}
+      SLAB_BASE_URL: ${{ secrets.SLAB_BASE_URL }}
+      SLAB_URL: ${{ secrets.SLAB_URL }}
+      JOB_SECRET: ${{ secrets.JOB_SECRET }}

.github/workflows/make_release_tfhe_safe_serialize.yml

@@ -0,0 +1,32 @@
+name: make_release_tfhe_safe_serialize
+
+on:
+  workflow_dispatch:
+    inputs:
+      dry_run:
+        description: "Dry-run"
+        type: boolean
+        default: true
+
+permissions: {}
+
+# zizmor: ignore[concurrency-limits] only Zama organization members can trigger this workflow
+
+jobs:
+  make-release:
+    name: make_release_tfhe_safe_serialize/make-release
+    uses: ./.github/workflows/make_release_common.yml
+    with:
+      package-name: "tfhe-safe-serialize"
+      dry-run: ${{ inputs.dry_run }}
+    permissions:
+      actions: read # Needed to detect the GitHub Actions environment
+      id-token: write # Needed to create the provenance via GitHub OIDC
+      contents: write # Needed to upload assets/artifacts
+    secrets:
+      BOT_USERNAME: ${{ secrets.BOT_USERNAME }}
+      SLACK_CHANNEL: ${{ secrets.SLACK_CHANNEL }}
+      SLACK_WEBHOOK: ${{ secrets.SLACK_WEBHOOK }}
+      REPO_CHECKOUT_TOKEN: ${{ secrets.REPO_CHECKOUT_TOKEN }}
+      ALLOWED_TEAM: ${{ secrets.RELEASE_TEAM }}
+      READ_ORG_TOKEN: ${{ secrets.READ_ORG_TOKEN }}

.github/workflows/make_release_zk_cuda.yml

@@ -0,0 +1,44 @@
+# Publish new release of CUDA Zero-Knowledge primitives on crates.io.
+name: make_release_zk_cuda
+
+on:
+  workflow_dispatch:
+    inputs:
+      dry_run:
+        description: "Dry-run"
+        type: boolean
+        default: true
+
+env:
+  ACTION_RUN_URL: ${{ github.server_url }}/${{ github.repository }}/actions/runs/${{ github.run_id }}
+  SLACK_CHANNEL: ${{ secrets.SLACK_CHANNEL }}
+  SLACK_ICON: https://pbs.twimg.com/profile_images/1274014582265298945/OjBKP9kn_400x400.png
+  SLACK_USERNAME: ${{ secrets.BOT_USERNAME }}
+  SLACK_WEBHOOK: ${{ secrets.SLACK_WEBHOOK }}
+
+permissions: {}
+
+# zizmor: ignore[concurrency-limits] only Zama organization members can trigger this workflow
+
+jobs:
+  make-release:
+    name: make_release_zk_cuda/make-release
+    uses: ./.github/workflows/make_release_common_cuda.yml
+    with:
+      package-name: "zk-cuda-backend"
+      dry-run: ${{ inputs.dry_run }}
+    permissions:
+      actions: read # Needed to detect the GitHub Actions environment
+      id-token: write # Needed to create the provenance via GitHub OIDC
+      contents: write # Needed to upload assets/artifacts
+    secrets:
+      BOT_USERNAME: ${{ secrets.BOT_USERNAME }}
+      SLACK_CHANNEL: ${{ secrets.SLACK_CHANNEL }}
+      SLACK_WEBHOOK: ${{ secrets.SLACK_WEBHOOK }}
+      REPO_CHECKOUT_TOKEN: ${{ secrets.REPO_CHECKOUT_TOKEN }}
+      ALLOWED_TEAM: ${{ secrets.RELEASE_TEAM }}
+      READ_ORG_TOKEN: ${{ secrets.READ_ORG_TOKEN }}
+      SLAB_ACTION_TOKEN: ${{ secrets.SLAB_ACTION_TOKEN }}
+      SLAB_BASE_URL: ${{ secrets.SLAB_BASE_URL }}
+      SLAB_URL: ${{ secrets.SLAB_URL }}
+      JOB_SECRET: ${{ secrets.JOB_SECRET }}

.github/workflows/parameters_check.yml

@@ -53,7 +53,7 @@ jobs:
 
       - name: Restore Sagemath image from cache
         id: docker-cache
-        uses: actions/cache/restore@cdf6c1fa76f9f475f3d7449005a359c84ca0f306 #v5.0.3
+        uses: actions/cache/restore@668228422ae6a00e4ad889ee87cd7109ec5666a7 #v5.0.4
         with:
           path: /tmp/sagemath_image
           key: sagemath-image-${{ env.SAGEMATH_VERSION }}-${{ github.sha }}
@@ -76,7 +76,7 @@ jobs:
       - name: Store Sagemath image in cache
         if: steps.docker-cache.outputs.cache-hit != 'true'
         continue-on-error: true
-        uses: actions/cache/save@cdf6c1fa76f9f475f3d7449005a359c84ca0f306 #v5.0.3
+        uses: actions/cache/save@668228422ae6a00e4ad889ee87cd7109ec5666a7 #v5.0.4
         with:
           path: /tmp/sagemath_image
           key: sagemath-image-${{ env.SAGEMATH_VERSION }}-${{ github.sha }}

Cargo.toml

@@ -19,6 +19,7 @@ members = [
     "utils/tfhe-backward-compat-checker",
     "utils/tfhe-backward-compat-data",
     "utils/tfhe-backward-compat-data/crates/add_new_version",
+    "utils/tfhe-safe-serialize",
     "utils/tfhe-versionable",
     "utils/tfhe-versionable-derive",
     "utils/wasm-par-mq",

LICENSE

@@ -1,6 +1,6 @@
 BSD 3-Clause Clear License
 
-Copyright © 2025 ZAMA.
+Copyright © 2026 ZAMA.
 All rights reserved.
 
 Redistribution and use in source and binary forms, with or without modification,

Makefile

@@ -312,7 +312,7 @@ semgrep_and_lint_gpu_code: semgrep_lint_setup_venv
 	find "$(TFHECUDA_SRC)" -name '*.h' -o -name '*.cuh' -o -name '*.cu' \
 		| grep -v '/cmake-build-debug/' \
 		| grep -v '/build/' \
-		| xargs venv/bin/semgrep --config "$(TFHECUDA_SRC)/.semgrep/release-ordering.yaml" --scan-unknown-extensions
+		| xargs venv/bin/semgrep --error --config "$(TFHECUDA_SRC)/.semgrep/release-ordering.yaml" --scan-unknown-extensions
 	venv/bin/python3 "scripts/check_scratch_cleanup.py"
 
 .PHONY: semver_check_cuda_backend # Run semver checks on tfhe-cuda-backend
@@ -360,7 +360,7 @@ check_fmt_toml: install_taplo
 
 .PHONY: check_typos # Check for typos in codebase
 check_typos: install_typos_checker
-	@git ls-files ":!*.png" ":!*.cbor" ":!*.bcode" ":!*.ico" ":!*/twiddles.cu" | typos --file-list - && echo "No typos found"
+	@git ls-files ":!*.png" ":!*.cbor" ":!*.bcode" ":!*.ico" ":!*/twiddles.cu" ":!*.hpu" | typos --file-list - && echo "No typos found"
 
 .PHONY: clippy_gpu # Run clippy lints on tfhe with "gpu" enabled
 clippy_gpu: install_rs_check_toolchain
@@ -557,6 +557,11 @@ clippy_versionable: install_rs_check_toolchain
 	RUSTFLAGS="$(RUSTFLAGS)" cargo "$(CARGO_RS_CHECK_TOOLCHAIN)" clippy --all-targets \
 		-p tfhe-versionable -- --no-deps -D warnings
 
+.PHONY: clippy_safe_serialize # Run clippy lints on tfhe-safe-serialize
+clippy_safe_serialize: install_rs_check_toolchain
+	RUSTFLAGS="$(RUSTFLAGS)" cargo "$(CARGO_RS_CHECK_TOOLCHAIN)" clippy --all-targets \
+		-p tfhe-safe-serialize -- --no-deps -D warnings
+
 .PHONY: clippy_param_dedup # Run clippy lints on param_dedup tool
 clippy_param_dedup: install_rs_check_toolchain
 	RUSTFLAGS="$(RUSTFLAGS)" cargo "$(CARGO_RS_CHECK_TOOLCHAIN)" clippy --all-targets \
@@ -582,6 +587,17 @@ clippy_backward_compat_data: install_rs_check_toolchain # the toolchain is selec
 		echo "Cannot run clippy for backward compat crate on non x86 platform for now."; \
 	fi
 
+.PHONY: check_backward_compat_locks_did_not_change # Check backward compat Cargo.lock files are up to date
+check_backward_compat_locks_did_not_change: install_rs_check_toolchain
+	@for crate in `ls -1 $(BACKWARD_COMPAT_DATA_DIR)/crates/ | grep generate_`; do \
+		echo "checking Cargo.lock for $$crate"; \
+		cargo "$(CARGO_RS_CHECK_TOOLCHAIN)" -Z unstable-options \
+			-C $(BACKWARD_COMPAT_DATA_DIR)/crates/$$crate metadata --locked --format-version 1 > /dev/null || \
+		( echo "Cargo.lock for $$crate is out of date. Update it with:" && \
+		  echo "  cd $(BACKWARD_COMPAT_DATA_DIR)/crates/$$crate && cargo metadata --format-version 1 > /dev/null" && \
+		  echo "then commit the updated Cargo.lock." && exit 1 ); \
+	done
+
 .PHONY: clippy_test_vectors # Run clippy lints on the test vectors app
 clippy_test_vectors: install_rs_check_toolchain
 	cd apps/test-vectors; RUSTFLAGS="$(RUSTFLAGS)" cargo "$(CARGO_RS_CHECK_TOOLCHAIN)" clippy --all-targets \
@@ -592,7 +608,7 @@ clippy_test_vectors: install_rs_check_toolchain
 .PHONY: clippy_all # Run all clippy targets
 clippy_all: clippy_rustdoc clippy clippy_boolean clippy_shortint clippy_integer clippy_all_targets \
 clippy_c_api clippy_js_wasm_api clippy_tasks clippy_core clippy_tfhe_csprng clippy_zk_pok clippy_zk_pok_wasm clippy_trivium \
-clippy_versionable clippy_tfhe_lints clippy_ws_tests clippy_bench clippy_param_dedup \
+clippy_versionable clippy_safe_serialize clippy_tfhe_lints clippy_ws_tests clippy_bench clippy_param_dedup \
 clippy_test_vectors clippy_backward_compat_data clippy_wasm_par_mq
 
 .PHONY: clippy_fast # Run main clippy targets
@@ -1270,6 +1286,11 @@ test_versionable:
 	RUSTFLAGS="$(RUSTFLAGS)" cargo test --profile $(CARGO_PROFILE) \
 		--all-targets -p tfhe-versionable
 
+.PHONY: test_safe_serialize # Run tests for tfhe-safe-serialize subcrate
+test_safe_serialize:
+	RUSTFLAGS="$(RUSTFLAGS)" cargo test --profile $(CARGO_PROFILE) \
+		--all-targets -p tfhe-safe-serialize
+
 # The backward compat data folder holds historical binary data but also rust code to generate and load them.
 .PHONY: gen_backward_compat_data # Re-generate backward compatibility data
 gen_backward_compat_data:
@@ -1924,25 +1945,25 @@ bench_hlapi_hpu: install_rs_check_toolchain
 	--bench hlapi \
 	--features=integer,internal-keycache,hpu,hpu-v80,pbs-stats -p tfhe-benchmark --
 
-.PHONY: bench_hlapi_erc20 # Run benchmarks for ERC20 operations
-bench_hlapi_erc20: install_rs_check_toolchain
+.PHONY: bench_hlapi_erc7984 # Run benchmarks for ERC7984 operations
+bench_hlapi_erc7984: install_rs_check_toolchain
 	RUSTFLAGS="$(RUSTFLAGS)" __TFHE_RS_BENCH_TYPE=$(BENCH_TYPE) \
 	cargo $(CARGO_RS_CHECK_TOOLCHAIN) bench \
-	--bench hlapi-erc20 \
+	--bench hlapi-erc7984 \
 	--features=integer,internal-keycache,pbs-stats -p tfhe-benchmark --
 
-.PHONY: bench_hlapi_erc20_gpu # Run benchmarks for ERC20 operations on GPU
-bench_hlapi_erc20_gpu: install_rs_check_toolchain
+.PHONY: bench_hlapi_erc7984_gpu # Run benchmarks for ERC7984 operations on GPU
+bench_hlapi_erc7984_gpu: install_rs_check_toolchain
 	RUSTFLAGS="$(RUSTFLAGS)" __TFHE_RS_BENCH_TYPE=$(BENCH_TYPE) __TFHE_RS_PARAM_TYPE=$(BENCH_PARAM_TYPE) \
 	cargo $(CARGO_RS_CHECK_TOOLCHAIN) bench \
-	--bench hlapi-erc20 \
+	--bench hlapi-erc7984 \
 	--features=integer,gpu,internal-keycache,pbs-stats -p tfhe-benchmark --profile release_lto_off --
 
-.PHONY: bench_hlapi_erc20_gpu_classical # Run benchmarks for ERC20 operations on GPU with classical parameters
-bench_hlapi_erc20_gpu_classical: install_rs_check_toolchain
+.PHONY: bench_hlapi_erc7984_gpu_classical # Run benchmarks for ERC7984 operations on GPU with classical parameters
+bench_hlapi_erc7984_gpu_classical: install_rs_check_toolchain
 	RUSTFLAGS="$(RUSTFLAGS)" __TFHE_RS_BENCH_TYPE=$(BENCH_TYPE) __TFHE_RS_PARAM_TYPE=classical \
 	cargo $(CARGO_RS_CHECK_TOOLCHAIN) bench \
-	--bench hlapi-erc20 \
+	--bench hlapi-erc7984 \
 	--features=integer,gpu,internal-keycache,pbs-stats -p tfhe-benchmark --profile release_lto_off --
 
 .PHONY: bench_hlapi_dex # Run benchmarks for DEX operations
@@ -1966,13 +1987,13 @@ bench_hlapi_dex_gpu_classical: install_rs_check_toolchain
 	--bench hlapi-dex \
 	--features=integer,gpu,internal-keycache,pbs-stats -p tfhe-benchmark --profile release_lto_off --
 
-.PHONY: bench_hlapi_erc20_hpu # Run benchmarks for ECR20 operations on HPU
-bench_hlapi_erc20_hpu: install_rs_check_toolchain
+.PHONY: bench_hlapi_erc7984_hpu # Run benchmarks for ECR20 operations on HPU
+bench_hlapi_erc7984_hpu: install_rs_check_toolchain
 	source ./setup_hpu.sh --config $(HPU_CONFIG); \
 	export V80_PCIE_DEV=${V80_PCIE_DEV}; \
 	RUSTFLAGS="$(RUSTFLAGS)" __TFHE_RS_BENCH_TYPE=$(BENCH_TYPE) \
 	cargo $(CARGO_RS_CHECK_TOOLCHAIN) bench \
-	--bench hlapi-erc20 \
+	--bench hlapi-erc7984 \
 	--features=integer,internal-keycache,hpu,hpu-v80,pbs-stats -p tfhe-benchmark --
 
 .PHONY: bench_tfhe_zk_pok # Run benchmarks for the tfhe_zk_pok crate
@@ -2028,10 +2049,10 @@ bench_summary: install_rs_check_toolchain
 	--bench hlapi-noise-squash \
 	--features=integer,internal-keycache,pbs-stats -p tfhe-benchmark -- '::decomp_noise_squash_comp::'
 
-	# ERC20
+	# ERC7984
 	RUSTFLAGS="$(RUSTFLAGS)" __TFHE_RS_BENCH_TYPE=$(BENCH_TYPE) __TFHE_RS_PARAM_TYPE=$(BENCH_PARAM_TYPE) \
 	cargo $(CARGO_RS_CHECK_TOOLCHAIN) bench \
-	--bench hlapi-erc20 \
+	--bench hlapi-erc7984 \
 	--features=integer,internal-keycache -p tfhe-benchmark -- '::transfer::overflow'
 
 	# DEX
@@ -2073,10 +2094,10 @@ bench_summary_gpu: install_rs_check_toolchain
 	--bench hlapi-noise-squash \
 	--features=integer,gpu,internal-keycache,pbs-stats -p tfhe-benchmark --profile release_lto_off -- '::decomp_noise_squash_comp::'
 
-	# ERC20
+	# ERC7984
 	RUSTFLAGS="$(RUSTFLAGS)" __TFHE_RS_BENCH_TYPE=$(BENCH_TYPE) __TFHE_RS_PARAM_TYPE=$(BENCH_PARAM_TYPE) \
 	cargo $(CARGO_RS_CHECK_TOOLCHAIN) bench \
-	--bench hlapi-erc20 \
+	--bench hlapi-erc7984 \
 	--features=integer,gpu,internal-keycache -p tfhe-benchmark --profile release_lto_off -- '::transfer::overflow'
 
 	# DEX
@@ -2255,6 +2276,7 @@ pcc_batch_5:
 	$(call run_recipe_with_details,clippy_tfhe_lints)
 	$(call run_recipe_with_details,check_compile_tests)
 	$(call run_recipe_with_details,clippy_backward_compat_data)
+	$(call run_recipe_with_details,check_backward_compat_locks_did_not_change)
 
 .PHONY: pcc_batch_6  # duration: 6'32''
 pcc_batch_6:
@@ -2266,6 +2288,7 @@ pcc_batch_6:
 	$(call run_recipe_with_details,clippy_zk_pok_wasm)
 	$(call run_recipe_with_details,clippy_trivium)
 	$(call run_recipe_with_details,clippy_versionable)
+	$(call run_recipe_with_details,clippy_safe_serialize)
 	$(call run_recipe_with_details,clippy_param_dedup)
 	$(call run_recipe_with_details,docs)
 

backends/tfhe-cuda-backend/Cargo.toml

@@ -1,6 +1,6 @@
 [package]
 name = "tfhe-cuda-backend"
-version = "0.14.0"
+version = "0.15.0"
 edition = "2021"
 authors = ["Zama team"]
 license = "BSD-3-Clause-Clear"

backends/tfhe-cuda-backend/LICENSE

@@ -1,6 +1,6 @@
 BSD 3-Clause Clear License
 
-Copyright © 2025 ZAMA.
+Copyright © 2026 ZAMA.
 All rights reserved.
 
 Redistribution and use in source and binary forms, with or without modification,

backends/tfhe-cuda-backend/build.rs

@@ -1,5 +1,14 @@
 use std::path::PathBuf;
-use std::process::Command;
+
+fn get_linux_distribution_name() -> Option<String> {
+    let content = std::fs::read_to_string("/etc/os-release").ok()?;
+    for line in content.lines() {
+        if let Some(value) = line.strip_prefix("NAME=") {
+            return Some(value.trim_matches('"').to_string());
+        }
+    }
+    None
+}
 
 fn main() {
     if let Ok(val) = std::env::var("DOCS_RS") {
@@ -28,9 +37,7 @@ fn main() {
     println!("cargo::rerun-if-changed=src");
 
     if std::env::consts::OS == "linux" {
-        let output = Command::new("./get_os_name.sh").output().unwrap();
-        let distribution = String::from_utf8(output.stdout).unwrap();
-        if distribution != "Ubuntu\n" {
+        if get_linux_distribution_name().as_deref() != Some("Ubuntu") {
             println!(
                 "cargo:warning=This Linux distribution is not officially supported. \
                 Only Ubuntu is supported by tfhe-cuda-backend at this time. Build may fail\n"

backends/tfhe-cuda-backend/cuda/include/aes/aes.h

@@ -4,22 +4,18 @@
 
 extern "C" {
 uint64_t scratch_cuda_integer_aes_ctr_encrypt_64_async(
-    CudaStreamsFFI streams, int8_t **mem_ptr, uint32_t glwe_dimension,
-    uint32_t polynomial_size, uint32_t lwe_dimension, uint32_t ks_level,
-    uint32_t ks_base_log, uint32_t pbs_level, uint32_t pbs_base_log,
-    uint32_t grouping_factor, uint32_t message_modulus, uint32_t carry_modulus,
-    PBS_TYPE pbs_type, bool allocate_gpu_memory,
-    PBS_MS_REDUCTION_T noise_reduction_type, uint32_t num_aes_inputs,
-    uint32_t sbox_parallelism);
+    CudaStreamsFFI streams, int8_t **mem_ptr,
+    CudaLweBootstrapKeyParamsFFI bsk_params, uint32_t ks_level,
+    uint32_t ks_base_log, uint32_t message_modulus, uint32_t carry_modulus,
+    bool allocate_gpu_memory, PBS_MS_REDUCTION_T noise_reduction_type,
+    uint32_t num_aes_inputs, uint32_t sbox_parallelism);
 
 uint64_t scratch_cuda_integer_aes_ctr_256_encrypt_64_async(
-    CudaStreamsFFI streams, int8_t **mem_ptr, uint32_t glwe_dimension,
-    uint32_t polynomial_size, uint32_t lwe_dimension, uint32_t ks_level,
-    uint32_t ks_base_log, uint32_t pbs_level, uint32_t pbs_base_log,
-    uint32_t grouping_factor, uint32_t message_modulus, uint32_t carry_modulus,
-    PBS_TYPE pbs_type, bool allocate_gpu_memory,
-    PBS_MS_REDUCTION_T noise_reduction_type, uint32_t num_aes_inputs,
-    uint32_t sbox_parallelism);
+    CudaStreamsFFI streams, int8_t **mem_ptr,
+    CudaLweBootstrapKeyParamsFFI bsk_params, uint32_t ks_level,
+    uint32_t ks_base_log, uint32_t message_modulus, uint32_t carry_modulus,
+    bool allocate_gpu_memory, PBS_MS_REDUCTION_T noise_reduction_type,
+    uint32_t num_aes_inputs, uint32_t sbox_parallelism);
 
 void cuda_integer_aes_ctr_encrypt_64_async(
     CudaStreamsFFI streams, CudaRadixCiphertextFFI *output,
@@ -34,12 +30,10 @@ void cleanup_cuda_integer_aes_ctr_256_encrypt_64(CudaStreamsFFI streams,
                                                  int8_t **mem_ptr_void);
 
 uint64_t scratch_cuda_integer_key_expansion_64_async(
-    CudaStreamsFFI streams, int8_t **mem_ptr, uint32_t glwe_dimension,
-    uint32_t polynomial_size, uint32_t lwe_dimension, uint32_t ks_level,
-    uint32_t ks_base_log, uint32_t pbs_level, uint32_t pbs_base_log,
-    uint32_t grouping_factor, uint32_t message_modulus, uint32_t carry_modulus,
-    PBS_TYPE pbs_type, bool allocate_gpu_memory,
-    PBS_MS_REDUCTION_T noise_reduction_type);
+    CudaStreamsFFI streams, int8_t **mem_ptr,
+    CudaLweBootstrapKeyParamsFFI bsk_params, uint32_t ks_level,
+    uint32_t ks_base_log, uint32_t message_modulus, uint32_t carry_modulus,
+    bool allocate_gpu_memory, PBS_MS_REDUCTION_T noise_reduction_type);
 
 void cuda_integer_key_expansion_64_async(CudaStreamsFFI streams,
                                          CudaRadixCiphertextFFI *expanded_keys,
@@ -57,12 +51,10 @@ void cuda_integer_aes_ctr_256_encrypt_64_async(
     int8_t *mem_ptr, void *const *bsks, void *const *ksks);
 
 uint64_t scratch_cuda_integer_key_expansion_256_64_async(
-    CudaStreamsFFI streams, int8_t **mem_ptr, uint32_t glwe_dimension,
-    uint32_t polynomial_size, uint32_t lwe_dimension, uint32_t ks_level,
-    uint32_t ks_base_log, uint32_t pbs_level, uint32_t pbs_base_log,
-    uint32_t grouping_factor, uint32_t message_modulus, uint32_t carry_modulus,
-    PBS_TYPE pbs_type, bool allocate_gpu_memory,
-    PBS_MS_REDUCTION_T noise_reduction_type);
+    CudaStreamsFFI streams, int8_t **mem_ptr,
+    CudaLweBootstrapKeyParamsFFI bsk_params, uint32_t ks_level,
+    uint32_t ks_base_log, uint32_t message_modulus, uint32_t carry_modulus,
+    bool allocate_gpu_memory, PBS_MS_REDUCTION_T noise_reduction_type);
 
 void cuda_integer_key_expansion_256_64_async(
     CudaStreamsFFI streams, CudaRadixCiphertextFFI *expanded_keys,

backends/tfhe-cuda-backend/cuda/include/ciphertext.h

@@ -36,5 +36,19 @@ void cuda_glwe_sample_extract_128_async(
     void const *glwe_array_in, uint32_t const *nth_array, uint32_t num_nths,
     uint32_t num_lwes_to_extract_per_glwe, uint32_t num_lwes_stored_per_glwe,
     uint32_t glwe_dimension, uint32_t polynomial_size);
+
+void cuda_modulus_switch_multi_bit_64_async(void *stream, uint32_t gpu_index,
+                                            void *lwe_array_out,
+                                            void *lwe_array_in, uint32_t size,
+                                            uint32_t log_modulus,
+                                            uint32_t degree,
+                                            uint32_t grouping_factor);
+
+void cuda_modulus_switch_multi_bit_128_async(void *stream, uint32_t gpu_index,
+                                             void *lwe_array_out,
+                                             void *lwe_array_in, uint32_t size,
+                                             uint32_t log_modulus,
+                                             uint32_t degree,
+                                             uint32_t grouping_factor);
 }
 #endif

backends/tfhe-cuda-backend/cuda/include/integer/compression/compression.h

@@ -17,10 +17,9 @@ uint64_t scratch_cuda_integer_decompress_radix_ciphertext_64_async(
     CudaStreamsFFI streams, int8_t **mem_ptr,
     uint32_t encryption_glwe_dimension, uint32_t encryption_polynomial_size,
     uint32_t compression_glwe_dimension, uint32_t compression_polynomial_size,
-    uint32_t lwe_dimension, uint32_t pbs_level, uint32_t pbs_base_log,
-    uint32_t grouping_factor, uint32_t num_blocks_to_decompress,
-    uint32_t message_modulus, uint32_t carry_modulus, PBS_TYPE pbs_type,
-    bool allocate_gpu_memory, PBS_MS_REDUCTION_T noise_reduction_type);
+    CudaLweBootstrapKeyParamsFFI bsk_params, uint32_t num_blocks_to_decompress,
+    uint32_t message_modulus, uint32_t carry_modulus, bool allocate_gpu_memory,
+    PBS_MS_REDUCTION_T noise_reduction_type);
 
 void cuda_integer_compress_radix_ciphertext_64_async(
     CudaStreamsFFI streams, CudaPackedGlweCiphertextListFFI *glwe_array_out,

backends/tfhe-cuda-backend/cuda/include/integer/integer.h

@@ -105,22 +105,32 @@ typedef struct {
   uint32_t polynomial_size;
 } CudaPackedGlweCiphertextListFFI;
 
+// FFI-boundary parameter struct for a LWE bootstrap key.
+// All fields are plain uint32_t for safe Rust/C++ interop.
+// Use crypto_params() (defined below) to obtain the strongly-typed C++ form.
+typedef struct {
+  uint32_t input_lwe_dimension;
+  uint32_t glwe_dimension;
+  uint32_t polynomial_size;
+  uint32_t base_log;
+  uint32_t level_count;
+  uint32_t big_lwe_dimension;
+  uint32_t pbs_type;
+  uint32_t grouping_factor;
+} CudaLweBootstrapKeyParamsFFI;
+
 uint64_t scratch_cuda_apply_univariate_lut_64_async(
     CudaStreamsFFI streams, int8_t **mem_ptr, void const *input_lut,
-    uint32_t lwe_dimension, uint32_t glwe_dimension, uint32_t polynomial_size,
-    uint32_t ks_level, uint32_t ks_base_log, uint32_t pbs_level,
-    uint32_t pbs_base_log, uint32_t grouping_factor,
-    uint32_t input_lwe_ciphertext_count, uint32_t message_modulus,
-    uint32_t carry_modulus, PBS_TYPE pbs_type, uint64_t lut_degree,
+    CudaLweBootstrapKeyParamsFFI bsk_params, uint32_t ks_level,
+    uint32_t ks_base_log, uint32_t input_lwe_ciphertext_count,
+    uint32_t message_modulus, uint32_t carry_modulus, uint64_t lut_degree,
     bool allocate_gpu_memory, PBS_MS_REDUCTION_T noise_reduction_type);
 uint64_t scratch_cuda_apply_many_univariate_lut_64_async(
     CudaStreamsFFI streams, int8_t **mem_ptr, void const *input_lut,
-    uint32_t lwe_dimension, uint32_t glwe_dimension, uint32_t polynomial_size,
-    uint32_t ks_level, uint32_t ks_base_log, uint32_t pbs_level,
-    uint32_t pbs_base_log, uint32_t grouping_factor, uint32_t num_radix_blocks,
-    uint32_t message_modulus, uint32_t carry_modulus, PBS_TYPE pbs_type,
-    uint32_t num_many_lut, uint64_t lut_degree, bool allocate_gpu_memory,
-    PBS_MS_REDUCTION_T noise_reduction_type);
+    CudaLweBootstrapKeyParamsFFI bsk_params, uint32_t ks_level,
+    uint32_t ks_base_log, uint32_t num_radix_blocks, uint32_t message_modulus,
+    uint32_t carry_modulus, uint32_t num_many_lut, uint64_t lut_degree,
+    bool allocate_gpu_memory, PBS_MS_REDUCTION_T noise_reduction_type);
 void cuda_apply_univariate_lut_64_async(
     CudaStreamsFFI streams, CudaRadixCiphertextFFI *output_radix_lwe,
     CudaRadixCiphertextFFI const *input_radix_lwe, int8_t *mem_ptr,
@@ -139,12 +149,10 @@ void cuda_apply_many_univariate_lut_64_async(
     uint32_t lut_stride);
 
 uint64_t scratch_cuda_full_propagation_64_inplace_async(
-    CudaStreamsFFI streams, int8_t **mem_ptr, uint32_t lwe_dimension,
-    uint32_t glwe_dimension, uint32_t polynomial_size, uint32_t ks_level,
-    uint32_t ks_base_log, uint32_t pbs_level, uint32_t pbs_base_log,
-    uint32_t grouping_factor, uint32_t message_modulus, uint32_t carry_modulus,
-    PBS_TYPE pbs_type, bool allocate_gpu_memory,
-    PBS_MS_REDUCTION_T noise_reduction_type);
+    CudaStreamsFFI streams, int8_t **mem_ptr,
+    CudaLweBootstrapKeyParamsFFI bsk_params, uint32_t ks_level,
+    uint32_t ks_base_log, uint32_t message_modulus, uint32_t carry_modulus,
+    bool allocate_gpu_memory, PBS_MS_REDUCTION_T noise_reduction_type);
 
 void cuda_full_propagation_64_inplace_async(
     CudaStreamsFFI streams, CudaRadixCiphertextFFI *input_blocks,
@@ -162,11 +170,9 @@ void cuda_integer_mult_inplace_64_async(
 uint64_t scratch_cuda_integer_mult_inplace_64_async(
     CudaStreamsFFI streams, int8_t **mem_ptr, bool const is_boolean_left,
     bool const is_boolean_right, uint32_t message_modulus,
-    uint32_t carry_modulus, uint32_t glwe_dimension, uint32_t lwe_dimension,
-    uint32_t polynomial_size, uint32_t pbs_base_log, uint32_t pbs_level,
-    uint32_t ks_base_log, uint32_t ks_level, uint32_t grouping_factor,
-    uint32_t num_blocks, PBS_TYPE pbs_type, bool allocate_gpu_memory,
-    PBS_MS_REDUCTION_T noise_reduction_type);
+    uint32_t carry_modulus, CudaLweBootstrapKeyParamsFFI bsk_params,
+    uint32_t ks_base_log, uint32_t ks_level, uint32_t num_blocks,
+    bool allocate_gpu_memory, PBS_MS_REDUCTION_T noise_reduction_type);
 
 void cleanup_cuda_integer_mult_inplace_64(CudaStreamsFFI streams,
                                           int8_t **mem_ptr_void);
@@ -183,12 +189,10 @@ void cuda_scalar_addition_ciphertext_64_inplace(
     uint32_t message_modulus, uint32_t carry_modulus);
 
 uint64_t scratch_cuda_logical_scalar_shift_64_inplace_async(
-    CudaStreamsFFI streams, int8_t **mem_ptr, uint32_t glwe_dimension,
-    uint32_t polynomial_size, uint32_t big_lwe_dimension,
-    uint32_t small_lwe_dimension, uint32_t ks_level, uint32_t ks_base_log,
-    uint32_t pbs_level, uint32_t pbs_base_log, uint32_t grouping_factor,
-    uint32_t num_blocks, uint32_t message_modulus, uint32_t carry_modulus,
-    PBS_TYPE pbs_type, SHIFT_OR_ROTATE_TYPE shift_type,
+    CudaStreamsFFI streams, int8_t **mem_ptr,
+    CudaLweBootstrapKeyParamsFFI bsk_params, uint32_t ks_level,
+    uint32_t ks_base_log, uint32_t num_blocks, uint32_t message_modulus,
+    uint32_t carry_modulus, SHIFT_OR_ROTATE_TYPE shift_type,
     bool allocate_gpu_memory, PBS_MS_REDUCTION_T noise_reduction_type);
 
 void cuda_logical_scalar_shift_64_inplace_async(
@@ -196,12 +200,10 @@ void cuda_logical_scalar_shift_64_inplace_async(
     int8_t *mem_ptr, void *const *bsks, void *const *ksks);
 
 uint64_t scratch_cuda_arithmetic_scalar_shift_64_inplace_async(
-    CudaStreamsFFI streams, int8_t **mem_ptr, uint32_t glwe_dimension,
-    uint32_t polynomial_size, uint32_t big_lwe_dimension,
-    uint32_t small_lwe_dimension, uint32_t ks_level, uint32_t ks_base_log,
-    uint32_t pbs_level, uint32_t pbs_base_log, uint32_t grouping_factor,
-    uint32_t num_blocks, uint32_t message_modulus, uint32_t carry_modulus,
-    PBS_TYPE pbs_type, SHIFT_OR_ROTATE_TYPE shift_type,
+    CudaStreamsFFI streams, int8_t **mem_ptr,
+    CudaLweBootstrapKeyParamsFFI bsk_params, uint32_t ks_level,
+    uint32_t ks_base_log, uint32_t num_blocks, uint32_t message_modulus,
+    uint32_t carry_modulus, SHIFT_OR_ROTATE_TYPE shift_type,
     bool allocate_gpu_memory, PBS_MS_REDUCTION_T noise_reduction_type);
 
 void cuda_arithmetic_scalar_shift_64_inplace_async(
@@ -215,12 +217,10 @@ void cleanup_cuda_arithmetic_scalar_shift_64_inplace(CudaStreamsFFI streams,
                                                      int8_t **mem_ptr_void);
 
 uint64_t scratch_cuda_shift_and_rotate_64_inplace_async(
-    CudaStreamsFFI streams, int8_t **mem_ptr, uint32_t glwe_dimension,
-    uint32_t polynomial_size, uint32_t big_lwe_dimension,
-    uint32_t small_lwe_dimension, uint32_t ks_level, uint32_t ks_base_log,
-    uint32_t pbs_level, uint32_t pbs_base_log, uint32_t grouping_factor,
-    uint32_t num_blocks, uint32_t message_modulus, uint32_t carry_modulus,
-    PBS_TYPE pbs_type, SHIFT_OR_ROTATE_TYPE shift_type, bool is_signed,
+    CudaStreamsFFI streams, int8_t **mem_ptr,
+    CudaLweBootstrapKeyParamsFFI bsk_params, uint32_t ks_level,
+    uint32_t ks_base_log, uint32_t num_blocks, uint32_t message_modulus,
+    uint32_t carry_modulus, SHIFT_OR_ROTATE_TYPE shift_type, bool is_signed,
     bool allocate_gpu_memory, PBS_MS_REDUCTION_T noise_reduction_type);
 
 void cuda_shift_and_rotate_64_inplace_async(
@@ -232,22 +232,18 @@ void cleanup_cuda_shift_and_rotate_64_inplace(CudaStreamsFFI streams,
                                               int8_t **mem_ptr_void);
 
 uint64_t scratch_cuda_integer_comparison_64_async(
-    CudaStreamsFFI streams, int8_t **mem_ptr, uint32_t glwe_dimension,
-    uint32_t polynomial_size, uint32_t big_lwe_dimension,
-    uint32_t small_lwe_dimension, uint32_t ks_level, uint32_t ks_base_log,
-    uint32_t pbs_level, uint32_t pbs_base_log, uint32_t grouping_factor,
-    uint32_t lwe_ciphertext_count, uint32_t message_modulus,
-    uint32_t carry_modulus, PBS_TYPE pbs_type, COMPARISON_TYPE op_type,
+    CudaStreamsFFI streams, int8_t **mem_ptr,
+    CudaLweBootstrapKeyParamsFFI bsk_params, uint32_t ks_level,
+    uint32_t ks_base_log, uint32_t lwe_ciphertext_count,
+    uint32_t message_modulus, uint32_t carry_modulus, COMPARISON_TYPE op_type,
     bool is_signed, bool allocate_gpu_memory,
     PBS_MS_REDUCTION_T noise_reduction_type);
 
 uint64_t scratch_cuda_integer_scalar_comparison_64_async(
-    CudaStreamsFFI streams, int8_t **mem_ptr, uint32_t glwe_dimension,
-    uint32_t polynomial_size, uint32_t big_lwe_dimension,
-    uint32_t small_lwe_dimension, uint32_t ks_level, uint32_t ks_base_log,
-    uint32_t pbs_level, uint32_t pbs_base_log, uint32_t grouping_factor,
-    uint32_t lwe_ciphertext_count, uint32_t message_modulus,
-    uint32_t carry_modulus, PBS_TYPE pbs_type, COMPARISON_TYPE op_type,
+    CudaStreamsFFI streams, int8_t **mem_ptr,
+    CudaLweBootstrapKeyParamsFFI bsk_params, uint32_t ks_level,
+    uint32_t ks_base_log, uint32_t lwe_ciphertext_count,
+    uint32_t message_modulus, uint32_t carry_modulus, COMPARISON_TYPE op_type,
     bool is_signed, bool allocate_gpu_memory,
     PBS_MS_REDUCTION_T noise_reduction_type);
 
@@ -276,12 +272,10 @@ void cuda_boolean_bitop_inplace_64_async(
     void *const *bsks, void *const *ksks);
 
 uint64_t scratch_cuda_boolean_bitop_inplace_64_async(
-    CudaStreamsFFI streams, int8_t **mem_ptr, uint32_t glwe_dimension,
-    uint32_t polynomial_size, uint32_t big_lwe_dimension,
-    uint32_t small_lwe_dimension, uint32_t ks_level, uint32_t ks_base_log,
-    uint32_t pbs_level, uint32_t pbs_base_log, uint32_t grouping_factor,
-    uint32_t lwe_ciphertext_count, uint32_t message_modulus,
-    uint32_t carry_modulus, PBS_TYPE pbs_type, BITOP_TYPE op_type,
+    CudaStreamsFFI streams, int8_t **mem_ptr,
+    CudaLweBootstrapKeyParamsFFI bsk_params, uint32_t ks_level,
+    uint32_t ks_base_log, uint32_t lwe_ciphertext_count,
+    uint32_t message_modulus, uint32_t carry_modulus, BITOP_TYPE op_type,
     bool is_unchecked, bool allocate_gpu_memory,
     PBS_MS_REDUCTION_T noise_reduction_type);
 
@@ -289,11 +283,9 @@ void cleanup_cuda_boolean_bitop_inplace_64(CudaStreamsFFI streams,
                                            int8_t **mem_ptr_void);
 
 uint64_t scratch_cuda_boolean_bitnot_64_async(
-    CudaStreamsFFI streams, int8_t **mem_ptr, uint32_t glwe_dimension,
-    uint32_t polynomial_size, uint32_t big_lwe_dimension,
-    uint32_t small_lwe_dimension, uint32_t ks_level, uint32_t ks_base_log,
-    uint32_t pbs_level, uint32_t pbs_base_log, uint32_t grouping_factor,
-    uint32_t message_modulus, uint32_t carry_modulus, PBS_TYPE pbs_type,
+    CudaStreamsFFI streams, int8_t **mem_ptr,
+    CudaLweBootstrapKeyParamsFFI bsk_params, uint32_t ks_level,
+    uint32_t ks_base_log, uint32_t message_modulus, uint32_t carry_modulus,
     uint32_t lwe_ciphertext_count, bool is_unchecked, bool allocate_gpu_memory,
     PBS_MS_REDUCTION_T noise_reduction_type);
 
@@ -311,6 +303,20 @@ void cuda_bitnot_ciphertext_64(CudaStreamsFFI streams,
                                uint32_t param_message_modulus,
                                uint32_t param_carry_modulus);
 
+uint64_t scratch_cuda_integer_bitop_inplace_64_async(
+    CudaStreamsFFI streams, int8_t **mem_ptr,
+    CudaLweBootstrapKeyParamsFFI bsk_params, uint32_t ks_level,
+    uint32_t ks_base_log, uint32_t lwe_ciphertext_count,
+    uint32_t message_modulus, uint32_t carry_modulus, BITOP_TYPE op_type,
+    bool allocate_gpu_memory, PBS_MS_REDUCTION_T noise_reduction_type);
+
+uint64_t scratch_cuda_integer_scalar_bitop_inplace_64_async(
+    CudaStreamsFFI streams, int8_t **mem_ptr,
+    CudaLweBootstrapKeyParamsFFI bsk_params, uint32_t ks_level,
+    uint32_t ks_base_log, uint32_t lwe_ciphertext_count,
+    uint32_t message_modulus, uint32_t carry_modulus, BITOP_TYPE op_type,
+    bool allocate_gpu_memory, PBS_MS_REDUCTION_T noise_reduction_type);
+
 void cuda_integer_bitop_inplace_64_async(
     CudaStreamsFFI streams, CudaRadixCiphertextFFI *lwe_array_inout,
     CudaRadixCiphertextFFI const *lwe_array_2, int8_t *mem_ptr,
@@ -322,38 +328,20 @@ void cuda_integer_scalar_bitop_inplace_64_async(
     uint32_t num_clear_blocks, int8_t *mem_ptr, void *const *bsks,
     void *const *ksks);
 
-uint64_t scratch_cuda_integer_bitop_inplace_64_async(
-    CudaStreamsFFI streams, int8_t **mem_ptr, uint32_t glwe_dimension,
-    uint32_t polynomial_size, uint32_t big_lwe_dimension,
-    uint32_t small_lwe_dimension, uint32_t ks_level, uint32_t ks_base_log,
-    uint32_t pbs_level, uint32_t pbs_base_log, uint32_t grouping_factor,
-    uint32_t lwe_ciphertext_count, uint32_t message_modulus,
-    uint32_t carry_modulus, PBS_TYPE pbs_type, BITOP_TYPE op_type,
-    bool allocate_gpu_memory, PBS_MS_REDUCTION_T noise_reduction_type);
-
 void cleanup_cuda_integer_bitop_inplace_64(CudaStreamsFFI streams,
                                            int8_t **mem_ptr_void);
 
-uint64_t scratch_cuda_integer_scalar_bitop_inplace_64_async(
-    CudaStreamsFFI streams, int8_t **mem_ptr, uint32_t glwe_dimension,
-    uint32_t polynomial_size, uint32_t big_lwe_dimension,
-    uint32_t small_lwe_dimension, uint32_t ks_level, uint32_t ks_base_log,
-    uint32_t pbs_level, uint32_t pbs_base_log, uint32_t grouping_factor,
-    uint32_t lwe_ciphertext_count, uint32_t message_modulus,
-    uint32_t carry_modulus, PBS_TYPE pbs_type, BITOP_TYPE op_type,
-    bool allocate_gpu_memory, PBS_MS_REDUCTION_T noise_reduction_type);
-
 void cleanup_cuda_integer_scalar_bitop_inplace_64(CudaStreamsFFI streams,
                                                   int8_t **mem_ptr_void);
 
-uint64_t scratch_cuda_cmux_64_async(
-    CudaStreamsFFI streams, int8_t **mem_ptr, uint32_t glwe_dimension,
-    uint32_t polynomial_size, uint32_t big_lwe_dimension,
-    uint32_t small_lwe_dimension, uint32_t ks_level, uint32_t ks_base_log,
-    uint32_t pbs_level, uint32_t pbs_base_log, uint32_t grouping_factor,
-    uint32_t lwe_ciphertext_count, uint32_t message_modulus,
-    uint32_t carry_modulus, PBS_TYPE pbs_type, bool allocate_gpu_memory,
-    PBS_MS_REDUCTION_T noise_reduction_type);
+uint64_t scratch_cuda_cmux_64_async(CudaStreamsFFI streams, int8_t **mem_ptr,
+                                    CudaLweBootstrapKeyParamsFFI bsk_params,
+                                    uint32_t ks_level, uint32_t ks_base_log,
+                                    uint32_t lwe_ciphertext_count,
+                                    uint32_t message_modulus,
+                                    uint32_t carry_modulus,
+                                    bool allocate_gpu_memory,
+                                    PBS_MS_REDUCTION_T noise_reduction_type);
 
 void cuda_cmux_64_async(CudaStreamsFFI streams,
                         CudaRadixCiphertextFFI *lwe_array_out,
@@ -365,12 +353,10 @@ void cuda_cmux_64_async(CudaStreamsFFI streams,
 void cleanup_cuda_cmux_64(CudaStreamsFFI streams, int8_t **mem_ptr_void);
 
 uint64_t scratch_cuda_scalar_rotate_64_inplace_async(
-    CudaStreamsFFI streams, int8_t **mem_ptr, uint32_t glwe_dimension,
-    uint32_t polynomial_size, uint32_t big_lwe_dimension,
-    uint32_t small_lwe_dimension, uint32_t ks_level, uint32_t ks_base_log,
-    uint32_t pbs_level, uint32_t pbs_base_log, uint32_t grouping_factor,
-    uint32_t num_blocks, uint32_t message_modulus, uint32_t carry_modulus,
-    PBS_TYPE pbs_type, SHIFT_OR_ROTATE_TYPE shift_type,
+    CudaStreamsFFI streams, int8_t **mem_ptr,
+    CudaLweBootstrapKeyParamsFFI bsk_params, uint32_t ks_level,
+    uint32_t ks_base_log, uint32_t num_blocks, uint32_t message_modulus,
+    uint32_t carry_modulus, SHIFT_OR_ROTATE_TYPE shift_type,
     bool allocate_gpu_memory, PBS_MS_REDUCTION_T noise_reduction_type);
 
 void cuda_scalar_rotate_64_inplace_async(CudaStreamsFFI streams,
@@ -382,21 +368,17 @@ void cleanup_cuda_scalar_rotate_64_inplace(CudaStreamsFFI streams,
                                            int8_t **mem_ptr_void);
 
 uint64_t scratch_cuda_propagate_single_carry_64_inplace_async(
-    CudaStreamsFFI streams, int8_t **mem_ptr, uint32_t glwe_dimension,
-    uint32_t polynomial_size, uint32_t big_lwe_dimension,
-    uint32_t small_lwe_dimension, uint32_t ks_level, uint32_t ks_base_log,
-    uint32_t pbs_level, uint32_t pbs_base_log, uint32_t grouping_factor,
-    uint32_t num_blocks, uint32_t message_modulus, uint32_t carry_modulus,
-    PBS_TYPE pbs_type, uint32_t requested_flag, bool allocate_gpu_memory,
+    CudaStreamsFFI streams, int8_t **mem_ptr,
+    CudaLweBootstrapKeyParamsFFI bsk_params, uint32_t ks_level,
+    uint32_t ks_base_log, uint32_t num_blocks, uint32_t message_modulus,
+    uint32_t carry_modulus, uint32_t requested_flag, bool allocate_gpu_memory,
     PBS_MS_REDUCTION_T noise_reduction_type);
 
 uint64_t scratch_cuda_add_and_propagate_single_carry_64_inplace_async(
-    CudaStreamsFFI streams, int8_t **mem_ptr, uint32_t glwe_dimension,
-    uint32_t polynomial_size, uint32_t big_lwe_dimension,
-    uint32_t small_lwe_dimension, uint32_t ks_level, uint32_t ks_base_log,
-    uint32_t pbs_level, uint32_t pbs_base_log, uint32_t grouping_factor,
-    uint32_t num_blocks, uint32_t message_modulus, uint32_t carry_modulus,
-    PBS_TYPE pbs_type, uint32_t requested_flag, bool allocate_gpu_memory,
+    CudaStreamsFFI streams, int8_t **mem_ptr,
+    CudaLweBootstrapKeyParamsFFI bsk_params, uint32_t ks_level,
+    uint32_t ks_base_log, uint32_t num_blocks, uint32_t message_modulus,
+    uint32_t carry_modulus, uint32_t requested_flag, bool allocate_gpu_memory,
     PBS_MS_REDUCTION_T noise_reduction_type);
 
 void cuda_propagate_single_carry_64_inplace_async(
@@ -418,12 +400,10 @@ void cleanup_cuda_add_and_propagate_single_carry_64_inplace(
     CudaStreamsFFI streams, int8_t **mem_ptr_void);
 
 uint64_t scratch_cuda_integer_overflowing_sub_64_inplace_async(
-    CudaStreamsFFI streams, int8_t **mem_ptr, uint32_t glwe_dimension,
-    uint32_t polynomial_size, uint32_t big_lwe_dimension,
-    uint32_t small_lwe_dimension, uint32_t ks_level, uint32_t ks_base_log,
-    uint32_t pbs_level, uint32_t pbs_base_log, uint32_t grouping_factor,
-    uint32_t num_blocks, uint32_t message_modulus, uint32_t carry_modulus,
-    PBS_TYPE pbs_type, uint32_t compute_overflow, bool allocate_gpu_memory,
+    CudaStreamsFFI streams, int8_t **mem_ptr,
+    CudaLweBootstrapKeyParamsFFI bsk_params, uint32_t ks_level,
+    uint32_t ks_base_log, uint32_t num_blocks, uint32_t message_modulus,
+    uint32_t carry_modulus, uint32_t compute_overflow, bool allocate_gpu_memory,
     PBS_MS_REDUCTION_T noise_reduction_type);
 
 void cuda_integer_overflowing_sub_64_inplace_async(
@@ -438,14 +418,12 @@ void cleanup_cuda_integer_overflowing_sub_64_inplace(CudaStreamsFFI streams,
                                                      int8_t **mem_ptr_void);
 
 uint64_t scratch_cuda_partial_sum_ciphertexts_vec_64_async(
-    CudaStreamsFFI streams, int8_t **mem_ptr, uint32_t glwe_dimension,
-    uint32_t polynomial_size, uint32_t lwe_dimension, uint32_t ks_level,
-    uint32_t ks_base_log, uint32_t pbs_level, uint32_t pbs_base_log,
-    uint32_t grouping_factor, uint32_t num_blocks_in_radix,
+    CudaStreamsFFI streams, int8_t **mem_ptr,
+    CudaLweBootstrapKeyParamsFFI bsk_params, uint32_t ks_level,
+    uint32_t ks_base_log, uint32_t num_blocks_in_radix,
     uint32_t max_num_radix_in_vec, uint32_t message_modulus,
-    uint32_t carry_modulus, PBS_TYPE pbs_type,
-    bool reduce_degrees_for_single_carry_propagation, bool allocate_gpu_memory,
-    PBS_MS_REDUCTION_T noise_reduction_type);
+    uint32_t carry_modulus, bool reduce_degrees_for_single_carry_propagation,
+    bool allocate_gpu_memory, PBS_MS_REDUCTION_T noise_reduction_type);
 
 void cuda_partial_sum_ciphertexts_vec_64_async(
     CudaStreamsFFI streams, CudaRadixCiphertextFFI *radix_lwe_out,
@@ -456,12 +434,11 @@ void cleanup_cuda_partial_sum_ciphertexts_vec_64(CudaStreamsFFI streams,
                                                  int8_t **mem_ptr_void);
 
 uint64_t scratch_cuda_integer_scalar_mul_64_async(
-    CudaStreamsFFI streams, int8_t **mem_ptr, uint32_t glwe_dimension,
-    uint32_t polynomial_size, uint32_t lwe_dimension, uint32_t ks_level,
-    uint32_t ks_base_log, uint32_t pbs_level, uint32_t pbs_base_log,
-    uint32_t grouping_factor, uint32_t num_blocks, uint32_t message_modulus,
-    uint32_t carry_modulus, PBS_TYPE pbs_type, uint32_t num_scalar_bits,
-    bool allocate_gpu_memory, PBS_MS_REDUCTION_T noise_reduction_type);
+    CudaStreamsFFI streams, int8_t **mem_ptr,
+    CudaLweBootstrapKeyParamsFFI bsk_params, uint32_t ks_level,
+    uint32_t ks_base_log, uint32_t num_blocks, uint32_t message_modulus,
+    uint32_t carry_modulus, uint32_t num_scalar_bits, bool allocate_gpu_memory,
+    PBS_MS_REDUCTION_T noise_reduction_type);
 
 void cuda_integer_scalar_mul_64_async(
     CudaStreamsFFI streams, CudaRadixCiphertextFFI *lwe_array,
@@ -474,11 +451,9 @@ void cleanup_cuda_integer_scalar_mul_64(CudaStreamsFFI streams,
 
 uint64_t scratch_cuda_integer_div_rem_64_async(
     CudaStreamsFFI streams, bool is_signed, int8_t **mem_ptr,
-    uint32_t glwe_dimension, uint32_t polynomial_size,
-    uint32_t big_lwe_dimension, uint32_t small_lwe_dimension, uint32_t ks_level,
-    uint32_t ks_base_log, uint32_t pbs_level, uint32_t pbs_base_log,
-    uint32_t grouping_factor, uint32_t num_blocks, uint32_t message_modulus,
-    uint32_t carry_modulus, PBS_TYPE pbs_type, bool allocate_gpu_memory,
+    CudaLweBootstrapKeyParamsFFI bsk_params, uint32_t ks_level,
+    uint32_t ks_base_log, uint32_t num_blocks, uint32_t message_modulus,
+    uint32_t carry_modulus, bool allocate_gpu_memory,
     PBS_MS_REDUCTION_T noise_reduction_type);
 
 void cuda_integer_div_rem_64_async(CudaStreamsFFI streams,
@@ -497,11 +472,9 @@ void cuda_integer_reverse_blocks_64_inplace_async(
 
 uint64_t scratch_cuda_integer_abs_inplace_64_async(
     CudaStreamsFFI streams, int8_t **mem_ptr, bool is_signed,
-    uint32_t glwe_dimension, uint32_t polynomial_size,
-    uint32_t big_lwe_dimension, uint32_t small_lwe_dimension, uint32_t ks_level,
-    uint32_t ks_base_log, uint32_t pbs_level, uint32_t pbs_base_log,
-    uint32_t grouping_factor, uint32_t num_blocks, uint32_t message_modulus,
-    uint32_t carry_modulus, PBS_TYPE pbs_type, bool allocate_gpu_memory,
+    CudaLweBootstrapKeyParamsFFI bsk_params, uint32_t ks_level,
+    uint32_t ks_base_log, uint32_t num_blocks, uint32_t message_modulus,
+    uint32_t carry_modulus, bool allocate_gpu_memory,
     PBS_MS_REDUCTION_T noise_reduction_type);
 
 void cuda_integer_abs_inplace_64_async(CudaStreamsFFI streams,
@@ -513,12 +486,10 @@ void cleanup_cuda_integer_abs_inplace_64(CudaStreamsFFI streams,
                                          int8_t **mem_ptr_void);
 
 uint64_t scratch_cuda_integer_are_all_comparisons_block_true_64_async(
-    CudaStreamsFFI streams, int8_t **mem_ptr, uint32_t glwe_dimension,
-    uint32_t polynomial_size, uint32_t big_lwe_dimension,
-    uint32_t small_lwe_dimension, uint32_t ks_level, uint32_t ks_base_log,
-    uint32_t pbs_level, uint32_t pbs_base_log, uint32_t grouping_factor,
-    uint32_t num_radix_blocks, uint32_t message_modulus, uint32_t carry_modulus,
-    PBS_TYPE pbs_type, bool allocate_gpu_memory,
+    CudaStreamsFFI streams, int8_t **mem_ptr,
+    CudaLweBootstrapKeyParamsFFI bsk_params, uint32_t ks_level,
+    uint32_t ks_base_log, uint32_t num_radix_blocks, uint32_t message_modulus,
+    uint32_t carry_modulus, bool allocate_gpu_memory,
     PBS_MS_REDUCTION_T noise_reduction_type);
 
 void cuda_integer_are_all_comparisons_block_true_64_async(
@@ -530,12 +501,10 @@ void cleanup_cuda_integer_are_all_comparisons_block_true_64(
     CudaStreamsFFI streams, int8_t **mem_ptr_void);
 
 uint64_t scratch_cuda_integer_is_at_least_one_comparisons_block_true_64_async(
-    CudaStreamsFFI streams, int8_t **mem_ptr, uint32_t glwe_dimension,
-    uint32_t polynomial_size, uint32_t big_lwe_dimension,
-    uint32_t small_lwe_dimension, uint32_t ks_level, uint32_t ks_base_log,
-    uint32_t pbs_level, uint32_t pbs_base_log, uint32_t grouping_factor,
-    uint32_t num_radix_blocks, uint32_t message_modulus, uint32_t carry_modulus,
-    PBS_TYPE pbs_type, bool allocate_gpu_memory,
+    CudaStreamsFFI streams, int8_t **mem_ptr,
+    CudaLweBootstrapKeyParamsFFI bsk_params, uint32_t ks_level,
+    uint32_t ks_base_log, uint32_t num_radix_blocks, uint32_t message_modulus,
+    uint32_t carry_modulus, bool allocate_gpu_memory,
     PBS_MS_REDUCTION_T noise_reduction_type);
 
 void cuda_integer_is_at_least_one_comparisons_block_true_64_async(
@@ -559,13 +528,11 @@ void trim_radix_blocks_msb_64(CudaRadixCiphertextFFI *output,
                               CudaStreamsFFI streams);
 
 uint64_t scratch_cuda_apply_noise_squashing_async(
-    CudaStreamsFFI streams, int8_t **mem_ptr, uint32_t lwe_dimension,
-    uint32_t glwe_dimension, uint32_t polynomial_size,
-    uint32_t input_glwe_dimension, uint32_t input_polynomial_size,
-    uint32_t ks_level, uint32_t ks_base_log, uint32_t pbs_level,
-    uint32_t pbs_base_log, uint32_t grouping_factor, uint32_t num_radix_blocks,
-    uint32_t num_original_blocks, uint32_t message_modulus,
-    uint32_t carry_modulus, PBS_TYPE pbs_type, bool allocate_gpu_memory,
+    CudaStreamsFFI streams, int8_t **mem_ptr,
+    CudaLweBootstrapKeyParamsFFI bsk_params, uint32_t input_glwe_dimension,
+    uint32_t input_polynomial_size, uint32_t ks_level, uint32_t ks_base_log,
+    uint32_t num_radix_blocks, uint32_t num_original_blocks,
+    uint32_t message_modulus, uint32_t carry_modulus, bool allocate_gpu_memory,
     PBS_MS_REDUCTION_T noise_reduction_type);
 
 void cuda_apply_noise_squashing_async(
@@ -577,12 +544,10 @@ void cleanup_cuda_apply_noise_squashing(CudaStreamsFFI streams,
                                         int8_t **mem_ptr_void);
 
 uint64_t scratch_cuda_sub_and_propagate_single_carry_64_inplace_async(
-    CudaStreamsFFI streams, int8_t **mem_ptr, uint32_t glwe_dimension,
-    uint32_t polynomial_size, uint32_t big_lwe_dimension,
-    uint32_t small_lwe_dimension, uint32_t ks_level, uint32_t ks_base_log,
-    uint32_t pbs_level, uint32_t pbs_base_log, uint32_t grouping_factor,
-    uint32_t num_blocks, uint32_t message_modulus, uint32_t carry_modulus,
-    PBS_TYPE pbs_type, uint32_t requested_flag, bool allocate_gpu_memory,
+    CudaStreamsFFI streams, int8_t **mem_ptr,
+    CudaLweBootstrapKeyParamsFFI bsk_params, uint32_t ks_level,
+    uint32_t ks_base_log, uint32_t num_blocks, uint32_t message_modulus,
+    uint32_t carry_modulus, uint32_t requested_flag, bool allocate_gpu_memory,
     PBS_MS_REDUCTION_T noise_reduction_type);
 
 void cuda_sub_and_propagate_single_carry_64_inplace_async(
@@ -595,13 +560,11 @@ void cleanup_cuda_sub_and_propagate_single_carry_64_inplace(
     CudaStreamsFFI streams, int8_t **mem_ptr_void);
 
 uint64_t scratch_cuda_integer_unsigned_scalar_div_radix_64_async(
-    CudaStreamsFFI streams, int8_t **mem_ptr, uint32_t glwe_dimension,
-    uint32_t polynomial_size, uint32_t lwe_dimension, uint32_t ks_level,
-    uint32_t ks_base_log, uint32_t pbs_level, uint32_t pbs_base_log,
-    uint32_t grouping_factor, uint32_t num_blocks, uint32_t message_modulus,
-    uint32_t carry_modulus, PBS_TYPE pbs_type,
-    const CudaScalarDivisorFFI *scalar_divisor_ffi, bool allocate_gpu_memory,
-    PBS_MS_REDUCTION_T noise_reduction_type);
+    CudaStreamsFFI streams, int8_t **mem_ptr,
+    CudaLweBootstrapKeyParamsFFI bsk_params, uint32_t ks_level,
+    uint32_t ks_base_log, uint32_t num_blocks, uint32_t message_modulus,
+    uint32_t carry_modulus, const CudaScalarDivisorFFI *scalar_divisor_ffi,
+    bool allocate_gpu_memory, PBS_MS_REDUCTION_T noise_reduction_type);
 
 void cuda_integer_unsigned_scalar_div_radix_64_async(
     CudaStreamsFFI streams, CudaRadixCiphertextFFI *numerator_ct,
@@ -612,13 +575,11 @@ void cleanup_cuda_integer_unsigned_scalar_div_radix_64(CudaStreamsFFI streams,
                                                        int8_t **mem_ptr_void);
 
 uint64_t scratch_cuda_integer_signed_scalar_div_radix_64_async(
-    CudaStreamsFFI streams, int8_t **mem_ptr, uint32_t glwe_dimension,
-    uint32_t polynomial_size, uint32_t lwe_dimension, uint32_t ks_level,
-    uint32_t ks_base_log, uint32_t pbs_level, uint32_t pbs_base_log,
-    uint32_t grouping_factor, uint32_t num_blocks, uint32_t message_modulus,
-    uint32_t carry_modulus, PBS_TYPE pbs_type,
-    const CudaScalarDivisorFFI *scalar_divisor_ffi, bool allocate_gpu_memory,
-    PBS_MS_REDUCTION_T noise_reduction_type);
+    CudaStreamsFFI streams, int8_t **mem_ptr,
+    CudaLweBootstrapKeyParamsFFI bsk_params, uint32_t ks_level,
+    uint32_t ks_base_log, uint32_t num_blocks, uint32_t message_modulus,
+    uint32_t carry_modulus, const CudaScalarDivisorFFI *scalar_divisor_ffi,
+    bool allocate_gpu_memory, PBS_MS_REDUCTION_T noise_reduction_type);
 
 void cuda_integer_signed_scalar_div_radix_64_async(
     CudaStreamsFFI streams, CudaRadixCiphertextFFI *numerator_ct,
@@ -629,12 +590,10 @@ void cleanup_cuda_integer_signed_scalar_div_radix_64(CudaStreamsFFI streams,
                                                      int8_t **mem_ptr_void);
 
 uint64_t scratch_cuda_integer_unsigned_scalar_div_rem_radix_64_async(
-    CudaStreamsFFI streams, int8_t **mem_ptr, uint32_t glwe_dimension,
-    uint32_t polynomial_size, uint32_t lwe_dimension, uint32_t ks_level,
-    uint32_t ks_base_log, uint32_t pbs_level, uint32_t pbs_base_log,
-    uint32_t grouping_factor, uint32_t num_blocks, uint32_t message_modulus,
-    uint32_t carry_modulus, PBS_TYPE pbs_type,
-    const CudaScalarDivisorFFI *scalar_divisor_ffi,
+    CudaStreamsFFI streams, int8_t **mem_ptr,
+    CudaLweBootstrapKeyParamsFFI bsk_params, uint32_t ks_level,
+    uint32_t ks_base_log, uint32_t num_blocks, uint32_t message_modulus,
+    uint32_t carry_modulus, const CudaScalarDivisorFFI *scalar_divisor_ffi,
     uint32_t const active_bits_divisor, bool allocate_gpu_memory,
     PBS_MS_REDUCTION_T noise_reduction_type);
 
@@ -651,12 +610,10 @@ void cleanup_cuda_integer_unsigned_scalar_div_rem_radix_64(
     CudaStreamsFFI streams, int8_t **mem_ptr_void);
 
 uint64_t scratch_cuda_integer_signed_scalar_div_rem_radix_64_async(
-    CudaStreamsFFI streams, int8_t **mem_ptr, uint32_t glwe_dimension,
-    uint32_t polynomial_size, uint32_t lwe_dimension, uint32_t ks_level,
-    uint32_t ks_base_log, uint32_t pbs_level, uint32_t pbs_base_log,
-    uint32_t grouping_factor, uint32_t num_blocks, uint32_t message_modulus,
-    uint32_t carry_modulus, PBS_TYPE pbs_type,
-    const CudaScalarDivisorFFI *scalar_divisor_ffi,
+    CudaStreamsFFI streams, int8_t **mem_ptr,
+    CudaLweBootstrapKeyParamsFFI bsk_params, uint32_t ks_level,
+    uint32_t ks_base_log, uint32_t num_blocks, uint32_t message_modulus,
+    uint32_t carry_modulus, const CudaScalarDivisorFFI *scalar_divisor_ffi,
     uint32_t const active_bits_divisor, bool allocate_gpu_memory,
     PBS_MS_REDUCTION_T noise_reduction_type);
 
@@ -672,12 +629,11 @@ void cleanup_cuda_integer_signed_scalar_div_rem_radix_64(CudaStreamsFFI streams,
                                                          int8_t **mem_ptr_void);
 
 uint64_t scratch_cuda_integer_count_of_consecutive_bits_64_async(
-    CudaStreamsFFI streams, int8_t **mem_ptr, uint32_t glwe_dimension,
-    uint32_t polynomial_size, uint32_t lwe_dimension, uint32_t ks_level,
-    uint32_t ks_base_log, uint32_t pbs_level, uint32_t pbs_base_log,
-    uint32_t grouping_factor, uint32_t num_blocks, uint32_t counter_num_blocks,
-    uint32_t message_modulus, uint32_t carry_modulus, PBS_TYPE pbs_type,
-    Direction direction, BitValue bit_value, bool allocate_gpu_memory,
+    CudaStreamsFFI streams, int8_t **mem_ptr,
+    CudaLweBootstrapKeyParamsFFI bsk_params, uint32_t ks_level,
+    uint32_t ks_base_log, uint32_t num_blocks, uint32_t counter_num_blocks,
+    uint32_t message_modulus, uint32_t carry_modulus, Direction direction,
+    BitValue bit_value, bool allocate_gpu_memory,
     PBS_MS_REDUCTION_T noise_reduction_type);
 
 void cuda_integer_count_of_consecutive_bits_64_async(
@@ -689,13 +645,12 @@ void cleanup_cuda_integer_count_of_consecutive_bits_64(CudaStreamsFFI streams,
                                                        int8_t **mem_ptr_void);
 
 uint64_t scratch_cuda_integer_grouped_oprf_64_async(
-    CudaStreamsFFI streams, int8_t **mem_ptr, uint32_t glwe_dimension,
-    uint32_t polynomial_size, uint32_t lwe_dimension, uint32_t ks_level,
-    uint32_t ks_base_log, uint32_t pbs_level, uint32_t pbs_base_log,
-    uint32_t grouping_factor, uint32_t num_blocks_to_process,
-    uint32_t message_modulus, uint32_t carry_modulus, PBS_TYPE pbs_type,
-    bool allocate_gpu_memory, uint32_t message_bits_per_block,
-    uint32_t total_random_bits, PBS_MS_REDUCTION_T noise_reduction_type);
+    CudaStreamsFFI streams, int8_t **mem_ptr,
+    CudaLweBootstrapKeyParamsFFI bsk_params, uint32_t ks_level,
+    uint32_t ks_base_log, uint32_t num_blocks_to_process,
+    uint32_t message_modulus, uint32_t carry_modulus, bool allocate_gpu_memory,
+    uint32_t message_bits_per_block, uint32_t total_random_bits,
+    PBS_MS_REDUCTION_T noise_reduction_type);
 
 void cuda_integer_grouped_oprf_64_async(CudaStreamsFFI streams,
                                         CudaRadixCiphertextFFI *radix_lwe_out,
@@ -707,31 +662,28 @@ void cleanup_cuda_integer_grouped_oprf_64(CudaStreamsFFI streams,
                                           int8_t **mem_ptr_void);
 
 uint64_t scratch_cuda_integer_grouped_oprf_custom_range_64_async(
-    CudaStreamsFFI streams, int8_t **mem_ptr, uint32_t glwe_dimension,
-    uint32_t polynomial_size, uint32_t lwe_dimension, uint32_t ks_level,
-    uint32_t ks_base_log, uint32_t pbs_level, uint32_t pbs_base_log,
-    uint32_t grouping_factor, uint32_t num_blocks_intermediate,
-    uint32_t message_modulus, uint32_t carry_modulus, PBS_TYPE pbs_type,
-    bool allocate_gpu_memory, uint32_t message_bits_per_block,
-    uint32_t num_input_random_bits, uint32_t num_scalar_bits,
-    PBS_MS_REDUCTION_T noise_reduction_type);
+    CudaStreamsFFI streams, int8_t **mem_ptr,
+    CudaLweBootstrapKeyParamsFFI bsk_params, uint32_t ks_level,
+    uint32_t ks_base_log, uint32_t num_blocks_intermediate,
+    uint32_t message_modulus, uint32_t carry_modulus, bool allocate_gpu_memory,
+    uint32_t message_bits_per_block, uint32_t num_input_random_bits,
+    uint32_t num_scalar_bits, PBS_MS_REDUCTION_T noise_reduction_type);
 
 void cuda_integer_grouped_oprf_custom_range_64_async(
     CudaStreamsFFI streams, CudaRadixCiphertextFFI *radix_lwe_out,
     uint32_t num_blocks_intermediate, const void *seeded_lwe_input,
     const uint64_t *decomposed_scalar, const uint64_t *has_at_least_one_set,
     uint32_t num_scalars, uint32_t shift, int8_t *mem, void *const *bsks,
-    void *const *ksks);
+    void *const *compute_bsks, void *const *ksks);
 
 void cleanup_cuda_integer_grouped_oprf_custom_range_64(CudaStreamsFFI streams,
                                                        int8_t **mem_ptr_void);
 
 uint64_t scratch_cuda_integer_ilog2_64_async(
-    CudaStreamsFFI streams, int8_t **mem_ptr, uint32_t glwe_dimension,
-    uint32_t polynomial_size, uint32_t lwe_dimension, uint32_t ks_level,
-    uint32_t ks_base_log, uint32_t pbs_level, uint32_t pbs_base_log,
-    uint32_t grouping_factor, uint32_t message_modulus, uint32_t carry_modulus,
-    PBS_TYPE pbs_type, uint32_t input_num_blocks, uint32_t counter_num_blocks,
+    CudaStreamsFFI streams, int8_t **mem_ptr,
+    CudaLweBootstrapKeyParamsFFI bsk_params, uint32_t ks_level,
+    uint32_t ks_base_log, uint32_t message_modulus, uint32_t carry_modulus,
+    uint32_t input_num_blocks, uint32_t counter_num_blocks,
     uint32_t num_bits_in_ciphertext, bool allocate_gpu_memory,
     PBS_MS_REDUCTION_T noise_reduction_type);
 
@@ -747,14 +699,12 @@ void cleanup_cuda_integer_ilog2_64(CudaStreamsFFI streams,
                                    int8_t **mem_ptr_void);
 
 uint64_t scratch_cuda_unchecked_match_value_64_async(
-    CudaStreamsFFI streams, int8_t **mem_ptr, uint32_t glwe_dimension,
-    uint32_t polynomial_size, uint32_t big_lwe_dimension,
-    uint32_t small_lwe_dimension, uint32_t ks_level, uint32_t ks_base_log,
-    uint32_t pbs_level, uint32_t pbs_base_log, uint32_t grouping_factor,
-    uint32_t num_matches, uint32_t num_input_blocks,
+    CudaStreamsFFI streams, int8_t **mem_ptr,
+    CudaLweBootstrapKeyParamsFFI bsk_params, uint32_t ks_level,
+    uint32_t ks_base_log, uint32_t num_matches, uint32_t num_input_blocks,
     uint32_t num_output_packed_blocks, uint32_t max_output_is_zero,
-    uint32_t message_modulus, uint32_t carry_modulus, PBS_TYPE pbs_type,
-    bool allocate_gpu_memory, PBS_MS_REDUCTION_T noise_reduction_type);
+    uint32_t message_modulus, uint32_t carry_modulus, bool allocate_gpu_memory,
+    PBS_MS_REDUCTION_T noise_reduction_type);
 
 void cuda_unchecked_match_value_64_async(
     CudaStreamsFFI streams, CudaRadixCiphertextFFI *lwe_array_out_result,
@@ -767,13 +717,11 @@ void cleanup_cuda_unchecked_match_value_64(CudaStreamsFFI streams,
                                            int8_t **mem_ptr_void);
 
 uint64_t scratch_cuda_cast_to_unsigned_64_async(
-    CudaStreamsFFI streams, int8_t **mem_ptr, uint32_t glwe_dimension,
-    uint32_t polynomial_size, uint32_t big_lwe_dimension,
-    uint32_t small_lwe_dimension, uint32_t ks_level, uint32_t ks_base_log,
-    uint32_t pbs_level, uint32_t pbs_base_log, uint32_t grouping_factor,
-    uint32_t num_input_blocks, uint32_t target_num_blocks, bool input_is_signed,
-    bool requires_full_propagate, uint32_t message_modulus,
-    uint32_t carry_modulus, PBS_TYPE pbs_type, bool allocate_gpu_memory,
+    CudaStreamsFFI streams, int8_t **mem_ptr,
+    CudaLweBootstrapKeyParamsFFI bsk_params, uint32_t ks_level,
+    uint32_t ks_base_log, uint32_t num_input_blocks, uint32_t target_num_blocks,
+    bool input_is_signed, bool requires_full_propagate,
+    uint32_t message_modulus, uint32_t carry_modulus, bool allocate_gpu_memory,
     PBS_MS_REDUCTION_T noise_reduction_type);
 
 void cuda_cast_to_unsigned_64_async(CudaStreamsFFI streams,
@@ -787,14 +735,12 @@ void cleanup_cuda_cast_to_unsigned_64(CudaStreamsFFI streams,
                                       int8_t **mem_ptr_void);
 
 uint64_t scratch_cuda_unchecked_match_value_or_64_async(
-    CudaStreamsFFI streams, int8_t **mem_ptr, uint32_t glwe_dimension,
-    uint32_t polynomial_size, uint32_t big_lwe_dimension,
-    uint32_t small_lwe_dimension, uint32_t ks_level, uint32_t ks_base_log,
-    uint32_t pbs_level, uint32_t pbs_base_log, uint32_t grouping_factor,
-    uint32_t num_matches, uint32_t num_input_blocks,
+    CudaStreamsFFI streams, int8_t **mem_ptr,
+    CudaLweBootstrapKeyParamsFFI bsk_params, uint32_t ks_level,
+    uint32_t ks_base_log, uint32_t num_matches, uint32_t num_input_blocks,
     uint32_t num_match_packed_blocks, uint32_t num_final_blocks,
     uint32_t max_output_is_zero, uint32_t message_modulus,
-    uint32_t carry_modulus, PBS_TYPE pbs_type, bool allocate_gpu_memory,
+    uint32_t carry_modulus, bool allocate_gpu_memory,
     PBS_MS_REDUCTION_T noise_reduction_type);
 
 void cuda_unchecked_match_value_or_64_async(
@@ -808,12 +754,10 @@ void cleanup_cuda_unchecked_match_value_or_64(CudaStreamsFFI streams,
                                               int8_t **mem_ptr_void);
 
 uint64_t scratch_cuda_unchecked_contains_64_async(
-    CudaStreamsFFI streams, int8_t **mem_ptr, uint32_t glwe_dimension,
-    uint32_t polynomial_size, uint32_t big_lwe_dimension,
-    uint32_t small_lwe_dimension, uint32_t ks_level, uint32_t ks_base_log,
-    uint32_t pbs_level, uint32_t pbs_base_log, uint32_t grouping_factor,
-    uint32_t num_inputs, uint32_t num_blocks, uint32_t message_modulus,
-    uint32_t carry_modulus, PBS_TYPE pbs_type, bool allocate_gpu_memory,
+    CudaStreamsFFI streams, int8_t **mem_ptr,
+    CudaLweBootstrapKeyParamsFFI bsk_params, uint32_t ks_level,
+    uint32_t ks_base_log, uint32_t num_inputs, uint32_t num_blocks,
+    uint32_t message_modulus, uint32_t carry_modulus, bool allocate_gpu_memory,
     PBS_MS_REDUCTION_T noise_reduction_type);
 
 void cuda_unchecked_contains_64_async(CudaStreamsFFI streams,
@@ -828,12 +772,10 @@ void cleanup_cuda_unchecked_contains_64(CudaStreamsFFI streams,
                                         int8_t **mem_ptr_void);
 
 uint64_t scratch_cuda_unchecked_contains_clear_64_async(
-    CudaStreamsFFI streams, int8_t **mem_ptr, uint32_t glwe_dimension,
-    uint32_t polynomial_size, uint32_t big_lwe_dimension,
-    uint32_t small_lwe_dimension, uint32_t ks_level, uint32_t ks_base_log,
-    uint32_t pbs_level, uint32_t pbs_base_log, uint32_t grouping_factor,
-    uint32_t num_inputs, uint32_t num_blocks, uint32_t message_modulus,
-    uint32_t carry_modulus, PBS_TYPE pbs_type, bool allocate_gpu_memory,
+    CudaStreamsFFI streams, int8_t **mem_ptr,
+    CudaLweBootstrapKeyParamsFFI bsk_params, uint32_t ks_level,
+    uint32_t ks_base_log, uint32_t num_inputs, uint32_t num_blocks,
+    uint32_t message_modulus, uint32_t carry_modulus, bool allocate_gpu_memory,
     PBS_MS_REDUCTION_T noise_reduction_type);
 
 void cuda_unchecked_contains_clear_64_async(
@@ -846,12 +788,10 @@ void cleanup_cuda_unchecked_contains_clear_64(CudaStreamsFFI streams,
                                               int8_t **mem_ptr_void);
 
 uint64_t scratch_cuda_unchecked_is_in_clears_64_async(
-    CudaStreamsFFI streams, int8_t **mem_ptr, uint32_t glwe_dimension,
-    uint32_t polynomial_size, uint32_t big_lwe_dimension,
-    uint32_t small_lwe_dimension, uint32_t ks_level, uint32_t ks_base_log,
-    uint32_t pbs_level, uint32_t pbs_base_log, uint32_t grouping_factor,
-    uint32_t num_clears, uint32_t num_blocks, uint32_t message_modulus,
-    uint32_t carry_modulus, PBS_TYPE pbs_type, bool allocate_gpu_memory,
+    CudaStreamsFFI streams, int8_t **mem_ptr,
+    CudaLweBootstrapKeyParamsFFI bsk_params, uint32_t ks_level,
+    uint32_t ks_base_log, uint32_t num_clears, uint32_t num_blocks,
+    uint32_t message_modulus, uint32_t carry_modulus, bool allocate_gpu_memory,
     PBS_MS_REDUCTION_T noise_reduction_type);
 
 void cuda_unchecked_is_in_clears_64_async(CudaStreamsFFI streams,
@@ -866,12 +806,10 @@ void cleanup_cuda_unchecked_is_in_clears_64(CudaStreamsFFI streams,
                                             int8_t **mem_ptr_void);
 
 uint64_t scratch_cuda_unchecked_index_in_clears_64_async(
-    CudaStreamsFFI streams, int8_t **mem_ptr, uint32_t glwe_dimension,
-    uint32_t polynomial_size, uint32_t big_lwe_dimension,
-    uint32_t small_lwe_dimension, uint32_t ks_level, uint32_t ks_base_log,
-    uint32_t pbs_level, uint32_t pbs_base_log, uint32_t grouping_factor,
-    uint32_t num_clears, uint32_t num_blocks, uint32_t num_blocks_index,
-    uint32_t message_modulus, uint32_t carry_modulus, PBS_TYPE pbs_type,
+    CudaStreamsFFI streams, int8_t **mem_ptr,
+    CudaLweBootstrapKeyParamsFFI bsk_params, uint32_t ks_level,
+    uint32_t ks_base_log, uint32_t num_clears, uint32_t num_blocks,
+    uint32_t num_blocks_index, uint32_t message_modulus, uint32_t carry_modulus,
     bool allocate_gpu_memory, PBS_MS_REDUCTION_T noise_reduction_type);
 
 void cuda_unchecked_index_in_clears_64_async(
@@ -885,12 +823,10 @@ void cleanup_cuda_unchecked_index_in_clears_64(CudaStreamsFFI streams,
                                                int8_t **mem_ptr_void);
 
 uint64_t scratch_cuda_unchecked_first_index_in_clears_64_async(
-    CudaStreamsFFI streams, int8_t **mem_ptr, uint32_t glwe_dimension,
-    uint32_t polynomial_size, uint32_t big_lwe_dimension,
-    uint32_t small_lwe_dimension, uint32_t ks_level, uint32_t ks_base_log,
-    uint32_t pbs_level, uint32_t pbs_base_log, uint32_t grouping_factor,
-    uint32_t num_unique, uint32_t num_blocks, uint32_t num_blocks_index,
-    uint32_t message_modulus, uint32_t carry_modulus, PBS_TYPE pbs_type,
+    CudaStreamsFFI streams, int8_t **mem_ptr,
+    CudaLweBootstrapKeyParamsFFI bsk_params, uint32_t ks_level,
+    uint32_t ks_base_log, uint32_t num_unique, uint32_t num_blocks,
+    uint32_t num_blocks_index, uint32_t message_modulus, uint32_t carry_modulus,
     bool allocate_gpu_memory, PBS_MS_REDUCTION_T noise_reduction_type);
 
 void cuda_unchecked_first_index_in_clears_64_async(
@@ -908,12 +844,10 @@ void cleanup_cuda_unchecked_first_index_in_clears_64(CudaStreamsFFI streams,
                                                      int8_t **mem_ptr_void);
 
 uint64_t scratch_cuda_unchecked_first_index_of_clear_64_async(
-    CudaStreamsFFI streams, int8_t **mem_ptr, uint32_t glwe_dimension,
-    uint32_t polynomial_size, uint32_t big_lwe_dimension,
-    uint32_t small_lwe_dimension, uint32_t ks_level, uint32_t ks_base_log,
-    uint32_t pbs_level, uint32_t pbs_base_log, uint32_t grouping_factor,
-    uint32_t num_inputs, uint32_t num_blocks, uint32_t num_blocks_index,
-    uint32_t message_modulus, uint32_t carry_modulus, PBS_TYPE pbs_type,
+    CudaStreamsFFI streams, int8_t **mem_ptr,
+    CudaLweBootstrapKeyParamsFFI bsk_params, uint32_t ks_level,
+    uint32_t ks_base_log, uint32_t num_inputs, uint32_t num_blocks,
+    uint32_t num_blocks_index, uint32_t message_modulus, uint32_t carry_modulus,
     bool allocate_gpu_memory, PBS_MS_REDUCTION_T noise_reduction_type);
 
 void cuda_unchecked_first_index_of_clear_64_async(
@@ -927,12 +861,10 @@ void cleanup_cuda_unchecked_first_index_of_clear_64(CudaStreamsFFI streams,
                                                     int8_t **mem_ptr_void);
 
 uint64_t scratch_cuda_unchecked_first_index_of_64_async(
-    CudaStreamsFFI streams, int8_t **mem_ptr, uint32_t glwe_dimension,
-    uint32_t polynomial_size, uint32_t big_lwe_dimension,
-    uint32_t small_lwe_dimension, uint32_t ks_level, uint32_t ks_base_log,
-    uint32_t pbs_level, uint32_t pbs_base_log, uint32_t grouping_factor,
-    uint32_t num_inputs, uint32_t num_blocks, uint32_t num_blocks_index,
-    uint32_t message_modulus, uint32_t carry_modulus, PBS_TYPE pbs_type,
+    CudaStreamsFFI streams, int8_t **mem_ptr,
+    CudaLweBootstrapKeyParamsFFI bsk_params, uint32_t ks_level,
+    uint32_t ks_base_log, uint32_t num_inputs, uint32_t num_blocks,
+    uint32_t num_blocks_index, uint32_t message_modulus, uint32_t carry_modulus,
     bool allocate_gpu_memory, PBS_MS_REDUCTION_T noise_reduction_type);
 
 void cuda_unchecked_first_index_of_64_async(
@@ -946,12 +878,10 @@ void cleanup_cuda_unchecked_first_index_of_64(CudaStreamsFFI streams,
                                               int8_t **mem_ptr_void);
 
 uint64_t scratch_cuda_unchecked_index_of_64_async(
-    CudaStreamsFFI streams, int8_t **mem_ptr, uint32_t glwe_dimension,
-    uint32_t polynomial_size, uint32_t big_lwe_dimension,
-    uint32_t small_lwe_dimension, uint32_t ks_level, uint32_t ks_base_log,
-    uint32_t pbs_level, uint32_t pbs_base_log, uint32_t grouping_factor,
-    uint32_t num_inputs, uint32_t num_blocks, uint32_t num_blocks_index,
-    uint32_t message_modulus, uint32_t carry_modulus, PBS_TYPE pbs_type,
+    CudaStreamsFFI streams, int8_t **mem_ptr,
+    CudaLweBootstrapKeyParamsFFI bsk_params, uint32_t ks_level,
+    uint32_t ks_base_log, uint32_t num_inputs, uint32_t num_blocks,
+    uint32_t num_blocks_index, uint32_t message_modulus, uint32_t carry_modulus,
     bool allocate_gpu_memory, PBS_MS_REDUCTION_T noise_reduction_type);
 
 void cuda_unchecked_index_of_64_async(CudaStreamsFFI streams,
@@ -967,12 +897,10 @@ void cleanup_cuda_unchecked_index_of_64(CudaStreamsFFI streams,
                                         int8_t **mem_ptr_void);
 
 uint64_t scratch_cuda_unchecked_index_of_clear_64_async(
-    CudaStreamsFFI streams, int8_t **mem_ptr, uint32_t glwe_dimension,
-    uint32_t polynomial_size, uint32_t big_lwe_dimension,
-    uint32_t small_lwe_dimension, uint32_t ks_level, uint32_t ks_base_log,
-    uint32_t pbs_level, uint32_t pbs_base_log, uint32_t grouping_factor,
-    uint32_t num_inputs, uint32_t num_blocks, uint32_t num_blocks_index,
-    uint32_t message_modulus, uint32_t carry_modulus, PBS_TYPE pbs_type,
+    CudaStreamsFFI streams, int8_t **mem_ptr,
+    CudaLweBootstrapKeyParamsFFI bsk_params, uint32_t ks_level,
+    uint32_t ks_base_log, uint32_t num_inputs, uint32_t num_blocks,
+    uint32_t num_blocks_index, uint32_t message_modulus, uint32_t carry_modulus,
     bool allocate_gpu_memory, PBS_MS_REDUCTION_T noise_reduction_type);
 
 void cuda_unchecked_index_of_clear_64_async(
@@ -987,12 +915,10 @@ void cleanup_cuda_unchecked_index_of_clear_64(CudaStreamsFFI streams,
                                               int8_t **mem_ptr_void);
 
 uint64_t scratch_cuda_unchecked_all_eq_slices_64_async(
-    CudaStreamsFFI streams, int8_t **mem_ptr, uint32_t glwe_dimension,
-    uint32_t polynomial_size, uint32_t big_lwe_dimension,
-    uint32_t small_lwe_dimension, uint32_t ks_level, uint32_t ks_base_log,
-    uint32_t pbs_level, uint32_t pbs_base_log, uint32_t grouping_factor,
-    uint32_t num_inputs, uint32_t num_blocks, uint32_t message_modulus,
-    uint32_t carry_modulus, PBS_TYPE pbs_type, bool allocate_gpu_memory,
+    CudaStreamsFFI streams, int8_t **mem_ptr,
+    CudaLweBootstrapKeyParamsFFI bsk_params, uint32_t ks_level,
+    uint32_t ks_base_log, uint32_t num_inputs, uint32_t num_blocks,
+    uint32_t message_modulus, uint32_t carry_modulus, bool allocate_gpu_memory,
     PBS_MS_REDUCTION_T noise_reduction_type);
 
 void cuda_unchecked_all_eq_slices_64_async(
@@ -1005,12 +931,10 @@ void cleanup_cuda_unchecked_all_eq_slices_64(CudaStreamsFFI streams,
                                              int8_t **mem_ptr_void);
 
 uint64_t scratch_cuda_unchecked_contains_sub_slice_64_async(
-    CudaStreamsFFI streams, int8_t **mem_ptr, uint32_t glwe_dimension,
-    uint32_t polynomial_size, uint32_t big_lwe_dimension,
-    uint32_t small_lwe_dimension, uint32_t ks_level, uint32_t ks_base_log,
-    uint32_t pbs_level, uint32_t pbs_base_log, uint32_t grouping_factor,
-    uint32_t num_lhs, uint32_t num_rhs, uint32_t num_blocks,
-    uint32_t message_modulus, uint32_t carry_modulus, PBS_TYPE pbs_type,
+    CudaStreamsFFI streams, int8_t **mem_ptr,
+    CudaLweBootstrapKeyParamsFFI bsk_params, uint32_t ks_level,
+    uint32_t ks_base_log, uint32_t num_lhs, uint32_t num_rhs,
+    uint32_t num_blocks, uint32_t message_modulus, uint32_t carry_modulus,
     bool allocate_gpu_memory, PBS_MS_REDUCTION_T noise_reduction_type);
 
 void cuda_unchecked_contains_sub_slice_64_async(
@@ -1023,12 +947,10 @@ void cleanup_cuda_unchecked_contains_sub_slice_64(CudaStreamsFFI streams,
                                                   int8_t **mem_ptr_void);
 
 uint64_t scratch_cuda_cast_to_signed_64_async(
-    CudaStreamsFFI streams, int8_t **mem_ptr, uint32_t glwe_dimension,
-    uint32_t polynomial_size, uint32_t lwe_dimension, uint32_t ks_level,
-    uint32_t ks_base_log, uint32_t pbs_level, uint32_t pbs_base_log,
-    uint32_t grouping_factor, uint32_t num_input_blocks,
-    uint32_t target_num_blocks, uint32_t message_modulus,
-    uint32_t carry_modulus, PBS_TYPE pbs_type, bool input_is_signed,
+    CudaStreamsFFI streams, int8_t **mem_ptr,
+    CudaLweBootstrapKeyParamsFFI bsk_params, uint32_t ks_level,
+    uint32_t ks_base_log, uint32_t num_input_blocks, uint32_t target_num_blocks,
+    uint32_t message_modulus, uint32_t carry_modulus, bool input_is_signed,
     bool allocate_gpu_memory, PBS_MS_REDUCTION_T noise_reduction_type);
 
 void cuda_cast_to_signed_64_async(CudaStreamsFFI streams,

backends/tfhe-cuda-backend/cuda/include/integer/integer_utilities.h

@@ -345,6 +345,21 @@ struct int_radix_params {
         message_modulus(message_modulus), carry_modulus(carry_modulus),
         noise_reduction_type(noise_reduction_type){};
 
+  int_radix_params(CudaLweBootstrapKeyParamsFFI bsk_params, uint32_t ks_level,
+                   uint32_t ks_base_log, uint32_t message_modulus,
+                   uint32_t carry_modulus,
+                   PBS_MS_REDUCTION_T noise_reduction_type)
+      : pbs_type((PBS_TYPE)bsk_params.pbs_type),
+        glwe_dimension(bsk_params.glwe_dimension),
+        polynomial_size(bsk_params.polynomial_size),
+        big_lwe_dimension(bsk_params.big_lwe_dimension),
+        small_lwe_dimension(bsk_params.input_lwe_dimension), ks_level(ks_level),
+        ks_base_log(ks_base_log), pbs_level(bsk_params.level_count),
+        pbs_base_log(bsk_params.base_log),
+        grouping_factor(bsk_params.grouping_factor),
+        message_modulus(message_modulus), carry_modulus(carry_modulus),
+        noise_reduction_type(noise_reduction_type){};
+
   int_radix_params() = default;
 
   void print() {

backends/tfhe-cuda-backend/cuda/include/kreyvium/kreyvium.h

@@ -5,12 +5,11 @@
 
 extern "C" {
 uint64_t scratch_cuda_kreyvium_generate_keystream_64_async(
-    CudaStreamsFFI streams, int8_t **mem_ptr, uint32_t glwe_dimension,
-    uint32_t polynomial_size, uint32_t lwe_dimension, uint32_t ks_level,
-    uint32_t ks_base_log, uint32_t pbs_level, uint32_t pbs_base_log,
-    uint32_t grouping_factor, uint32_t message_modulus, uint32_t carry_modulus,
-    PBS_TYPE pbs_type, bool allocate_gpu_memory,
-    PBS_MS_REDUCTION_T noise_reduction_type, uint32_t num_inputs);
+    CudaStreamsFFI streams, int8_t **mem_ptr,
+    CudaLweBootstrapKeyParamsFFI bsk_params, uint32_t ks_level,
+    uint32_t ks_base_log, uint32_t message_modulus, uint32_t carry_modulus,
+    bool allocate_gpu_memory, PBS_MS_REDUCTION_T noise_reduction_type,
+    uint32_t num_inputs);
 
 void cuda_kreyvium_generate_keystream_64_async(
     CudaStreamsFFI streams, CudaRadixCiphertextFFI *keystream_output,

backends/tfhe-cuda-backend/cuda/include/pbs/programmable_bootstrap_multibit.h

@@ -39,6 +39,28 @@ void cleanup_cuda_multi_bit_programmable_bootstrap_64(void *stream,
                                                       uint32_t gpu_index,
                                                       int8_t **pbs_buffer);
 
+// Noise-tests-namespaced wrappers for scratch/cleanup, so that callers
+// working with the noise-tests PBS variant use a consistent naming scheme.
+uint64_t scratch_cuda_multi_bit_programmable_bootstrap_noise_tests_64_async(
+    void *stream, uint32_t gpu_index, int8_t **pbs_buffer,
+    uint32_t glwe_dimension, uint32_t polynomial_size, uint32_t level_count,
+    uint32_t input_lwe_ciphertext_count, bool allocate_gpu_memory);
+
+void cleanup_cuda_multi_bit_programmable_bootstrap_noise_tests_64(
+    void *stream, uint32_t gpu_index, int8_t **pbs_buffer);
+
+// Noise tests variant: 64-bit torus, polynomial_size=2048 only. Uses the
+// NOISE_TESTS keybundle mode for noise analysis purposes.
+void cuda_multi_bit_programmable_bootstrap_noise_tests_64_async(
+    void *stream, uint32_t gpu_index, void *lwe_array_out,
+    void const *lwe_output_indexes, void const *lut_vector,
+    void const *lut_vector_indexes, void const *lwe_array_in,
+    void const *lwe_input_indexes, void const *bootstrapping_key,
+    int8_t *buffer, uint32_t lwe_dimension, uint32_t glwe_dimension,
+    uint32_t polynomial_size, uint32_t grouping_factor, uint32_t base_log,
+    uint32_t level_count, uint32_t num_samples, uint32_t num_many_lut,
+    uint32_t lut_stride);
+
 uint64_t scratch_cuda_multi_bit_programmable_bootstrap_128_async(
     void *stream, uint32_t gpu_index, int8_t **buffer, uint32_t glwe_dimension,
     uint32_t polynomial_size, uint32_t level_count,
@@ -56,6 +78,23 @@ void cuda_multi_bit_programmable_bootstrap_128_async(
 void cleanup_cuda_multi_bit_programmable_bootstrap_128(void *stream,
                                                        const uint32_t gpu_index,
                                                        int8_t **buffer);
+
+uint64_t scratch_cuda_multi_bit_programmable_bootstrap_noise_tests_128_async(
+    void *stream, uint32_t gpu_index, int8_t **pbs_buffer,
+    uint32_t glwe_dimension, uint32_t polynomial_size, uint32_t level_count,
+    uint32_t input_lwe_ciphertext_count, bool allocate_gpu_memory);
+
+void cleanup_cuda_multi_bit_programmable_bootstrap_noise_tests_128(
+    void *stream, uint32_t gpu_index, int8_t **pbs_buffer);
+
+void cuda_multi_bit_programmable_bootstrap_noise_tests_128_async(
+    void *stream, uint32_t gpu_index, void *lwe_array_out,
+    void const *lwe_output_indexes, void const *lut_vector,
+    void const *lwe_array_in, void const *lwe_input_indexes,
+    void const *bootstrapping_key, int8_t *buffer, uint32_t lwe_dimension,
+    uint32_t glwe_dimension, uint32_t polynomial_size, uint32_t grouping_factor,
+    uint32_t base_log, uint32_t level_count, uint32_t num_samples,
+    uint32_t num_many_lut, uint32_t lut_stride);
 }
 
 #endif // CUDA_MULTI_BIT_H

backends/tfhe-cuda-backend/cuda/include/trivium/trivium.h

@@ -5,12 +5,11 @@
 
 extern "C" {
 uint64_t scratch_cuda_trivium_generate_keystream_64_async(
-    CudaStreamsFFI streams, int8_t **mem_ptr, uint32_t glwe_dimension,
-    uint32_t polynomial_size, uint32_t lwe_dimension, uint32_t ks_level,
-    uint32_t ks_base_log, uint32_t pbs_level, uint32_t pbs_base_log,
-    uint32_t grouping_factor, uint32_t message_modulus, uint32_t carry_modulus,
-    PBS_TYPE pbs_type, bool allocate_gpu_memory,
-    PBS_MS_REDUCTION_T noise_reduction_type, uint32_t num_inputs);
+    CudaStreamsFFI streams, int8_t **mem_ptr,
+    CudaLweBootstrapKeyParamsFFI bsk_params, uint32_t ks_level,
+    uint32_t ks_base_log, uint32_t message_modulus, uint32_t carry_modulus,
+    bool allocate_gpu_memory, PBS_MS_REDUCTION_T noise_reduction_type,
+    uint32_t num_inputs);
 
 void cuda_trivium_generate_keystream_64_async(
     CudaStreamsFFI streams, CudaRadixCiphertextFFI *keystream_output,

backends/tfhe-cuda-backend/cuda/include/zk/zk_utilities.h

@@ -105,11 +105,11 @@ template <typename Torus> struct zk_expand_mem {
   uint32_t num_lwes;
   uint32_t num_compact_lists;
 
-  int_radix_lut<Torus> *message_and_carry_extract_luts;
-  int_radix_lut<Torus> *identity_lut;
+  int_radix_lut<Torus> *message_and_carry_extract_luts = nullptr;
+  int_radix_lut<Torus> *identity_lut = nullptr;
 
-  Torus *tmp_expanded_lwes;
-  Torus *tmp_ksed_small_to_big_expanded_lwes;
+  Torus *tmp_expanded_lwes = nullptr;
+  Torus *tmp_ksed_small_to_big_expanded_lwes = nullptr;
 
   bool gpu_memory_allocated;
 
@@ -148,66 +148,6 @@ template <typename Torus> struct zk_expand_mem {
       PANIC("GPU backend requires carry_modulus equal to message_modulus")
     }
 
-    // We create the identity LUT only if we are doing a SANITY_CHECK
-    if (expand_kind == EXPAND_KIND::SANITY_CHECK) {
-      identity_lut =
-          new int_radix_lut<Torus>(streams, computing_params, 1, 2 * num_lwes,
-                                   allocate_gpu_memory, size_tracker);
-
-      auto identity_lut_f = [](Torus x) -> Torus { return x; };
-
-      identity_lut->generate_and_broadcast_lut(streams, {0}, {identity_lut_f},
-                                               LUT_0_FOR_ALL_BLOCKS);
-    }
-
-    auto message_extract_lut_f = [casting_params](Torus x) -> Torus {
-      return x % casting_params.message_modulus;
-    };
-    auto carry_extract_lut_f = [casting_params](Torus x) -> Torus {
-      return (x / casting_params.carry_modulus) %
-             casting_params.message_modulus;
-    };
-
-    // Booleans have to be sanitized
-    auto sanitize_bool_f = [](Torus x) -> Torus { return x == 0 ? 0 : 1; };
-    auto message_extract_and_sanitize_bool_lut_f =
-        [message_extract_lut_f, sanitize_bool_f](Torus x) -> Torus {
-      return sanitize_bool_f(message_extract_lut_f(x));
-    };
-    auto carry_extract_and_sanitize_bool_lut_f =
-        [carry_extract_lut_f, sanitize_bool_f](Torus x) -> Torus {
-      return sanitize_bool_f(carry_extract_lut_f(x));
-    };
-
-    /** In case the casting key casts from BIG to SMALL key we run a single KS
-    to expand using the casting key as ksk. Otherwise, in case the casting key
-    casts from SMALL to BIG key, we first keyswitch from SMALL to BIG using
-    the casting key as ksk, then we keyswitch from BIG to SMALL using the
-    computing ksk, and lastly we apply the PBS. The output is always on the
-    BIG key.
-    **/
-    auto params = casting_params;
-    if (casting_key_type == SMALL_TO_BIG) {
-      params = computing_params;
-    }
-    message_and_carry_extract_luts = new int_radix_lut<Torus>(
-        streams, params, 4, 2 * num_lwes, allocate_gpu_memory, size_tracker);
-
-    // We are always packing two LWEs. We just need to be sure we have enough
-    // space in the carry part to store a message of the same size as is in the
-    // message part.
-    if (params.carry_modulus < params.message_modulus)
-      PANIC("Carry modulus must be at least as large as message modulus");
-    auto num_packed_msgs = 2;
-
-    // Adjust indexes to permute the output and access the correct LUT
-    auto h_indexes_in = static_cast<Torus *>(
-        malloc(safe_mul_sizeof<Torus>(num_packed_msgs, num_lwes)));
-    auto h_indexes_out = static_cast<Torus *>(
-        malloc(safe_mul_sizeof<Torus>(num_packed_msgs, num_lwes)));
-    auto h_lut_indexes = static_cast<Torus *>(
-        malloc(safe_mul_sizeof<Torus>(num_packed_msgs, num_lwes)));
-
     d_expand_jobs =
         static_cast<expand_job<Torus> *>(cuda_malloc_with_size_tracking_async(
             safe_mul_sizeof<expand_job<Torus>>(num_lwes), streams.stream(0),
@@ -216,144 +156,202 @@ template <typename Torus> struct zk_expand_mem {
     h_expand_jobs = static_cast<expand_job<Torus> *>(
         malloc(safe_mul_sizeof<expand_job<Torus>>(num_lwes)));
 
-    /*
-     * Each LWE contains encrypted data in both carry and message spaces
-     * that needs to be extracted.
-     *
-     * The loop processes each compact list (k) and for each LWE within that
-     * list:
-     * 1. Sets input indexes to read each LWE twice (for carry and message
-     * extraction)
-     * 2. Creates output indexes to properly reorder the results
-     * 3. Selects appropriate LUT index based on whether boolean sanitization is
-     * needed
-     *
-     * We want the output to have always first the content of the message part
-     * and then the content of the carry part of each LWE.
-     *
-     * i.e. msg_extract(LWE_0), carry_extract(LWE_0), msg_extract(LWE_1),
-     * carry_extract(LWE_1), ...
-     *
-     * Aiming that behavior, with 4 LWEs we would have:
-     *
-     * // Each LWE is processed twice
-     * h_indexes_in   = {0, 1, 2, 3, 0, 1, 2, 3}
-     *
-     * // First 4 use message LUT, last 4 use carry LUT
-     * h_lut_indexes  = {0, 0, 0, 0, 1, 1, 1, 1}
-     *
-     * // Reorders output so message and carry for each LWE appear together
-     * h_indexes_out  = {0, 2, 4, 6, 1, 3, 5, 7}
-     *
-     * If an LWE contains a boolean value, its LUT index is shifted by
-     * num_packed_msgs to use the sanitization LUT (which ensures output is
-     * exactly 0 or 1).
-     */
-    auto offset = 0;
-    for (int k = 0; k < num_compact_lists; k++) {
-      auto num_lwes_in_kth = this->num_lwes_per_compact_list[k];
-      for (int i = 0; i < num_packed_msgs * num_lwes_in_kth; i++) {
-        auto lwe_index = i + num_packed_msgs * offset;
-        auto lwe_index_in_list = i % num_lwes_in_kth;
-        PANIC_IF_FALSE(lwe_index < num_packed_msgs * num_lwes,
-                       "Cuda error: index %d is beyond the max value %d",
-                       lwe_index, num_packed_msgs * num_lwes);
-        h_indexes_in[lwe_index] = lwe_index_in_list + offset;
-        h_indexes_out[lwe_index] =
-            num_packed_msgs * h_indexes_in[lwe_index] + i / num_lwes_in_kth;
-        PANIC_IF_FALSE(h_indexes_in[lwe_index] < num_packed_msgs * num_lwes,
-                       "Cuda error: index %lu is beyond the max value %lu",
-                       (unsigned long)h_indexes_in[lwe_index],
-                       (unsigned long)(num_packed_msgs * num_lwes));
-        PANIC_IF_FALSE(h_indexes_out[lwe_index] < num_packed_msgs * num_lwes,
-                       "Cuda error: index %lu is beyond the max value %lu",
-                       (unsigned long)h_indexes_out[lwe_index],
-                       (unsigned long)(num_packed_msgs * num_lwes));
-        // is_boolean_array tells us which input is a boolean and thus the
-        // related output needs boolean sanitization. It naturally has
-        // total_blocks entries, but h_indexes_out reaches
-        // message_modulus * ceil(total_blocks/2) - 1. When total_blocks is odd,
-        // the ceiling causes out-of-bounds access. Reading garbage "true" would
-        // set h_lut_indexes to an invalid index pointing to uninitialized
-        // memory instead of a real LUT. Rust pads is_boolean_array with FALSE
-        // to match.
-        PANIC_IF_FALSE(h_indexes_out[lwe_index] < is_boolean_array_len,
-                       "Cuda error: index %lu for is_boolean_array is out of "
-                       "bounds (len is %lu)",
-                       (unsigned long)h_indexes_out[lwe_index],
-                       (unsigned long)is_boolean_array_len);
+    // NO_CASTING expands directly into the output buffer — no LUTs, no PBS,
+    // no intermediate buffers needed.
+    if (expand_kind != EXPAND_KIND::NO_CASTING) {
+      /** In case the casting key casts from BIG to SMALL key we run a single KS
+      to expand using the casting key as ksk. Otherwise, in case the casting key
+      casts from SMALL to BIG key, we first keyswitch from SMALL to BIG using
+      the casting key as ksk, then we keyswitch from BIG to SMALL using the
+      computing ksk, and lastly we apply the PBS. The output is always on the
+      BIG key.
+      **/
+      auto params = casting_params;
+      if (casting_key_type == SMALL_TO_BIG) {
+        params = computing_params;
       }
-      offset += num_lwes_in_kth;
-    }
 
-    message_and_carry_extract_luts->set_lwe_indexes(
-        streams.stream(0), streams.gpu_index(0), h_indexes_in, h_indexes_out);
+      // We always pack two LWEs (message and carry parts per LWE)
+      auto num_packed_msgs = 2;
 
-    auto active_streams =
-        streams.active_gpu_subset(2 * num_lwes, params.pbs_type);
+      // Adjust indexes to permute the output and access the correct LUT.
+      //
+      // The loop below fills h_indexes_in and h_indexes_out so that the output
+      // is ordered as: msg_extract(LWE_0), carry_extract(LWE_0),
+      // msg_extract(LWE_1), carry_extract(LWE_1), ...
+      //
+      // With 4 LWEs the arrays look like:
+      //   h_indexes_in  = {0, 1, 2, 3, 0, 1, 2, 3}  (each LWE read twice)
+      //   h_lut_indexes = {0, 0, 0, 0, 1, 1, 1, 1}  (msg LUT then carry LUT)
+      //   h_indexes_out = {0, 2, 4, 6, 1, 3, 5, 7}  (interleaved output)
+      //
+      // If an LWE contains a boolean its LUT index is shifted by
+      // num_packed_msgs to use the sanitization LUT (output clamped to {0, 1}).
+      auto h_indexes_in = static_cast<Torus *>(
+          malloc(safe_mul_sizeof<Torus>(num_packed_msgs, num_lwes)));
+      auto h_indexes_out = static_cast<Torus *>(
+          malloc(safe_mul_sizeof<Torus>(num_packed_msgs, num_lwes)));
 
-    // Index generator for message/carry extraction LUTs
-    auto index_gen = [num_compact_lists,
-                      num_lwes_per_compact_list =
-                          this->num_lwes_per_compact_list,
-                      num_packed_msgs, is_boolean_array,
-                      h_indexes_out](Torus *h_lut_indexes, uint32_t) {
       auto offset = 0;
       for (int k = 0; k < num_compact_lists; k++) {
-        auto num_lwes_in_kth = num_lwes_per_compact_list[k];
+        auto num_lwes_in_kth = this->num_lwes_per_compact_list[k];
         for (int i = 0; i < num_packed_msgs * num_lwes_in_kth; i++) {
           auto lwe_index = i + num_packed_msgs * offset;
-          auto boolean_offset =
-              is_boolean_array[h_indexes_out[lwe_index]] ? num_packed_msgs : 0;
-          h_lut_indexes[lwe_index] = i / num_lwes_in_kth + boolean_offset;
+          auto lwe_index_in_list = i % num_lwes_in_kth;
+          PANIC_IF_FALSE(lwe_index < num_packed_msgs * num_lwes,
+                         "Cuda error: index %d is beyond the max value %d",
+                         lwe_index, num_packed_msgs * num_lwes);
+          h_indexes_in[lwe_index] = lwe_index_in_list + offset;
+          h_indexes_out[lwe_index] =
+              num_packed_msgs * h_indexes_in[lwe_index] + i / num_lwes_in_kth;
+          PANIC_IF_FALSE(h_indexes_in[lwe_index] < num_packed_msgs * num_lwes,
+                         "Cuda error: index %lu is beyond the max value %lu",
+                         (unsigned long)h_indexes_in[lwe_index],
+                         (unsigned long)(num_packed_msgs * num_lwes));
+          PANIC_IF_FALSE(h_indexes_out[lwe_index] < num_packed_msgs * num_lwes,
+                         "Cuda error: index %lu is beyond the max value %lu",
+                         (unsigned long)h_indexes_out[lwe_index],
+                         (unsigned long)(num_packed_msgs * num_lwes));
+          // is_boolean_array tells us which input is a boolean and thus the
+          // related output needs boolean sanitization. It naturally has
+          // total_blocks entries, but h_indexes_out reaches
+          // message_modulus * ceil(total_blocks/2) - 1. When total_blocks is
+          // odd, the ceiling causes out-of-bounds access. Reading garbage
+          // "true" would set h_lut_indexes to an invalid index pointing to
+          // uninitialized memory instead of a real LUT. Rust pads
+          // is_boolean_array with FALSE to match.
+          PANIC_IF_FALSE(h_indexes_out[lwe_index] < is_boolean_array_len,
+                         "Cuda error: index %lu for is_boolean_array is out of "
+                         "bounds (len is %lu)",
+                         (unsigned long)h_indexes_out[lwe_index],
+                         (unsigned long)is_boolean_array_len);
         }
         offset += num_lwes_in_kth;
       }
-    };
 
-    message_and_carry_extract_luts->generate_and_broadcast_lut(
-        active_streams, {0, 1, 2, 3},
-        {message_extract_lut_f, carry_extract_lut_f,
-         message_extract_and_sanitize_bool_lut_f,
-         carry_extract_and_sanitize_bool_lut_f},
-        index_gen, true, {}, h_lut_indexes);
+      auto active_streams =
+          streams.active_gpu_subset(2 * num_lwes, params.pbs_type);
 
-    message_and_carry_extract_luts->allocate_lwe_vector_for_non_trivial_indexes(
-        active_streams, 2 * num_lwes, size_tracker, allocate_gpu_memory);
-    // The expanded LWEs will always be on the casting key format
-    tmp_expanded_lwes = (Torus *)cuda_malloc_with_size_tracking_async(
-        safe_mul_sizeof<Torus>(num_lwes, casting_params.big_lwe_dimension + 1),
-        streams.stream(0), streams.gpu_index(0), size_tracker,
-        allocate_gpu_memory);
+      // SANITY_CHECK uses identity_lut (skipping the full message/carry
+      // extraction LUT and the SMALL_TO_BIG intermediate buffer).
+      if (expand_kind == EXPAND_KIND::SANITY_CHECK) {
+        identity_lut =
+            new int_radix_lut<Torus>(streams, casting_params, 1, 2 * num_lwes,
+                                     allocate_gpu_memory, size_tracker);
 
-    tmp_ksed_small_to_big_expanded_lwes =
-        (Torus *)cuda_malloc_with_size_tracking_async(
-            safe_mul_sizeof<Torus>(num_lwes,
-                                   casting_params.big_lwe_dimension + 1),
-            streams.stream(0), streams.gpu_index(0), size_tracker,
-            allocate_gpu_memory);
+        auto identity_lut_f = [](Torus x) -> Torus { return x; };
+        identity_lut->generate_and_broadcast_lut(streams, {0}, {identity_lut_f},
+                                                 LUT_0_FOR_ALL_BLOCKS);
+        identity_lut->set_lwe_indexes(streams.stream(0), streams.gpu_index(0),
+                                      h_indexes_in, h_indexes_out);
+        identity_lut->allocate_lwe_vector_for_non_trivial_indexes(
+            active_streams, 2 * num_lwes, size_tracker, allocate_gpu_memory);
+      } else {
+        // We are always packing two LWEs. We just need to be sure we have
+        // enough space in the carry part to store a message of the same size
+        // as is in the message part.
+        if (params.carry_modulus < params.message_modulus)
+          PANIC("Carry modulus must be at least as large as message modulus");
+
+        message_and_carry_extract_luts =
+            new int_radix_lut<Torus>(streams, params, 4, 2 * num_lwes,
+                                     allocate_gpu_memory, size_tracker);
+        message_and_carry_extract_luts->set_lwe_indexes(
+            streams.stream(0), streams.gpu_index(0), h_indexes_in,
+            h_indexes_out);
+
+        auto message_extract_lut_f = [casting_params](Torus x) -> Torus {
+          return x % casting_params.message_modulus;
+        };
+        auto carry_extract_lut_f = [casting_params](Torus x) -> Torus {
+          return (x / casting_params.carry_modulus) %
+                 casting_params.message_modulus;
+        };
+        auto sanitize_bool_f = [](Torus x) -> Torus { return x == 0 ? 0 : 1; };
+        auto message_extract_and_sanitize_bool_lut_f =
+            [message_extract_lut_f, sanitize_bool_f](Torus x) -> Torus {
+          return sanitize_bool_f(message_extract_lut_f(x));
+        };
+        auto carry_extract_and_sanitize_bool_lut_f =
+            [carry_extract_lut_f, sanitize_bool_f](Torus x) -> Torus {
+          return sanitize_bool_f(carry_extract_lut_f(x));
+        };
+
+        auto h_lut_indexes = static_cast<Torus *>(
+            malloc(safe_mul_sizeof<Torus>(num_packed_msgs, num_lwes)));
+
+        auto index_gen = [num_compact_lists,
+                          num_lwes_per_compact_list =
+                              this->num_lwes_per_compact_list,
+                          num_packed_msgs, is_boolean_array,
+                          h_indexes_out](Torus *h_lut_indexes, uint32_t) {
+          auto offset = 0;
+          for (int k = 0; k < num_compact_lists; k++) {
+            auto num_lwes_in_kth = num_lwes_per_compact_list[k];
+            for (int i = 0; i < num_packed_msgs * num_lwes_in_kth; i++) {
+              auto lwe_index = i + num_packed_msgs * offset;
+              auto boolean_offset = is_boolean_array[h_indexes_out[lwe_index]]
+                                        ? num_packed_msgs
+                                        : 0;
+              h_lut_indexes[lwe_index] = i / num_lwes_in_kth + boolean_offset;
+            }
+            offset += num_lwes_in_kth;
+          }
+        };
+
+        message_and_carry_extract_luts->generate_and_broadcast_lut(
+            active_streams, {0, 1, 2, 3},
+            {message_extract_lut_f, carry_extract_lut_f,
+             message_extract_and_sanitize_bool_lut_f,
+             carry_extract_and_sanitize_bool_lut_f},
+            index_gen, true, {}, h_lut_indexes);
+        message_and_carry_extract_luts
+            ->allocate_lwe_vector_for_non_trivial_indexes(
+                active_streams, 2 * num_lwes, size_tracker,
+                allocate_gpu_memory);
+        free(h_lut_indexes);
+
+        // SANITY_CHECK panics on SMALL_TO_BIG, so this buffer is only needed
+        // on the full casting path.
+        tmp_ksed_small_to_big_expanded_lwes =
+            (Torus *)cuda_malloc_with_size_tracking_async(
+                safe_mul_sizeof<Torus>(num_lwes,
+                                       casting_params.big_lwe_dimension + 1),
+                streams.stream(0), streams.gpu_index(0), size_tracker,
+                allocate_gpu_memory);
+      }
+
+      // The expanded LWEs will always be on the casting key format
+      tmp_expanded_lwes = (Torus *)cuda_malloc_with_size_tracking_async(
+          safe_mul_sizeof<Torus>(num_lwes,
+                                 casting_params.big_lwe_dimension + 1),
+          streams.stream(0), streams.gpu_index(0), size_tracker,
+          allocate_gpu_memory);
+
+      free(h_indexes_in);
+      free(h_indexes_out);
+    }
 
     cuda_synchronize_stream(streams.stream(0), streams.gpu_index(0));
-    free(h_indexes_in);
-    free(h_indexes_out);
-    free(h_lut_indexes);
   }
 
   void release(CudaStreams streams) {
-    message_and_carry_extract_luts->release(streams);
-    delete message_and_carry_extract_luts;
-
-    if (expand_kind == EXPAND_KIND::SANITY_CHECK) {
-      identity_lut->release(streams);
-      delete identity_lut;
+    if (expand_kind != EXPAND_KIND::NO_CASTING) {
+      if (expand_kind == EXPAND_KIND::SANITY_CHECK) {
+        identity_lut->release(streams);
+        delete identity_lut;
+      } else {
+        message_and_carry_extract_luts->release(streams);
+        delete message_and_carry_extract_luts;
+        cuda_drop_with_size_tracking_async(
+            tmp_ksed_small_to_big_expanded_lwes, streams.stream(0),
+            streams.gpu_index(0), gpu_memory_allocated);
+      }
+      cuda_drop_with_size_tracking_async(tmp_expanded_lwes, streams.stream(0),
+                                         streams.gpu_index(0),
+                                         gpu_memory_allocated);
     }
 
-    cuda_drop_with_size_tracking_async(tmp_expanded_lwes, streams.stream(0),
-                                       streams.gpu_index(0),
-                                       gpu_memory_allocated);
-    cuda_drop_with_size_tracking_async(tmp_ksed_small_to_big_expanded_lwes,
-                                       streams.stream(0), streams.gpu_index(0),
-                                       gpu_memory_allocated);
     cuda_drop_with_size_tracking_async(d_expand_jobs, streams.stream(0),
                                        streams.gpu_index(0),
                                        gpu_memory_allocated);

backends/tfhe-cuda-backend/cuda/src/aes/aes.cu

@@ -2,19 +2,14 @@
 #include "aes.cuh"
 
 uint64_t scratch_cuda_integer_aes_ctr_encrypt_64_async(
-    CudaStreamsFFI streams, int8_t **mem_ptr, uint32_t glwe_dimension,
-    uint32_t polynomial_size, uint32_t lwe_dimension, uint32_t ks_level,
-    uint32_t ks_base_log, uint32_t pbs_level, uint32_t pbs_base_log,
-    uint32_t grouping_factor, uint32_t message_modulus, uint32_t carry_modulus,
-    PBS_TYPE pbs_type, bool allocate_gpu_memory,
-    PBS_MS_REDUCTION_T noise_reduction_type, uint32_t num_aes_inputs,
-    uint32_t sbox_parallelism) {
+    CudaStreamsFFI streams, int8_t **mem_ptr,
+    CudaLweBootstrapKeyParamsFFI bsk_params, uint32_t ks_level,
+    uint32_t ks_base_log, uint32_t message_modulus, uint32_t carry_modulus,
+    bool allocate_gpu_memory, PBS_MS_REDUCTION_T noise_reduction_type,
+    uint32_t num_aes_inputs, uint32_t sbox_parallelism) {
 
-  int_radix_params params(pbs_type, glwe_dimension, polynomial_size,
-                          glwe_dimension * polynomial_size, lwe_dimension,
-                          ks_level, ks_base_log, pbs_level, pbs_base_log,
-                          grouping_factor, message_modulus, carry_modulus,
-                          noise_reduction_type);
+  int_radix_params params(bsk_params, ks_level, ks_base_log, message_modulus,
+                          carry_modulus, noise_reduction_type);
 
   return scratch_cuda_integer_aes_encrypt<uint64_t>(
       CudaStreams(streams), (int_aes_encrypt_buffer<uint64_t> **)mem_ptr,
@@ -22,19 +17,14 @@ uint64_t scratch_cuda_integer_aes_ctr_encrypt_64_async(
 }
 
 uint64_t scratch_cuda_integer_aes_ctr_256_encrypt_64_async(
-    CudaStreamsFFI streams, int8_t **mem_ptr, uint32_t glwe_dimension,
-    uint32_t polynomial_size, uint32_t lwe_dimension, uint32_t ks_level,
-    uint32_t ks_base_log, uint32_t pbs_level, uint32_t pbs_base_log,
-    uint32_t grouping_factor, uint32_t message_modulus, uint32_t carry_modulus,
-    PBS_TYPE pbs_type, bool allocate_gpu_memory,
-    PBS_MS_REDUCTION_T noise_reduction_type, uint32_t num_aes_inputs,
-    uint32_t sbox_parallelism) {
+    CudaStreamsFFI streams, int8_t **mem_ptr,
+    CudaLweBootstrapKeyParamsFFI bsk_params, uint32_t ks_level,
+    uint32_t ks_base_log, uint32_t message_modulus, uint32_t carry_modulus,
+    bool allocate_gpu_memory, PBS_MS_REDUCTION_T noise_reduction_type,
+    uint32_t num_aes_inputs, uint32_t sbox_parallelism) {
 
-  int_radix_params params(pbs_type, glwe_dimension, polynomial_size,
-                          glwe_dimension * polynomial_size, lwe_dimension,
-                          ks_level, ks_base_log, pbs_level, pbs_base_log,
-                          grouping_factor, message_modulus, carry_modulus,
-                          noise_reduction_type);
+  int_radix_params params(bsk_params, ks_level, ks_base_log, message_modulus,
+                          carry_modulus, noise_reduction_type);
 
   return scratch_cuda_integer_aes_encrypt<uint64_t>(
       CudaStreams(streams), (int_aes_encrypt_buffer<uint64_t> **)mem_ptr,
@@ -78,18 +68,13 @@ void cleanup_cuda_integer_aes_ctr_256_encrypt_64(CudaStreamsFFI streams,
 }
 
 uint64_t scratch_cuda_integer_key_expansion_64_async(
-    CudaStreamsFFI streams, int8_t **mem_ptr, uint32_t glwe_dimension,
-    uint32_t polynomial_size, uint32_t lwe_dimension, uint32_t ks_level,
-    uint32_t ks_base_log, uint32_t pbs_level, uint32_t pbs_base_log,
-    uint32_t grouping_factor, uint32_t message_modulus, uint32_t carry_modulus,
-    PBS_TYPE pbs_type, bool allocate_gpu_memory,
-    PBS_MS_REDUCTION_T noise_reduction_type) {
+    CudaStreamsFFI streams, int8_t **mem_ptr,
+    CudaLweBootstrapKeyParamsFFI bsk_params, uint32_t ks_level,
+    uint32_t ks_base_log, uint32_t message_modulus, uint32_t carry_modulus,
+    bool allocate_gpu_memory, PBS_MS_REDUCTION_T noise_reduction_type) {
 
-  int_radix_params params(pbs_type, glwe_dimension, polynomial_size,
-                          glwe_dimension * polynomial_size, lwe_dimension,
-                          ks_level, ks_base_log, pbs_level, pbs_base_log,
-                          grouping_factor, message_modulus, carry_modulus,
-                          noise_reduction_type);
+  int_radix_params params(bsk_params, ks_level, ks_base_log, message_modulus,
+                          carry_modulus, noise_reduction_type);
 
   return scratch_cuda_integer_key_expansion<uint64_t>(
       CudaStreams(streams), (int_key_expansion_buffer<uint64_t> **)mem_ptr,

backends/tfhe-cuda-backend/cuda/src/aes/aes.cuh

@@ -390,7 +390,7 @@ __host__ void vectorized_sbox_n_bytes(CudaStreams streams,
   XOR(&wires_a[6], &wires_a[15], &input_bits[7]);
   XOR(&wires_a[10], &wires_a[15], &wires_b[0]);
   XOR(&wires_a[11], &wires_a[20], &wires_a[9]);
-  FLUSH(&wires_a[6], &wires_a[10]);
+  FLUSH(&wires_a[6], &wires_a[10], &wires_a[11]);
   XOR(&wires_a[7], &input_bits[7], &wires_a[11]);
   FLUSH(&wires_a[7]);
   XOR(&wires_a[17], &wires_a[10], &wires_a[11]);
@@ -426,7 +426,7 @@ __host__ void vectorized_sbox_n_bytes(CudaStreams streams,
   XOR(&wires_b[22], &wires_b[18], &wires_a[19]);
   XOR(&wires_b[23], &wires_b[19], &wires_a[21]);
   XOR(&wires_b[24], &wires_b[20], &wires_a[18]);
-  FLUSH(&wires_b[21], &wires_b[23], &wires_b[24]);
+  FLUSH(&wires_b[21], &wires_b[22], &wires_b[23], &wires_b[24]);
   XOR(&wires_b[25], &wires_b[21], &wires_b[22]);
   FLUSH(&wires_b[25]);
 
@@ -468,7 +468,7 @@ __host__ void vectorized_sbox_n_bytes(CudaStreams streams,
 
   XOR(&wires_b[37], &wires_b[36], &wires_b[34]);
   XOR(&wires_b[38], &wires_b[27], &wires_b[36]);
-  FLUSH(&wires_b[38]);
+  FLUSH(&wires_b[38], &wires_b[37]);
   XOR(&wires_b[44], &wires_b[33], &wires_b[37]);
 
   CudaRadixCiphertextFFI *and_outs_6[] = {&wires_b[39]};
@@ -479,7 +479,7 @@ __host__ void vectorized_sbox_n_bytes(CudaStreams streams,
   XOR(&wires_b[40], &wires_b[25], &wires_b[39]);
   XOR(&wires_b[41], &wires_b[40], &wires_b[37]);
   XOR(&wires_b[43], &wires_b[29], &wires_b[40]);
-  FLUSH(&wires_b[41]);
+  FLUSH(&wires_b[41], &wires_b[40], &wires_b[43], &wires_b[44]);
   XOR(&wires_b[45], &wires_b[42], &wires_b[41]);
   FLUSH(&wires_b[45]);
 
@@ -514,6 +514,7 @@ __host__ void vectorized_sbox_n_bytes(CudaStreams streams,
   XOR(&wires_b[57], &wires_b[50], &wires_b[53]);
   XOR(&wires_b[58], &wires_c[4], &wires_b[46]);
   XOR(&wires_b[59], &wires_c[3], &wires_b[54]);
+  FLUSH(&wires_b[57], &wires_b[58]);
   XOR(&wires_b[60], &wires_b[46], &wires_b[57]);
   XOR(&wires_b[61], &wires_c[14], &wires_b[57]);
   XOR(&wires_b[62], &wires_b[52], &wires_b[58]);
@@ -589,6 +590,7 @@ __host__ void vectorized_sbox_n_bytes(CudaStreams streams,
 #undef FLUSH
 #undef AND
 #undef ADD_ONE_FLUSH
+#undef ADD_ONE
 }
 
 /**

backends/tfhe-cuda-backend/cuda/src/aes/aes256.cu

@@ -14,18 +14,13 @@ void cuda_integer_aes_ctr_256_encrypt_64_async(
 }
 
 uint64_t scratch_cuda_integer_key_expansion_256_64_async(
-    CudaStreamsFFI streams, int8_t **mem_ptr, uint32_t glwe_dimension,
-    uint32_t polynomial_size, uint32_t lwe_dimension, uint32_t ks_level,
-    uint32_t ks_base_log, uint32_t pbs_level, uint32_t pbs_base_log,
-    uint32_t grouping_factor, uint32_t message_modulus, uint32_t carry_modulus,
-    PBS_TYPE pbs_type, bool allocate_gpu_memory,
-    PBS_MS_REDUCTION_T noise_reduction_type) {
+    CudaStreamsFFI streams, int8_t **mem_ptr,
+    CudaLweBootstrapKeyParamsFFI bsk_params, uint32_t ks_level,
+    uint32_t ks_base_log, uint32_t message_modulus, uint32_t carry_modulus,
+    bool allocate_gpu_memory, PBS_MS_REDUCTION_T noise_reduction_type) {
 
-  int_radix_params params(pbs_type, glwe_dimension, polynomial_size,
-                          glwe_dimension * polynomial_size, lwe_dimension,
-                          ks_level, ks_base_log, pbs_level, pbs_base_log,
-                          grouping_factor, message_modulus, carry_modulus,
-                          noise_reduction_type);
+  int_radix_params params(bsk_params, ks_level, ks_base_log, message_modulus,
+                          carry_modulus, noise_reduction_type);
 
   return scratch_cuda_integer_key_expansion_256<uint64_t>(
       CudaStreams(streams), (int_key_expansion_256_buffer<uint64_t> **)mem_ptr,

backends/tfhe-cuda-backend/cuda/src/crypto/ciphertext.cu

@@ -150,3 +150,31 @@ void cuda_glwe_sample_extract_128_async(
           "N's are powers of two in the interval [256..4096].")
   }
 }
+
+void cuda_modulus_switch_multi_bit_64_async(void *stream, uint32_t gpu_index,
+                                            void *lwe_array_out,
+                                            void *lwe_array_in, uint32_t size,
+                                            uint32_t log_modulus,
+                                            uint32_t degree,
+                                            uint32_t grouping_factor) {
+
+  host_modulus_switch_multi_bit<uint64_t>(
+      static_cast<cudaStream_t>(stream), gpu_index,
+      static_cast<uint64_t *>(lwe_array_out),
+      static_cast<uint64_t *>(lwe_array_in), size, log_modulus, degree,
+      grouping_factor);
+}
+
+void cuda_modulus_switch_multi_bit_128_async(void *stream, uint32_t gpu_index,
+                                             void *lwe_array_out,
+                                             void *lwe_array_in, uint32_t size,
+                                             uint32_t log_modulus,
+                                             uint32_t degree,
+                                             uint32_t grouping_factor) {
+
+  host_modulus_switch_multi_bit<__uint128_t>(
+      static_cast<cudaStream_t>(stream), gpu_index,
+      static_cast<__uint128_t *>(lwe_array_out),
+      static_cast<__uint128_t *>(lwe_array_in), size, log_modulus, degree,
+      grouping_factor);
+}

backends/tfhe-cuda-backend/cuda/src/crypto/torus.cuh

@@ -463,5 +463,48 @@ __global__ void __launch_bounds__(512)
       return;
   }
 }
+// This function is only used for noise tests, it follows the same logic
+// that is embedded in the keybundle just we need a global function to
+// be able to test it individually.
+template <typename Torus, class params>
+__global__ void
+modulus_switch_multi_bit(Torus *array_out, const Torus *array_in, int size,
+                         uint32_t log_modulus, uint32_t grouping_factor) {
+  const int tid = threadIdx.x + blockIdx.x * blockDim.x;
+  if (tid < size) {
+    int num_monomials = 1 << grouping_factor;
+    int input_offset = tid * grouping_factor;
+    int output_offset = tid * num_monomials;
+    // We calculate all monomials even if the first one is never used.
+    for (int ggsw_idx = 0; ggsw_idx < num_monomials; ggsw_idx++) {
+      array_out[ggsw_idx + output_offset] =
+          calculates_monomial_degree<Torus, params>(&array_in[input_offset],
+                                                    ggsw_idx, grouping_factor);
+    }
+  }
+}
+// This aims to be launched only from the noise tests.
+//  That is why we support a specific set of parameters
+template <typename Torus>
+__host__ void host_modulus_switch_multi_bit(
+    cudaStream_t stream, uint32_t gpu_index, Torus *array_out, Torus *array_in,
+    int size, uint32_t log_modulus, uint32_t degree, uint32_t grouping_factor) {
+  check_cuda_error(cudaSetDevice(gpu_index));
+  int multibit_size = size / grouping_factor;
+  int num_threads = 0, num_blocks = 0;
+  getNumBlocksAndThreads(multibit_size, 1024, num_blocks, num_threads);
+  switch (degree) {
+  case 2048:
+    modulus_switch_multi_bit<Torus, Degree<2048>>
+        <<<num_blocks, num_threads, 0, stream>>>(
+            array_out, array_in, multibit_size, log_modulus, grouping_factor);
+    break;
+  default:
+    PANIC("Cuda error: unsupported polynomial size. Supported "
+          "N's are powers of two in the interval [2048].")
+  };
+
+  check_cuda_error(cudaGetLastError());
+}
 
 #endif // CNCRT_TORUS_H

backends/tfhe-cuda-backend/cuda/src/integer/abs.cu

@@ -2,17 +2,12 @@
 
 uint64_t scratch_cuda_integer_abs_inplace_64_async(
     CudaStreamsFFI streams, int8_t **mem_ptr, bool is_signed,
-    uint32_t glwe_dimension, uint32_t polynomial_size,
-    uint32_t big_lwe_dimension, uint32_t small_lwe_dimension, uint32_t ks_level,
-    uint32_t ks_base_log, uint32_t pbs_level, uint32_t pbs_base_log,
-    uint32_t grouping_factor, uint32_t num_blocks, uint32_t message_modulus,
-    uint32_t carry_modulus, PBS_TYPE pbs_type, bool allocate_gpu_memory,
+    CudaLweBootstrapKeyParamsFFI bsk_params, uint32_t ks_level,
+    uint32_t ks_base_log, uint32_t num_blocks, uint32_t message_modulus,
+    uint32_t carry_modulus, bool allocate_gpu_memory,
     PBS_MS_REDUCTION_T noise_reduction_type) {
-
-  int_radix_params params(pbs_type, glwe_dimension, polynomial_size,
-                          big_lwe_dimension, small_lwe_dimension, ks_level,
-                          ks_base_log, pbs_level, pbs_base_log, grouping_factor,
-                          message_modulus, carry_modulus, noise_reduction_type);
+  int_radix_params params(bsk_params, ks_level, ks_base_log, message_modulus,
+                          carry_modulus, noise_reduction_type);
 
   return scratch_cuda_integer_abs<uint64_t>(
       CudaStreams(streams), (int_abs_buffer<uint64_t> **)mem_ptr, is_signed,

backends/tfhe-cuda-backend/cuda/src/integer/bitwise_ops.cu

@@ -11,19 +11,14 @@ void cuda_boolean_bitop_inplace_64_async(
 }
 
 uint64_t scratch_cuda_boolean_bitop_inplace_64_async(
-    CudaStreamsFFI streams, int8_t **mem_ptr, uint32_t glwe_dimension,
-    uint32_t polynomial_size, uint32_t big_lwe_dimension,
-    uint32_t small_lwe_dimension, uint32_t ks_level, uint32_t ks_base_log,
-    uint32_t pbs_level, uint32_t pbs_base_log, uint32_t grouping_factor,
-    uint32_t lwe_ciphertext_count, uint32_t message_modulus,
-    uint32_t carry_modulus, PBS_TYPE pbs_type, BITOP_TYPE op_type,
+    CudaStreamsFFI streams, int8_t **mem_ptr,
+    CudaLweBootstrapKeyParamsFFI bsk_params, uint32_t ks_level,
+    uint32_t ks_base_log, uint32_t lwe_ciphertext_count,
+    uint32_t message_modulus, uint32_t carry_modulus, BITOP_TYPE op_type,
     bool is_unchecked, bool allocate_gpu_memory,
     PBS_MS_REDUCTION_T noise_reduction_type) {
-
-  int_radix_params params(pbs_type, glwe_dimension, polynomial_size,
-                          big_lwe_dimension, small_lwe_dimension, ks_level,
-                          ks_base_log, pbs_level, pbs_base_log, grouping_factor,
-                          message_modulus, carry_modulus, noise_reduction_type);
+  int_radix_params params(bsk_params, ks_level, ks_base_log, message_modulus,
+                          carry_modulus, noise_reduction_type);
 
   return scratch_cuda_boolean_bitop<uint64_t>(
       CudaStreams(streams), (boolean_bitop_buffer<uint64_t> **)mem_ptr,
@@ -41,18 +36,13 @@ void cleanup_cuda_boolean_bitop_inplace_64(CudaStreamsFFI streams,
 }
 
 uint64_t scratch_cuda_boolean_bitnot_64_async(
-    CudaStreamsFFI streams, int8_t **mem_ptr, uint32_t glwe_dimension,
-    uint32_t polynomial_size, uint32_t big_lwe_dimension,
-    uint32_t small_lwe_dimension, uint32_t ks_level, uint32_t ks_base_log,
-    uint32_t pbs_level, uint32_t pbs_base_log, uint32_t grouping_factor,
-    uint32_t message_modulus, uint32_t carry_modulus, PBS_TYPE pbs_type,
+    CudaStreamsFFI streams, int8_t **mem_ptr,
+    CudaLweBootstrapKeyParamsFFI bsk_params, uint32_t ks_level,
+    uint32_t ks_base_log, uint32_t message_modulus, uint32_t carry_modulus,
     uint32_t lwe_ciphertext_count, bool is_unchecked, bool allocate_gpu_memory,
     PBS_MS_REDUCTION_T noise_reduction_type) {
-
-  int_radix_params params(pbs_type, glwe_dimension, polynomial_size,
-                          big_lwe_dimension, small_lwe_dimension, ks_level,
-                          ks_base_log, pbs_level, pbs_base_log, grouping_factor,
-                          message_modulus, carry_modulus, noise_reduction_type);
+  int_radix_params params(bsk_params, ks_level, ks_base_log, message_modulus,
+                          carry_modulus, noise_reduction_type);
 
   return scratch_cuda_boolean_bitnot<uint64_t>(
       CudaStreams(streams), (boolean_bitnot_buffer<uint64_t> **)mem_ptr, params,
@@ -78,6 +68,34 @@ void cleanup_cuda_boolean_bitnot_64(CudaStreamsFFI streams,
   *mem_ptr_void = nullptr;
 }
 
+uint64_t scratch_cuda_integer_bitop_inplace_64_async(
+    CudaStreamsFFI streams, int8_t **mem_ptr,
+    CudaLweBootstrapKeyParamsFFI bsk_params, uint32_t ks_level,
+    uint32_t ks_base_log, uint32_t lwe_ciphertext_count,
+    uint32_t message_modulus, uint32_t carry_modulus, BITOP_TYPE op_type,
+    bool allocate_gpu_memory, PBS_MS_REDUCTION_T noise_reduction_type) {
+  int_radix_params params(bsk_params, ks_level, ks_base_log, message_modulus,
+                          carry_modulus, noise_reduction_type);
+
+  return scratch_cuda_bitop<uint64_t>(
+      CudaStreams(streams), (int_bitop_buffer<uint64_t> **)mem_ptr,
+      lwe_ciphertext_count, params, op_type, allocate_gpu_memory);
+}
+
+uint64_t scratch_cuda_integer_scalar_bitop_inplace_64_async(
+    CudaStreamsFFI streams, int8_t **mem_ptr,
+    CudaLweBootstrapKeyParamsFFI bsk_params, uint32_t ks_level,
+    uint32_t ks_base_log, uint32_t lwe_ciphertext_count,
+    uint32_t message_modulus, uint32_t carry_modulus, BITOP_TYPE op_type,
+    bool allocate_gpu_memory, PBS_MS_REDUCTION_T noise_reduction_type) {
+  int_radix_params params(bsk_params, ks_level, ks_base_log, message_modulus,
+                          carry_modulus, noise_reduction_type);
+
+  return scratch_cuda_bitop<uint64_t>(
+      CudaStreams(streams), (int_bitop_buffer<uint64_t> **)mem_ptr,
+      lwe_ciphertext_count, params, op_type, allocate_gpu_memory);
+}
+
 void cuda_bitnot_ciphertext_64(CudaStreamsFFI streams,
                                CudaRadixCiphertextFFI *radix_ciphertext,
                                uint32_t ct_message_modulus,
@@ -99,25 +117,6 @@ void cuda_integer_bitop_inplace_64_async(
                        (uint64_t **)(ksks));
 }
 
-uint64_t scratch_cuda_integer_bitop_inplace_64_async(
-    CudaStreamsFFI streams, int8_t **mem_ptr, uint32_t glwe_dimension,
-    uint32_t polynomial_size, uint32_t big_lwe_dimension,
-    uint32_t small_lwe_dimension, uint32_t ks_level, uint32_t ks_base_log,
-    uint32_t pbs_level, uint32_t pbs_base_log, uint32_t grouping_factor,
-    uint32_t lwe_ciphertext_count, uint32_t message_modulus,
-    uint32_t carry_modulus, PBS_TYPE pbs_type, BITOP_TYPE op_type,
-    bool allocate_gpu_memory, PBS_MS_REDUCTION_T noise_reduction_type) {
-
-  int_radix_params params(pbs_type, glwe_dimension, polynomial_size,
-                          big_lwe_dimension, small_lwe_dimension, ks_level,
-                          ks_base_log, pbs_level, pbs_base_log, grouping_factor,
-                          message_modulus, carry_modulus, noise_reduction_type);
-
-  return scratch_cuda_bitop<uint64_t>(
-      CudaStreams(streams), (int_bitop_buffer<uint64_t> **)mem_ptr,
-      lwe_ciphertext_count, params, op_type, allocate_gpu_memory);
-}
-
 void cleanup_cuda_integer_bitop_inplace_64(CudaStreamsFFI streams,
                                            int8_t **mem_ptr_void) {
 
@@ -128,25 +127,6 @@ void cleanup_cuda_integer_bitop_inplace_64(CudaStreamsFFI streams,
   *mem_ptr_void = nullptr;
 }
 
-uint64_t scratch_cuda_integer_scalar_bitop_inplace_64_async(
-    CudaStreamsFFI streams, int8_t **mem_ptr, uint32_t glwe_dimension,
-    uint32_t polynomial_size, uint32_t big_lwe_dimension,
-    uint32_t small_lwe_dimension, uint32_t ks_level, uint32_t ks_base_log,
-    uint32_t pbs_level, uint32_t pbs_base_log, uint32_t grouping_factor,
-    uint32_t lwe_ciphertext_count, uint32_t message_modulus,
-    uint32_t carry_modulus, PBS_TYPE pbs_type, BITOP_TYPE op_type,
-    bool allocate_gpu_memory, PBS_MS_REDUCTION_T noise_reduction_type) {
-
-  int_radix_params params(pbs_type, glwe_dimension, polynomial_size,
-                          big_lwe_dimension, small_lwe_dimension, ks_level,
-                          ks_base_log, pbs_level, pbs_base_log, grouping_factor,
-                          message_modulus, carry_modulus, noise_reduction_type);
-
-  return scratch_cuda_bitop<uint64_t>(
-      CudaStreams(streams), (int_bitop_buffer<uint64_t> **)mem_ptr,
-      lwe_ciphertext_count, params, op_type, allocate_gpu_memory);
-}
-
 void cleanup_cuda_integer_scalar_bitop_inplace_64(CudaStreamsFFI streams,
                                                   int8_t **mem_ptr_void) {
 

backends/tfhe-cuda-backend/cuda/src/integer/cast.cu

@@ -34,19 +34,14 @@ void trim_radix_blocks_msb_64(CudaRadixCiphertextFFI *output,
 }
 
 uint64_t scratch_cuda_cast_to_unsigned_64_async(
-    CudaStreamsFFI streams, int8_t **mem_ptr, uint32_t glwe_dimension,
-    uint32_t polynomial_size, uint32_t big_lwe_dimension,
-    uint32_t small_lwe_dimension, uint32_t ks_level, uint32_t ks_base_log,
-    uint32_t pbs_level, uint32_t pbs_base_log, uint32_t grouping_factor,
-    uint32_t num_input_blocks, uint32_t target_num_blocks, bool input_is_signed,
-    bool requires_full_propagate, uint32_t message_modulus,
-    uint32_t carry_modulus, PBS_TYPE pbs_type, bool allocate_gpu_memory,
+    CudaStreamsFFI streams, int8_t **mem_ptr,
+    CudaLweBootstrapKeyParamsFFI bsk_params, uint32_t ks_level,
+    uint32_t ks_base_log, uint32_t num_input_blocks, uint32_t target_num_blocks,
+    bool input_is_signed, bool requires_full_propagate,
+    uint32_t message_modulus, uint32_t carry_modulus, bool allocate_gpu_memory,
     PBS_MS_REDUCTION_T noise_reduction_type) {
-
-  int_radix_params params(pbs_type, glwe_dimension, polynomial_size,
-                          big_lwe_dimension, small_lwe_dimension, ks_level,
-                          ks_base_log, pbs_level, pbs_base_log, grouping_factor,
-                          message_modulus, carry_modulus, noise_reduction_type);
+  int_radix_params params(bsk_params, ks_level, ks_base_log, message_modulus,
+                          carry_modulus, noise_reduction_type);
 
   return scratch_cuda_cast_to_unsigned<uint64_t>(
       CudaStreams(streams), (int_cast_to_unsigned_buffer<uint64_t> **)mem_ptr,
@@ -80,19 +75,13 @@ void cleanup_cuda_cast_to_unsigned_64(CudaStreamsFFI streams,
 }
 
 uint64_t scratch_cuda_cast_to_signed_64_async(
-    CudaStreamsFFI streams, int8_t **mem_ptr, uint32_t glwe_dimension,
-    uint32_t polynomial_size, uint32_t lwe_dimension, uint32_t ks_level,
-    uint32_t ks_base_log, uint32_t pbs_level, uint32_t pbs_base_log,
-    uint32_t grouping_factor, uint32_t num_input_blocks,
-    uint32_t target_num_blocks, uint32_t message_modulus,
-    uint32_t carry_modulus, PBS_TYPE pbs_type, bool input_is_signed,
+    CudaStreamsFFI streams, int8_t **mem_ptr,
+    CudaLweBootstrapKeyParamsFFI bsk_params, uint32_t ks_level,
+    uint32_t ks_base_log, uint32_t num_input_blocks, uint32_t target_num_blocks,
+    uint32_t message_modulus, uint32_t carry_modulus, bool input_is_signed,
     bool allocate_gpu_memory, PBS_MS_REDUCTION_T noise_reduction_type) {
-
-  int_radix_params params(pbs_type, glwe_dimension, polynomial_size,
-                          glwe_dimension * polynomial_size, lwe_dimension,
-                          ks_level, ks_base_log, pbs_level, pbs_base_log,
-                          grouping_factor, message_modulus, carry_modulus,
-                          noise_reduction_type);
+  int_radix_params params(bsk_params, ks_level, ks_base_log, message_modulus,
+                          carry_modulus, noise_reduction_type);
 
   return scratch_cuda_cast_to_signed<uint64_t>(
       CudaStreams(streams), (int_cast_to_signed_buffer<uint64_t> **)mem_ptr,

backends/tfhe-cuda-backend/cuda/src/integer/cmux.cu

@@ -1,18 +1,16 @@
 #include "integer/cmux.cuh"
 
-uint64_t scratch_cuda_cmux_64_async(
-    CudaStreamsFFI streams, int8_t **mem_ptr, uint32_t glwe_dimension,
-    uint32_t polynomial_size, uint32_t big_lwe_dimension,
-    uint32_t small_lwe_dimension, uint32_t ks_level, uint32_t ks_base_log,
-    uint32_t pbs_level, uint32_t pbs_base_log, uint32_t grouping_factor,
-    uint32_t lwe_ciphertext_count, uint32_t message_modulus,
-    uint32_t carry_modulus, PBS_TYPE pbs_type, bool allocate_gpu_memory,
-    PBS_MS_REDUCTION_T noise_reduction_type) {
+uint64_t scratch_cuda_cmux_64_async(CudaStreamsFFI streams, int8_t **mem_ptr,
+                                    CudaLweBootstrapKeyParamsFFI bsk_params,
+                                    uint32_t ks_level, uint32_t ks_base_log,
+                                    uint32_t lwe_ciphertext_count,
+                                    uint32_t message_modulus,
+                                    uint32_t carry_modulus,
+                                    bool allocate_gpu_memory,
+                                    PBS_MS_REDUCTION_T noise_reduction_type) {
   PUSH_RANGE("scratch cmux")
-  int_radix_params params(pbs_type, glwe_dimension, polynomial_size,
-                          big_lwe_dimension, small_lwe_dimension, ks_level,
-                          ks_base_log, pbs_level, pbs_base_log, grouping_factor,
-                          message_modulus, carry_modulus, noise_reduction_type);
+  int_radix_params params(bsk_params, ks_level, ks_base_log, message_modulus,
+                          carry_modulus, noise_reduction_type);
 
   std::function<uint64_t(uint64_t)> predicate_lut_f =
       [](uint64_t x) -> uint64_t { return x == 1; };

backends/tfhe-cuda-backend/cuda/src/integer/comparison.cu

@@ -1,18 +1,14 @@
 #include "integer/comparison.cuh"
 
 uint64_t scratch_cuda_integer_comparison_64_async(
-    CudaStreamsFFI streams, int8_t **mem_ptr, uint32_t glwe_dimension,
-    uint32_t polynomial_size, uint32_t big_lwe_dimension,
-    uint32_t small_lwe_dimension, uint32_t ks_level, uint32_t ks_base_log,
-    uint32_t pbs_level, uint32_t pbs_base_log, uint32_t grouping_factor,
-    uint32_t num_radix_blocks, uint32_t message_modulus, uint32_t carry_modulus,
-    PBS_TYPE pbs_type, COMPARISON_TYPE op_type, bool is_signed,
+    CudaStreamsFFI streams, int8_t **mem_ptr,
+    CudaLweBootstrapKeyParamsFFI bsk_params, uint32_t ks_level,
+    uint32_t ks_base_log, uint32_t num_radix_blocks, uint32_t message_modulus,
+    uint32_t carry_modulus, COMPARISON_TYPE op_type, bool is_signed,
     bool allocate_gpu_memory, PBS_MS_REDUCTION_T noise_reduction_type) {
   PUSH_RANGE("scratch comparison")
-  int_radix_params params(pbs_type, glwe_dimension, polynomial_size,
-                          big_lwe_dimension, small_lwe_dimension, ks_level,
-                          ks_base_log, pbs_level, pbs_base_log, grouping_factor,
-                          message_modulus, carry_modulus, noise_reduction_type);
+  int_radix_params params(bsk_params, ks_level, ks_base_log, message_modulus,
+                          carry_modulus, noise_reduction_type);
 
   uint64_t size_tracker = 0;
   switch (op_type) {
@@ -38,18 +34,14 @@ uint64_t scratch_cuda_integer_comparison_64_async(
 }
 
 uint64_t scratch_cuda_integer_scalar_comparison_64_async(
-    CudaStreamsFFI streams, int8_t **mem_ptr, uint32_t glwe_dimension,
-    uint32_t polynomial_size, uint32_t big_lwe_dimension,
-    uint32_t small_lwe_dimension, uint32_t ks_level, uint32_t ks_base_log,
-    uint32_t pbs_level, uint32_t pbs_base_log, uint32_t grouping_factor,
-    uint32_t num_radix_blocks, uint32_t message_modulus, uint32_t carry_modulus,
-    PBS_TYPE pbs_type, COMPARISON_TYPE op_type, bool is_signed,
+    CudaStreamsFFI streams, int8_t **mem_ptr,
+    CudaLweBootstrapKeyParamsFFI bsk_params, uint32_t ks_level,
+    uint32_t ks_base_log, uint32_t num_radix_blocks, uint32_t message_modulus,
+    uint32_t carry_modulus, COMPARISON_TYPE op_type, bool is_signed,
     bool allocate_gpu_memory, PBS_MS_REDUCTION_T noise_reduction_type) {
   PUSH_RANGE("scratch scalar comparison")
-  int_radix_params params(pbs_type, glwe_dimension, polynomial_size,
-                          big_lwe_dimension, small_lwe_dimension, ks_level,
-                          ks_base_log, pbs_level, pbs_base_log, grouping_factor,
-                          message_modulus, carry_modulus, noise_reduction_type);
+  int_radix_params params(bsk_params, ks_level, ks_base_log, message_modulus,
+                          carry_modulus, noise_reduction_type);
 
   uint64_t size_tracker = 0;
   switch (op_type) {
@@ -151,18 +143,13 @@ void cleanup_cuda_integer_scalar_comparison_64(CudaStreamsFFI streams,
 }
 
 uint64_t scratch_cuda_integer_are_all_comparisons_block_true_64_async(
-    CudaStreamsFFI streams, int8_t **mem_ptr, uint32_t glwe_dimension,
-    uint32_t polynomial_size, uint32_t big_lwe_dimension,
-    uint32_t small_lwe_dimension, uint32_t ks_level, uint32_t ks_base_log,
-    uint32_t pbs_level, uint32_t pbs_base_log, uint32_t grouping_factor,
-    uint32_t num_radix_blocks, uint32_t message_modulus, uint32_t carry_modulus,
-    PBS_TYPE pbs_type, bool allocate_gpu_memory,
+    CudaStreamsFFI streams, int8_t **mem_ptr,
+    CudaLweBootstrapKeyParamsFFI bsk_params, uint32_t ks_level,
+    uint32_t ks_base_log, uint32_t num_radix_blocks, uint32_t message_modulus,
+    uint32_t carry_modulus, bool allocate_gpu_memory,
     PBS_MS_REDUCTION_T noise_reduction_type) {
-
-  int_radix_params params(pbs_type, glwe_dimension, polynomial_size,
-                          big_lwe_dimension, small_lwe_dimension, ks_level,
-                          ks_base_log, pbs_level, pbs_base_log, grouping_factor,
-                          message_modulus, carry_modulus, noise_reduction_type);
+  int_radix_params params(bsk_params, ks_level, ks_base_log, message_modulus,
+                          carry_modulus, noise_reduction_type);
 
   return scratch_cuda_comparison_check<uint64_t>(
       CudaStreams(streams), (int_comparison_buffer<uint64_t> **)mem_ptr,
@@ -196,18 +183,13 @@ void cleanup_cuda_integer_are_all_comparisons_block_true_64(
 }
 
 uint64_t scratch_cuda_integer_is_at_least_one_comparisons_block_true_64_async(
-    CudaStreamsFFI streams, int8_t **mem_ptr, uint32_t glwe_dimension,
-    uint32_t polynomial_size, uint32_t big_lwe_dimension,
-    uint32_t small_lwe_dimension, uint32_t ks_level, uint32_t ks_base_log,
-    uint32_t pbs_level, uint32_t pbs_base_log, uint32_t grouping_factor,
-    uint32_t num_radix_blocks, uint32_t message_modulus, uint32_t carry_modulus,
-    PBS_TYPE pbs_type, bool allocate_gpu_memory,
+    CudaStreamsFFI streams, int8_t **mem_ptr,
+    CudaLweBootstrapKeyParamsFFI bsk_params, uint32_t ks_level,
+    uint32_t ks_base_log, uint32_t num_radix_blocks, uint32_t message_modulus,
+    uint32_t carry_modulus, bool allocate_gpu_memory,
     PBS_MS_REDUCTION_T noise_reduction_type) {
-
-  int_radix_params params(pbs_type, glwe_dimension, polynomial_size,
-                          big_lwe_dimension, small_lwe_dimension, ks_level,
-                          ks_base_log, pbs_level, pbs_base_log, grouping_factor,
-                          message_modulus, carry_modulus, noise_reduction_type);
+  int_radix_params params(bsk_params, ks_level, ks_base_log, message_modulus,
+                          carry_modulus, noise_reduction_type);
 
   return scratch_cuda_comparison_check<uint64_t>(
       CudaStreams(streams), (int_comparison_buffer<uint64_t> **)mem_ptr,

backends/tfhe-cuda-backend/cuda/src/integer/compression/compression.cu

@@ -23,22 +23,24 @@ uint64_t scratch_cuda_integer_decompress_radix_ciphertext_64_async(
     CudaStreamsFFI streams, int8_t **mem_ptr,
     uint32_t encryption_glwe_dimension, uint32_t encryption_polynomial_size,
     uint32_t compression_glwe_dimension, uint32_t compression_polynomial_size,
-    uint32_t lwe_dimension, uint32_t pbs_level, uint32_t pbs_base_log,
-    uint32_t grouping_factor, uint32_t num_blocks_to_decompress,
-    uint32_t message_modulus, uint32_t carry_modulus, PBS_TYPE pbs_type,
-    bool allocate_gpu_memory, PBS_MS_REDUCTION_T noise_reduction_type) {
+    CudaLweBootstrapKeyParamsFFI bsk_params, uint32_t num_blocks_to_decompress,
+    uint32_t message_modulus, uint32_t carry_modulus, bool allocate_gpu_memory,
+    PBS_MS_REDUCTION_T noise_reduction_type) {
 
   // Decompression doesn't keyswitch, so big and small dimensions are the same
   int_radix_params encryption_params(
-      pbs_type, encryption_glwe_dimension, encryption_polynomial_size,
-      lwe_dimension, lwe_dimension, 0, 0, pbs_level, pbs_base_log,
-      grouping_factor, message_modulus, carry_modulus, noise_reduction_type);
+      (PBS_TYPE)bsk_params.pbs_type, encryption_glwe_dimension,
+      encryption_polynomial_size, bsk_params.big_lwe_dimension,
+      bsk_params.big_lwe_dimension, 0, 0, bsk_params.level_count,
+      bsk_params.base_log, bsk_params.grouping_factor, message_modulus,
+      carry_modulus, noise_reduction_type);
 
   int_radix_params compression_params(
-      pbs_type, compression_glwe_dimension, compression_polynomial_size,
-      lwe_dimension, compression_glwe_dimension * compression_polynomial_size,
-      0, 0, pbs_level, pbs_base_log, grouping_factor, message_modulus,
-      carry_modulus, noise_reduction_type);
+      (PBS_TYPE)bsk_params.pbs_type, compression_glwe_dimension,
+      compression_polynomial_size, bsk_params.big_lwe_dimension,
+      compression_glwe_dimension * compression_polynomial_size, 0, 0,
+      bsk_params.level_count, bsk_params.base_log, bsk_params.grouping_factor,
+      message_modulus, carry_modulus, noise_reduction_type);
 
   return scratch_cuda_integer_decompress_radix_ciphertext<uint64_t>(
       CudaStreams(streams), (int_decompression<uint64_t> **)mem_ptr,

backends/tfhe-cuda-backend/cuda/src/integer/div_rem.cu

@@ -2,17 +2,13 @@
 
 uint64_t scratch_cuda_integer_div_rem_64_async(
     CudaStreamsFFI streams, bool is_signed, int8_t **mem_ptr,
-    uint32_t glwe_dimension, uint32_t polynomial_size,
-    uint32_t big_lwe_dimension, uint32_t small_lwe_dimension, uint32_t ks_level,
-    uint32_t ks_base_log, uint32_t pbs_level, uint32_t pbs_base_log,
-    uint32_t grouping_factor, uint32_t num_blocks, uint32_t message_modulus,
-    uint32_t carry_modulus, PBS_TYPE pbs_type, bool allocate_gpu_memory,
+    CudaLweBootstrapKeyParamsFFI bsk_params, uint32_t ks_level,
+    uint32_t ks_base_log, uint32_t num_blocks, uint32_t message_modulus,
+    uint32_t carry_modulus, bool allocate_gpu_memory,
     PBS_MS_REDUCTION_T noise_reduction_type) {
   PUSH_RANGE("scratch div")
-  int_radix_params params(pbs_type, glwe_dimension, polynomial_size,
-                          big_lwe_dimension, small_lwe_dimension, ks_level,
-                          ks_base_log, pbs_level, pbs_base_log, grouping_factor,
-                          message_modulus, carry_modulus, noise_reduction_type);
+  int_radix_params params(bsk_params, ks_level, ks_base_log, message_modulus,
+                          carry_modulus, noise_reduction_type);
 
   return scratch_cuda_integer_div_rem<uint64_t>(
       CudaStreams(streams), is_signed, (int_div_rem_memory<uint64_t> **)mem_ptr,

backends/tfhe-cuda-backend/cuda/src/integer/ilog2.cu

@@ -1,19 +1,14 @@
 #include "ilog2.cuh"
 
 uint64_t scratch_cuda_integer_count_of_consecutive_bits_64_async(
-    CudaStreamsFFI streams, int8_t **mem_ptr, uint32_t glwe_dimension,
-    uint32_t polynomial_size, uint32_t lwe_dimension, uint32_t ks_level,
-    uint32_t ks_base_log, uint32_t pbs_level, uint32_t pbs_base_log,
-    uint32_t grouping_factor, uint32_t num_blocks, uint32_t counter_num_blocks,
-    uint32_t message_modulus, uint32_t carry_modulus, PBS_TYPE pbs_type,
-    Direction direction, BitValue bit_value, bool allocate_gpu_memory,
+    CudaStreamsFFI streams, int8_t **mem_ptr,
+    CudaLweBootstrapKeyParamsFFI bsk_params, uint32_t ks_level,
+    uint32_t ks_base_log, uint32_t num_blocks, uint32_t counter_num_blocks,
+    uint32_t message_modulus, uint32_t carry_modulus, Direction direction,
+    BitValue bit_value, bool allocate_gpu_memory,
     PBS_MS_REDUCTION_T noise_reduction_type) {
-
-  int_radix_params params(pbs_type, glwe_dimension, polynomial_size,
-                          glwe_dimension * polynomial_size, lwe_dimension,
-                          ks_level, ks_base_log, pbs_level, pbs_base_log,
-                          grouping_factor, message_modulus, carry_modulus,
-                          noise_reduction_type);
+  int_radix_params params(bsk_params, ks_level, ks_base_log, message_modulus,
+                          carry_modulus, noise_reduction_type);
 
   return scratch_integer_count_of_consecutive_bits<uint64_t>(
       CudaStreams(streams), params,
@@ -53,19 +48,14 @@ void cleanup_cuda_integer_count_of_consecutive_bits_64(CudaStreamsFFI streams,
 }
 
 uint64_t scratch_cuda_integer_ilog2_64_async(
-    CudaStreamsFFI streams, int8_t **mem_ptr, uint32_t glwe_dimension,
-    uint32_t polynomial_size, uint32_t lwe_dimension, uint32_t ks_level,
-    uint32_t ks_base_log, uint32_t pbs_level, uint32_t pbs_base_log,
-    uint32_t grouping_factor, uint32_t message_modulus, uint32_t carry_modulus,
-    PBS_TYPE pbs_type, uint32_t input_num_blocks, uint32_t counter_num_blocks,
+    CudaStreamsFFI streams, int8_t **mem_ptr,
+    CudaLweBootstrapKeyParamsFFI bsk_params, uint32_t ks_level,
+    uint32_t ks_base_log, uint32_t message_modulus, uint32_t carry_modulus,
+    uint32_t input_num_blocks, uint32_t counter_num_blocks,
     uint32_t num_bits_in_ciphertext, bool allocate_gpu_memory,
     PBS_MS_REDUCTION_T noise_reduction_type) {
-
-  int_radix_params params(pbs_type, glwe_dimension, polynomial_size,
-                          glwe_dimension * polynomial_size, lwe_dimension,
-                          ks_level, ks_base_log, pbs_level, pbs_base_log,
-                          grouping_factor, message_modulus, carry_modulus,
-                          noise_reduction_type);
+  int_radix_params params(bsk_params, ks_level, ks_base_log, message_modulus,
+                          carry_modulus, noise_reduction_type);
 
   return scratch_integer_ilog2<uint64_t>(
       CudaStreams(streams), params, (int_ilog2_buffer<uint64_t> **)mem_ptr,

backends/tfhe-cuda-backend/cuda/src/integer/integer.cu

@@ -15,17 +15,12 @@ void cuda_full_propagation_64_inplace_async(
 }
 
 uint64_t scratch_cuda_full_propagation_64_inplace_async(
-    CudaStreamsFFI streams, int8_t **mem_ptr, uint32_t lwe_dimension,
-    uint32_t glwe_dimension, uint32_t polynomial_size, uint32_t ks_level,
-    uint32_t ks_base_log, uint32_t pbs_level, uint32_t pbs_base_log,
-    uint32_t grouping_factor, uint32_t message_modulus, uint32_t carry_modulus,
-    PBS_TYPE pbs_type, bool allocate_gpu_memory,
-    PBS_MS_REDUCTION_T noise_reduction_type) {
-  int_radix_params params(pbs_type, glwe_dimension, polynomial_size,
-                          glwe_dimension * polynomial_size, lwe_dimension,
-                          ks_level, ks_base_log, pbs_level, pbs_base_log,
-                          grouping_factor, message_modulus, carry_modulus,
-                          noise_reduction_type);
+    CudaStreamsFFI streams, int8_t **mem_ptr,
+    CudaLweBootstrapKeyParamsFFI bsk_params, uint32_t ks_level,
+    uint32_t ks_base_log, uint32_t message_modulus, uint32_t carry_modulus,
+    bool allocate_gpu_memory, PBS_MS_REDUCTION_T noise_reduction_type) {
+  int_radix_params params(bsk_params, ks_level, ks_base_log, message_modulus,
+                          carry_modulus, noise_reduction_type);
 
   return scratch_cuda_full_propagation<uint64_t>(
       CudaStreams(streams), (int_fullprop_buffer<uint64_t> **)mem_ptr, params,
@@ -44,17 +39,13 @@ void cleanup_cuda_full_propagation_64_inplace(CudaStreamsFFI streams,
 }
 
 uint64_t scratch_cuda_propagate_single_carry_64_inplace_async(
-    CudaStreamsFFI streams, int8_t **mem_ptr, uint32_t glwe_dimension,
-    uint32_t polynomial_size, uint32_t big_lwe_dimension,
-    uint32_t small_lwe_dimension, uint32_t ks_level, uint32_t ks_base_log,
-    uint32_t pbs_level, uint32_t pbs_base_log, uint32_t grouping_factor,
-    uint32_t num_blocks, uint32_t message_modulus, uint32_t carry_modulus,
-    PBS_TYPE pbs_type, uint32_t requested_flag, bool allocate_gpu_memory,
+    CudaStreamsFFI streams, int8_t **mem_ptr,
+    CudaLweBootstrapKeyParamsFFI bsk_params, uint32_t ks_level,
+    uint32_t ks_base_log, uint32_t num_blocks, uint32_t message_modulus,
+    uint32_t carry_modulus, uint32_t requested_flag, bool allocate_gpu_memory,
     PBS_MS_REDUCTION_T noise_reduction_type) {
-  int_radix_params params(pbs_type, glwe_dimension, polynomial_size,
-                          big_lwe_dimension, small_lwe_dimension, ks_level,
-                          ks_base_log, pbs_level, pbs_base_log, grouping_factor,
-                          message_modulus, carry_modulus, noise_reduction_type);
+  int_radix_params params(bsk_params, ks_level, ks_base_log, message_modulus,
+                          carry_modulus, noise_reduction_type);
 
   return scratch_cuda_propagate_single_carry_inplace<uint64_t>(
       CudaStreams(streams), (int_sc_prop_memory<uint64_t> **)mem_ptr,
@@ -62,17 +53,13 @@ uint64_t scratch_cuda_propagate_single_carry_64_inplace_async(
 }
 
 uint64_t scratch_cuda_add_and_propagate_single_carry_64_inplace_async(
-    CudaStreamsFFI streams, int8_t **mem_ptr, uint32_t glwe_dimension,
-    uint32_t polynomial_size, uint32_t big_lwe_dimension,
-    uint32_t small_lwe_dimension, uint32_t ks_level, uint32_t ks_base_log,
-    uint32_t pbs_level, uint32_t pbs_base_log, uint32_t grouping_factor,
-    uint32_t num_blocks, uint32_t message_modulus, uint32_t carry_modulus,
-    PBS_TYPE pbs_type, uint32_t requested_flag, bool allocate_gpu_memory,
+    CudaStreamsFFI streams, int8_t **mem_ptr,
+    CudaLweBootstrapKeyParamsFFI bsk_params, uint32_t ks_level,
+    uint32_t ks_base_log, uint32_t num_blocks, uint32_t message_modulus,
+    uint32_t carry_modulus, uint32_t requested_flag, bool allocate_gpu_memory,
     PBS_MS_REDUCTION_T noise_reduction_type) {
-  int_radix_params params(pbs_type, glwe_dimension, polynomial_size,
-                          big_lwe_dimension, small_lwe_dimension, ks_level,
-                          ks_base_log, pbs_level, pbs_base_log, grouping_factor,
-                          message_modulus, carry_modulus, noise_reduction_type);
+  int_radix_params params(bsk_params, ks_level, ks_base_log, message_modulus,
+                          carry_modulus, noise_reduction_type);
 
   return scratch_cuda_propagate_single_carry_inplace<uint64_t>(
       CudaStreams(streams), (int_sc_prop_memory<uint64_t> **)mem_ptr,
@@ -80,17 +67,13 @@ uint64_t scratch_cuda_add_and_propagate_single_carry_64_inplace_async(
 }
 
 uint64_t scratch_cuda_integer_overflowing_sub_64_inplace_async(
-    CudaStreamsFFI streams, int8_t **mem_ptr, uint32_t glwe_dimension,
-    uint32_t polynomial_size, uint32_t big_lwe_dimension,
-    uint32_t small_lwe_dimension, uint32_t ks_level, uint32_t ks_base_log,
-    uint32_t pbs_level, uint32_t pbs_base_log, uint32_t grouping_factor,
-    uint32_t num_blocks, uint32_t message_modulus, uint32_t carry_modulus,
-    PBS_TYPE pbs_type, uint32_t compute_overflow, bool allocate_gpu_memory,
+    CudaStreamsFFI streams, int8_t **mem_ptr,
+    CudaLweBootstrapKeyParamsFFI bsk_params, uint32_t ks_level,
+    uint32_t ks_base_log, uint32_t num_blocks, uint32_t message_modulus,
+    uint32_t carry_modulus, uint32_t compute_overflow, bool allocate_gpu_memory,
     PBS_MS_REDUCTION_T noise_reduction_type) {
-  int_radix_params params(pbs_type, glwe_dimension, polynomial_size,
-                          big_lwe_dimension, small_lwe_dimension, ks_level,
-                          ks_base_log, pbs_level, pbs_base_log, grouping_factor,
-                          message_modulus, carry_modulus, noise_reduction_type);
+  int_radix_params params(bsk_params, ks_level, ks_base_log, message_modulus,
+                          carry_modulus, noise_reduction_type);
 
   return scratch_cuda_integer_overflowing_sub<uint64_t>(
       CudaStreams(streams), (int_borrow_prop_memory<uint64_t> **)mem_ptr,
@@ -170,17 +153,12 @@ void cleanup_cuda_integer_overflowing_sub_64_inplace(CudaStreamsFFI streams,
 
 uint64_t scratch_cuda_apply_univariate_lut_64_async(
     CudaStreamsFFI streams, int8_t **mem_ptr, void const *input_lut,
-    uint32_t lwe_dimension, uint32_t glwe_dimension, uint32_t polynomial_size,
-    uint32_t ks_level, uint32_t ks_base_log, uint32_t pbs_level,
-    uint32_t pbs_base_log, uint32_t grouping_factor, uint32_t num_radix_blocks,
-    uint32_t message_modulus, uint32_t carry_modulus, PBS_TYPE pbs_type,
-    uint64_t lut_degree, bool allocate_gpu_memory,
+    CudaLweBootstrapKeyParamsFFI bsk_params, uint32_t ks_level,
+    uint32_t ks_base_log, uint32_t num_radix_blocks, uint32_t message_modulus,
+    uint32_t carry_modulus, uint64_t lut_degree, bool allocate_gpu_memory,
     PBS_MS_REDUCTION_T noise_reduction_type) {
-  int_radix_params params(pbs_type, glwe_dimension, polynomial_size,
-                          glwe_dimension * polynomial_size, lwe_dimension,
-                          ks_level, ks_base_log, pbs_level, pbs_base_log,
-                          grouping_factor, message_modulus, carry_modulus,
-                          noise_reduction_type);
+  int_radix_params params(bsk_params, ks_level, ks_base_log, message_modulus,
+                          carry_modulus, noise_reduction_type);
 
   return scratch_cuda_apply_univariate_lut<uint64_t>(
       CudaStreams(streams), (int_radix_lut<uint64_t> **)mem_ptr,
@@ -190,17 +168,12 @@ uint64_t scratch_cuda_apply_univariate_lut_64_async(
 
 uint64_t scratch_cuda_apply_many_univariate_lut_64_async(
     CudaStreamsFFI streams, int8_t **mem_ptr, void const *input_lut,
-    uint32_t lwe_dimension, uint32_t glwe_dimension, uint32_t polynomial_size,
-    uint32_t ks_level, uint32_t ks_base_log, uint32_t pbs_level,
-    uint32_t pbs_base_log, uint32_t grouping_factor, uint32_t num_radix_blocks,
-    uint32_t message_modulus, uint32_t carry_modulus, PBS_TYPE pbs_type,
-    uint32_t num_many_lut, uint64_t lut_degree, bool allocate_gpu_memory,
-    PBS_MS_REDUCTION_T noise_reduction_type) {
-  int_radix_params params(pbs_type, glwe_dimension, polynomial_size,
-                          glwe_dimension * polynomial_size, lwe_dimension,
-                          ks_level, ks_base_log, pbs_level, pbs_base_log,
-                          grouping_factor, message_modulus, carry_modulus,
-                          noise_reduction_type);
+    CudaLweBootstrapKeyParamsFFI bsk_params, uint32_t ks_level,
+    uint32_t ks_base_log, uint32_t num_radix_blocks, uint32_t message_modulus,
+    uint32_t carry_modulus, uint32_t num_many_lut, uint64_t lut_degree,
+    bool allocate_gpu_memory, PBS_MS_REDUCTION_T noise_reduction_type) {
+  int_radix_params params(bsk_params, ks_level, ks_base_log, message_modulus,
+                          carry_modulus, noise_reduction_type);
 
   return scratch_cuda_apply_many_univariate_lut<uint64_t>(
       CudaStreams(streams), (int_radix_lut<uint64_t> **)mem_ptr,
@@ -294,19 +267,14 @@ uint64_t scratch_cuda_apply_noise_squashing_mem(
 }
 
 uint64_t scratch_cuda_apply_noise_squashing_async(
-    CudaStreamsFFI streams, int8_t **mem_ptr, uint32_t lwe_dimension,
-    uint32_t glwe_dimension, uint32_t polynomial_size,
-    uint32_t input_glwe_dimension, uint32_t input_polynomial_size,
-    uint32_t ks_level, uint32_t ks_base_log, uint32_t pbs_level,
-    uint32_t pbs_base_log, uint32_t grouping_factor, uint32_t num_radix_blocks,
-    uint32_t original_num_blocks, uint32_t message_modulus,
-    uint32_t carry_modulus, PBS_TYPE pbs_type, bool allocate_gpu_memory,
+    CudaStreamsFFI streams, int8_t **mem_ptr,
+    CudaLweBootstrapKeyParamsFFI bsk_params, uint32_t input_glwe_dimension,
+    uint32_t input_polynomial_size, uint32_t ks_level, uint32_t ks_base_log,
+    uint32_t num_radix_blocks, uint32_t original_num_blocks,
+    uint32_t message_modulus, uint32_t carry_modulus, bool allocate_gpu_memory,
     PBS_MS_REDUCTION_T noise_reduction_type) {
-  int_radix_params params(pbs_type, glwe_dimension, polynomial_size,
-                          glwe_dimension * polynomial_size, lwe_dimension,
-                          ks_level, ks_base_log, pbs_level, pbs_base_log,
-                          grouping_factor, message_modulus, carry_modulus,
-                          noise_reduction_type);
+  int_radix_params params(bsk_params, ks_level, ks_base_log, message_modulus,
+                          carry_modulus, noise_reduction_type);
 
   return scratch_cuda_apply_noise_squashing_mem(
       streams, params, (int_noise_squashing_lut<uint64_t> **)mem_ptr,

backends/tfhe-cuda-backend/cuda/src/integer/multiplication.cu

@@ -122,16 +122,12 @@ void cuda_integer_mult_inplace_64_async(
 uint64_t scratch_cuda_integer_mult_inplace_64_async(
     CudaStreamsFFI streams, int8_t **mem_ptr, bool const is_boolean_left,
     bool const is_boolean_right, uint32_t message_modulus,
-    uint32_t carry_modulus, uint32_t glwe_dimension, uint32_t lwe_dimension,
-    uint32_t polynomial_size, uint32_t pbs_base_log, uint32_t pbs_level,
-    uint32_t ks_base_log, uint32_t ks_level, uint32_t grouping_factor,
-    uint32_t num_radix_blocks, PBS_TYPE pbs_type, bool allocate_gpu_memory,
-    PBS_MS_REDUCTION_T noise_reduction_type) {
-  int_radix_params params(pbs_type, glwe_dimension, polynomial_size,
-                          polynomial_size * glwe_dimension, lwe_dimension,
-                          ks_level, ks_base_log, pbs_level, pbs_base_log,
-                          grouping_factor, message_modulus, carry_modulus,
-                          noise_reduction_type);
+    uint32_t carry_modulus, CudaLweBootstrapKeyParamsFFI bsk_params,
+    uint32_t ks_base_log, uint32_t ks_level, uint32_t num_radix_blocks,
+    bool allocate_gpu_memory, PBS_MS_REDUCTION_T noise_reduction_type) {
+  const uint32_t polynomial_size = bsk_params.polynomial_size;
+  int_radix_params params(bsk_params, ks_level, ks_base_log, message_modulus,
+                          carry_modulus, noise_reduction_type);
 
   switch (polynomial_size) {
   case 256:
@@ -164,20 +160,14 @@ void cleanup_cuda_integer_mult_inplace_64(CudaStreamsFFI streams,
 }
 
 uint64_t scratch_cuda_partial_sum_ciphertexts_vec_64_async(
-    CudaStreamsFFI streams, int8_t **mem_ptr, uint32_t glwe_dimension,
-    uint32_t polynomial_size, uint32_t lwe_dimension, uint32_t ks_level,
-    uint32_t ks_base_log, uint32_t pbs_level, uint32_t pbs_base_log,
-    uint32_t grouping_factor, uint32_t num_blocks_in_radix,
+    CudaStreamsFFI streams, int8_t **mem_ptr,
+    CudaLweBootstrapKeyParamsFFI bsk_params, uint32_t ks_level,
+    uint32_t ks_base_log, uint32_t num_blocks_in_radix,
     uint32_t max_num_radix_in_vec, uint32_t message_modulus,
-    uint32_t carry_modulus, PBS_TYPE pbs_type,
-    bool reduce_degrees_for_single_carry_propagation, bool allocate_gpu_memory,
-    PBS_MS_REDUCTION_T noise_reduction_type) {
-
-  int_radix_params params(pbs_type, glwe_dimension, polynomial_size,
-                          glwe_dimension * polynomial_size, lwe_dimension,
-                          ks_level, ks_base_log, pbs_level, pbs_base_log,
-                          grouping_factor, message_modulus, carry_modulus,
-                          noise_reduction_type);
+    uint32_t carry_modulus, bool reduce_degrees_for_single_carry_propagation,
+    bool allocate_gpu_memory, PBS_MS_REDUCTION_T noise_reduction_type) {
+  int_radix_params params(bsk_params, ks_level, ks_base_log, message_modulus,
+                          carry_modulus, noise_reduction_type);
   return scratch_cuda_integer_partial_sum_ciphertexts_vec<uint64_t>(
       CudaStreams(streams),
       (int_sum_ciphertexts_vec_memory<uint64_t> **)mem_ptr, num_blocks_in_radix,

backends/tfhe-cuda-backend/cuda/src/integer/oprf.cu

@@ -1,19 +1,14 @@
 #include "integer/oprf.cuh"
 
 uint64_t scratch_cuda_integer_grouped_oprf_64_async(
-    CudaStreamsFFI streams, int8_t **mem_ptr, uint32_t glwe_dimension,
-    uint32_t polynomial_size, uint32_t lwe_dimension, uint32_t ks_level,
-    uint32_t ks_base_log, uint32_t pbs_level, uint32_t pbs_base_log,
-    uint32_t grouping_factor, uint32_t num_blocks_to_process,
-    uint32_t message_modulus, uint32_t carry_modulus, PBS_TYPE pbs_type,
-    bool allocate_gpu_memory, uint32_t message_bits_per_block,
-    uint32_t total_random_bits, PBS_MS_REDUCTION_T noise_reduction_type) {
-
-  int_radix_params params(pbs_type, glwe_dimension, polynomial_size,
-                          glwe_dimension * polynomial_size, lwe_dimension,
-                          ks_level, ks_base_log, pbs_level, pbs_base_log,
-                          grouping_factor, message_modulus, carry_modulus,
-                          noise_reduction_type);
+    CudaStreamsFFI streams, int8_t **mem_ptr,
+    CudaLweBootstrapKeyParamsFFI bsk_params, uint32_t ks_level,
+    uint32_t ks_base_log, uint32_t num_blocks_to_process,
+    uint32_t message_modulus, uint32_t carry_modulus, bool allocate_gpu_memory,
+    uint32_t message_bits_per_block, uint32_t total_random_bits,
+    PBS_MS_REDUCTION_T noise_reduction_type) {
+  int_radix_params params(bsk_params, ks_level, ks_base_log, message_modulus,
+                          carry_modulus, noise_reduction_type);
 
   return scratch_cuda_integer_grouped_oprf<uint64_t>(
       CudaStreams(streams), (int_grouped_oprf_memory<uint64_t> **)mem_ptr,
@@ -45,20 +40,14 @@ void cleanup_cuda_integer_grouped_oprf_64(CudaStreamsFFI streams,
 }
 
 uint64_t scratch_cuda_integer_grouped_oprf_custom_range_64_async(
-    CudaStreamsFFI streams, int8_t **mem_ptr, uint32_t glwe_dimension,
-    uint32_t polynomial_size, uint32_t lwe_dimension, uint32_t ks_level,
-    uint32_t ks_base_log, uint32_t pbs_level, uint32_t pbs_base_log,
-    uint32_t grouping_factor, uint32_t num_blocks_intermediate,
-    uint32_t message_modulus, uint32_t carry_modulus, PBS_TYPE pbs_type,
-    bool allocate_gpu_memory, uint32_t message_bits_per_block,
-    uint32_t num_input_random_bits, uint32_t num_scalar_bits,
-    PBS_MS_REDUCTION_T noise_reduction_type) {
-
-  int_radix_params params(pbs_type, glwe_dimension, polynomial_size,
-                          glwe_dimension * polynomial_size, lwe_dimension,
-                          ks_level, ks_base_log, pbs_level, pbs_base_log,
-                          grouping_factor, message_modulus, carry_modulus,
-                          noise_reduction_type);
+    CudaStreamsFFI streams, int8_t **mem_ptr,
+    CudaLweBootstrapKeyParamsFFI bsk_params, uint32_t ks_level,
+    uint32_t ks_base_log, uint32_t num_blocks_intermediate,
+    uint32_t message_modulus, uint32_t carry_modulus, bool allocate_gpu_memory,
+    uint32_t message_bits_per_block, uint32_t num_input_random_bits,
+    uint32_t num_scalar_bits, PBS_MS_REDUCTION_T noise_reduction_type) {
+  int_radix_params params(bsk_params, ks_level, ks_base_log, message_modulus,
+                          carry_modulus, noise_reduction_type);
 
   return scratch_cuda_integer_grouped_oprf_custom_range<uint64_t>(
       CudaStreams(streams),
@@ -72,13 +61,13 @@ void cuda_integer_grouped_oprf_custom_range_64_async(
     uint32_t num_blocks_intermediate, const void *seeded_lwe_input,
     const uint64_t *decomposed_scalar, const uint64_t *has_at_least_one_set,
     uint32_t num_scalars, uint32_t shift, int8_t *mem, void *const *bsks,
-    void *const *ksks) {
+    void *const *compute_bsks, void *const *ksks) {
 
   host_integer_grouped_oprf_custom_range<uint64_t>(
       CudaStreams(streams), radix_lwe_out, num_blocks_intermediate,
       (const uint64_t *)seeded_lwe_input, decomposed_scalar,
       has_at_least_one_set, num_scalars, shift,
-      (int_grouped_oprf_custom_range_memory<uint64_t> *)mem, bsks,
+      (int_grouped_oprf_custom_range_memory<uint64_t> *)mem, bsks, compute_bsks,
       (uint64_t *const *)ksks);
 }
 

backends/tfhe-cuda-backend/cuda/src/integer/oprf.cuh

@@ -114,7 +114,7 @@ void host_integer_grouped_oprf_custom_range(
     const Torus *decomposed_scalar, const Torus *has_at_least_one_set,
     uint32_t num_scalars, uint32_t shift,
     int_grouped_oprf_custom_range_memory<Torus> *mem_ptr, void *const *bsks,
-    Torus *const *ksks) {
+    void *const *compute_bsks, Torus *const *ksks) {
 
   CudaRadixCiphertextFFI *computation_buffer = mem_ptr->tmp_oprf_output;
   set_zero_radix_ciphertext_slice_async<Torus>(
@@ -127,12 +127,12 @@ void host_integer_grouped_oprf_custom_range(
 
   host_integer_scalar_mul_radix<Torus>(
       streams, computation_buffer, decomposed_scalar, has_at_least_one_set,
-      mem_ptr->scalar_mul_buffer, bsks, ksks, mem_ptr->params.message_modulus,
-      num_scalars);
+      mem_ptr->scalar_mul_buffer, compute_bsks, ksks,
+      mem_ptr->params.message_modulus, num_scalars);
 
-  host_logical_scalar_shift_inplace<Torus>(streams, computation_buffer, shift,
-                                           mem_ptr->logical_scalar_shift_buffer,
-                                           bsks, ksks, num_blocks_intermediate);
+  host_logical_scalar_shift_inplace<Torus>(
+      streams, computation_buffer, shift, mem_ptr->logical_scalar_shift_buffer,
+      compute_bsks, ksks, num_blocks_intermediate);
 
   uint32_t num_blocks_output = radix_lwe_out->num_radix_blocks;
   uint32_t blocks_to_copy =

backends/tfhe-cuda-backend/cuda/src/integer/scalar_div.cu

@@ -1,19 +1,13 @@
 #include "scalar_div.cuh"
 
 uint64_t scratch_cuda_integer_unsigned_scalar_div_radix_64_async(
-    CudaStreamsFFI streams, int8_t **mem_ptr, uint32_t glwe_dimension,
-    uint32_t polynomial_size, uint32_t lwe_dimension, uint32_t ks_level,
-    uint32_t ks_base_log, uint32_t pbs_level, uint32_t pbs_base_log,
-    uint32_t grouping_factor, uint32_t num_blocks, uint32_t message_modulus,
-    uint32_t carry_modulus, PBS_TYPE pbs_type,
-    const CudaScalarDivisorFFI *scalar_divisor_ffi, bool allocate_gpu_memory,
-    PBS_MS_REDUCTION_T noise_reduction_type) {
-
-  int_radix_params params(pbs_type, glwe_dimension, polynomial_size,
-                          glwe_dimension * polynomial_size, lwe_dimension,
-                          ks_level, ks_base_log, pbs_level, pbs_base_log,
-                          grouping_factor, message_modulus, carry_modulus,
-                          noise_reduction_type);
+    CudaStreamsFFI streams, int8_t **mem_ptr,
+    CudaLweBootstrapKeyParamsFFI bsk_params, uint32_t ks_level,
+    uint32_t ks_base_log, uint32_t num_blocks, uint32_t message_modulus,
+    uint32_t carry_modulus, const CudaScalarDivisorFFI *scalar_divisor_ffi,
+    bool allocate_gpu_memory, PBS_MS_REDUCTION_T noise_reduction_type) {
+  int_radix_params params(bsk_params, ks_level, ks_base_log, message_modulus,
+                          carry_modulus, noise_reduction_type);
 
   return scratch_integer_unsigned_scalar_div_radix<uint64_t>(
       CudaStreams(streams), params,
@@ -45,19 +39,13 @@ void cleanup_cuda_integer_unsigned_scalar_div_radix_64(CudaStreamsFFI streams,
 }
 
 uint64_t scratch_cuda_integer_signed_scalar_div_radix_64_async(
-    CudaStreamsFFI streams, int8_t **mem_ptr, uint32_t glwe_dimension,
-    uint32_t polynomial_size, uint32_t lwe_dimension, uint32_t ks_level,
-    uint32_t ks_base_log, uint32_t pbs_level, uint32_t pbs_base_log,
-    uint32_t grouping_factor, uint32_t num_blocks, uint32_t message_modulus,
-    uint32_t carry_modulus, PBS_TYPE pbs_type,
-    const CudaScalarDivisorFFI *scalar_divisor_ffi, bool allocate_gpu_memory,
-    PBS_MS_REDUCTION_T noise_reduction_type) {
-
-  int_radix_params params(pbs_type, glwe_dimension, polynomial_size,
-                          glwe_dimension * polynomial_size, lwe_dimension,
-                          ks_level, ks_base_log, pbs_level, pbs_base_log,
-                          grouping_factor, message_modulus, carry_modulus,
-                          noise_reduction_type);
+    CudaStreamsFFI streams, int8_t **mem_ptr,
+    CudaLweBootstrapKeyParamsFFI bsk_params, uint32_t ks_level,
+    uint32_t ks_base_log, uint32_t num_blocks, uint32_t message_modulus,
+    uint32_t carry_modulus, const CudaScalarDivisorFFI *scalar_divisor_ffi,
+    bool allocate_gpu_memory, PBS_MS_REDUCTION_T noise_reduction_type) {
+  int_radix_params params(bsk_params, ks_level, ks_base_log, message_modulus,
+                          carry_modulus, noise_reduction_type);
 
   return scratch_integer_signed_scalar_div_radix<uint64_t>(
       CudaStreams(streams), params,
@@ -89,20 +77,14 @@ void cleanup_cuda_integer_signed_scalar_div_radix_64(CudaStreamsFFI streams,
 }
 
 uint64_t scratch_cuda_integer_unsigned_scalar_div_rem_radix_64_async(
-    CudaStreamsFFI streams, int8_t **mem_ptr, uint32_t glwe_dimension,
-    uint32_t polynomial_size, uint32_t lwe_dimension, uint32_t ks_level,
-    uint32_t ks_base_log, uint32_t pbs_level, uint32_t pbs_base_log,
-    uint32_t grouping_factor, uint32_t num_blocks, uint32_t message_modulus,
-    uint32_t carry_modulus, PBS_TYPE pbs_type,
-    const CudaScalarDivisorFFI *scalar_divisor_ffi,
+    CudaStreamsFFI streams, int8_t **mem_ptr,
+    CudaLweBootstrapKeyParamsFFI bsk_params, uint32_t ks_level,
+    uint32_t ks_base_log, uint32_t num_blocks, uint32_t message_modulus,
+    uint32_t carry_modulus, const CudaScalarDivisorFFI *scalar_divisor_ffi,
     uint32_t const active_bits_divisor, bool allocate_gpu_memory,
     PBS_MS_REDUCTION_T noise_reduction_type) {
-
-  int_radix_params params(pbs_type, glwe_dimension, polynomial_size,
-                          glwe_dimension * polynomial_size, lwe_dimension,
-                          ks_level, ks_base_log, pbs_level, pbs_base_log,
-                          grouping_factor, message_modulus, carry_modulus,
-                          noise_reduction_type);
+  int_radix_params params(bsk_params, ks_level, ks_base_log, message_modulus,
+                          carry_modulus, noise_reduction_type);
 
   return scratch_integer_unsigned_scalar_div_rem_radix<uint64_t>(
       CudaStreams(streams), params,
@@ -143,20 +125,14 @@ void cleanup_cuda_integer_unsigned_scalar_div_rem_radix_64(
 }
 
 uint64_t scratch_cuda_integer_signed_scalar_div_rem_radix_64_async(
-    CudaStreamsFFI streams, int8_t **mem_ptr, uint32_t glwe_dimension,
-    uint32_t polynomial_size, uint32_t lwe_dimension, uint32_t ks_level,
-    uint32_t ks_base_log, uint32_t pbs_level, uint32_t pbs_base_log,
-    uint32_t grouping_factor, uint32_t num_blocks, uint32_t message_modulus,
-    uint32_t carry_modulus, PBS_TYPE pbs_type,
-    const CudaScalarDivisorFFI *scalar_divisor_ffi,
+    CudaStreamsFFI streams, int8_t **mem_ptr,
+    CudaLweBootstrapKeyParamsFFI bsk_params, uint32_t ks_level,
+    uint32_t ks_base_log, uint32_t num_blocks, uint32_t message_modulus,
+    uint32_t carry_modulus, const CudaScalarDivisorFFI *scalar_divisor_ffi,
     uint32_t const active_bits_divisor, bool allocate_gpu_memory,
     PBS_MS_REDUCTION_T noise_reduction_type) {
-
-  int_radix_params params(pbs_type, glwe_dimension, polynomial_size,
-                          glwe_dimension * polynomial_size, lwe_dimension,
-                          ks_level, ks_base_log, pbs_level, pbs_base_log,
-                          grouping_factor, message_modulus, carry_modulus,
-                          noise_reduction_type);
+  int_radix_params params(bsk_params, ks_level, ks_base_log, message_modulus,
+                          carry_modulus, noise_reduction_type);
 
   return scratch_integer_signed_scalar_div_rem_radix<uint64_t>(
       CudaStreams(streams), params,

backends/tfhe-cuda-backend/cuda/src/integer/scalar_mul.cu

@@ -1,18 +1,13 @@
 #include "integer/scalar_mul.cuh"
 
 uint64_t scratch_cuda_integer_scalar_mul_64_async(
-    CudaStreamsFFI streams, int8_t **mem_ptr, uint32_t glwe_dimension,
-    uint32_t polynomial_size, uint32_t lwe_dimension, uint32_t ks_level,
-    uint32_t ks_base_log, uint32_t pbs_level, uint32_t pbs_base_log,
-    uint32_t grouping_factor, uint32_t num_blocks, uint32_t message_modulus,
-    uint32_t carry_modulus, PBS_TYPE pbs_type, uint32_t num_scalar_bits,
-    bool allocate_gpu_memory, PBS_MS_REDUCTION_T noise_reduction_type) {
-
-  int_radix_params params(pbs_type, glwe_dimension, polynomial_size,
-                          glwe_dimension * polynomial_size, lwe_dimension,
-                          ks_level, ks_base_log, pbs_level, pbs_base_log,
-                          grouping_factor, message_modulus, carry_modulus,
-                          noise_reduction_type);
+    CudaStreamsFFI streams, int8_t **mem_ptr,
+    CudaLweBootstrapKeyParamsFFI bsk_params, uint32_t ks_level,
+    uint32_t ks_base_log, uint32_t num_blocks, uint32_t message_modulus,
+    uint32_t carry_modulus, uint32_t num_scalar_bits, bool allocate_gpu_memory,
+    PBS_MS_REDUCTION_T noise_reduction_type) {
+  int_radix_params params(bsk_params, ks_level, ks_base_log, message_modulus,
+                          carry_modulus, noise_reduction_type);
 
   return scratch_cuda_scalar_mul<uint64_t>(
       CudaStreams(streams), (int_scalar_mul_buffer<uint64_t> **)mem_ptr,

backends/tfhe-cuda-backend/cuda/src/integer/scalar_rotate.cu

@@ -1,18 +1,13 @@
 #include "scalar_rotate.cuh"
 
 uint64_t scratch_cuda_scalar_rotate_64_inplace_async(
-    CudaStreamsFFI streams, int8_t **mem_ptr, uint32_t glwe_dimension,
-    uint32_t polynomial_size, uint32_t big_lwe_dimension,
-    uint32_t small_lwe_dimension, uint32_t ks_level, uint32_t ks_base_log,
-    uint32_t pbs_level, uint32_t pbs_base_log, uint32_t grouping_factor,
-    uint32_t num_blocks, uint32_t message_modulus, uint32_t carry_modulus,
-    PBS_TYPE pbs_type, SHIFT_OR_ROTATE_TYPE shift_type,
+    CudaStreamsFFI streams, int8_t **mem_ptr,
+    CudaLweBootstrapKeyParamsFFI bsk_params, uint32_t ks_level,
+    uint32_t ks_base_log, uint32_t num_blocks, uint32_t message_modulus,
+    uint32_t carry_modulus, SHIFT_OR_ROTATE_TYPE shift_type,
     bool allocate_gpu_memory, PBS_MS_REDUCTION_T noise_reduction_type) {
-
-  int_radix_params params(pbs_type, glwe_dimension, polynomial_size,
-                          big_lwe_dimension, small_lwe_dimension, ks_level,
-                          ks_base_log, pbs_level, pbs_base_log, grouping_factor,
-                          message_modulus, carry_modulus, noise_reduction_type);
+  int_radix_params params(bsk_params, ks_level, ks_base_log, message_modulus,
+                          carry_modulus, noise_reduction_type);
 
   return scratch_cuda_scalar_rotate<uint64_t>(
       CudaStreams(streams),

backends/tfhe-cuda-backend/cuda/src/integer/scalar_shifts.cu

@@ -1,18 +1,13 @@
 #include "scalar_shifts.cuh"
 
 uint64_t scratch_cuda_logical_scalar_shift_64_inplace_async(
-    CudaStreamsFFI streams, int8_t **mem_ptr, uint32_t glwe_dimension,
-    uint32_t polynomial_size, uint32_t big_lwe_dimension,
-    uint32_t small_lwe_dimension, uint32_t ks_level, uint32_t ks_base_log,
-    uint32_t pbs_level, uint32_t pbs_base_log, uint32_t grouping_factor,
-    uint32_t num_blocks, uint32_t message_modulus, uint32_t carry_modulus,
-    PBS_TYPE pbs_type, SHIFT_OR_ROTATE_TYPE shift_type,
+    CudaStreamsFFI streams, int8_t **mem_ptr,
+    CudaLweBootstrapKeyParamsFFI bsk_params, uint32_t ks_level,
+    uint32_t ks_base_log, uint32_t num_blocks, uint32_t message_modulus,
+    uint32_t carry_modulus, SHIFT_OR_ROTATE_TYPE shift_type,
     bool allocate_gpu_memory, PBS_MS_REDUCTION_T noise_reduction_type) {
-
-  int_radix_params params(pbs_type, glwe_dimension, polynomial_size,
-                          big_lwe_dimension, small_lwe_dimension, ks_level,
-                          ks_base_log, pbs_level, pbs_base_log, grouping_factor,
-                          message_modulus, carry_modulus, noise_reduction_type);
+  int_radix_params params(bsk_params, ks_level, ks_base_log, message_modulus,
+                          carry_modulus, noise_reduction_type);
 
   return scratch_cuda_logical_scalar_shift<uint64_t>(
       CudaStreams(streams),
@@ -35,18 +30,13 @@ void cuda_logical_scalar_shift_64_inplace_async(
 }
 
 uint64_t scratch_cuda_arithmetic_scalar_shift_64_inplace_async(
-    CudaStreamsFFI streams, int8_t **mem_ptr, uint32_t glwe_dimension,
-    uint32_t polynomial_size, uint32_t big_lwe_dimension,
-    uint32_t small_lwe_dimension, uint32_t ks_level, uint32_t ks_base_log,
-    uint32_t pbs_level, uint32_t pbs_base_log, uint32_t grouping_factor,
-    uint32_t num_blocks, uint32_t message_modulus, uint32_t carry_modulus,
-    PBS_TYPE pbs_type, SHIFT_OR_ROTATE_TYPE shift_type,
+    CudaStreamsFFI streams, int8_t **mem_ptr,
+    CudaLweBootstrapKeyParamsFFI bsk_params, uint32_t ks_level,
+    uint32_t ks_base_log, uint32_t num_blocks, uint32_t message_modulus,
+    uint32_t carry_modulus, SHIFT_OR_ROTATE_TYPE shift_type,
     bool allocate_gpu_memory, PBS_MS_REDUCTION_T noise_reduction_type) {
-
-  int_radix_params params(pbs_type, glwe_dimension, polynomial_size,
-                          big_lwe_dimension, small_lwe_dimension, ks_level,
-                          ks_base_log, pbs_level, pbs_base_log, grouping_factor,
-                          message_modulus, carry_modulus, noise_reduction_type);
+  int_radix_params params(bsk_params, ks_level, ks_base_log, message_modulus,
+                          carry_modulus, noise_reduction_type);
 
   return scratch_cuda_arithmetic_scalar_shift<uint64_t>(
       CudaStreams(streams),

backends/tfhe-cuda-backend/cuda/src/integer/shift_and_rotate.cu

@@ -1,18 +1,13 @@
 #include "shift_and_rotate.cuh"
 
 uint64_t scratch_cuda_shift_and_rotate_64_inplace_async(
-    CudaStreamsFFI streams, int8_t **mem_ptr, uint32_t glwe_dimension,
-    uint32_t polynomial_size, uint32_t big_lwe_dimension,
-    uint32_t small_lwe_dimension, uint32_t ks_level, uint32_t ks_base_log,
-    uint32_t pbs_level, uint32_t pbs_base_log, uint32_t grouping_factor,
-    uint32_t num_blocks, uint32_t message_modulus, uint32_t carry_modulus,
-    PBS_TYPE pbs_type, SHIFT_OR_ROTATE_TYPE shift_type, bool is_signed,
+    CudaStreamsFFI streams, int8_t **mem_ptr,
+    CudaLweBootstrapKeyParamsFFI bsk_params, uint32_t ks_level,
+    uint32_t ks_base_log, uint32_t num_blocks, uint32_t message_modulus,
+    uint32_t carry_modulus, SHIFT_OR_ROTATE_TYPE shift_type, bool is_signed,
     bool allocate_gpu_memory, PBS_MS_REDUCTION_T noise_reduction_type) {
-
-  int_radix_params params(pbs_type, glwe_dimension, polynomial_size,
-                          big_lwe_dimension, small_lwe_dimension, ks_level,
-                          ks_base_log, pbs_level, pbs_base_log, grouping_factor,
-                          message_modulus, carry_modulus, noise_reduction_type);
+  int_radix_params params(bsk_params, ks_level, ks_base_log, message_modulus,
+                          carry_modulus, noise_reduction_type);
 
   return scratch_cuda_shift_and_rotate<uint64_t>(
       CudaStreams(streams), (int_shift_and_rotate_buffer<uint64_t> **)mem_ptr,

backends/tfhe-cuda-backend/cuda/src/integer/subtraction.cu

@@ -1,18 +1,13 @@
 #include "subtraction.cuh"
 
 uint64_t scratch_cuda_sub_and_propagate_single_carry_64_inplace_async(
-    CudaStreamsFFI streams, int8_t **mem_ptr, uint32_t glwe_dimension,
-    uint32_t polynomial_size, uint32_t big_lwe_dimension,
-    uint32_t small_lwe_dimension, uint32_t ks_level, uint32_t ks_base_log,
-    uint32_t pbs_level, uint32_t pbs_base_log, uint32_t grouping_factor,
-    uint32_t num_blocks, uint32_t message_modulus, uint32_t carry_modulus,
-    PBS_TYPE pbs_type, uint32_t requested_flag, bool allocate_gpu_memory,
+    CudaStreamsFFI streams, int8_t **mem_ptr,
+    CudaLweBootstrapKeyParamsFFI bsk_params, uint32_t ks_level,
+    uint32_t ks_base_log, uint32_t num_blocks, uint32_t message_modulus,
+    uint32_t carry_modulus, uint32_t requested_flag, bool allocate_gpu_memory,
     PBS_MS_REDUCTION_T noise_reduction_type) {
-
-  int_radix_params params(pbs_type, glwe_dimension, polynomial_size,
-                          big_lwe_dimension, small_lwe_dimension, ks_level,
-                          ks_base_log, pbs_level, pbs_base_log, grouping_factor,
-                          message_modulus, carry_modulus, noise_reduction_type);
+  int_radix_params params(bsk_params, ks_level, ks_base_log, message_modulus,
+                          carry_modulus, noise_reduction_type);
 
   return scratch_cuda_sub_and_propagate_single_carry<uint64_t>(
       CudaStreams(streams), (int_sub_and_propagate<uint64_t> **)mem_ptr,

backends/tfhe-cuda-backend/cuda/src/integer/vector_comparison.cu

@@ -1,18 +1,13 @@
 #include "integer/vector_comparison.cuh"
 
 uint64_t scratch_cuda_unchecked_all_eq_slices_64_async(
-    CudaStreamsFFI streams, int8_t **mem_ptr, uint32_t glwe_dimension,
-    uint32_t polynomial_size, uint32_t big_lwe_dimension,
-    uint32_t small_lwe_dimension, uint32_t ks_level, uint32_t ks_base_log,
-    uint32_t pbs_level, uint32_t pbs_base_log, uint32_t grouping_factor,
-    uint32_t num_inputs, uint32_t num_blocks, uint32_t message_modulus,
-    uint32_t carry_modulus, PBS_TYPE pbs_type, bool allocate_gpu_memory,
+    CudaStreamsFFI streams, int8_t **mem_ptr,
+    CudaLweBootstrapKeyParamsFFI bsk_params, uint32_t ks_level,
+    uint32_t ks_base_log, uint32_t num_inputs, uint32_t num_blocks,
+    uint32_t message_modulus, uint32_t carry_modulus, bool allocate_gpu_memory,
     PBS_MS_REDUCTION_T noise_reduction_type) {
-
-  int_radix_params params(pbs_type, glwe_dimension, polynomial_size,
-                          big_lwe_dimension, small_lwe_dimension, ks_level,
-                          ks_base_log, pbs_level, pbs_base_log, grouping_factor,
-                          message_modulus, carry_modulus, noise_reduction_type);
+  int_radix_params params(bsk_params, ks_level, ks_base_log, message_modulus,
+                          carry_modulus, noise_reduction_type);
 
   return scratch_cuda_unchecked_all_eq_slices<uint64_t>(
       CudaStreams(streams),
@@ -50,18 +45,13 @@ void cleanup_cuda_unchecked_all_eq_slices_64(CudaStreamsFFI streams,
 }
 
 uint64_t scratch_cuda_unchecked_contains_sub_slice_64_async(
-    CudaStreamsFFI streams, int8_t **mem_ptr, uint32_t glwe_dimension,
-    uint32_t polynomial_size, uint32_t big_lwe_dimension,
-    uint32_t small_lwe_dimension, uint32_t ks_level, uint32_t ks_base_log,
-    uint32_t pbs_level, uint32_t pbs_base_log, uint32_t grouping_factor,
-    uint32_t num_lhs, uint32_t num_rhs, uint32_t num_blocks,
-    uint32_t message_modulus, uint32_t carry_modulus, PBS_TYPE pbs_type,
+    CudaStreamsFFI streams, int8_t **mem_ptr,
+    CudaLweBootstrapKeyParamsFFI bsk_params, uint32_t ks_level,
+    uint32_t ks_base_log, uint32_t num_lhs, uint32_t num_rhs,
+    uint32_t num_blocks, uint32_t message_modulus, uint32_t carry_modulus,
     bool allocate_gpu_memory, PBS_MS_REDUCTION_T noise_reduction_type) {
-
-  int_radix_params params(pbs_type, glwe_dimension, polynomial_size,
-                          big_lwe_dimension, small_lwe_dimension, ks_level,
-                          ks_base_log, pbs_level, pbs_base_log, grouping_factor,
-                          message_modulus, carry_modulus, noise_reduction_type);
+  int_radix_params params(bsk_params, ks_level, ks_base_log, message_modulus,
+                          carry_modulus, noise_reduction_type);
 
   return scratch_cuda_unchecked_contains_sub_slice<uint64_t>(
       CudaStreams(streams),

backends/tfhe-cuda-backend/cuda/src/integer/vector_find.cu

@@ -1,19 +1,14 @@
 #include "integer/vector_find.cuh"
 
 uint64_t scratch_cuda_unchecked_match_value_64_async(
-    CudaStreamsFFI streams, int8_t **mem_ptr, uint32_t glwe_dimension,
-    uint32_t polynomial_size, uint32_t big_lwe_dimension,
-    uint32_t small_lwe_dimension, uint32_t ks_level, uint32_t ks_base_log,
-    uint32_t pbs_level, uint32_t pbs_base_log, uint32_t grouping_factor,
-    uint32_t num_matches, uint32_t num_input_blocks,
+    CudaStreamsFFI streams, int8_t **mem_ptr,
+    CudaLweBootstrapKeyParamsFFI bsk_params, uint32_t ks_level,
+    uint32_t ks_base_log, uint32_t num_matches, uint32_t num_input_blocks,
     uint32_t num_output_packed_blocks, uint32_t max_output_is_zero,
-    uint32_t message_modulus, uint32_t carry_modulus, PBS_TYPE pbs_type,
-    bool allocate_gpu_memory, PBS_MS_REDUCTION_T noise_reduction_type) {
-
-  int_radix_params params(pbs_type, glwe_dimension, polynomial_size,
-                          big_lwe_dimension, small_lwe_dimension, ks_level,
-                          ks_base_log, pbs_level, pbs_base_log, grouping_factor,
-                          message_modulus, carry_modulus, noise_reduction_type);
+    uint32_t message_modulus, uint32_t carry_modulus, bool allocate_gpu_memory,
+    PBS_MS_REDUCTION_T noise_reduction_type) {
+  int_radix_params params(bsk_params, ks_level, ks_base_log, message_modulus,
+                          carry_modulus, noise_reduction_type);
 
   return scratch_cuda_unchecked_match_value<uint64_t>(
       CudaStreams(streams), (int_unchecked_match_buffer<uint64_t> **)mem_ptr,
@@ -56,20 +51,15 @@ void cleanup_cuda_unchecked_match_value_64(CudaStreamsFFI streams,
 }
 
 uint64_t scratch_cuda_unchecked_match_value_or_64_async(
-    CudaStreamsFFI streams, int8_t **mem_ptr, uint32_t glwe_dimension,
-    uint32_t polynomial_size, uint32_t big_lwe_dimension,
-    uint32_t small_lwe_dimension, uint32_t ks_level, uint32_t ks_base_log,
-    uint32_t pbs_level, uint32_t pbs_base_log, uint32_t grouping_factor,
-    uint32_t num_matches, uint32_t num_input_blocks,
+    CudaStreamsFFI streams, int8_t **mem_ptr,
+    CudaLweBootstrapKeyParamsFFI bsk_params, uint32_t ks_level,
+    uint32_t ks_base_log, uint32_t num_matches, uint32_t num_input_blocks,
     uint32_t num_match_packed_blocks, uint32_t num_final_blocks,
     uint32_t max_output_is_zero, uint32_t message_modulus,
-    uint32_t carry_modulus, PBS_TYPE pbs_type, bool allocate_gpu_memory,
+    uint32_t carry_modulus, bool allocate_gpu_memory,
     PBS_MS_REDUCTION_T noise_reduction_type) {
-
-  int_radix_params params(pbs_type, glwe_dimension, polynomial_size,
-                          big_lwe_dimension, small_lwe_dimension, ks_level,
-                          ks_base_log, pbs_level, pbs_base_log, grouping_factor,
-                          message_modulus, carry_modulus, noise_reduction_type);
+  int_radix_params params(bsk_params, ks_level, ks_base_log, message_modulus,
+                          carry_modulus, noise_reduction_type);
 
   return scratch_cuda_unchecked_match_value_or<uint64_t>(
       CudaStreams(streams),
@@ -107,18 +97,13 @@ void cleanup_cuda_unchecked_match_value_or_64(CudaStreamsFFI streams,
 }
 
 uint64_t scratch_cuda_unchecked_contains_64_async(
-    CudaStreamsFFI streams, int8_t **mem_ptr, uint32_t glwe_dimension,
-    uint32_t polynomial_size, uint32_t big_lwe_dimension,
-    uint32_t small_lwe_dimension, uint32_t ks_level, uint32_t ks_base_log,
-    uint32_t pbs_level, uint32_t pbs_base_log, uint32_t grouping_factor,
-    uint32_t num_inputs, uint32_t num_blocks, uint32_t message_modulus,
-    uint32_t carry_modulus, PBS_TYPE pbs_type, bool allocate_gpu_memory,
+    CudaStreamsFFI streams, int8_t **mem_ptr,
+    CudaLweBootstrapKeyParamsFFI bsk_params, uint32_t ks_level,
+    uint32_t ks_base_log, uint32_t num_inputs, uint32_t num_blocks,
+    uint32_t message_modulus, uint32_t carry_modulus, bool allocate_gpu_memory,
     PBS_MS_REDUCTION_T noise_reduction_type) {
-
-  int_radix_params params(pbs_type, glwe_dimension, polynomial_size,
-                          big_lwe_dimension, small_lwe_dimension, ks_level,
-                          ks_base_log, pbs_level, pbs_base_log, grouping_factor,
-                          message_modulus, carry_modulus, noise_reduction_type);
+  int_radix_params params(bsk_params, ks_level, ks_base_log, message_modulus,
+                          carry_modulus, noise_reduction_type);
 
   return scratch_cuda_unchecked_contains<uint64_t>(
       CudaStreams(streams), (int_unchecked_contains_buffer<uint64_t> **)mem_ptr,
@@ -157,18 +142,13 @@ void cleanup_cuda_unchecked_contains_64(CudaStreamsFFI streams,
 }
 
 uint64_t scratch_cuda_unchecked_contains_clear_64_async(
-    CudaStreamsFFI streams, int8_t **mem_ptr, uint32_t glwe_dimension,
-    uint32_t polynomial_size, uint32_t big_lwe_dimension,
-    uint32_t small_lwe_dimension, uint32_t ks_level, uint32_t ks_base_log,
-    uint32_t pbs_level, uint32_t pbs_base_log, uint32_t grouping_factor,
-    uint32_t num_inputs, uint32_t num_blocks, uint32_t message_modulus,
-    uint32_t carry_modulus, PBS_TYPE pbs_type, bool allocate_gpu_memory,
+    CudaStreamsFFI streams, int8_t **mem_ptr,
+    CudaLweBootstrapKeyParamsFFI bsk_params, uint32_t ks_level,
+    uint32_t ks_base_log, uint32_t num_inputs, uint32_t num_blocks,
+    uint32_t message_modulus, uint32_t carry_modulus, bool allocate_gpu_memory,
     PBS_MS_REDUCTION_T noise_reduction_type) {
-
-  int_radix_params params(pbs_type, glwe_dimension, polynomial_size,
-                          big_lwe_dimension, small_lwe_dimension, ks_level,
-                          ks_base_log, pbs_level, pbs_base_log, grouping_factor,
-                          message_modulus, carry_modulus, noise_reduction_type);
+  int_radix_params params(bsk_params, ks_level, ks_base_log, message_modulus,
+                          carry_modulus, noise_reduction_type);
 
   return scratch_cuda_unchecked_contains_clear<uint64_t>(
       CudaStreams(streams),
@@ -202,18 +182,13 @@ void cleanup_cuda_unchecked_contains_clear_64(CudaStreamsFFI streams,
 }
 
 uint64_t scratch_cuda_unchecked_is_in_clears_64_async(
-    CudaStreamsFFI streams, int8_t **mem_ptr, uint32_t glwe_dimension,
-    uint32_t polynomial_size, uint32_t big_lwe_dimension,
-    uint32_t small_lwe_dimension, uint32_t ks_level, uint32_t ks_base_log,
-    uint32_t pbs_level, uint32_t pbs_base_log, uint32_t grouping_factor,
-    uint32_t num_clears, uint32_t num_blocks, uint32_t message_modulus,
-    uint32_t carry_modulus, PBS_TYPE pbs_type, bool allocate_gpu_memory,
+    CudaStreamsFFI streams, int8_t **mem_ptr,
+    CudaLweBootstrapKeyParamsFFI bsk_params, uint32_t ks_level,
+    uint32_t ks_base_log, uint32_t num_clears, uint32_t num_blocks,
+    uint32_t message_modulus, uint32_t carry_modulus, bool allocate_gpu_memory,
     PBS_MS_REDUCTION_T noise_reduction_type) {
-
-  int_radix_params params(pbs_type, glwe_dimension, polynomial_size,
-                          big_lwe_dimension, small_lwe_dimension, ks_level,
-                          ks_base_log, pbs_level, pbs_base_log, grouping_factor,
-                          message_modulus, carry_modulus, noise_reduction_type);
+  int_radix_params params(bsk_params, ks_level, ks_base_log, message_modulus,
+                          carry_modulus, noise_reduction_type);
 
   return scratch_cuda_unchecked_is_in_clears<uint64_t>(
       CudaStreams(streams),
@@ -247,18 +222,13 @@ void cleanup_cuda_unchecked_is_in_clears_64(CudaStreamsFFI streams,
 }
 
 uint64_t scratch_cuda_unchecked_index_in_clears_64_async(
-    CudaStreamsFFI streams, int8_t **mem_ptr, uint32_t glwe_dimension,
-    uint32_t polynomial_size, uint32_t big_lwe_dimension,
-    uint32_t small_lwe_dimension, uint32_t ks_level, uint32_t ks_base_log,
-    uint32_t pbs_level, uint32_t pbs_base_log, uint32_t grouping_factor,
-    uint32_t num_clears, uint32_t num_blocks, uint32_t num_blocks_index,
-    uint32_t message_modulus, uint32_t carry_modulus, PBS_TYPE pbs_type,
+    CudaStreamsFFI streams, int8_t **mem_ptr,
+    CudaLweBootstrapKeyParamsFFI bsk_params, uint32_t ks_level,
+    uint32_t ks_base_log, uint32_t num_clears, uint32_t num_blocks,
+    uint32_t num_blocks_index, uint32_t message_modulus, uint32_t carry_modulus,
     bool allocate_gpu_memory, PBS_MS_REDUCTION_T noise_reduction_type) {
-
-  int_radix_params params(pbs_type, glwe_dimension, polynomial_size,
-                          big_lwe_dimension, small_lwe_dimension, ks_level,
-                          ks_base_log, pbs_level, pbs_base_log, grouping_factor,
-                          message_modulus, carry_modulus, noise_reduction_type);
+  int_radix_params params(bsk_params, ks_level, ks_base_log, message_modulus,
+                          carry_modulus, noise_reduction_type);
 
   return scratch_cuda_unchecked_index_in_clears<uint64_t>(
       CudaStreams(streams),
@@ -299,18 +269,13 @@ void cleanup_cuda_unchecked_index_in_clears_64(CudaStreamsFFI streams,
 }
 
 uint64_t scratch_cuda_unchecked_first_index_in_clears_64_async(
-    CudaStreamsFFI streams, int8_t **mem_ptr, uint32_t glwe_dimension,
-    uint32_t polynomial_size, uint32_t big_lwe_dimension,
-    uint32_t small_lwe_dimension, uint32_t ks_level, uint32_t ks_base_log,
-    uint32_t pbs_level, uint32_t pbs_base_log, uint32_t grouping_factor,
-    uint32_t num_unique, uint32_t num_blocks, uint32_t num_blocks_index,
-    uint32_t message_modulus, uint32_t carry_modulus, PBS_TYPE pbs_type,
+    CudaStreamsFFI streams, int8_t **mem_ptr,
+    CudaLweBootstrapKeyParamsFFI bsk_params, uint32_t ks_level,
+    uint32_t ks_base_log, uint32_t num_unique, uint32_t num_blocks,
+    uint32_t num_blocks_index, uint32_t message_modulus, uint32_t carry_modulus,
     bool allocate_gpu_memory, PBS_MS_REDUCTION_T noise_reduction_type) {
-
-  int_radix_params params(pbs_type, glwe_dimension, polynomial_size,
-                          big_lwe_dimension, small_lwe_dimension, ks_level,
-                          ks_base_log, pbs_level, pbs_base_log, grouping_factor,
-                          message_modulus, carry_modulus, noise_reduction_type);
+  int_radix_params params(bsk_params, ks_level, ks_base_log, message_modulus,
+                          carry_modulus, noise_reduction_type);
 
   return scratch_cuda_unchecked_first_index_in_clears<uint64_t>(
       CudaStreams(streams),
@@ -351,18 +316,13 @@ void cleanup_cuda_unchecked_first_index_in_clears_64(CudaStreamsFFI streams,
 }
 
 uint64_t scratch_cuda_unchecked_first_index_of_clear_64_async(
-    CudaStreamsFFI streams, int8_t **mem_ptr, uint32_t glwe_dimension,
-    uint32_t polynomial_size, uint32_t big_lwe_dimension,
-    uint32_t small_lwe_dimension, uint32_t ks_level, uint32_t ks_base_log,
-    uint32_t pbs_level, uint32_t pbs_base_log, uint32_t grouping_factor,
-    uint32_t num_inputs, uint32_t num_blocks, uint32_t num_blocks_index,
-    uint32_t message_modulus, uint32_t carry_modulus, PBS_TYPE pbs_type,
+    CudaStreamsFFI streams, int8_t **mem_ptr,
+    CudaLweBootstrapKeyParamsFFI bsk_params, uint32_t ks_level,
+    uint32_t ks_base_log, uint32_t num_inputs, uint32_t num_blocks,
+    uint32_t num_blocks_index, uint32_t message_modulus, uint32_t carry_modulus,
     bool allocate_gpu_memory, PBS_MS_REDUCTION_T noise_reduction_type) {
-
-  int_radix_params params(pbs_type, glwe_dimension, polynomial_size,
-                          big_lwe_dimension, small_lwe_dimension, ks_level,
-                          ks_base_log, pbs_level, pbs_base_log, grouping_factor,
-                          message_modulus, carry_modulus, noise_reduction_type);
+  int_radix_params params(bsk_params, ks_level, ks_base_log, message_modulus,
+                          carry_modulus, noise_reduction_type);
 
   return scratch_cuda_unchecked_first_index_of_clear<uint64_t>(
       CudaStreams(streams),
@@ -403,18 +363,13 @@ void cleanup_cuda_unchecked_first_index_of_clear_64(CudaStreamsFFI streams,
 }
 
 uint64_t scratch_cuda_unchecked_first_index_of_64_async(
-    CudaStreamsFFI streams, int8_t **mem_ptr, uint32_t glwe_dimension,
-    uint32_t polynomial_size, uint32_t big_lwe_dimension,
-    uint32_t small_lwe_dimension, uint32_t ks_level, uint32_t ks_base_log,
-    uint32_t pbs_level, uint32_t pbs_base_log, uint32_t grouping_factor,
-    uint32_t num_inputs, uint32_t num_blocks, uint32_t num_blocks_index,
-    uint32_t message_modulus, uint32_t carry_modulus, PBS_TYPE pbs_type,
+    CudaStreamsFFI streams, int8_t **mem_ptr,
+    CudaLweBootstrapKeyParamsFFI bsk_params, uint32_t ks_level,
+    uint32_t ks_base_log, uint32_t num_inputs, uint32_t num_blocks,
+    uint32_t num_blocks_index, uint32_t message_modulus, uint32_t carry_modulus,
     bool allocate_gpu_memory, PBS_MS_REDUCTION_T noise_reduction_type) {
-
-  int_radix_params params(pbs_type, glwe_dimension, polynomial_size,
-                          big_lwe_dimension, small_lwe_dimension, ks_level,
-                          ks_base_log, pbs_level, pbs_base_log, grouping_factor,
-                          message_modulus, carry_modulus, noise_reduction_type);
+  int_radix_params params(bsk_params, ks_level, ks_base_log, message_modulus,
+                          carry_modulus, noise_reduction_type);
 
   return scratch_cuda_unchecked_first_index_of<uint64_t>(
       CudaStreams(streams),
@@ -455,18 +410,13 @@ void cleanup_cuda_unchecked_first_index_of_64(CudaStreamsFFI streams,
 }
 
 uint64_t scratch_cuda_unchecked_index_of_64_async(
-    CudaStreamsFFI streams, int8_t **mem_ptr, uint32_t glwe_dimension,
-    uint32_t polynomial_size, uint32_t big_lwe_dimension,
-    uint32_t small_lwe_dimension, uint32_t ks_level, uint32_t ks_base_log,
-    uint32_t pbs_level, uint32_t pbs_base_log, uint32_t grouping_factor,
-    uint32_t num_inputs, uint32_t num_blocks, uint32_t num_blocks_index,
-    uint32_t message_modulus, uint32_t carry_modulus, PBS_TYPE pbs_type,
+    CudaStreamsFFI streams, int8_t **mem_ptr,
+    CudaLweBootstrapKeyParamsFFI bsk_params, uint32_t ks_level,
+    uint32_t ks_base_log, uint32_t num_inputs, uint32_t num_blocks,
+    uint32_t num_blocks_index, uint32_t message_modulus, uint32_t carry_modulus,
     bool allocate_gpu_memory, PBS_MS_REDUCTION_T noise_reduction_type) {
-
-  int_radix_params params(pbs_type, glwe_dimension, polynomial_size,
-                          big_lwe_dimension, small_lwe_dimension, ks_level,
-                          ks_base_log, pbs_level, pbs_base_log, grouping_factor,
-                          message_modulus, carry_modulus, noise_reduction_type);
+  int_radix_params params(bsk_params, ks_level, ks_base_log, message_modulus,
+                          carry_modulus, noise_reduction_type);
 
   return scratch_cuda_unchecked_index_of<uint64_t>(
       CudaStreams(streams), (int_unchecked_index_of_buffer<uint64_t> **)mem_ptr,
@@ -508,18 +458,13 @@ void cleanup_cuda_unchecked_index_of_64(CudaStreamsFFI streams,
 }
 
 uint64_t scratch_cuda_unchecked_index_of_clear_64_async(
-    CudaStreamsFFI streams, int8_t **mem_ptr, uint32_t glwe_dimension,
-    uint32_t polynomial_size, uint32_t big_lwe_dimension,
-    uint32_t small_lwe_dimension, uint32_t ks_level, uint32_t ks_base_log,
-    uint32_t pbs_level, uint32_t pbs_base_log, uint32_t grouping_factor,
-    uint32_t num_inputs, uint32_t num_blocks, uint32_t num_blocks_index,
-    uint32_t message_modulus, uint32_t carry_modulus, PBS_TYPE pbs_type,
+    CudaStreamsFFI streams, int8_t **mem_ptr,
+    CudaLweBootstrapKeyParamsFFI bsk_params, uint32_t ks_level,
+    uint32_t ks_base_log, uint32_t num_inputs, uint32_t num_blocks,
+    uint32_t num_blocks_index, uint32_t message_modulus, uint32_t carry_modulus,
     bool allocate_gpu_memory, PBS_MS_REDUCTION_T noise_reduction_type) {
-
-  int_radix_params params(pbs_type, glwe_dimension, polynomial_size,
-                          big_lwe_dimension, small_lwe_dimension, ks_level,
-                          ks_base_log, pbs_level, pbs_base_log, grouping_factor,
-                          message_modulus, carry_modulus, noise_reduction_type);
+  int_radix_params params(bsk_params, ks_level, ks_base_log, message_modulus,
+                          carry_modulus, noise_reduction_type);
 
   return scratch_cuda_unchecked_index_of_clear<uint64_t>(
       CudaStreams(streams),

backends/tfhe-cuda-backend/cuda/src/kreyvium/kreyvium.cu

@@ -2,18 +2,14 @@
 #include "kreyvium.cuh"
 
 uint64_t scratch_cuda_kreyvium_generate_keystream_64_async(
-    CudaStreamsFFI streams, int8_t **mem_ptr, uint32_t glwe_dimension,
-    uint32_t polynomial_size, uint32_t lwe_dimension, uint32_t ks_level,
-    uint32_t ks_base_log, uint32_t pbs_level, uint32_t pbs_base_log,
-    uint32_t grouping_factor, uint32_t message_modulus, uint32_t carry_modulus,
-    PBS_TYPE pbs_type, bool allocate_gpu_memory,
-    PBS_MS_REDUCTION_T noise_reduction_type, uint32_t num_inputs) {
+    CudaStreamsFFI streams, int8_t **mem_ptr,
+    CudaLweBootstrapKeyParamsFFI bsk_params, uint32_t ks_level,
+    uint32_t ks_base_log, uint32_t message_modulus, uint32_t carry_modulus,
+    bool allocate_gpu_memory, PBS_MS_REDUCTION_T noise_reduction_type,
+    uint32_t num_inputs) {
 
-  int_radix_params params(pbs_type, glwe_dimension, polynomial_size,
-                          glwe_dimension * polynomial_size, lwe_dimension,
-                          ks_level, ks_base_log, pbs_level, pbs_base_log,
-                          grouping_factor, message_modulus, carry_modulus,
-                          noise_reduction_type);
+  int_radix_params params(bsk_params, ks_level, ks_base_log, message_modulus,
+                          carry_modulus, noise_reduction_type);
 
   return scratch_cuda_kreyvium_encrypt<uint64_t>(
       CudaStreams(streams), (int_kreyvium_buffer<uint64_t> **)mem_ptr, params,

backends/tfhe-cuda-backend/cuda/src/pbs/programmable_bootstrap_cg_multibit.cuh

@@ -420,6 +420,39 @@ __host__ void host_cg_multi_bit_programmable_bootstrap(
   }
 }
 
+// Noise tests variant: identical to host_cg_multi_bit_programmable_bootstrap
+// but uses NOISE_TESTS keybundle mode.
+template <typename Torus, class params>
+__host__ void host_cg_multi_bit_programmable_bootstrap_noise_tests(
+    cudaStream_t stream, uint32_t gpu_index, Torus *lwe_array_out,
+    Torus const *lwe_output_indexes, Torus const *lut_vector,
+    Torus const *lut_vector_indexes, Torus const *lwe_array_in,
+    Torus const *lwe_input_indexes, uint64_t const *bootstrapping_key,
+    pbs_buffer<Torus, MULTI_BIT> *buffer, uint32_t glwe_dimension,
+    uint32_t lwe_dimension, uint32_t polynomial_size, uint32_t grouping_factor,
+    uint32_t base_log, uint32_t level_count, uint32_t num_samples,
+    uint32_t num_many_lut, uint32_t lut_stride) {
+
+  auto lwe_chunk_size = buffer->lwe_chunk_size;
+
+  for (uint32_t lwe_offset = 0; lwe_offset < (lwe_dimension / grouping_factor);
+       lwe_offset += lwe_chunk_size) {
+
+    // Compute a keybundle with NOISE_TESTS mode instead of GENERIC
+    execute_compute_keybundle_noise_tests<Torus, params>(
+        stream, gpu_index, lwe_array_in, lwe_input_indexes, bootstrapping_key,
+        buffer, num_samples, lwe_dimension, glwe_dimension, polynomial_size,
+        grouping_factor, level_count, lwe_offset);
+
+    execute_cg_external_product_loop<Torus, params>(
+        stream, gpu_index, lut_vector, lut_vector_indexes, lwe_array_in,
+        lwe_input_indexes, lwe_array_out, lwe_output_indexes, buffer,
+        num_samples, lwe_dimension, glwe_dimension, polynomial_size,
+        grouping_factor, base_log, level_count, lwe_offset, num_many_lut,
+        lut_stride);
+  }
+}
+
 // Verify if the grid size satisfies the cooperative group constraints
 template <typename Torus, class params>
 __host__ bool verify_cuda_programmable_bootstrap_cg_multi_bit_grid_size(

backends/tfhe-cuda-backend/cuda/src/pbs/programmable_bootstrap_multibit.cu

@@ -645,6 +645,103 @@ void cleanup_cuda_multi_bit_programmable_bootstrap_64(void *stream,
   *buffer = nullptr;
 }
 
+// Noise-tests-namespaced wrappers: delegate to the standard scratch/cleanup so
+// that callers using the noise-tests PBS variant have a consistent API.
+uint64_t scratch_cuda_multi_bit_programmable_bootstrap_noise_tests_64_async(
+    void *stream, uint32_t gpu_index, int8_t **pbs_buffer,
+    uint32_t glwe_dimension, uint32_t polynomial_size, uint32_t level_count,
+    uint32_t input_lwe_ciphertext_count, bool allocate_gpu_memory) {
+  return scratch_cuda_multi_bit_programmable_bootstrap_64_async(
+      stream, gpu_index, pbs_buffer, glwe_dimension, polynomial_size,
+      level_count, input_lwe_ciphertext_count, allocate_gpu_memory);
+}
+
+void cleanup_cuda_multi_bit_programmable_bootstrap_noise_tests_64(
+    void *stream, uint32_t gpu_index, int8_t **pbs_buffer) {
+  cleanup_cuda_multi_bit_programmable_bootstrap_64(stream, gpu_index,
+                                                   pbs_buffer);
+}
+
+// Noise tests variant of the 64-bit multi-bit PBS, restricted to
+// polynomial_size=2048. The main difference is that the input
+// is assumed to be modulus switched before bootstrapping.
+void cuda_multi_bit_programmable_bootstrap_noise_tests_64_async(
+    void *stream, uint32_t gpu_index, void *lwe_array_out,
+    void const *lwe_output_indexes, void const *lut_vector,
+    void const *lut_vector_indexes, void const *lwe_array_in,
+    void const *lwe_input_indexes, void const *bootstrapping_key,
+    int8_t *mem_ptr, uint32_t lwe_dimension, uint32_t glwe_dimension,
+    uint32_t polynomial_size, uint32_t grouping_factor, uint32_t base_log,
+    uint32_t level_count, uint32_t num_samples, uint32_t num_many_lut,
+    uint32_t lut_stride) {
+
+  PANIC_IF_FALSE(num_samples == 1,
+                 "Cuda error (multi-bit PBS): num_samples (%d) should be 1",
+                 num_samples);
+
+  PANIC_IF_FALSE(base_log <= 64,
+                 "Cuda error (multi-bit PBS): base log (%d) should be <= 64",
+                 base_log);
+  PANIC_IF_FALSE(polynomial_size == 2048,
+                 "Cuda error (multi-bit PBS noise tests): only polynomial "
+                 "size 2048 is supported, got %d.",
+                 polynomial_size);
+
+  pbs_buffer<uint64_t, MULTI_BIT> *buffer =
+      (pbs_buffer<uint64_t, MULTI_BIT> *)mem_ptr;
+
+  switch (buffer->pbs_variant) {
+  case PBS_VARIANT::TBC:
+#if CUDA_ARCH >= 900
+  {
+    host_tbc_multi_bit_programmable_bootstrap_noise_tests<uint64_t,
+                                                          Degree<2048>>(
+        static_cast<cudaStream_t>(stream), gpu_index,
+        static_cast<uint64_t *>(lwe_array_out),
+        static_cast<const uint64_t *>(lwe_output_indexes),
+        static_cast<const uint64_t *>(lut_vector),
+        static_cast<const uint64_t *>(lut_vector_indexes),
+        static_cast<const uint64_t *>(lwe_array_in),
+        static_cast<const uint64_t *>(lwe_input_indexes),
+        static_cast<const uint64_t *>(bootstrapping_key), buffer,
+        glwe_dimension, lwe_dimension, polynomial_size, grouping_factor,
+        base_log, level_count, num_samples, num_many_lut, lut_stride);
+  } break;
+#else
+    PANIC("Cuda error (multi-bit PBS): TBC pbs is not supported.")
+#endif
+  case PBS_VARIANT::CG:
+    host_cg_multi_bit_programmable_bootstrap_noise_tests<uint64_t,
+                                                         Degree<2048>>(
+        static_cast<cudaStream_t>(stream), gpu_index,
+        static_cast<uint64_t *>(lwe_array_out),
+        static_cast<const uint64_t *>(lwe_output_indexes),
+        static_cast<const uint64_t *>(lut_vector),
+        static_cast<const uint64_t *>(lut_vector_indexes),
+        static_cast<const uint64_t *>(lwe_array_in),
+        static_cast<const uint64_t *>(lwe_input_indexes),
+        static_cast<const uint64_t *>(bootstrapping_key), buffer,
+        glwe_dimension, lwe_dimension, polynomial_size, grouping_factor,
+        base_log, level_count, num_samples, num_many_lut, lut_stride);
+    break;
+  case PBS_VARIANT::DEFAULT:
+    host_multi_bit_programmable_bootstrap_noise_tests<uint64_t, Degree<2048>>(
+        static_cast<cudaStream_t>(stream), gpu_index,
+        static_cast<uint64_t *>(lwe_array_out),
+        static_cast<const uint64_t *>(lwe_output_indexes),
+        static_cast<const uint64_t *>(lut_vector),
+        static_cast<const uint64_t *>(lut_vector_indexes),
+        static_cast<const uint64_t *>(lwe_array_in),
+        static_cast<const uint64_t *>(lwe_input_indexes),
+        static_cast<const uint64_t *>(bootstrapping_key), buffer,
+        glwe_dimension, lwe_dimension, polynomial_size, grouping_factor,
+        base_log, level_count, num_samples, num_many_lut, lut_stride);
+    break;
+  default:
+    PANIC("Cuda error (multi-bit PBS): unsupported implementation variant.")
+  }
+}
+
 /**
  * Computes divisors of the product of num_sms (streaming multiprocessors on the
  * GPU) and max_blocks_per_sm (maximum active blocks per SM to launch

backends/tfhe-cuda-backend/cuda/src/pbs/programmable_bootstrap_multibit.cuh

@@ -25,7 +25,8 @@ get_start_ith_ggsw_offset(uint32_t polynomial_size, int glwe_dimension,
          level_count;
 }
 
-template <typename Torus, class params, sharedMemDegree SMD>
+template <typename Torus, class params, sharedMemDegree SMD,
+          bool runs_noise_test = false>
 __global__ void device_multi_bit_programmable_bootstrap_keybundle(
     const Torus *__restrict__ lwe_array_in,
     const Torus *__restrict__ lwe_input_indexes, double2 *keybundle_array,
@@ -55,9 +56,6 @@ __global__ void device_multi_bit_programmable_bootstrap_keybundle(
 
   if (lwe_iteration < (lwe_dimension / grouping_factor)) {
 
-    const Torus *block_lwe_array_in =
-        &lwe_array_in[lwe_input_indexes[input_idx] * (lwe_dimension + 1)];
-
     double2 *keybundle = keybundle_array +
                          // select the input
                          input_idx * keybundle_size_per_input;
@@ -86,10 +84,40 @@ __global__ void device_multi_bit_programmable_bootstrap_keybundle(
     // Precalculate the monomial degrees and store them in shared memory
     uint32_t *monomial_degrees = (uint32_t *)selected_memory;
     if (threadIdx.x < (1 << grouping_factor)) {
-      const Torus *lwe_array_group =
-          block_lwe_array_in + rev_lwe_iteration * grouping_factor;
-      monomial_degrees[threadIdx.x] = calculates_monomial_degree<Torus, params>(
-          lwe_array_group, threadIdx.x, grouping_factor);
+      if constexpr (runs_noise_test == true) {
+        // For noise tests the input array contains the input lwe but also the
+        // modswitched results. This allows to avoid changing the accumulation
+        // kernel for the noise tests since the input body will stay in the same
+        // position. The layout of the input array is the following:
+        // | input lwe     | modswitched inputs       |
+        // | lwe size      | lwe_size*grouping_factor |
+
+        // This offset allows to jump directly to the modswitched inputs,
+        // skipping the input lwe
+        const Torus modswitched_offset = lwe_dimension + 1;
+
+        const Torus *block_lwe_array_in =
+            &lwe_array_in[lwe_input_indexes[input_idx] *
+                              (lwe_dimension / grouping_factor) *
+                              (1 << grouping_factor) +
+                          modswitched_offset];
+
+        const Torus *lwe_array_group =
+            block_lwe_array_in + rev_lwe_iteration * (1 << grouping_factor);
+        monomial_degrees[threadIdx.x] = lwe_array_group[threadIdx.x];
+
+      } else {
+        // In production we calculate the monomial degrees on the fly, since
+        // they are not stored in the input array.
+        const Torus *block_lwe_array_in =
+            &lwe_array_in[lwe_input_indexes[input_idx] * (lwe_dimension + 1)];
+
+        const Torus *lwe_array_group =
+            block_lwe_array_in + rev_lwe_iteration * grouping_factor;
+        monomial_degrees[threadIdx.x] =
+            calculates_monomial_degree<Torus, params>(
+                lwe_array_group, threadIdx.x, grouping_factor);
+      }
     }
     __syncthreads();
 
@@ -145,7 +173,8 @@ __global__ void device_multi_bit_programmable_bootstrap_keybundle(
 // Then we can just calculate the offset needed to apply this coefficients, and
 // the operation transforms into a pointwise vector multiplication, avoiding to
 // perform extra instructions other than MADD
-template <typename Torus, class params, sharedMemDegree SMD>
+template <typename Torus, class params, sharedMemDegree SMD,
+          bool runs_noise_test = false>
 __global__ void device_multi_bit_programmable_bootstrap_keybundle_2_2_params(
     const Torus *__restrict__ lwe_array_in,
     const Torus *__restrict__ lwe_input_indexes, double2 *keybundle_array,
@@ -219,10 +248,40 @@ __global__ void device_multi_bit_programmable_bootstrap_keybundle_2_2_params(
     uint32_t *monomial_degrees = (uint32_t *)selected_memory;
 
     if (threadIdx.x < (1 << grouping_factor)) {
-      const Torus *lwe_array_group =
-          block_lwe_array_in + rev_lwe_iteration * grouping_factor;
-      monomial_degrees[threadIdx.x] = calculates_monomial_degree<Torus, params>(
-          lwe_array_group, threadIdx.x, grouping_factor);
+      if constexpr (runs_noise_test == true) {
+        // For noise tests the input array contains the input lwe but also the
+        // modswitched results. This allows to avoid changing the accumulation
+        // kernel for the noise tests since the input body will stay in the same
+        // position. The layout of the input array is the following:
+        // | input lwe     | modswitched inputs       |
+        // | lwe size      | lwe_size*grouping_factor |
+
+        // This offset allows to jump directly to the modswitched inputs,
+        // skipping the input lwe
+        const Torus modswitched_offset = lwe_dimension + 1;
+
+        const Torus *block_lwe_array_in =
+            &lwe_array_in[lwe_input_indexes[input_idx] *
+                              (lwe_dimension / grouping_factor) *
+                              (1 << grouping_factor) +
+                          modswitched_offset];
+
+        const Torus *lwe_array_group =
+            block_lwe_array_in + rev_lwe_iteration * (1 << grouping_factor);
+        monomial_degrees[threadIdx.x] = lwe_array_group[threadIdx.x];
+
+      } else {
+        // In production we calculate the monomial degrees on the fly, since
+        // they are not stored in the input array.
+        const Torus *block_lwe_array_in =
+            &lwe_array_in[lwe_input_indexes[input_idx] * (lwe_dimension + 1)];
+
+        const Torus *lwe_array_group =
+            block_lwe_array_in + rev_lwe_iteration * grouping_factor;
+        monomial_degrees[threadIdx.x] =
+            calculates_monomial_degree<Torus, params>(
+                lwe_array_group, threadIdx.x, grouping_factor);
+      }
     }
     __syncthreads();
 
@@ -662,6 +721,7 @@ enum class MultiBitKeybundleLaunchMode {
   AUTO,
   GENERIC,
   SPECIALIZED_2_2,
+  NOISE_TESTS,
 };
 
 template <typename Torus, class params>
@@ -726,30 +786,65 @@ __host__ void execute_compute_keybundle_with_mode(
     bool use_specialized =
         launch_mode == MultiBitKeybundleLaunchMode::SPECIALIZED_2_2 ||
         (launch_mode == MultiBitKeybundleLaunchMode::AUTO &&
+         can_use_specialized) ||
+        (launch_mode == MultiBitKeybundleLaunchMode::NOISE_TESTS &&
          can_use_specialized);
+    bool use_noise_test_template =
+        launch_mode == MultiBitKeybundleLaunchMode::NOISE_TESTS;
     if (use_specialized) {
       dim3 thds_new_keybundle(512, 1, 1);
-      check_cuda_error(cudaFuncSetAttribute(
-          device_multi_bit_programmable_bootstrap_keybundle_2_2_params<
-              Torus, Degree<2048>, FULLSM>,
-          cudaFuncAttributeMaxDynamicSharedMemorySize, 3 * full_sm_keybundle));
-      check_cuda_error(cudaFuncSetCacheConfig(
-          device_multi_bit_programmable_bootstrap_keybundle_2_2_params<
-              Torus, Degree<2048>, FULLSM>,
-          cudaFuncCachePreferShared));
-      check_cuda_error(cudaGetLastError());
-      device_multi_bit_programmable_bootstrap_keybundle_2_2_params<
-          Torus, Degree<2048>, FULLSM><<<grid_keybundle, thds_new_keybundle,
-                                         3 * full_sm_keybundle, stream>>>(
-          lwe_array_in, lwe_input_indexes, keybundle_fft, bootstrapping_key,
-          lwe_dimension, lwe_offset, chunk_size, keybundle_size_per_input);
+      if (use_noise_test_template) {
+        // Set up the noise-test variant of the specialized 2_2 kernel
+        check_cuda_error(cudaFuncSetAttribute(
+            device_multi_bit_programmable_bootstrap_keybundle_2_2_params<
+                Torus, Degree<2048>, FULLSM, true>,
+            cudaFuncAttributeMaxDynamicSharedMemorySize,
+            3 * full_sm_keybundle));
+        check_cuda_error(cudaFuncSetCacheConfig(
+            device_multi_bit_programmable_bootstrap_keybundle_2_2_params<
+                Torus, Degree<2048>, FULLSM, true>,
+            cudaFuncCachePreferShared));
+        check_cuda_error(cudaGetLastError());
+        device_multi_bit_programmable_bootstrap_keybundle_2_2_params<
+            Torus, Degree<2048>, FULLSM, true>
+            <<<grid_keybundle, thds_new_keybundle, 3 * full_sm_keybundle,
+               stream>>>(lwe_array_in, lwe_input_indexes, keybundle_fft,
+                         bootstrapping_key, lwe_dimension, lwe_offset,
+                         chunk_size, keybundle_size_per_input);
+      } else {
+        check_cuda_error(cudaFuncSetAttribute(
+            device_multi_bit_programmable_bootstrap_keybundle_2_2_params<
+                Torus, Degree<2048>, FULLSM>,
+            cudaFuncAttributeMaxDynamicSharedMemorySize,
+            3 * full_sm_keybundle));
+        check_cuda_error(cudaFuncSetCacheConfig(
+            device_multi_bit_programmable_bootstrap_keybundle_2_2_params<
+                Torus, Degree<2048>, FULLSM>,
+            cudaFuncCachePreferShared));
+        check_cuda_error(cudaGetLastError());
+        device_multi_bit_programmable_bootstrap_keybundle_2_2_params<
+            Torus, Degree<2048>, FULLSM><<<grid_keybundle, thds_new_keybundle,
+                                           3 * full_sm_keybundle, stream>>>(
+            lwe_array_in, lwe_input_indexes, keybundle_fft, bootstrapping_key,
+            lwe_dimension, lwe_offset, chunk_size, keybundle_size_per_input);
+      }
     } else {
-      device_multi_bit_programmable_bootstrap_keybundle<Torus, params, FULLSM>
-          <<<grid_keybundle, thds, full_sm_keybundle, stream>>>(
-              lwe_array_in, lwe_input_indexes, keybundle_fft, bootstrapping_key,
-              lwe_dimension, glwe_dimension, polynomial_size, grouping_factor,
-              level_count, lwe_offset, chunk_size, keybundle_size_per_input,
-              d_mem, 0);
+      if (use_noise_test_template) {
+        device_multi_bit_programmable_bootstrap_keybundle<Torus, params, FULLSM,
+                                                          true>
+            <<<grid_keybundle, thds, full_sm_keybundle, stream>>>(
+                lwe_array_in, lwe_input_indexes, keybundle_fft,
+                bootstrapping_key, lwe_dimension, glwe_dimension,
+                polynomial_size, grouping_factor, level_count, lwe_offset,
+                chunk_size, keybundle_size_per_input, d_mem, 0);
+      } else {
+        device_multi_bit_programmable_bootstrap_keybundle<Torus, params, FULLSM>
+            <<<grid_keybundle, thds, full_sm_keybundle, stream>>>(
+                lwe_array_in, lwe_input_indexes, keybundle_fft,
+                bootstrapping_key, lwe_dimension, glwe_dimension,
+                polynomial_size, grouping_factor, level_count, lwe_offset,
+                chunk_size, keybundle_size_per_input, d_mem, 0);
+      }
     }
   }
   check_cuda_error(cudaGetLastError());
@@ -796,6 +891,20 @@ __host__ void execute_compute_keybundle_2_2_specialized(
       grouping_factor, level_count, lwe_offset,
       MultiBitKeybundleLaunchMode::SPECIALIZED_2_2);
 }
+// Used only to run noise tests
+template <typename Torus, class params>
+__host__ void execute_compute_keybundle_noise_tests(
+    cudaStream_t stream, uint32_t gpu_index, Torus const *lwe_array_in,
+    Torus const *lwe_input_indexes, Torus const *bootstrapping_key,
+    pbs_buffer<Torus, MULTI_BIT> *buffer, uint32_t num_samples,
+    uint32_t lwe_dimension, uint32_t glwe_dimension, uint32_t polynomial_size,
+    uint32_t grouping_factor, uint32_t level_count, uint32_t lwe_offset) {
+  execute_compute_keybundle_with_mode<Torus, params>(
+      stream, gpu_index, lwe_array_in, lwe_input_indexes, bootstrapping_key,
+      buffer, num_samples, lwe_dimension, glwe_dimension, polynomial_size,
+      grouping_factor, level_count, lwe_offset,
+      MultiBitKeybundleLaunchMode::NOISE_TESTS);
+}
 
 template <typename Torus, class params, bool is_first_iter>
 __host__ void execute_step_one(
@@ -955,4 +1064,62 @@ __host__ void host_multi_bit_programmable_bootstrap(
     }
   }
 }
+
+template <typename Torus, class params>
+__host__ void host_multi_bit_programmable_bootstrap_noise_tests(
+    cudaStream_t stream, uint32_t gpu_index, Torus *lwe_array_out,
+    Torus const *lwe_output_indexes, Torus const *lut_vector,
+    Torus const *lut_vector_indexes, Torus const *lwe_array_in,
+    Torus const *lwe_input_indexes, Torus const *bootstrapping_key,
+    pbs_buffer<Torus, MULTI_BIT> *buffer, uint32_t glwe_dimension,
+    uint32_t lwe_dimension, uint32_t polynomial_size, uint32_t grouping_factor,
+    uint32_t base_log, uint32_t level_count, uint32_t num_samples,
+    uint32_t num_many_lut, uint32_t lut_stride) {
+
+  auto lwe_chunk_size = buffer->lwe_chunk_size;
+
+  for (uint32_t lwe_offset = 0; lwe_offset < (lwe_dimension / grouping_factor);
+       lwe_offset += lwe_chunk_size) {
+
+    // Compute a keybundle with NOISE_TESTS mode to enable the specialized
+    // runs_noise_test=true kernel variant for noise measurement
+    execute_compute_keybundle_with_mode<Torus, params>(
+        stream, gpu_index, lwe_array_in, lwe_input_indexes, bootstrapping_key,
+        buffer, num_samples, lwe_dimension, glwe_dimension, polynomial_size,
+        grouping_factor, level_count, lwe_offset,
+        MultiBitKeybundleLaunchMode::NOISE_TESTS);
+    // Accumulate (same as standard path)
+    uint32_t chunk_size =
+        std::min((uint32_t)lwe_chunk_size,
+                 (lwe_dimension / grouping_factor) - lwe_offset);
+    for (uint32_t j = 0; j < chunk_size; j++) {
+      bool is_first_iter = (j + lwe_offset) == 0;
+      bool is_last_iter =
+          (j + lwe_offset) + 1 == (lwe_dimension / grouping_factor);
+      if (is_first_iter) {
+        execute_step_one<Torus, params, true>(
+            stream, gpu_index, lut_vector, lut_vector_indexes, lwe_array_in,
+            lwe_input_indexes, buffer, num_samples, lwe_dimension,
+            glwe_dimension, polynomial_size, base_log, level_count);
+      } else {
+        execute_step_one<Torus, params, false>(
+            stream, gpu_index, lut_vector, lut_vector_indexes, lwe_array_in,
+            lwe_input_indexes, buffer, num_samples, lwe_dimension,
+            glwe_dimension, polynomial_size, base_log, level_count);
+      }
+
+      if (is_last_iter) {
+        execute_step_two<Torus, params, true>(
+            stream, gpu_index, lwe_array_out, lwe_output_indexes, buffer,
+            num_samples, glwe_dimension, polynomial_size, level_count, j,
+            num_many_lut, lut_stride);
+      } else {
+        execute_step_two<Torus, params, false>(
+            stream, gpu_index, lwe_array_out, lwe_output_indexes, buffer,
+            num_samples, glwe_dimension, polynomial_size, level_count, j,
+            num_many_lut, lut_stride);
+      }
+    }
+  }
+}
 #endif // MULTIBIT_PBS_H

backends/tfhe-cuda-backend/cuda/src/pbs/programmable_bootstrap_multibit_128.cu

@@ -293,6 +293,81 @@ void cleanup_cuda_multi_bit_programmable_bootstrap_128(void *stream,
   *buffer = nullptr;
 }
 
+// Noise-tests-namespaced wrappers: delegate to the standard scratch/cleanup so
+// that callers using the noise-tests PBS128 variant have a consistent API.
+uint64_t scratch_cuda_multi_bit_programmable_bootstrap_noise_tests_128_async(
+    void *stream, uint32_t gpu_index, int8_t **pbs_buffer,
+    uint32_t glwe_dimension, uint32_t polynomial_size, uint32_t level_count,
+    uint32_t input_lwe_ciphertext_count, bool allocate_gpu_memory) {
+  return scratch_cuda_multi_bit_programmable_bootstrap_128_async(
+      stream, gpu_index, pbs_buffer, glwe_dimension, polynomial_size,
+      level_count, input_lwe_ciphertext_count, allocate_gpu_memory);
+}
+
+void cleanup_cuda_multi_bit_programmable_bootstrap_noise_tests_128(
+    void *stream, uint32_t gpu_index, int8_t **pbs_buffer) {
+  cleanup_cuda_multi_bit_programmable_bootstrap_128(stream, gpu_index,
+                                                    pbs_buffer);
+  cuda_synchronize_stream(static_cast<cudaStream_t>(stream), gpu_index);
+}
+
+// Noise tests variant of the 128-bit multi-bit PBS, restricted to
+// polynomial_size=2048. The input is assumed to contain precomputed
+// modswitched values in the extended input array layout.
+void cuda_multi_bit_programmable_bootstrap_noise_tests_128_async(
+    void *stream, uint32_t gpu_index, void *lwe_array_out,
+    void const *lwe_output_indexes, void const *lut_vector,
+    void const *lwe_array_in, void const *lwe_input_indexes,
+    void const *bootstrapping_key, int8_t *mem_ptr, uint32_t lwe_dimension,
+    uint32_t glwe_dimension, uint32_t polynomial_size, uint32_t grouping_factor,
+    uint32_t base_log, uint32_t level_count, uint32_t num_samples,
+    uint32_t num_many_lut, uint32_t lut_stride) {
+
+  PANIC_IF_FALSE(num_samples == 1,
+                 "Cuda error (multi-bit PBS): num_samples (%d) should be 1",
+                 num_samples);
+  PANIC_IF_FALSE(base_log <= 64,
+                 "Cuda error (multi-bit PBS): base log (%d) should be <= 64",
+                 base_log);
+  PANIC_IF_FALSE(polynomial_size == 2048,
+                 "Cuda error (multi-bit PBS128 noise tests): only polynomial "
+                 "size 2048 is supported, got %d.",
+                 polynomial_size);
+
+  auto *buffer =
+      reinterpret_cast<pbs_buffer_128<uint64_t, MULTI_BIT> *>(mem_ptr);
+  switch (buffer->pbs_variant) {
+  case PBS_VARIANT::CG:
+    host_cg_multi_bit_programmable_bootstrap_noise_tests_128<uint64_t,
+                                                             Degree<2048>>(
+        static_cast<cudaStream_t>(stream), gpu_index,
+        static_cast<__uint128_t *>(lwe_array_out),
+        static_cast<const uint64_t *>(lwe_output_indexes),
+        static_cast<const __uint128_t *>(lut_vector),
+        static_cast<const uint64_t *>(lwe_array_in),
+        static_cast<const uint64_t *>(lwe_input_indexes),
+        static_cast<const __uint128_t *>(bootstrapping_key), buffer,
+        glwe_dimension, lwe_dimension, polynomial_size, grouping_factor,
+        base_log, level_count, num_samples, num_many_lut, lut_stride);
+    break;
+  case PBS_VARIANT::DEFAULT:
+    host_multi_bit_programmable_bootstrap_noise_tests_128<uint64_t,
+                                                          Degree<2048>>(
+        static_cast<cudaStream_t>(stream), gpu_index,
+        static_cast<__uint128_t *>(lwe_array_out),
+        static_cast<const uint64_t *>(lwe_output_indexes),
+        static_cast<const __uint128_t *>(lut_vector),
+        static_cast<const uint64_t *>(lwe_array_in),
+        static_cast<const uint64_t *>(lwe_input_indexes),
+        static_cast<const __uint128_t *>(bootstrapping_key), buffer,
+        glwe_dimension, lwe_dimension, polynomial_size, grouping_factor,
+        base_log, level_count, num_samples, num_many_lut, lut_stride);
+    break;
+  default:
+    PANIC("Cuda error (multi-bit PBS): unsupported implementation variant.")
+  }
+}
+
 /**
  * Computes divisors of the product of num_sms (streaming multiprocessors on the
  * GPU) and max_blocks_per_sm (maximum active blocks per SM to launch

backends/tfhe-cuda-backend/cuda/src/pbs/programmable_bootstrap_multibit_128.cuh

@@ -18,7 +18,8 @@ uint64_t get_buffer_size_full_sm_multibit_programmable_bootstrap_128_keybundle(
                                       (size_t)2); // accumulator
 }
 
-template <typename InputTorus, class params, sharedMemDegree SMD>
+template <typename InputTorus, class params, sharedMemDegree SMD,
+          bool runs_noise_test = false>
 __global__ void device_multi_bit_programmable_bootstrap_keybundle_128(
     const InputTorus *__restrict__ lwe_array_in,
     const InputTorus *__restrict__ lwe_input_indexes, double *keybundle_array,
@@ -80,11 +81,35 @@ __global__ void device_multi_bit_programmable_bootstrap_keybundle_128(
     // Precalculate the monomial degrees and store them in shared memory
     uint32_t *monomial_degrees = (uint32_t *)selected_memory;
     if (threadIdx.x < (1 << grouping_factor)) {
-      auto lwe_array_group =
-          block_lwe_array_in + rev_lwe_iteration * grouping_factor;
-      monomial_degrees[threadIdx.x] =
-          calculates_monomial_degree<InputTorus, params>(
-              lwe_array_group, threadIdx.x, grouping_factor);
+      if constexpr (runs_noise_test == true) {
+        // For noise tests the input array contains the input lwe but also the
+        // modswitched results. This allows to avoid changing the accumulation
+        // kernel for the noise tests since the input body will stay in the same
+        // position. The layout of the input array is the following:
+        // | input lwe     | modswitched inputs       |
+        // | lwe size      | lwe_size*grouping_factor |
+
+        // This offset allows to jump directly to the modswitched inputs,
+        // skipping the input lwe
+        const InputTorus modswitched_offset = lwe_dimension + 1;
+
+        const InputTorus *block_lwe_array_in_noise =
+            &lwe_array_in[lwe_input_indexes[input_idx] *
+                              (lwe_dimension / grouping_factor) *
+                              (1 << grouping_factor) +
+                          modswitched_offset];
+
+        const InputTorus *lwe_array_group =
+            block_lwe_array_in_noise +
+            rev_lwe_iteration * (1 << grouping_factor);
+        monomial_degrees[threadIdx.x] = lwe_array_group[threadIdx.x];
+      } else {
+        auto lwe_array_group =
+            block_lwe_array_in + rev_lwe_iteration * grouping_factor;
+        monomial_degrees[threadIdx.x] =
+            calculates_monomial_degree<InputTorus, params>(
+                lwe_array_group, threadIdx.x, grouping_factor);
+      }
     }
     __syncthreads();
 
@@ -588,6 +613,74 @@ __host__ void execute_compute_keybundle_128(
   check_cuda_error(cudaGetLastError());
 }
 
+// Used only to run noise tests: launches the keybundle kernel with the
+// runs_noise_test=true variant, which reads modswitched inputs from the
+// extended input array layout instead of computing them on-the-fly
+template <typename InputTorus, class params>
+__host__ void execute_compute_keybundle_noise_tests_128(
+    cudaStream_t stream, uint32_t gpu_index, InputTorus const *lwe_array_in,
+    InputTorus const *lwe_input_indexes, __uint128_t const *bootstrapping_key,
+    pbs_buffer_128<InputTorus, MULTI_BIT> *buffer, uint32_t num_samples,
+    uint32_t lwe_dimension, uint32_t glwe_dimension, uint32_t polynomial_size,
+    uint32_t grouping_factor, uint32_t level_count, uint32_t lwe_offset) {
+  cuda_set_device(gpu_index);
+
+  auto lwe_chunk_size = buffer->lwe_chunk_size;
+  uint64_t chunk_size = std::min(
+      lwe_chunk_size, (uint64_t)(lwe_dimension / grouping_factor) - lwe_offset);
+
+  uint64_t keybundle_size_per_input =
+      lwe_chunk_size * level_count * (glwe_dimension + 1) *
+      (glwe_dimension + 1) * (polynomial_size / 2) * 4;
+
+  uint64_t full_sm_keybundle =
+      get_buffer_size_full_sm_multibit_programmable_bootstrap_128_keybundle<
+          __uint128_t>(polynomial_size);
+  auto max_shared_memory = cuda_get_max_shared_memory(gpu_index);
+
+  auto d_mem = buffer->d_mem_keybundle;
+  auto keybundle_fft = buffer->keybundle_fft;
+
+  dim3 grid_keybundle(num_samples * chunk_size,
+                      (glwe_dimension + 1) * (glwe_dimension + 1), level_count);
+  dim3 thds(polynomial_size / params::opt, 1, 1);
+
+  if (max_shared_memory < full_sm_keybundle) {
+    check_cuda_error(cudaFuncSetAttribute(
+        device_multi_bit_programmable_bootstrap_keybundle_128<
+            InputTorus, params, NOSM, true>,
+        cudaFuncAttributeMaxDynamicSharedMemorySize, 0));
+    check_cuda_error(cudaFuncSetCacheConfig(
+        device_multi_bit_programmable_bootstrap_keybundle_128<
+            InputTorus, params, NOSM, true>,
+        cudaFuncCachePreferShared));
+    device_multi_bit_programmable_bootstrap_keybundle_128<InputTorus, params,
+                                                          NOSM, true>
+        <<<grid_keybundle, thds, 0, stream>>>(
+            lwe_array_in, lwe_input_indexes, keybundle_fft, bootstrapping_key,
+            lwe_dimension, glwe_dimension, polynomial_size, grouping_factor,
+            level_count, lwe_offset, chunk_size, keybundle_size_per_input,
+            d_mem, full_sm_keybundle);
+  } else {
+    check_cuda_error(cudaFuncSetAttribute(
+        device_multi_bit_programmable_bootstrap_keybundle_128<
+            InputTorus, params, FULLSM, true>,
+        cudaFuncAttributeMaxDynamicSharedMemorySize, full_sm_keybundle));
+    check_cuda_error(cudaFuncSetCacheConfig(
+        device_multi_bit_programmable_bootstrap_keybundle_128<
+            InputTorus, params, FULLSM, true>,
+        cudaFuncCachePreferShared));
+    device_multi_bit_programmable_bootstrap_keybundle_128<InputTorus, params,
+                                                          FULLSM, true>
+        <<<grid_keybundle, thds, full_sm_keybundle, stream>>>(
+            lwe_array_in, lwe_input_indexes, keybundle_fft, bootstrapping_key,
+            lwe_dimension, glwe_dimension, polynomial_size, grouping_factor,
+            level_count, lwe_offset, chunk_size, keybundle_size_per_input,
+            d_mem, 0);
+  }
+  check_cuda_error(cudaGetLastError());
+}
+
 template <typename InputTorus, class params, bool is_first_iter>
 __host__ void execute_step_one_128(
     cudaStream_t stream, uint32_t gpu_index, __uint128_t const *lut_vector,
@@ -1200,4 +1293,96 @@ supports_cooperative_groups_on_multibit_programmable_bootstrap_128(
   }
 }
 
+// Noise tests variant: identical to
+// host_cg_multi_bit_programmable_bootstrap_128 but uses the noise-test
+// keybundle (runs_noise_test=true) instead of the standard one.
+template <typename InputTorus, class params>
+__host__ void host_cg_multi_bit_programmable_bootstrap_noise_tests_128(
+    cudaStream_t stream, uint32_t gpu_index, __uint128_t *lwe_array_out,
+    InputTorus const *lwe_output_indexes, __uint128_t const *lut_vector,
+    InputTorus const *lwe_array_in, InputTorus const *lwe_input_indexes,
+    __uint128_t const *bootstrapping_key,
+    pbs_buffer_128<InputTorus, MULTI_BIT> *buffer, uint32_t glwe_dimension,
+    uint32_t lwe_dimension, uint32_t polynomial_size, uint32_t grouping_factor,
+    uint32_t base_log, uint32_t level_count, uint32_t num_samples,
+    uint32_t num_many_lut, uint32_t lut_stride) {
+
+  auto lwe_chunk_size = buffer->lwe_chunk_size;
+
+  for (uint32_t lwe_offset = 0; lwe_offset < (lwe_dimension / grouping_factor);
+       lwe_offset += lwe_chunk_size) {
+
+    // Compute a keybundle with the noise-test kernel variant
+    // (runs_noise_test=true) to read precomputed modswitched values
+    execute_compute_keybundle_noise_tests_128<InputTorus, params>(
+        stream, gpu_index, lwe_array_in, lwe_input_indexes, bootstrapping_key,
+        buffer, num_samples, lwe_dimension, glwe_dimension, polynomial_size,
+        grouping_factor, level_count, lwe_offset);
+
+    execute_cg_external_product_loop_128<InputTorus, params>(
+        stream, gpu_index, lut_vector, lwe_array_in, lwe_input_indexes,
+        lwe_array_out, lwe_output_indexes, buffer, num_samples, lwe_dimension,
+        glwe_dimension, polynomial_size, grouping_factor, base_log, level_count,
+        lwe_offset, num_many_lut, lut_stride);
+  }
+}
+
+template <typename InputTorus, class params>
+__host__ void host_multi_bit_programmable_bootstrap_noise_tests_128(
+    cudaStream_t stream, uint32_t gpu_index, __uint128_t *lwe_array_out,
+    InputTorus const *lwe_output_indexes, __uint128_t const *lut_vector,
+    InputTorus const *lwe_array_in, InputTorus const *lwe_input_indexes,
+    __uint128_t const *bootstrapping_key,
+    pbs_buffer_128<InputTorus, MULTI_BIT> *buffer, uint32_t glwe_dimension,
+    uint32_t lwe_dimension, uint32_t polynomial_size, uint32_t grouping_factor,
+    uint32_t base_log, uint32_t level_count, uint32_t num_samples,
+    uint32_t num_many_lut, uint32_t lut_stride) {
+
+  auto lwe_chunk_size = buffer->lwe_chunk_size;
+
+  for (uint32_t lwe_offset = 0; lwe_offset < (lwe_dimension / grouping_factor);
+       lwe_offset += lwe_chunk_size) {
+
+    // Compute a keybundle with the noise-test kernel variant
+    // (runs_noise_test=true) to read precomputed modswitched values
+    execute_compute_keybundle_noise_tests_128<InputTorus, params>(
+        stream, gpu_index, lwe_array_in, lwe_input_indexes, bootstrapping_key,
+        buffer, num_samples, lwe_dimension, glwe_dimension, polynomial_size,
+        grouping_factor, level_count, lwe_offset);
+
+    // Accumulate (same as standard path)
+    uint64_t chunk_size =
+        std::min((uint32_t)lwe_chunk_size,
+                 (lwe_dimension / grouping_factor) - lwe_offset);
+    for (uint32_t j = 0; j < chunk_size; j++) {
+      bool is_first_iter = (j + lwe_offset) == 0;
+      bool is_last_iter =
+          (j + lwe_offset) + 1 == (lwe_dimension / grouping_factor);
+      if (is_first_iter) {
+        execute_step_one_128<InputTorus, params, true>(
+            stream, gpu_index, lut_vector, lwe_array_in, lwe_input_indexes,
+            buffer, num_samples, lwe_dimension, glwe_dimension, polynomial_size,
+            base_log, level_count);
+      } else {
+        execute_step_one_128<InputTorus, params, false>(
+            stream, gpu_index, lut_vector, lwe_array_in, lwe_input_indexes,
+            buffer, num_samples, lwe_dimension, glwe_dimension, polynomial_size,
+            base_log, level_count);
+      }
+
+      if (is_last_iter) {
+        execute_step_two_128<InputTorus, params, true>(
+            stream, gpu_index, lwe_array_out, lwe_output_indexes, buffer,
+            num_samples, glwe_dimension, polynomial_size, level_count, j,
+            num_many_lut, lut_stride);
+      } else {
+        execute_step_two_128<InputTorus, params, false>(
+            stream, gpu_index, lwe_array_out, lwe_output_indexes, buffer,
+            num_samples, glwe_dimension, polynomial_size, level_count, j,
+            num_many_lut, lut_stride);
+      }
+    }
+  }
+}
+
 #endif // PROGRAMMABLE_BOOTSTRAP_MULTIBIT_128_CUH

backends/tfhe-cuda-backend/cuda/src/pbs/programmable_bootstrap_tbc_multibit.cuh

@@ -795,6 +795,40 @@ __host__ void host_tbc_multi_bit_programmable_bootstrap_2_2_specialized(
       MultiBitTbcLaunchMode::SPECIALIZED_2_2);
 }
 
+// Noise tests variant: uses NOISE_TESTS keybundle mode for the keybundle step
+// while keeping the standard AUTO accumulate behaviour for the TBC loop.
+template <typename Torus, class params>
+__host__ void host_tbc_multi_bit_programmable_bootstrap_noise_tests(
+    cudaStream_t stream, uint32_t gpu_index, Torus *lwe_array_out,
+    Torus const *lwe_output_indexes, Torus const *lut_vector,
+    Torus const *lut_vector_indexes, Torus const *lwe_array_in,
+    Torus const *lwe_input_indexes, Torus const *bootstrapping_key,
+    pbs_buffer<Torus, MULTI_BIT> *buffer, uint32_t glwe_dimension,
+    uint32_t lwe_dimension, uint32_t polynomial_size, uint32_t grouping_factor,
+    uint32_t base_log, uint32_t level_count, uint32_t num_samples,
+    uint32_t num_many_lut, uint32_t lut_stride) {
+  cuda_set_device(gpu_index);
+
+  auto lwe_chunk_size = buffer->lwe_chunk_size;
+  for (uint32_t lwe_offset = 0; lwe_offset < (lwe_dimension / grouping_factor);
+       lwe_offset += lwe_chunk_size) {
+
+    // Keybundle with NOISE_TESTS mode; the TBC accumulate uses AUTO as usual
+    execute_compute_keybundle_noise_tests<Torus, params>(
+        stream, gpu_index, lwe_array_in, lwe_input_indexes, bootstrapping_key,
+        buffer, num_samples, lwe_dimension, glwe_dimension, polynomial_size,
+        grouping_factor, level_count, lwe_offset);
+
+    // Accumulate (unchanged from standard TBC path)
+    execute_tbc_external_product_loop<Torus, params>(
+        stream, gpu_index, lut_vector, lut_vector_indexes, lwe_array_in,
+        lwe_input_indexes, lwe_array_out, lwe_output_indexes, buffer,
+        num_samples, lwe_dimension, glwe_dimension, polynomial_size,
+        grouping_factor, base_log, level_count, lwe_offset, num_many_lut,
+        lut_stride, MultiBitTbcLaunchMode::AUTO);
+  }
+}
+
 template <typename Torus>
 bool supports_distributed_shared_memory_on_multibit_programmable_bootstrap(
     uint32_t polynomial_size, uint32_t max_shared_memory) {

backends/tfhe-cuda-backend/cuda/src/trivium/trivium.cu

@@ -2,18 +2,14 @@
 #include "trivium.cuh"
 
 uint64_t scratch_cuda_trivium_generate_keystream_64_async(
-    CudaStreamsFFI streams, int8_t **mem_ptr, uint32_t glwe_dimension,
-    uint32_t polynomial_size, uint32_t lwe_dimension, uint32_t ks_level,
-    uint32_t ks_base_log, uint32_t pbs_level, uint32_t pbs_base_log,
-    uint32_t grouping_factor, uint32_t message_modulus, uint32_t carry_modulus,
-    PBS_TYPE pbs_type, bool allocate_gpu_memory,
-    PBS_MS_REDUCTION_T noise_reduction_type, uint32_t num_inputs) {
+    CudaStreamsFFI streams, int8_t **mem_ptr,
+    CudaLweBootstrapKeyParamsFFI bsk_params, uint32_t ks_level,
+    uint32_t ks_base_log, uint32_t message_modulus, uint32_t carry_modulus,
+    bool allocate_gpu_memory, PBS_MS_REDUCTION_T noise_reduction_type,
+    uint32_t num_inputs) {
 
-  int_radix_params params(pbs_type, glwe_dimension, polynomial_size,
-                          glwe_dimension * polynomial_size, lwe_dimension,
-                          ks_level, ks_base_log, pbs_level, pbs_base_log,
-                          grouping_factor, message_modulus, carry_modulus,
-                          noise_reduction_type);
+  int_radix_params params(bsk_params, ks_level, ks_base_log, message_modulus,
+                          carry_modulus, noise_reduction_type);
 
   return scratch_cuda_trivium_encrypt<uint64_t>(
       CudaStreams(streams), (int_trivium_buffer<uint64_t> **)mem_ptr, params,

backends/tfhe-cuda-backend/cuda/src/zk/zk.cuh

@@ -119,71 +119,73 @@ __host__ void host_expand_without_verification(
       streams.stream(0), streams.gpu_index(0), true);
 
   if (mem_ptr->expand_kind == EXPAND_KIND::NO_CASTING) {
+    // This path is added to mimic the CPU fallback behaviour for the no_casting
+    // expand, which is needed for the noise sanity checks.
     host_lwe_expand<Torus, params>(streams.stream(0), streams.gpu_index(0),
                                    lwe_array_out, d_expand_jobs, num_lwes);
-    return;
-  }
 
-  host_lwe_expand<Torus, params>(streams.stream(0), streams.gpu_index(0),
-                                 expanded_lwes, d_expand_jobs, num_lwes);
+  } else {
+    // This is our default path for the expand with casting if needed.
+    host_lwe_expand<Torus, params>(streams.stream(0), streams.gpu_index(0),
+                                   expanded_lwes, d_expand_jobs, num_lwes);
 
-  auto lwe_array_input = expanded_lwes;
-  auto ksks = casting_keys;
-  auto message_and_carry_extract_luts = mem_ptr->message_and_carry_extract_luts;
+    auto lwe_array_input = expanded_lwes;
+    auto ksks = casting_keys;
+    auto message_and_carry_extract_luts =
+        mem_ptr->message_and_carry_extract_luts;
 
-  auto lut = mem_ptr->message_and_carry_extract_luts;
-  if (casting_key_type == SMALL_TO_BIG) {
-    if (mem_ptr->expand_kind == EXPAND_KIND::SANITY_CHECK) {
-      PANIC("SANITY_CHECK not supported for SMALL_TO_BIG casting");
+    auto lut = mem_ptr->message_and_carry_extract_luts;
+    if (casting_key_type == SMALL_TO_BIG) {
+      if (mem_ptr->expand_kind == EXPAND_KIND::SANITY_CHECK) {
+        PANIC("SANITY_CHECK not supported for SMALL_TO_BIG casting");
+      }
+      // Keyswitch from small to big key if needed
+      auto ksed_small_to_big_expanded_lwes =
+          mem_ptr->tmp_ksed_small_to_big_expanded_lwes;
+      std::vector<Torus *> lwe_trivial_indexes_vec =
+          lut->lwe_trivial_indexes_vec;
+
+      auto casting_params = mem_ptr->casting_params;
+      auto casting_output_dimension = casting_params.big_lwe_dimension;
+      auto casting_input_dimension = casting_params.small_lwe_dimension;
+      auto casting_ks_level = casting_params.ks_level;
+      auto casting_ks_base_log = casting_params.ks_base_log;
+
+      // apply keyswitch to BIG
+      execute_keyswitch_async<Torus>(
+          streams.get_ith(0), ksed_small_to_big_expanded_lwes,
+          lwe_trivial_indexes_vec[0], expanded_lwes, lwe_trivial_indexes_vec[0],
+          casting_keys, casting_input_dimension, casting_output_dimension,
+          casting_ks_base_log, casting_ks_level, num_lwes,
+          lut->using_trivial_lwe_indexes, lut->ks_tmp_buf_vec);
+
+      // In this case, the next keyswitch will use the compute ksk
+      ksks = compute_ksks;
+      lwe_array_input = ksed_small_to_big_expanded_lwes;
     }
-    // Keyswitch from small to big key if needed
-    auto ksed_small_to_big_expanded_lwes =
-        mem_ptr->tmp_ksed_small_to_big_expanded_lwes;
-    std::vector<Torus *> lwe_trivial_indexes_vec = lut->lwe_trivial_indexes_vec;
 
-    auto casting_params = mem_ptr->casting_params;
-    auto casting_output_dimension = casting_params.big_lwe_dimension;
-    auto casting_input_dimension = casting_params.small_lwe_dimension;
-    auto casting_ks_level = casting_params.ks_level;
-    auto casting_ks_base_log = casting_params.ks_base_log;
+    // Apply LUT
+    cuda_memset_async(lwe_array_out, 0,
+                      safe_mul_sizeof<Torus>((size_t)(lwe_dimension + 1),
+                                             (size_t)num_lwes, (size_t)2),
+                      streams.stream(0), streams.gpu_index(0));
+    CudaRadixCiphertextFFI output;
+    into_radix_ciphertext(&output, lwe_array_out, 2 * num_lwes, lwe_dimension);
+    CudaRadixCiphertextFFI input;
+    into_radix_ciphertext(&input, lwe_array_input, 2 * num_lwes, lwe_dimension);
+    // This is a special case only for our noise sanity checks
+    // If we are doing a SANITY_CHECK expand, we just apply the identity LUT
+    // This replicates the CPU fallback behaviour of the casting expand
+    auto final_lut = (mem_ptr->expand_kind == EXPAND_KIND::SANITY_CHECK
+                          ? mem_ptr->identity_lut
+                          : message_and_carry_extract_luts);
 
-    // apply keyswitch to BIG
-    execute_keyswitch_async<Torus>(
-        streams.get_ith(0), ksed_small_to_big_expanded_lwes,
-        lwe_trivial_indexes_vec[0], expanded_lwes, lwe_trivial_indexes_vec[0],
-        casting_keys, casting_input_dimension, casting_output_dimension,
-        casting_ks_base_log, casting_ks_level, num_lwes,
-        lut->using_trivial_lwe_indexes, lut->ks_tmp_buf_vec);
-
-    // In this case, the next keyswitch will use the compute ksk
-    ksks = compute_ksks;
-    lwe_array_input = ksed_small_to_big_expanded_lwes;
-  }
-
-  // Apply LUT
-  cuda_memset_async(lwe_array_out, 0,
-                    safe_mul_sizeof<Torus>((size_t)(lwe_dimension + 1),
-                                           (size_t)num_lwes, (size_t)2),
-                    streams.stream(0), streams.gpu_index(0));
-  CudaRadixCiphertextFFI output;
-  into_radix_ciphertext(&output, lwe_array_out, 2 * num_lwes, lwe_dimension);
-  CudaRadixCiphertextFFI input;
-  into_radix_ciphertext(&input, lwe_array_input, 2 * num_lwes, lwe_dimension);
-  // This is a special case only for our noise sanity checks
-  // If we are doing a SANITY_CHECK expand, we just apply the identity LUT
-  // This replicates the CPU fallback behaviour of the casting expand
-  if (mem_ptr->expand_kind == EXPAND_KIND::SANITY_CHECK) {
     integer_radix_apply_univariate_lookup_table<Torus>(
-        streams, &output, &input, bsks, ksks, mem_ptr->identity_lut,
-        2 * num_lwes);
-    return;
-  }
+        streams, &output, &input, bsks, ksks, final_lut, 2 * num_lwes);
 
-  integer_radix_apply_univariate_lookup_table<Torus>(
-      streams, &output, &input, bsks, ksks, message_and_carry_extract_luts,
-      2 * num_lwes);
-  release_cpu_radix_ciphertext_async(&input);
-  release_cpu_radix_ciphertext_async(&output);
+    release_cpu_radix_ciphertext_async(&input);
+    release_cpu_radix_ciphertext_async(&output);
+  }
   compact_lwe_lists.release();
 }
 

backends/tfhe-cuda-backend/get_os_name.sh

@@ -1,3 +0,0 @@
-#!/usr/bin/env bash
-
-cat /etc/os-release | grep "\<NAME\>" | sed "s/NAME=\"//g" | sed "s/\"//g"