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1 Commits

Author SHA1 Message Date
Agnes Leroy
5e85a22050 chore(gpu): remove sub streams from overflowing subtraction 2025-09-22 09:53:08 +02:00
407 changed files with 10902 additions and 25449 deletions

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@@ -7,8 +7,6 @@ self-hosted-runner:
- large_ubuntu_16
- large_ubuntu_16-22.04
- v80-desktop
- v80-marais
- v80-couperin
# Configuration variables in array of strings defined in your repository or
# organization. `null` means disabling configuration variables check.
# Empty array means no configuration variable is allowed.

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@@ -66,9 +66,14 @@ jobs:
- name: Checkout tfhe-rs
uses: actions/checkout@08c6903cd8c0fde910a37f88322edcfb5dd907a8
with:
persist-credentials: 'true' # Needed to pull lfs data
persist-credentials: 'false'
token: ${{ env.CHECKOUT_TOKEN }}
- name: Install latest stable
uses: dtolnay/rust-toolchain@e97e2d8cc328f1b50210efc529dca0028893a2d9 # zizmor: ignore[stale-action-refs] this action doesn't create releases
with:
toolchain: stable
# Cache key is an aggregated hash of lfs files hashes
- name: Get LFS data sha
id: hash-lfs-data
@@ -78,7 +83,7 @@ jobs:
- name: Retrieve data from cache
id: retrieve-data-cache
uses: actions/cache/restore@0057852bfaa89a56745cba8c7296529d2fc39830 #v4.3.0
uses: actions/cache/restore@0400d5f644dc74513175e3cd8d07132dd4860809 #v4.2.4
with:
path: |
utils/tfhe-backward-compat-data/**/*.cbor
@@ -90,16 +95,6 @@ jobs:
run: |
make pull_backward_compat_data
# Pull token was stored by action/checkout to be used by lfs, we don't need it anymore
- name: Remove git credentials
run: |
git config --local --unset-all http.https://github.com/.extraheader
- name: Install latest stable
uses: dtolnay/rust-toolchain@e97e2d8cc328f1b50210efc529dca0028893a2d9 # zizmor: ignore[stale-action-refs] this action doesn't create releases
with:
toolchain: stable
- name: Run backward compatibility tests
run: |
make test_backward_compatibility_ci
@@ -107,7 +102,7 @@ jobs:
- name: Store data in cache
if: steps.retrieve-data-cache.outputs.cache-hit != 'true'
continue-on-error: true
uses: actions/cache/save@0057852bfaa89a56745cba8c7296529d2fc39830 #v4.3.0
uses: actions/cache/save@0400d5f644dc74513175e3cd8d07132dd4860809 #v4.2.4
with:
path: |
utils/tfhe-backward-compat-data/**/*.cbor

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@@ -217,7 +217,7 @@ jobs:
- name: Node cache restoration
id: node-cache
uses: actions/cache/restore@0057852bfaa89a56745cba8c7296529d2fc39830 #v4.3.0
uses: actions/cache/restore@0400d5f644dc74513175e3cd8d07132dd4860809 #v4.2.4
with:
path: |
~/.nvm
@@ -230,7 +230,7 @@ jobs:
make install_node
- name: Node cache save
uses: actions/cache/save@0057852bfaa89a56745cba8c7296529d2fc39830 #v4.3.0
uses: actions/cache/save@0400d5f644dc74513175e3cd8d07132dd4860809 #v4.2.4
if: steps.node-cache.outputs.cache-hit != 'true'
with:
path: |

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@@ -107,7 +107,6 @@ jobs:
group: ${{ github.workflow_ref }}${{ github.ref == 'refs/heads/main' && github.sha || '' }}
cancel-in-progress: ${{ github.ref != 'refs/heads/main' }}
runs-on: ${{ needs.setup-instance.outputs.runner-name }}
timeout-minutes: 480 # 8 hours
steps:
- name: Checkout tfhe-rs
uses: actions/checkout@08c6903cd8c0fde910a37f88322edcfb5dd907a8

View File

@@ -78,7 +78,7 @@ jobs:
- name: Node cache restoration
id: node-cache
uses: actions/cache/restore@0057852bfaa89a56745cba8c7296529d2fc39830 #v4.3.0
uses: actions/cache/restore@0400d5f644dc74513175e3cd8d07132dd4860809 #v4.2.4
with:
path: |
~/.nvm
@@ -91,7 +91,7 @@ jobs:
make install_node
- name: Node cache save
uses: actions/cache/save@0057852bfaa89a56745cba8c7296529d2fc39830 #v4.3.0
uses: actions/cache/save@0400d5f644dc74513175e3cd8d07132dd4860809 #v4.2.4
if: steps.node-cache.outputs.cache-hit != 'true'
with:
path: |

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@@ -3,16 +3,6 @@ name: benchmark_core_crypto
on:
workflow_dispatch:
inputs:
param_type:
description: "Parameters type"
type: choice
default: classical
options:
- classical
- multi_bit
- both
schedule:
# Weekly benchmarks will be triggered each Saturday at 5a.m.
- cron: '0 5 * * 6'
@@ -32,38 +22,8 @@ env:
permissions: {}
jobs:
prepare-matrix:
name: benchmark_core_crypto/prepare-matrix
runs-on: ubuntu-latest
if: github.event_name != 'schedule' ||
(github.event_name == 'schedule' && github.repository == 'zama-ai/tfhe-rs')
outputs:
param_type: ${{ steps.set_param_type.outputs.param_type }}
steps:
- name: Set parameters types
if: github.event_name == 'workflow_dispatch'
run: |
if [[ "${INPUTS_PARAM_TYPE}" == "both" ]]; then
echo "PARAM_TYPE=[\"classical\", \"multi_bit\"]" >> "${GITHUB_ENV}"
else
echo "PARAM_TYPE=[\"${INPUTS_PARAM_TYPE}\"]" >> "${GITHUB_ENV}"
fi
env:
INPUTS_PARAM_TYPE: ${{ inputs.param_type }}
- name: Default parameters type
if: github.event_name != 'workflow_dispatch'
run: |
echo "PARAM_TYPE=[\"classical\"]" >> "${GITHUB_ENV}"
- name: Set parameters types output
id: set_param_type
run: | # zizmor: ignore[template-injection] this env variable is safe
echo "param_type=${{ toJSON(env.PARAM_TYPE) }}" >> "${GITHUB_OUTPUT}"
setup-instance:
name: benchmark_core_crypto/setup-instance
needs: prepare-matrix
runs-on: ubuntu-latest
if: github.event_name != 'schedule' ||
(github.event_name == 'schedule' && github.repository == 'zama-ai/tfhe-rs')
@@ -83,16 +43,11 @@ jobs:
core-crypto-benchmarks:
name: benchmark_core_crypto/core-crypto-benchmarks
needs: [ prepare-matrix, setup-instance ]
needs: setup-instance
runs-on: ${{ needs.setup-instance.outputs.runner-name }}
concurrency:
group: ${{ github.workflow_ref }}
cancel-in-progress: ${{ github.ref != 'refs/heads/main' }}
timeout-minutes: 1440 # 24 hours
strategy:
max-parallel: 1
matrix:
param_type: ${{ fromJSON(needs.prepare-matrix.outputs.param_type) }}
steps:
- name: Checkout tfhe-rs repo with tags
uses: actions/checkout@08c6903cd8c0fde910a37f88322edcfb5dd907a8
@@ -123,8 +78,6 @@ jobs:
make bench_pbs
make bench_pbs128
make bench_ks
env:
BENCH_PARAM_TYPE: ${{ matrix.param_type }}
- name: Parse results
run: |
@@ -143,7 +96,7 @@ jobs:
- name: Upload parsed results artifact
uses: actions/upload-artifact@ea165f8d65b6e75b540449e92b4886f43607fa02
with:
name: ${{ github.sha }}_core_crypto_${{ matrix.param_type }}_pbs
name: ${{ github.sha }}_core_crypto
path: ${{ env.RESULTS_FILENAME }}
- name: Checkout Slab repo

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@@ -16,7 +16,7 @@ permissions: {}
jobs:
hlapi-benchmarks-hpu:
name: Execute HLAPI benchmarks for HPU backend
runs-on: v80-marais
runs-on: v80-desktop
concurrency:
group: ${{ github.workflow }}_${{ github.ref }}
cancel-in-progress: ${{ github.ref != 'refs/heads/main' }}
@@ -60,14 +60,11 @@ jobs:
persist-credentials: 'false'
token: ${{ secrets.REPO_CHECKOUT_TOKEN }}
- name: Select HPU board
run: |
echo "V80_PCIE_DEV=24" >> "${GITHUB_ENV}"
echo "V80_SERIAL_NUMBER=XFL12NWY3ZKG" >> "${GITHUB_ENV}"
- name: Run benchmarks
run: |
make pull_hpu_files
export V80_SERIAL_NUMBER=XFL12E4XJXWK
source /opt/xilinx/Vivado/2024.2/settings64.sh
make bench_hlapi_erc20_hpu
make bench_hlapi_hpu

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@@ -29,7 +29,7 @@ permissions: {}
jobs:
prepare-matrix:
name: Prepare operations matrix
runs-on: v80-marais
runs-on: v80-desktop
outputs:
bench_type: ${{ steps.set_bench_type.outputs.bench_type }}
steps:
@@ -48,17 +48,17 @@ jobs:
if: github.event_name != 'workflow_dispatch'
run: |
echo "BENCH_TYPE=[\"latency\"]" >> "${GITHUB_ENV}"
- name: Set benchmark types output
id: set_bench_type
run: | # zizmor: ignore[template-injection] this env variable is safe
echo "bench_type=${{ toJSON(env.BENCH_TYPE) }}" >> "${GITHUB_OUTPUT}"
integer-benchmarks-hpu:
name: benchmark_hpu_integer/integer-benchmarks-hpu
needs: prepare-matrix
runs-on: v80-marais
runs-on: v80-desktop
concurrency:
group: ${{ github.workflow }}_${{ github.ref }}
cancel-in-progress: ${{ github.ref != 'refs/heads/main' }}
@@ -111,15 +111,11 @@ jobs:
run: |
echo "FAST_BENCH=FALSE" >> "${GITHUB_ENV}"
- name: Select HPU board
run: |
echo "V80_PCIE_DEV=24" >> "${GITHUB_ENV}"
echo "V80_SERIAL_NUMBER=XFL12NWY3ZKG" >> "${GITHUB_ENV}"
- name: Run benchmarks
run: |
echo "${V80_PCIE_DEV} ${V80_SERIAL_NUMBER}"
make pull_hpu_files
export V80_SERIAL_NUMBER=XFL12E4XJXWK
source /opt/xilinx/Vivado/2024.2/settings64.sh
make BENCH_TYPE="${BENCH_TYPE}" bench_integer_hpu
env:
BENCH_TYPE: ${{ matrix.bench_type }}

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@@ -44,7 +44,7 @@ jobs:
custom-env: ${{ steps.get_custom_env.outputs.custom_env }}
steps:
- name: Checkout tfhe-rs repo
uses: actions/checkout@08c6903cd8c0fde910a37f88322edcfb5dd907a8
uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683
with:
persist-credentials: 'false'
token: ${{ secrets.REPO_CHECKOUT_TOKEN }}
@@ -132,7 +132,7 @@ jobs:
gcc: 11
steps:
- name: Checkout tfhe-rs repo
uses: actions/checkout@08c6903cd8c0fde910a37f88322edcfb5dd907a8
uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683
with:
fetch-depth: 0
persist-credentials: 'false'
@@ -159,7 +159,7 @@ jobs:
command: ${{ fromJson(needs.prepare-benchmarks.outputs.commands) }}
steps:
- name: Checkout tfhe-rs repo with tags
uses: actions/checkout@08c6903cd8c0fde910a37f88322edcfb5dd907a8
uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683
with:
fetch-depth: 0
persist-credentials: 'false'
@@ -213,7 +213,7 @@ jobs:
toolchain: nightly
- name: Checkout Slab repo
uses: actions/checkout@08c6903cd8c0fde910a37f88322edcfb5dd907a8
uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683
with:
repository: zama-ai/slab
path: slab

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@@ -117,7 +117,7 @@ jobs:
- name: Node cache restoration
id: node-cache
uses: actions/cache/restore@0057852bfaa89a56745cba8c7296529d2fc39830 #v4.3.0
uses: actions/cache/restore@0400d5f644dc74513175e3cd8d07132dd4860809 #v4.2.4
with:
path: |
~/.nvm
@@ -130,7 +130,7 @@ jobs:
make install_node
- name: Node cache save
uses: actions/cache/save@0057852bfaa89a56745cba8c7296529d2fc39830 #v4.3.0
uses: actions/cache/save@0400d5f644dc74513175e3cd8d07132dd4860809 #v4.2.4
if: steps.node-cache.outputs.cache-hit != 'true'
with:
path: |

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@@ -1,6 +1,4 @@
# Run cargo audit
name: cargo_audit
on:
workflow_dispatch:
schedule:

View File

@@ -18,95 +18,17 @@ permissions:
contents: read
jobs:
prepare-parallel-pcc-matrix:
name: cargo_build/prepare-parallel-pcc-matrix
runs-on: ubuntu-latest
outputs:
matrix_command: ${{ steps.set-pcc-commands-matrix.outputs.commands }}
steps:
- uses: actions/checkout@08c6903cd8c0fde910a37f88322edcfb5dd907a8
with:
persist-credentials: "false"
token: ${{ env.CHECKOUT_TOKEN }}
# Fetch all the Make recipes that start with `pcc_batch_`
- name: Set pcc commands matrix
id: set-pcc-commands-matrix
run: |
COMMANDS=$(grep -oE '^pcc_batch_[^:]*:' Makefile | sed 's/:/\"/; s/^/\"/' | paste -sd,)
echo "commands=[${COMMANDS}]" >> "$GITHUB_OUTPUT"
parallel-pcc-cpu:
name: cargo_build/parallel-pcc-cpu
needs: prepare-parallel-pcc-matrix
runs-on: large_ubuntu_16
strategy:
matrix:
command: ${{fromJson(needs.prepare-parallel-pcc-matrix.outputs.matrix_command)}}
fail-fast: false
steps:
- name: Checkout tfhe-rs repo
uses: actions/checkout@08c6903cd8c0fde910a37f88322edcfb5dd907a8
with:
persist-credentials: 'false'
token: ${{ env.CHECKOUT_TOKEN }}
- name: Install latest stable
uses: dtolnay/rust-toolchain@e97e2d8cc328f1b50210efc529dca0028893a2d9 # zizmor: ignore[stale-action-refs] this action doesn't create releases
with:
toolchain: stable
- name: Run pcc checks batch
run: |
make "${COMMAND}"
env:
COMMAND: ${{ matrix.command }}
pcc-hpu:
name: cargo_build/pcc-hpu
runs-on: large_ubuntu_16
steps:
- uses: actions/checkout@08c6903cd8c0fde910a37f88322edcfb5dd907a8
with:
persist-credentials: 'false'
token: ${{ env.CHECKOUT_TOKEN }}
- name: Install latest stable
uses: dtolnay/rust-toolchain@e97e2d8cc328f1b50210efc529dca0028893a2d9 # zizmor: ignore[stale-action-refs] this action doesn't create releases
with:
toolchain: stable
- name: Run Hpu pcc checks
run: |
make pcc_hpu
build-tfhe-full:
name: cargo_build/build-tfhe-full
cargo-builds:
name: cargo_build/cargo-builds (bpr)
runs-on: ${{ matrix.os }}
strategy:
matrix:
# GitHub macos-latest are now M1 macs, so use ours, we limit what runs so it will be fast
# even with a few PRs
os: [large_ubuntu_16, macos-latest-xlarge, large_windows_16_latest]
os: [large_ubuntu_16, macos-latest, windows-latest]
fail-fast: false
steps:
- uses: actions/checkout@08c6903cd8c0fde910a37f88322edcfb5dd907a8
with:
persist-credentials: 'false'
token: ${{ env.CHECKOUT_TOKEN }}
- name: Install latest stable
uses: dtolnay/rust-toolchain@e97e2d8cc328f1b50210efc529dca0028893a2d9 # zizmor: ignore[stale-action-refs] this action doesn't create releases
with:
toolchain: stable
- name: Build Release tfhe full
run: |
make build_tfhe_full
build:
name: cargo_build/build
runs-on: large_ubuntu_16
steps:
- uses: actions/checkout@08c6903cd8c0fde910a37f88322edcfb5dd907a8
with:
@@ -119,6 +41,7 @@ jobs:
toolchain: stable
- name: Install and run newline linter checks
if: ${{ contains(matrix.os, 'ubuntu') }}
run: |
wget https://github.com/fernandrone/linelint/releases/download/0.0.6/linelint-linux-amd64
echo "16b70fb7b471d6f95cbdc0b4e5dc2b0ac9e84ba9ecdc488f7bdf13df823aca4b linelint-linux-amd64" > checksum
@@ -127,93 +50,60 @@ jobs:
mv linelint-linux-amd64 /usr/local/bin/linelint
make check_newline
- name: Run pcc checks
if: ${{ contains(matrix.os, 'ubuntu') }}
run: |
make pcc
- name: Build tfhe-csprng
if: ${{ contains(matrix.os, 'ubuntu') }}
run: |
make build_tfhe_csprng
- name: Build with MSRV
if: ${{ contains(matrix.os, 'ubuntu') }}
run: |
make build_tfhe_msrv
- name: Build coverage tests
run: |
make build_tfhe_coverage
build-layers:
name: cargo_build/build-layers
runs-on: large_ubuntu_16
steps:
- uses: actions/checkout@08c6903cd8c0fde910a37f88322edcfb5dd907a8
with:
persist-credentials: 'false'
token: ${{ env.CHECKOUT_TOKEN }}
- name: Install latest stable
uses: dtolnay/rust-toolchain@e97e2d8cc328f1b50210efc529dca0028893a2d9 # zizmor: ignore[stale-action-refs] this action doesn't create releases
with:
toolchain: stable
- name: Build Release core
if: ${{ contains(matrix.os, 'ubuntu') }}
run: |
make build_core AVX512_SUPPORT=ON
make build_core_experimental AVX512_SUPPORT=ON
- name: Build Release boolean
if: ${{ contains(matrix.os, 'ubuntu') }}
run: |
make build_boolean
- name: Build Release shortint
if: ${{ contains(matrix.os, 'ubuntu') }}
run: |
make build_shortint
- name: Build Release integer
if: ${{ contains(matrix.os, 'ubuntu') }}
run: |
make build_integer
build-c-api:
name: cargo_build/build-c-api
runs-on: large_ubuntu_16
steps:
- uses: actions/checkout@08c6903cd8c0fde910a37f88322edcfb5dd907a8
with:
persist-credentials: 'false'
token: ${{ env.CHECKOUT_TOKEN }}
- name: Install latest stable
uses: dtolnay/rust-toolchain@e97e2d8cc328f1b50210efc529dca0028893a2d9 # zizmor: ignore[stale-action-refs] this action doesn't create releases
with:
toolchain: stable
- name: Build Release tfhe full
run: |
make build_tfhe_full
- name: Build Release c_api
if: ${{ contains(matrix.os, 'ubuntu') }}
run: |
make build_c_api
- name: Build coverage tests
if: ${{ contains(matrix.os, 'ubuntu') }}
run: |
make build_tfhe_coverage
- name: Run Hpu pcc checks
if: ${{ contains(matrix.os, 'ubuntu') }}
run: |
make pcc_hpu
# The wasm build check is a bit annoying to set-up here and is done during the tests in
# aws_tfhe_tests.yml
cargo-builds:
name: cargo_build/cargo-builds (bpr)
needs: [ parallel-pcc-cpu, pcc-hpu, build-tfhe-full, build, build-layers, build-c-api ]
if: ${{ always() }}
runs-on: ubuntu-latest
steps:
- name: Check all builds success
if: needs.parallel-pcc-cpu.result == 'success' &&
needs.pcc-hpu.result == 'success' &&
needs.build-tfhe-full.result == 'success' &&
needs.build.result == 'success' &&
needs.build-layers.result == 'success' &&
needs.build-c-api.result == 'success'
run: |
echo "All tfhe-rs build checks passed"
- name: Check builds failure
if: needs.parallel-pcc-cpu.result != 'success' ||
needs.pcc-hpu.result != 'success' ||
needs.build-tfhe-full.result != 'success' ||
needs.build.result != 'success' ||
needs.build-layers.result != 'success' ||
needs.build-c-api.result != 'success'
run: |
echo "Some tfhe-rs build checks failed"
exit 1

View File

@@ -42,7 +42,7 @@ jobs:
GH_TOKEN: ${{ env.CHECKOUT_TOKEN }}
- name: Ensure SHA pinned actions
uses: zgosalvez/github-actions-ensure-sha-pinned-actions@9e9574ef04ea69da568d6249bd69539ccc704e74 # v4.0.0
uses: zgosalvez/github-actions-ensure-sha-pinned-actions@fc87bb5b5a97953d987372e74478de634726b3e5 # v3.0.25
with:
allowlist: |
slsa-framework/slsa-github-generator

View File

@@ -193,7 +193,7 @@ jobs:
uses: foundry-rs/foundry-toolchain@82dee4ba654bd2146511f85f0d013af94670c4de
- name: Cache cargo
uses: actions/cache@0057852bfaa89a56745cba8c7296529d2fc39830 # v4.3.0
uses: actions/cache@0400d5f644dc74513175e3cd8d07132dd4860809 # v4.2.4
with:
path: |
~/.cargo/registry
@@ -210,7 +210,7 @@ jobs:
password: ${{ secrets.GITHUB_TOKEN }}
- name: Login to Chainguard Registry
uses: docker/login-action@184bdaa0721073962dff0199f1fb9940f07167d1 # v3.5.0
uses: docker/login-action@9780b0c442fbb1117ed29e0efdff1e18412f7567 # v3.3.0
with:
registry: cgr.dev
username: ${{ secrets.CGR_USERNAME }}

View File

@@ -101,12 +101,6 @@ jobs:
- name: Prepare package
run: |
cargo package -p tfhe-cuda-backend
- uses: actions/upload-artifact@ea165f8d65b6e75b540449e92b4886f43607fa02 # v4.6.2
with:
name: crate-tfhe-cuda-backend
path: target/package/*.crate
- name: generate hash
id: hash
run: cd target/package && echo "hash=$(sha256sum ./*.crate | base64 -w0)" >> "${GITHUB_OUTPUT}"
@@ -175,12 +169,6 @@ jobs:
env:
GCC_VERSION: ${{ matrix.gcc }}
- name: Download artifact
uses: actions/download-artifact@634f93cb2916e3fdff6788551b99b062d0335ce0 # v5.0.0
with:
name: crate-tfhe-cuda-backend
path: target/package
- name: Authenticate on registry
uses: rust-lang/crates-io-auth-action@e919bc7605cde86df457cf5b93c5e103838bd879 # v1.0.1
id: auth

View File

@@ -24,13 +24,6 @@ jobs:
with:
package-name: "tfhe-hpu-backend"
dry-run: ${{ inputs.dry_run }}
permissions:
# Needed to detect the GitHub Actions environment
actions: read
# Needed to create the provenance via GitHub OIDC
id-token: write
# Needed to upload assets/artifacts
contents: write
secrets:
BOT_USERNAME: ${{ secrets.BOT_USERNAME }}
SLACK_CHANNEL: ${{ secrets.SLACK_CHANNEL }}

View File

@@ -42,13 +42,6 @@ jobs:
with:
package-name: "tfhe"
dry-run: ${{ inputs.dry_run }}
permissions:
# Needed to detect the GitHub Actions environment
actions: read
# Needed to create the provenance via GitHub OIDC
id-token: write
# Needed to upload assets/artifacts
contents: write
secrets:
BOT_USERNAME: ${{ secrets.BOT_USERNAME }}
SLACK_CHANNEL: ${{ secrets.SLACK_CHANNEL }}
@@ -85,7 +78,7 @@ jobs:
- name: Publish web package
if: ${{ inputs.push_web_package }}
uses: JS-DevTools/npm-publish@7f8fe47b3bea1be0c3aec2b717c5ec1f3e03410b
uses: JS-DevTools/npm-publish@19c28f1ef146469e409470805ea4279d47c3d35c
with:
token: ${{ secrets.NPM_TOKEN }}
package: tfhe/pkg/package.json
@@ -103,7 +96,7 @@ jobs:
- name: Publish Node package
if: ${{ inputs.push_node_package }}
uses: JS-DevTools/npm-publish@7f8fe47b3bea1be0c3aec2b717c5ec1f3e03410b
uses: JS-DevTools/npm-publish@19c28f1ef146469e409470805ea4279d47c3d35c
with:
token: ${{ secrets.NPM_TOKEN }}
package: tfhe/pkg/package.json

View File

@@ -17,13 +17,6 @@ jobs:
with:
package-name: "tfhe-csprng"
dry-run: ${{ inputs.dry_run }}
permissions:
# Needed to detect the GitHub Actions environment
actions: read
# Needed to create the provenance via GitHub OIDC
id-token: write
# Needed to upload assets/artifacts
contents: write
secrets:
BOT_USERNAME: ${{ secrets.BOT_USERNAME }}
SLACK_CHANNEL: ${{ secrets.SLACK_CHANNEL }}

View File

@@ -25,13 +25,6 @@ jobs:
with:
package-name: "tfhe-fft"
dry-run: ${{ inputs.dry_run }}
permissions:
# Needed to detect the GitHub Actions environment
actions: read
# Needed to create the provenance via GitHub OIDC
id-token: write
# Needed to upload assets/artifacts
contents: write
secrets:
BOT_USERNAME: ${{ secrets.BOT_USERNAME }}
SLACK_CHANNEL: ${{ secrets.SLACK_CHANNEL }}

View File

@@ -25,13 +25,6 @@ jobs:
with:
package-name: "tfhe-ntt"
dry-run: ${{ inputs.dry_run }}
permissions:
# Needed to detect the GitHub Actions environment
actions: read
# Needed to create the provenance via GitHub OIDC
id-token: write
# Needed to upload assets/artifacts
contents: write
secrets:
BOT_USERNAME: ${{ secrets.BOT_USERNAME }}
SLACK_CHANNEL: ${{ secrets.SLACK_CHANNEL }}

View File

@@ -24,13 +24,6 @@ jobs:
with:
package-name: "tfhe-versionable-derive"
dry-run: ${{ inputs.dry_run }}
permissions:
# Needed to detect the GitHub Actions environment
actions: read
# Needed to create the provenance via GitHub OIDC
id-token: write
# Needed to upload assets/artifacts
contents: write
secrets:
BOT_USERNAME: ${{ secrets.BOT_USERNAME }}
SLACK_CHANNEL: ${{ secrets.SLACK_CHANNEL }}
@@ -46,13 +39,6 @@ jobs:
with:
package-name: "tfhe-versionable"
dry-run: ${{ inputs.dry_run }}
permissions:
# Needed to detect the GitHub Actions environment
actions: read
# Needed to create the provenance via GitHub OIDC
id-token: write
# Needed to upload assets/artifacts
contents: write
secrets:
BOT_USERNAME: ${{ secrets.BOT_USERNAME }}
SLACK_CHANNEL: ${{ secrets.SLACK_CHANNEL }}

View File

@@ -24,13 +24,6 @@ jobs:
with:
package-name: "tfhe-zk-pok"
dry-run: ${{ inputs.dry_run }}
permissions:
# Needed to detect the GitHub Actions environment
actions: read
# Needed to create the provenance via GitHub OIDC
id-token: write
# Needed to upload assets/artifacts
contents: write
secrets:
BOT_USERNAME: ${{ secrets.BOT_USERNAME }}
SLACK_CHANNEL: ${{ secrets.SLACK_CHANNEL }}

View File

@@ -24,7 +24,7 @@ exclude = [
]
[workspace.dependencies]
aligned-vec = { version = "0.6", default-features = false }
bytemuck = "<1.24"
bytemuck = "1.14.3"
dyn-stack = { version = "0.11", default-features = false }
itertools = "0.14"
num-complex = "0.4"
@@ -54,10 +54,3 @@ debug-assertions = false
[workspace.metadata.dylint]
libraries = [{ path = "utils/tfhe-lints" }]
[profile.debug_lto_off]
inherits = "dev"
debug = true
lto = "off"
debug-assertions = false
overflow-checks = false

View File

@@ -54,7 +54,6 @@ TFHECUDA_BUILD=$(TFHECUDA_SRC)/build
# tfhe-hpu-backend
HPU_CONFIG=v80
V80_PCIE_DEV?=01
# Exclude these files from coverage reports
define COVERAGE_EXCLUDED_FILES
@@ -746,16 +745,6 @@ test_integer_short_run_gpu: install_rs_check_toolchain install_cargo_nextest
RUSTFLAGS="$(RUSTFLAGS)" cargo $(CARGO_RS_BUILD_TOOLCHAIN) test --profile $(CARGO_PROFILE) \
--features=integer,gpu -p tfhe -- integer::gpu::server_key::radix::tests_long_run::test_random_op_sequence integer::gpu::server_key::radix::tests_long_run::test_signed_random_op_sequence --test-threads=1 --nocapture
.PHONY: build_debug_integer_short_run_gpu # Run the long run integer tests on the gpu backend
build_debug_integer_short_run_gpu: install_rs_check_toolchain install_cargo_nextest
RUSTFLAGS="$(RUSTFLAGS)" cargo $(CARGO_RS_BUILD_TOOLCHAIN) test -vv --no-run --profile debug_lto_off \
--features=integer,gpu-debug-fake-multi-gpu -p tfhe
RUSTFLAGS="$(RUSTFLAGS)" cargo $(CARGO_RS_BUILD_TOOLCHAIN) test --profile debug_lto_off \
--features=integer,gpu-debug-fake-multi-gpu -p tfhe -- integer::gpu::server_key::radix::tests_long_run::test_random_op_sequence::test_gpu_short_random --list
@echo "To debug fake-multi-gpu short run tests run:"
@echo "TFHE_RS_TEST_LONG_TESTS_MINIMAL=TRUE <executable> integer::gpu::server_key::radix::tests_long_run::test_random_op_sequence::test_gpu_short_random_op_sequence_param_gpu_multi_bit_group_4_message_2_carry_2_ks_pbs_tuniform_2m128 --nocapture"
@echo "Where <executable> = the one printed in the () in the 'Running unittests src/lib.rs ()' line above"
.PHONY: test_integer_compression
test_integer_compression: install_rs_build_toolchain
RUSTFLAGS="$(RUSTFLAGS)" cargo $(CARGO_RS_BUILD_TOOLCHAIN) test --profile $(CARGO_PROFILE) \
@@ -1020,11 +1009,6 @@ build_one_hl_api_test_gpu: install_rs_build_toolchain
RUSTFLAGS="$(RUSTFLAGS)" cargo $(CARGO_RS_BUILD_TOOLCHAIN) test --no-run \
--features=integer,gpu-debug -vv -p tfhe -- "$${TEST}" --test-threads=1 --nocapture
.PHONY: build_one_hl_api_test_fake_multi_gpu
build_one_hl_api_test_fake_multi_gpu: install_rs_build_toolchain
RUSTFLAGS="$(RUSTFLAGS)" cargo $(CARGO_RS_BUILD_TOOLCHAIN) test --no-run \
--features=integer,gpu-debug-fake-multi-gpu -vv -p tfhe -- "$${TEST}" --test-threads=1 --nocapture
test_high_level_api_hpu: install_rs_build_toolchain install_cargo_nextest
ifeq ($(HPU_CONFIG), v80)
RUSTFLAGS="$(RUSTFLAGS)" cargo $(CARGO_RS_BUILD_TOOLCHAIN) nextest run --cargo-profile $(CARGO_PROFILE) \
@@ -1205,8 +1189,6 @@ check_compile_tests: install_rs_build_toolchain
--features=experimental,boolean,shortint,integer,internal-keycache \
-p tfhe
.PHONY: check_compile_tests_c_api # Build C API tests without running them
check_compile_tests_c_api: install_rs_build_toolchain
@if [[ "$(OS)" == "Linux" || "$(OS)" == "Darwin" ]]; then \
"$(MAKE)" build_c_api && \
./scripts/c_api_tests.sh --build-only --cargo-profile "$(CARGO_PROFILE)"; \
@@ -1344,12 +1326,11 @@ bench_signed_integer_gpu: install_rs_check_toolchain
.PHONY: bench_integer_hpu # Run benchmarks for integer on HPU backend
bench_integer_hpu: install_rs_check_toolchain
source ./setup_hpu.sh --config $(HPU_CONFIG); \
export V80_PCIE_DEV=${V80_PCIE_DEV}; \
source ./setup_hpu.sh --config $(HPU_CONFIG) -p ; \
RUSTFLAGS="$(RUSTFLAGS)" __TFHE_RS_BENCH_OP_FLAVOR=$(BENCH_OP_FLAVOR) __TFHE_RS_FAST_BENCH=$(FAST_BENCH) __TFHE_RS_BENCH_TYPE=$(BENCH_TYPE) \
cargo $(CARGO_RS_CHECK_TOOLCHAIN) bench \
--bench integer-bench \
--features=integer,internal-keycache,pbs-stats,hpu,hpu-v80 -p tfhe-benchmark -- --quick
--features=integer,internal-keycache,pbs-stats,hpu,hpu-v80 -p tfhe-benchmark --
.PHONY: bench_integer_compression # Run benchmarks for unsigned integer compression
bench_integer_compression: install_rs_check_toolchain
@@ -1522,22 +1503,21 @@ bench_web_js_api_parallel_firefox_ci: setup_venv
bench_hlapi: install_rs_check_toolchain
RUSTFLAGS="$(RUSTFLAGS)" cargo $(CARGO_RS_CHECK_TOOLCHAIN) bench \
--bench hlapi \
--features=integer,internal-keycache,nightly-avx512,pbs-stats -p tfhe-benchmark --
--features=integer,internal-keycache,nightly-avx512 -p tfhe-benchmark --
.PHONY: bench_hlapi_gpu # Run benchmarks for integer operations on GPU
bench_hlapi_gpu: install_rs_check_toolchain
RUSTFLAGS="$(RUSTFLAGS)" cargo $(CARGO_RS_CHECK_TOOLCHAIN) bench \
--bench hlapi \
--features=integer,gpu,internal-keycache,nightly-avx512,pbs-stats -p tfhe-benchmark --
--features=integer,gpu,internal-keycache,nightly-avx512 -p tfhe-benchmark --
.PHONY: bench_hlapi_hpu # Run benchmarks for HLAPI operations on HPU
bench_hlapi_hpu: install_rs_check_toolchain
source ./setup_hpu.sh --config $(HPU_CONFIG); \
export V80_PCIE_DEV=${V80_PCIE_DEV}; \
source ./setup_hpu.sh --config $(HPU_CONFIG) -p ; \
RUSTFLAGS="$(RUSTFLAGS)" \
cargo $(CARGO_RS_CHECK_TOOLCHAIN) bench \
--bench hlapi \
--features=integer,internal-keycache,hpu,hpu-v80,pbs-stats -p tfhe-benchmark --
--features=integer,internal-keycache,hpu,hpu-v80 -p tfhe-benchmark --
.PHONY: bench_hlapi_erc20 # Run benchmarks for ERC20 operations
bench_hlapi_erc20: install_rs_check_toolchain
@@ -1565,8 +1545,7 @@ bench_hlapi_dex_gpu: install_rs_check_toolchain
.PHONY: bench_hlapi_erc20_hpu # Run benchmarks for ECR20 operations on HPU
bench_hlapi_erc20_hpu: install_rs_check_toolchain
source ./setup_hpu.sh --config $(HPU_CONFIG); \
export V80_PCIE_DEV=${V80_PCIE_DEV}; \
source ./setup_hpu.sh --config $(HPU_CONFIG) -p ; \
RUSTFLAGS="$(RUSTFLAGS)" \
cargo $(CARGO_RS_CHECK_TOOLCHAIN) bench \
--bench hlapi-erc20 \
@@ -1683,38 +1662,11 @@ sha256_bool: install_rs_check_toolchain
RUSTFLAGS="$(RUSTFLAGS)" cargo $(CARGO_RS_CHECK_TOOLCHAIN) run --profile $(CARGO_PROFILE) \
--example sha256_bool --features=boolean
.PHONY: pcc # pcc stands for pre commit checks for CPU compilation
pcc: pcc_batch_1 pcc_batch_2 pcc_batch_3 pcc_batch_4 pcc_batch_5 pcc_batch_6 pcc_batch_7
#
# PCC split into several batches to speed-up CI feedback.
# Each batch have roughly the same execution time.
# Durations are given from GitHub Ubuntu large runner with 16 CPU.
#
.PHONY: pcc_batch_1 # duration: 6'10''
pcc_batch_1: no_tfhe_typo no_dbg_log check_parameter_export_ok check_fmt check_typos lint_doc \
check_md_docs_are_tested check_intra_md_links check_doc_paths_use_dash test_tfhe_lints tfhe_lints \
clippy_rustdoc
.PHONY: pcc_batch_2 # duration: 6'10''
pcc_batch_2: clippy clippy_all_targets
.PHONY: pcc_batch_3 # duration: 6'50''
pcc_batch_3: clippy_shortint clippy_integer
.PHONY: pcc_batch_4 # duration: 7'40''
pcc_batch_4: clippy_core clippy_js_wasm_api clippy_ws_tests clippy_bench
.PHONY: pcc_batch_5 # duration: 7'20''
pcc_batch_5: clippy_tfhe_lints check_compile_tests clippy_backward_compat_data
.PHONY: pcc_batch_6 # duration: 4'50'' (shortest one, extend it with further checks)
pcc_batch_6: clippy_boolean clippy_c_api clippy_tasks clippy_tfhe_csprng clippy_zk_pok \
clippy_trivium clippy_versionable clippy_param_dedup
.PHONY: pcc_batch_7 # duration: 7'50'' (currently PCC execution bottleneck)
pcc_batch_7: check_compile_tests_c_api
.PHONY: pcc # pcc stands for pre commit checks (except GPU)
pcc: no_tfhe_typo no_dbg_log check_parameter_export_ok check_fmt check_typos lint_doc \
check_md_docs_are_tested check_intra_md_links check_doc_paths_use_dash \
clippy_all check_compile_tests test_tfhe_lints \
tfhe_lints
.PHONY: pcc_gpu # pcc stands for pre commit checks for GPU compilation
pcc_gpu: check_rust_bindings_did_not_change clippy_rustdoc_gpu \

View File

@@ -45,7 +45,7 @@ production-ready library for all the advanced features of TFHE.
- **Short integer API** that enables exact, unbounded FHE integer arithmetics with up to 8 bits of message space
- **Size-efficient public key encryption**
- **Ciphertext and server key compression** for efficient data transfer
- **Full Rust API, C bindings to the Rust High-Level API, and client-side JavaScript API using WASM**.
- **Full Rust API, C bindings to the Rust High-Level API, and client-side Javascript API using WASM**.
*Learn more about TFHE-rs features in the [documentation](https://docs.zama.ai/tfhe-rs/readme).*
<br></br>
@@ -79,7 +79,7 @@ tfhe = { version = "*", features = ["boolean", "shortint", "integer"] }
```
> [!Note]
> Note: You need Rust version 1.84 or newer to compile TFHE-rs. You can check your version with `rustc --version`.
> Note: You need to use Rust version >= 1.84 to compile TFHE-rs.
> [!Note]
> Note: AArch64-based machines are not supported for Windows as it's currently missing an entropy source to be able to seed the [CSPRNGs](https://en.wikipedia.org/wiki/Cryptographically_secure_pseudorandom_number_generator) used in TFHE-rs.
@@ -147,7 +147,7 @@ To run this code, use the following command:
> [!Note]
> Note that when running code that uses `TFHE-rs`, it is highly recommended
to run in release mode with cargo's `--release` flag to have the best performance possible.
to run in release mode with cargo's `--release` flag to have the best performances possible.
*Find an example with more explanations in [this part of the documentation](https://docs.zama.ai/tfhe-rs/get-started/quick-start)*

View File

@@ -13,7 +13,6 @@ extend-ignore-identifiers-re = [
# Example in trivium
"C9217BA0D762ACA1",
"0x[0-9a-fA-F]+",
"xrt_coreutil",
]
[files]

View File

@@ -1,6 +1,6 @@
[package]
name = "tfhe-cuda-backend"
version = "0.12.0"
version = "0.11.0"
edition = "2021"
authors = ["Zama team"]
license = "BSD-3-Clause-Clear"
@@ -20,4 +20,3 @@ bindgen = "0.71"
experimental-multi-arch = []
profile = []
debug = []
debug-fake-multi-gpu = []

View File

@@ -48,16 +48,13 @@ fn main() {
// Conditionally pass the "USE_NVTOOLS" variable to CMake if the feature is enabled
if cfg!(feature = "profile") {
cmake_config.define("USE_NVTOOLS", "ON");
println!("cargo:rustc-link-lib=nvToolsExt");
} else {
cmake_config.define("USE_NVTOOLS", "OFF");
}
if cfg!(feature = "debug") {
cmake_config.define("CMAKE_BUILD_TYPE", "Debug");
} else if cfg!(feature = "debug-fake-multi-gpu") {
cmake_config.define("CMAKE_BUILD_TYPE", "DebugOnlyCpu");
cmake_config.define("CMAKE_VERBOSE_MAKEFILE", "ON");
cmake_config.define("FAKE_MULTI_GPU", "ON");
}
// Build the CMake project
@@ -84,7 +81,6 @@ fn main() {
"cuda/include/ciphertext.h",
"cuda/include/integer/compression/compression.h",
"cuda/include/integer/integer.h",
"cuda/include/aes/aes.h",
"cuda/include/zk/zk.h",
"cuda/include/keyswitch/keyswitch.h",
"cuda/include/keyswitch/ks_enums.h",

View File

@@ -87,9 +87,6 @@ if(CMAKE_BUILD_TYPE_LOWERCASE STREQUAL "debug")
add_definitions(-DDEBUG)
set(OPTIMIZATION_FLAGS "${OPTIMIZATION_FLAGS} -O0 -G -g")
set(USE_NVTOOLS 1)
elseif(CMAKE_BUILD_TYPE_LOWERCASE STREQUAL "debugonlycpu")
message("Compiling GPU kernels in Release and CPU code in Debug")
set(OPTIMIZATION_FLAGS "${OPTIMIZATION_FLAGS} -O0 -g")
else()
# Release mode
message("Compiling in Release mode")
@@ -102,11 +99,6 @@ if(${USE_NVTOOLS})
add_definitions(-DUSE_NVTOOLS)
endif()
if(${FAKE_MULTI_GPU})
message(STATUS "Fake multi-gpu debugging is enabled")
add_definitions(-DDEBUG_FAKE_MULTI_GPU)
endif()
# in production, should use -arch=sm_70 --ptxas-options=-v to see register spills -lineinfo for better debugging to use
# nvtx when profiling -lnvToolsExt
set(CMAKE_CUDA_FLAGS

View File

@@ -1,44 +0,0 @@
#ifndef AES_H
#define AES_H
#include "../integer/integer.h"
extern "C" {
uint64_t scratch_cuda_integer_aes_encrypt_64(
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);
void cuda_integer_aes_ctr_encrypt_64(CudaStreamsFFI streams,
CudaRadixCiphertextFFI *output,
CudaRadixCiphertextFFI const *iv,
CudaRadixCiphertextFFI const *round_keys,
const uint64_t *counter_bits_le_all_blocks,
uint32_t num_aes_inputs, int8_t *mem_ptr,
void *const *bsks, void *const *ksks);
void cleanup_cuda_integer_aes_encrypt_64(CudaStreamsFFI streams,
int8_t **mem_ptr_void);
uint64_t scratch_cuda_integer_key_expansion_64(
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);
void cuda_integer_key_expansion_64(CudaStreamsFFI streams,
CudaRadixCiphertextFFI *expanded_keys,
CudaRadixCiphertextFFI const *key,
int8_t *mem_ptr, void *const *bsks,
void *const *ksks);
void cleanup_cuda_integer_key_expansion_64(CudaStreamsFFI streams,
int8_t **mem_ptr_void);
}
#endif

View File

@@ -1,440 +0,0 @@
#ifndef AES_UTILITIES
#define AES_UTILITIES
#include "../integer/integer_utilities.h"
/**
* This structure holds pre-computed LUTs for essential bitwise operations
* required by the homomorphic AES circuit. Pre-computing these tables allows
* for efficient application of non-linear functions like AND during the PBS
* process. It includes LUTs for:
* - AND: for the non-linear part of the S-Box.
* - FLUSH: to clear carry bits and isolate the message bit (x -> x & 1).
* - CARRY: to extract the carry bit for additions (x -> (x >> 1) & 1).
*/
template <typename Torus> struct int_aes_lut_buffers {
int_radix_lut<Torus> *and_lut;
int_radix_lut<Torus> *flush_lut;
int_radix_lut<Torus> *carry_lut;
int_aes_lut_buffers(CudaStreams streams, const int_radix_params &params,
bool allocate_gpu_memory, uint32_t num_aes_inputs,
uint32_t sbox_parallelism, uint64_t &size_tracker) {
constexpr uint32_t AES_STATE_BITS = 128;
constexpr uint32_t SBOX_MAX_AND_GATES = 18;
this->and_lut = new int_radix_lut<Torus>(
streams, params, 1,
SBOX_MAX_AND_GATES * num_aes_inputs * sbox_parallelism,
allocate_gpu_memory, size_tracker);
std::function<Torus(Torus, Torus)> and_lambda =
[](Torus a, Torus b) -> Torus { return a & b; };
generate_device_accumulator_bivariate<Torus>(
streams.stream(0), streams.gpu_index(0), this->and_lut->get_lut(0, 0),
this->and_lut->get_degree(0), this->and_lut->get_max_degree(0),
params.glwe_dimension, params.polynomial_size, params.message_modulus,
params.carry_modulus, and_lambda, allocate_gpu_memory);
auto active_streams_and_lut = streams.active_gpu_subset(
SBOX_MAX_AND_GATES * num_aes_inputs * sbox_parallelism);
this->and_lut->broadcast_lut(active_streams_and_lut);
this->flush_lut = new int_radix_lut<Torus>(
streams, params, 1, AES_STATE_BITS * num_aes_inputs,
allocate_gpu_memory, size_tracker);
std::function<Torus(Torus)> flush_lambda = [](Torus x) -> Torus {
return x & 1;
};
generate_device_accumulator(
streams.stream(0), streams.gpu_index(0), this->flush_lut->get_lut(0, 0),
this->flush_lut->get_degree(0), this->flush_lut->get_max_degree(0),
params.glwe_dimension, params.polynomial_size, params.message_modulus,
params.carry_modulus, flush_lambda, allocate_gpu_memory);
auto active_streams_flush_lut =
streams.active_gpu_subset(AES_STATE_BITS * num_aes_inputs);
this->flush_lut->broadcast_lut(active_streams_flush_lut);
this->carry_lut = new int_radix_lut<Torus>(
streams, params, 1, num_aes_inputs, allocate_gpu_memory, size_tracker);
std::function<Torus(Torus)> carry_lambda = [](Torus x) -> Torus {
return (x >> 1) & 1;
};
generate_device_accumulator(
streams.stream(0), streams.gpu_index(0), this->carry_lut->get_lut(0, 0),
this->carry_lut->get_degree(0), this->carry_lut->get_max_degree(0),
params.glwe_dimension, params.polynomial_size, params.message_modulus,
params.carry_modulus, carry_lambda, allocate_gpu_memory);
auto active_streams_carry_lut = streams.active_gpu_subset(num_aes_inputs);
this->carry_lut->broadcast_lut(active_streams_carry_lut);
}
void release(CudaStreams streams) {
this->and_lut->release(streams);
delete this->and_lut;
this->and_lut = nullptr;
this->flush_lut->release(streams);
delete this->flush_lut;
this->flush_lut = nullptr;
this->carry_lut->release(streams);
delete this->carry_lut;
this->carry_lut = nullptr;
}
};
/**
* The operations within an AES round, particularly MixColumns, require
* intermediate storage for calculations. These buffers are designed to hold
* temporary values like copies of columns or the results of multiplications,
* avoiding overwriting data that is still needed in the same round.
*/
template <typename Torus> struct int_aes_round_workspaces {
CudaRadixCiphertextFFI *mix_columns_col_copy_buffer;
CudaRadixCiphertextFFI *mix_columns_mul_workspace_buffer;
CudaRadixCiphertextFFI *vec_tmp_bit_buffer;
int_aes_round_workspaces(CudaStreams streams, const int_radix_params &params,
bool allocate_gpu_memory, uint32_t num_aes_inputs,
uint64_t &size_tracker) {
constexpr uint32_t BITS_PER_BYTE = 8;
constexpr uint32_t BYTES_PER_COLUMN = 4;
constexpr uint32_t BITS_PER_COLUMN = BITS_PER_BYTE * BYTES_PER_COLUMN;
constexpr uint32_t MIX_COLUMNS_MUL_WORKSPACE_BYTES = BYTES_PER_COLUMN + 1;
this->mix_columns_col_copy_buffer = new CudaRadixCiphertextFFI;
create_zero_radix_ciphertext_async<Torus>(
streams.stream(0), streams.gpu_index(0),
this->mix_columns_col_copy_buffer, BITS_PER_COLUMN * num_aes_inputs,
params.big_lwe_dimension, size_tracker, allocate_gpu_memory);
this->mix_columns_mul_workspace_buffer = new CudaRadixCiphertextFFI;
create_zero_radix_ciphertext_async<Torus>(
streams.stream(0), streams.gpu_index(0),
this->mix_columns_mul_workspace_buffer,
MIX_COLUMNS_MUL_WORKSPACE_BYTES * BITS_PER_BYTE * num_aes_inputs,
params.big_lwe_dimension, size_tracker, allocate_gpu_memory);
this->vec_tmp_bit_buffer = new CudaRadixCiphertextFFI;
create_zero_radix_ciphertext_async<Torus>(
streams.stream(0), streams.gpu_index(0), this->vec_tmp_bit_buffer,
num_aes_inputs, params.big_lwe_dimension, size_tracker,
allocate_gpu_memory);
}
void release(CudaStreams streams, bool allocate_gpu_memory) {
release_radix_ciphertext_async(streams.stream(0), streams.gpu_index(0),
this->mix_columns_col_copy_buffer,
allocate_gpu_memory);
delete this->mix_columns_col_copy_buffer;
this->mix_columns_col_copy_buffer = nullptr;
release_radix_ciphertext_async(streams.stream(0), streams.gpu_index(0),
this->mix_columns_mul_workspace_buffer,
allocate_gpu_memory);
delete this->mix_columns_mul_workspace_buffer;
this->mix_columns_mul_workspace_buffer = nullptr;
release_radix_ciphertext_async(streams.stream(0), streams.gpu_index(0),
this->vec_tmp_bit_buffer,
allocate_gpu_memory);
delete this->vec_tmp_bit_buffer;
this->vec_tmp_bit_buffer = nullptr;
}
};
/**
* In CTR mode, a counter is homomorphically added to the encrypted IV. This
* structure holds the necessary buffers for this 128-bit ripple-carry
* addition, such as the buffer for the propagating carry bit
* (`vec_tmp_carry_buffer`) across the addition chain.
*/
template <typename Torus> struct int_aes_counter_workspaces {
CudaRadixCiphertextFFI *vec_tmp_carry_buffer;
CudaRadixCiphertextFFI *vec_tmp_sum_buffer;
CudaRadixCiphertextFFI *vec_trivial_b_bits_buffer;
Torus *h_counter_bits_buffer;
Torus *d_counter_bits_buffer;
int_aes_counter_workspaces(CudaStreams streams,
const int_radix_params &params,
bool allocate_gpu_memory, uint32_t num_aes_inputs,
uint64_t &size_tracker) {
this->vec_tmp_carry_buffer = new CudaRadixCiphertextFFI;
create_zero_radix_ciphertext_async<Torus>(
streams.stream(0), streams.gpu_index(0), this->vec_tmp_carry_buffer,
num_aes_inputs, params.big_lwe_dimension, size_tracker,
allocate_gpu_memory);
this->vec_tmp_sum_buffer = new CudaRadixCiphertextFFI;
create_zero_radix_ciphertext_async<Torus>(
streams.stream(0), streams.gpu_index(0), this->vec_tmp_sum_buffer,
num_aes_inputs, params.big_lwe_dimension, size_tracker,
allocate_gpu_memory);
this->vec_trivial_b_bits_buffer = new CudaRadixCiphertextFFI;
create_zero_radix_ciphertext_async<Torus>(
streams.stream(0), streams.gpu_index(0),
this->vec_trivial_b_bits_buffer, num_aes_inputs,
params.big_lwe_dimension, size_tracker, allocate_gpu_memory);
this->h_counter_bits_buffer =
(Torus *)malloc(num_aes_inputs * sizeof(Torus));
size_tracker += num_aes_inputs * sizeof(Torus);
this->d_counter_bits_buffer = (Torus *)cuda_malloc_with_size_tracking_async(
num_aes_inputs * sizeof(Torus), streams.stream(0), streams.gpu_index(0),
size_tracker, allocate_gpu_memory);
}
void release(CudaStreams streams, bool allocate_gpu_memory) {
release_radix_ciphertext_async(streams.stream(0), streams.gpu_index(0),
this->vec_tmp_carry_buffer,
allocate_gpu_memory);
delete this->vec_tmp_carry_buffer;
this->vec_tmp_carry_buffer = nullptr;
release_radix_ciphertext_async(streams.stream(0), streams.gpu_index(0),
this->vec_tmp_sum_buffer,
allocate_gpu_memory);
delete this->vec_tmp_sum_buffer;
this->vec_tmp_sum_buffer = nullptr;
release_radix_ciphertext_async(streams.stream(0), streams.gpu_index(0),
this->vec_trivial_b_bits_buffer,
allocate_gpu_memory);
delete this->vec_trivial_b_bits_buffer;
this->vec_trivial_b_bits_buffer = nullptr;
free(this->h_counter_bits_buffer);
if (allocate_gpu_memory) {
cuda_drop_async(this->d_counter_bits_buffer, streams.stream(0),
streams.gpu_index(0));
streams.synchronize();
}
}
};
/**
* This structure allocates the most significant memory blocks:
* - `sbox_internal_workspace`: A large workspace for the complex, parallel
* evaluation of the S-Box circuit.
* - `main_bitsliced_states_buffer`: Holds the entire set of AES states in a
* bitsliced layout, which is optimal for parallel bitwise operations on the
* GPU.
* - Other buffers are used for data layout transformations (transposition) and
* for batching small operations into larger, more efficient launches.
*/
template <typename Torus> struct int_aes_main_workspaces {
CudaRadixCiphertextFFI *sbox_internal_workspace;
CudaRadixCiphertextFFI *initial_states_and_jit_key_workspace;
CudaRadixCiphertextFFI *main_bitsliced_states_buffer;
CudaRadixCiphertextFFI *tmp_tiled_key_buffer;
CudaRadixCiphertextFFI *batch_processing_buffer;
int_aes_main_workspaces(CudaStreams streams, const int_radix_params &params,
bool allocate_gpu_memory, uint32_t num_aes_inputs,
uint32_t sbox_parallelism, uint64_t &size_tracker) {
constexpr uint32_t AES_STATE_BITS = 128;
constexpr uint32_t SBOX_MAX_AND_GATES = 18;
constexpr uint32_t BATCH_BUFFER_OPERANDS = 3;
this->sbox_internal_workspace = new CudaRadixCiphertextFFI;
create_zero_radix_ciphertext_async<Torus>(
streams.stream(0), streams.gpu_index(0), this->sbox_internal_workspace,
num_aes_inputs * AES_STATE_BITS * sbox_parallelism,
params.big_lwe_dimension, size_tracker, allocate_gpu_memory);
this->initial_states_and_jit_key_workspace = new CudaRadixCiphertextFFI;
create_zero_radix_ciphertext_async<Torus>(
streams.stream(0), streams.gpu_index(0),
this->initial_states_and_jit_key_workspace,
num_aes_inputs * AES_STATE_BITS, params.big_lwe_dimension, size_tracker,
allocate_gpu_memory);
this->main_bitsliced_states_buffer = new CudaRadixCiphertextFFI;
create_zero_radix_ciphertext_async<Torus>(
streams.stream(0), streams.gpu_index(0),
this->main_bitsliced_states_buffer, num_aes_inputs * AES_STATE_BITS,
params.big_lwe_dimension, size_tracker, allocate_gpu_memory);
this->tmp_tiled_key_buffer = new CudaRadixCiphertextFFI;
create_zero_radix_ciphertext_async<Torus>(
streams.stream(0), streams.gpu_index(0), this->tmp_tiled_key_buffer,
num_aes_inputs * AES_STATE_BITS, params.big_lwe_dimension, size_tracker,
allocate_gpu_memory);
this->batch_processing_buffer = new CudaRadixCiphertextFFI;
create_zero_radix_ciphertext_async<Torus>(
streams.stream(0), streams.gpu_index(0), this->batch_processing_buffer,
num_aes_inputs * SBOX_MAX_AND_GATES * BATCH_BUFFER_OPERANDS *
sbox_parallelism,
params.big_lwe_dimension, size_tracker, allocate_gpu_memory);
}
void release(CudaStreams streams, bool allocate_gpu_memory) {
release_radix_ciphertext_async(streams.stream(0), streams.gpu_index(0),
this->sbox_internal_workspace,
allocate_gpu_memory);
delete this->sbox_internal_workspace;
this->sbox_internal_workspace = nullptr;
release_radix_ciphertext_async(streams.stream(0), streams.gpu_index(0),
this->initial_states_and_jit_key_workspace,
allocate_gpu_memory);
delete this->initial_states_and_jit_key_workspace;
this->initial_states_and_jit_key_workspace = nullptr;
release_radix_ciphertext_async(streams.stream(0), streams.gpu_index(0),
this->main_bitsliced_states_buffer,
allocate_gpu_memory);
delete this->main_bitsliced_states_buffer;
this->main_bitsliced_states_buffer = nullptr;
release_radix_ciphertext_async(streams.stream(0), streams.gpu_index(0),
this->tmp_tiled_key_buffer,
allocate_gpu_memory);
delete this->tmp_tiled_key_buffer;
this->tmp_tiled_key_buffer = nullptr;
release_radix_ciphertext_async(streams.stream(0), streams.gpu_index(0),
this->batch_processing_buffer,
allocate_gpu_memory);
delete this->batch_processing_buffer;
this->batch_processing_buffer = nullptr;
}
};
/**
* This structure acts as a container, holding instances of all the other buffer
* management structs. It provides a
* single object to manage the entire lifecycle of memory needed for a complete
* AES-CTR encryption operation.
*/
template <typename Torus> struct int_aes_encrypt_buffer {
int_radix_params params;
bool allocate_gpu_memory;
uint32_t num_aes_inputs;
uint32_t sbox_parallel_instances;
int_aes_lut_buffers<Torus> *luts;
int_aes_round_workspaces<Torus> *round_workspaces;
int_aes_counter_workspaces<Torus> *counter_workspaces;
int_aes_main_workspaces<Torus> *main_workspaces;
int_aes_encrypt_buffer(CudaStreams streams, const int_radix_params &params,
bool allocate_gpu_memory, uint32_t num_aes_inputs,
uint32_t sbox_parallelism, uint64_t &size_tracker) {
PANIC_IF_FALSE(num_aes_inputs >= 1,
"num_aes_inputs should be greater or equal to 1");
this->params = params;
this->allocate_gpu_memory = allocate_gpu_memory;
this->num_aes_inputs = num_aes_inputs;
this->sbox_parallel_instances = sbox_parallelism;
this->luts = new int_aes_lut_buffers<Torus>(
streams, params, allocate_gpu_memory, num_aes_inputs, sbox_parallelism,
size_tracker);
this->round_workspaces = new int_aes_round_workspaces<Torus>(
streams, params, allocate_gpu_memory, num_aes_inputs, size_tracker);
this->counter_workspaces = new int_aes_counter_workspaces<Torus>(
streams, params, allocate_gpu_memory, num_aes_inputs, size_tracker);
this->main_workspaces = new int_aes_main_workspaces<Torus>(
streams, params, allocate_gpu_memory, num_aes_inputs, sbox_parallelism,
size_tracker);
}
void release(CudaStreams streams) {
luts->release(streams);
delete luts;
luts = nullptr;
round_workspaces->release(streams, allocate_gpu_memory);
delete round_workspaces;
round_workspaces = nullptr;
counter_workspaces->release(streams, allocate_gpu_memory);
delete counter_workspaces;
counter_workspaces = nullptr;
main_workspaces->release(streams, allocate_gpu_memory);
delete main_workspaces;
main_workspaces = nullptr;
}
};
/**
* This structure holds the buffer for the 44 words of the expanded key
* and temporary storage for word manipulations.
* It contains its own instance of `int_aes_encrypt_buffer` because the
* key expansion algorithm itself requires using the S-Box.
* This separation ensures that memory for key expansion can be allocated and
* freed independently of the main encryption process.
*/
template <typename Torus> struct int_key_expansion_buffer {
int_radix_params params;
bool allocate_gpu_memory;
CudaRadixCiphertextFFI *words_buffer;
CudaRadixCiphertextFFI *tmp_word_buffer;
CudaRadixCiphertextFFI *tmp_rotated_word_buffer;
int_aes_encrypt_buffer<Torus> *aes_encrypt_buffer;
int_key_expansion_buffer(CudaStreams streams, const int_radix_params &params,
bool allocate_gpu_memory, uint64_t &size_tracker) {
this->params = params;
this->allocate_gpu_memory = allocate_gpu_memory;
constexpr uint32_t TOTAL_WORDS = 44;
constexpr uint32_t BITS_PER_WORD = 32;
constexpr uint32_t TOTAL_BITS = TOTAL_WORDS * BITS_PER_WORD;
this->words_buffer = new CudaRadixCiphertextFFI;
create_zero_radix_ciphertext_async<Torus>(
streams.stream(0), streams.gpu_index(0), this->words_buffer, TOTAL_BITS,
params.big_lwe_dimension, size_tracker, allocate_gpu_memory);
this->tmp_word_buffer = new CudaRadixCiphertextFFI;
create_zero_radix_ciphertext_async<Torus>(
streams.stream(0), streams.gpu_index(0), this->tmp_word_buffer,
BITS_PER_WORD, params.big_lwe_dimension, size_tracker,
allocate_gpu_memory);
this->tmp_rotated_word_buffer = new CudaRadixCiphertextFFI;
create_zero_radix_ciphertext_async<Torus>(
streams.stream(0), streams.gpu_index(0), this->tmp_rotated_word_buffer,
BITS_PER_WORD, params.big_lwe_dimension, size_tracker,
allocate_gpu_memory);
this->aes_encrypt_buffer = new int_aes_encrypt_buffer<Torus>(
streams, params, allocate_gpu_memory, 1, 4, size_tracker);
}
void release(CudaStreams streams) {
release_radix_ciphertext_async(streams.stream(0), streams.gpu_index(0),
this->words_buffer, allocate_gpu_memory);
delete this->words_buffer;
release_radix_ciphertext_async(streams.stream(0), streams.gpu_index(0),
this->tmp_word_buffer, allocate_gpu_memory);
delete this->tmp_word_buffer;
release_radix_ciphertext_async(streams.stream(0), streams.gpu_index(0),
this->tmp_rotated_word_buffer,
allocate_gpu_memory);
delete this->tmp_rotated_word_buffer;
this->aes_encrypt_buffer->release(streams);
delete this->aes_encrypt_buffer;
}
};
#endif

View File

@@ -5,7 +5,6 @@
#include <cstdio>
#include <cstdlib>
#include <cuda_runtime.h>
#include <memory>
extern "C" {
@@ -141,34 +140,4 @@ template <typename Torus>
void cuda_set_value_async(cudaStream_t stream, uint32_t gpu_index,
Torus *d_array, Torus value, Torus n);
template <class T> struct malloc_with_size_tracking_async_deleter {
private:
cudaStream_t _stream;
uint32_t _gpu_index;
uint64_t &_size_tracker;
bool _allocate_gpu_memory;
public:
malloc_with_size_tracking_async_deleter(cudaStream_t stream,
uint32_t gpu_index,
uint64_t &size_tracker,
bool allocate_gpu_memory)
: _stream(stream), _gpu_index(gpu_index), _size_tracker(size_tracker),
_allocate_gpu_memory(allocate_gpu_memory)
{}
void operator()(T *ptr) { cuda_drop_with_size_tracking_async(ptr, _stream, _gpu_index, _allocate_gpu_memory) ; }
};
template <class T>
std::shared_ptr<T> cuda_make_shared_with_size_tracking_async(
uint64_t size, cudaStream_t stream, uint32_t gpu_index,
uint64_t &size_tracker, bool allocate_gpu_memory) {
return std::shared_ptr<T>(
(T*)cuda_malloc_with_size_tracking_async(size, stream, gpu_index,
size_tracker, allocate_gpu_memory),
malloc_with_size_tracking_async_deleter<T>(
stream, gpu_index, size_tracker, allocate_gpu_memory));
}
#endif

View File

@@ -78,9 +78,10 @@ public:
get_active_gpu_count(num_radix_blocks, _gpu_count));
}
// Returns a CudaStreams struct containing only the ith stream
CudaStreams get_ith(int i) const {
return CudaStreams(&_streams[i], &_gpu_indexes[i], 1);
// Returns a subset containing only the first gpu of this set. It
// is used to create subset of streams for mono-GPU functions
CudaStreams subset_first_gpu() const {
return CudaStreams(_streams, _gpu_indexes, 1);
}
// Synchronize all the streams in the set
@@ -183,93 +184,4 @@ public:
}
};
struct CudaStreamsBarrier {
private:
std::vector<cudaEvent_t> _events;
CudaStreams _streams;
CudaStreamsBarrier(const CudaStreamsBarrier &) {} // Prevent copy-construction
CudaStreamsBarrier &operator=(const CudaStreamsBarrier &) {
return *this;
} // Prevent assignment
public:
void create_on(const CudaStreams &streams) {
_streams = streams;
GPU_ASSERT(streams.count() > 1, "CudaStreamsFirstWaitsWorkersBarrier: "
"Attempted to create on single GPU");
_events.resize(streams.count());
for (int i = 0; i < streams.count(); i++) {
_events[i] = cuda_create_event(streams.gpu_index(i));
}
}
CudaStreamsBarrier(){};
void local_streams_wait_for_stream_0(const CudaStreams &user_streams) {
GPU_ASSERT(!_events.empty(),
"CudaStreamsBarrier: must call create_on before use");
GPU_ASSERT(user_streams.gpu_index(0) == _streams.gpu_index(0),
"CudaStreamsBarrier: synchronization can only be performed on "
"the GPUs the barrier was initially created on.");
cuda_event_record(_events[0], user_streams.stream(0),
user_streams.gpu_index(0));
for (int j = 1; j < user_streams.count(); j++) {
GPU_ASSERT(user_streams.gpu_index(j) == _streams.gpu_index(j),
"CudaStreamsBarrier: synchronization can only be performed on "
"the GPUs the barrier was initially created on.");
cuda_stream_wait_event(user_streams.stream(j), _events[0],
user_streams.gpu_index(j));
}
}
void stream_0_wait_for_local_streams(const CudaStreams &user_streams) {
GPU_ASSERT(
!_events.empty(),
"CudaStreamsFirstWaitsWorkersBarrier: must call create_on before use");
GPU_ASSERT(
user_streams.count() <= _events.size(),
"CudaStreamsFirstWaitsWorkersBarrier: trying to synchronize too many "
"streams. "
"The barrier was created on a LUT that had %lu active streams, while "
"the user stream set has %u streams",
_events.size(), user_streams.count());
if (user_streams.count() > 1) {
// Worker GPUs record their events
for (int j = 1; j < user_streams.count(); j++) {
GPU_ASSERT(_streams.gpu_index(j) == user_streams.gpu_index(j),
"CudaStreamsBarrier: The user stream "
"set GPU[%d]=%u while the LUT stream set GPU[%d]=%u",
j, user_streams.gpu_index(j), j, _streams.gpu_index(j));
cuda_event_record(_events[j], user_streams.stream(j),
user_streams.gpu_index(j));
}
// GPU 0 waits for all workers
for (int j = 1; j < user_streams.count(); j++) {
cuda_stream_wait_event(user_streams.stream(0), _events[j],
user_streams.gpu_index(0));
}
}
}
void release() {
for (int j = 0; j < _streams.count(); j++) {
cuda_event_destroy(_events[j], _streams.gpu_index(j));
}
_events.clear();
}
~CudaStreamsBarrier() {
GPU_ASSERT(_events.empty(),
"CudaStreamsBarrier: must "
"call release before destruction: events size = %lu",
_events.size());
}
};
#endif

View File

@@ -4,6 +4,26 @@
#include "../../pbs/pbs_enums.h"
#include "../integer.h"
typedef struct {
void *ptr;
uint32_t num_radix_blocks;
uint32_t lwe_dimension;
} CudaLweCiphertextListFFI;
typedef struct {
void *ptr;
uint32_t storage_log_modulus;
uint32_t lwe_per_glwe;
// Input LWEs are grouped by groups of `lwe_per_glwe`(the last group may be
// smaller)
// Each group is then packed into one GLWE with `lwe_per_glwe` bodies (one for
// each LWE of the group). In the end the total number of bodies is equal to
// the number of input LWE
uint32_t total_lwe_bodies_count;
uint32_t glwe_dimension;
uint32_t polynomial_size;
} CudaPackedGlweCiphertextListFFI;
extern "C" {
uint64_t scratch_cuda_integer_compress_radix_ciphertext_64(
CudaStreamsFFI streams, int8_t **mem_ptr,

View File

@@ -86,26 +86,6 @@ typedef struct {
bool const divisor_has_more_bits_than_numerator;
} CudaScalarDivisorFFI;
typedef struct {
void *ptr;
uint32_t num_radix_blocks;
uint32_t lwe_dimension;
} CudaLweCiphertextListFFI;
typedef struct {
void *ptr;
uint32_t storage_log_modulus;
uint32_t lwe_per_glwe;
// Input LWEs are grouped by groups of `lwe_per_glwe`(the last group may be
// smaller)
// Each group is then packed into one GLWE with `lwe_per_glwe` bodies (one for
// each LWE of the group). In the end the total number of bodies is equal to
// the number of input LWE
uint32_t total_lwe_bodies_count;
uint32_t glwe_dimension;
uint32_t polynomial_size;
} CudaPackedGlweCiphertextListFFI;
uint64_t scratch_cuda_apply_univariate_lut_kb_64(
CudaStreamsFFI streams, int8_t **mem_ptr, void const *input_lut,
uint32_t lwe_dimension, uint32_t glwe_dimension, uint32_t polynomial_size,
@@ -125,7 +105,9 @@ uint64_t scratch_cuda_apply_many_univariate_lut_kb_64(
void cuda_apply_univariate_lut_kb_64(
CudaStreamsFFI streams, CudaRadixCiphertextFFI *output_radix_lwe,
CudaRadixCiphertextFFI const *input_radix_lwe, int8_t *mem_ptr,
void *const *ksks, void *const *bsks);
void *const *ksks,
CudaModulusSwitchNoiseReductionKeyFFI const *ms_noise_reduction_key,
void *const *bsks);
void cleanup_cuda_apply_univariate_lut_kb_64(CudaStreamsFFI streams,
int8_t **mem_ptr_void);
@@ -143,8 +125,9 @@ void cuda_apply_bivariate_lut_kb_64(
CudaStreamsFFI streams, CudaRadixCiphertextFFI *output_radix_lwe,
CudaRadixCiphertextFFI const *input_radix_lwe_1,
CudaRadixCiphertextFFI const *input_radix_lwe_2, int8_t *mem_ptr,
void *const *ksks, void *const *bsks, uint32_t num_radix_blocks,
uint32_t shift);
void *const *ksks,
CudaModulusSwitchNoiseReductionKeyFFI const *ms_noise_reduction_key,
void *const *bsks, uint32_t num_radix_blocks, uint32_t shift);
void cleanup_cuda_apply_bivariate_lut_kb_64(CudaStreamsFFI streams,
int8_t **mem_ptr_void);
@@ -152,8 +135,9 @@ void cleanup_cuda_apply_bivariate_lut_kb_64(CudaStreamsFFI streams,
void cuda_apply_many_univariate_lut_kb_64(
CudaStreamsFFI streams, CudaRadixCiphertextFFI *output_radix_lwe,
CudaRadixCiphertextFFI const *input_radix_lwe, int8_t *mem_ptr,
void *const *ksks, void *const *bsks, uint32_t num_luts,
uint32_t lut_stride);
void *const *ksks,
CudaModulusSwitchNoiseReductionKeyFFI const *ms_noise_reduction_key,
void *const *bsks, uint32_t num_luts, uint32_t lut_stride);
uint64_t scratch_cuda_full_propagation_64(
CudaStreamsFFI streams, int8_t **mem_ptr, uint32_t lwe_dimension,
@@ -163,10 +147,11 @@ uint64_t scratch_cuda_full_propagation_64(
PBS_TYPE pbs_type, bool allocate_gpu_memory,
PBS_MS_REDUCTION_T noise_reduction_type);
void cuda_full_propagation_64_inplace(CudaStreamsFFI streams,
CudaRadixCiphertextFFI *input_blocks,
int8_t *mem_ptr, void *const *ksks,
void *const *bsks, uint32_t num_blocks);
void cuda_full_propagation_64_inplace(
CudaStreamsFFI streams, CudaRadixCiphertextFFI *input_blocks,
int8_t *mem_ptr, void *const *ksks,
CudaModulusSwitchNoiseReductionKeyFFI const *ms_noise_reduction_key,
void *const *bsks, uint32_t num_blocks);
void cleanup_cuda_full_propagation(CudaStreamsFFI streams,
int8_t **mem_ptr_void);
@@ -184,8 +169,9 @@ void cuda_integer_mult_radix_ciphertext_kb_64(
CudaStreamsFFI streams, CudaRadixCiphertextFFI *radix_lwe_out,
CudaRadixCiphertextFFI const *radix_lwe_left, bool const is_bool_left,
CudaRadixCiphertextFFI const *radix_lwe_right, bool const is_bool_right,
void *const *bsks, void *const *ksks, int8_t *mem_ptr,
uint32_t polynomial_size, uint32_t num_blocks);
void *const *bsks, void *const *ksks,
CudaModulusSwitchNoiseReductionKeyFFI const *ms_noise_reduction_key,
int8_t *mem_ptr, uint32_t polynomial_size, uint32_t num_blocks);
void cleanup_cuda_integer_mult(CudaStreamsFFI streams, int8_t **mem_ptr_void);
@@ -210,7 +196,8 @@ uint64_t scratch_cuda_integer_radix_logical_scalar_shift_kb_64(
void cuda_integer_radix_logical_scalar_shift_kb_64_inplace(
CudaStreamsFFI streams, CudaRadixCiphertextFFI *lwe_array, uint32_t shift,
int8_t *mem_ptr, void *const *bsks, void *const *ksks);
int8_t *mem_ptr, void *const *bsks, void *const *ksks,
CudaModulusSwitchNoiseReductionKeyFFI const *ms_noise_reduction_key);
uint64_t scratch_cuda_integer_radix_arithmetic_scalar_shift_kb_64(
CudaStreamsFFI streams, int8_t **mem_ptr, uint32_t glwe_dimension,
@@ -223,7 +210,8 @@ uint64_t scratch_cuda_integer_radix_arithmetic_scalar_shift_kb_64(
void cuda_integer_radix_arithmetic_scalar_shift_kb_64_inplace(
CudaStreamsFFI streams, CudaRadixCiphertextFFI *lwe_array, uint32_t shift,
int8_t *mem_ptr, void *const *bsks, void *const *ksks);
int8_t *mem_ptr, void *const *bsks, void *const *ksks,
CudaModulusSwitchNoiseReductionKeyFFI const *ms_noise_reduction_key);
void cleanup_cuda_integer_radix_logical_scalar_shift(CudaStreamsFFI streams,
int8_t **mem_ptr_void);
@@ -243,7 +231,8 @@ uint64_t scratch_cuda_integer_radix_shift_and_rotate_kb_64(
void cuda_integer_radix_shift_and_rotate_kb_64_inplace(
CudaStreamsFFI streams, CudaRadixCiphertextFFI *lwe_array,
CudaRadixCiphertextFFI const *lwe_shift, int8_t *mem_ptr, void *const *bsks,
void *const *ksks);
void *const *ksks,
CudaModulusSwitchNoiseReductionKeyFFI const *ms_noise_reduction_key);
void cleanup_cuda_integer_radix_shift_and_rotate(CudaStreamsFFI streams,
int8_t **mem_ptr_void);
@@ -262,13 +251,16 @@ void cuda_comparison_integer_radix_ciphertext_kb_64(
CudaStreamsFFI streams, CudaRadixCiphertextFFI *lwe_array_out,
CudaRadixCiphertextFFI const *lwe_array_1,
CudaRadixCiphertextFFI const *lwe_array_2, int8_t *mem_ptr,
void *const *bsks, void *const *ksks);
void *const *bsks, void *const *ksks,
CudaModulusSwitchNoiseReductionKeyFFI const *ms_noise_reduction_key);
void cuda_scalar_comparison_integer_radix_ciphertext_kb_64(
CudaStreamsFFI streams, CudaRadixCiphertextFFI *lwe_array_out,
CudaRadixCiphertextFFI const *lwe_array_in, void const *scalar_blocks,
void const *h_scalar_blocks, int8_t *mem_ptr, void *const *bsks,
void *const *ksks, uint32_t num_scalar_blocks);
void *const *ksks,
CudaModulusSwitchNoiseReductionKeyFFI const *ms_noise_reduction_key,
uint32_t num_scalar_blocks);
void cleanup_cuda_integer_comparison(CudaStreamsFFI streams,
int8_t **mem_ptr_void);
@@ -286,13 +278,15 @@ void cuda_bitop_integer_radix_ciphertext_kb_64(
CudaStreamsFFI streams, CudaRadixCiphertextFFI *lwe_array_out,
CudaRadixCiphertextFFI const *lwe_array_1,
CudaRadixCiphertextFFI const *lwe_array_2, int8_t *mem_ptr,
void *const *bsks, void *const *ksks);
void *const *bsks, void *const *ksks,
CudaModulusSwitchNoiseReductionKeyFFI const *ms_noise_reduction_key);
void cuda_scalar_bitop_integer_radix_ciphertext_kb_64(
CudaStreamsFFI streams, CudaRadixCiphertextFFI *lwe_array_out,
CudaRadixCiphertextFFI const *lwe_array_input, void const *clear_blocks,
void const *h_clear_blocks, uint32_t num_clear_blocks, int8_t *mem_ptr,
void *const *bsks, void *const *ksks);
void *const *bsks, void *const *ksks,
CudaModulusSwitchNoiseReductionKeyFFI const *ms_noise_reduction_key);
void cleanup_cuda_integer_bitop(CudaStreamsFFI streams, int8_t **mem_ptr_void);
@@ -310,7 +304,8 @@ void cuda_cmux_integer_radix_ciphertext_kb_64(
CudaRadixCiphertextFFI const *lwe_condition,
CudaRadixCiphertextFFI const *lwe_array_true,
CudaRadixCiphertextFFI const *lwe_array_false, int8_t *mem_ptr,
void *const *bsks, void *const *ksks);
void *const *bsks, void *const *ksks,
CudaModulusSwitchNoiseReductionKeyFFI const *ms_noise_reduction_key);
void cleanup_cuda_integer_radix_cmux(CudaStreamsFFI streams,
int8_t **mem_ptr_void);
@@ -326,7 +321,8 @@ uint64_t scratch_cuda_integer_radix_scalar_rotate_kb_64(
void cuda_integer_radix_scalar_rotate_kb_64_inplace(
CudaStreamsFFI streams, CudaRadixCiphertextFFI *lwe_array, uint32_t n,
int8_t *mem_ptr, void *const *bsks, void *const *ksks);
int8_t *mem_ptr, void *const *bsks, void *const *ksks,
CudaModulusSwitchNoiseReductionKeyFFI const *ms_noise_reduction_key);
void cleanup_cuda_integer_radix_scalar_rotate(CudaStreamsFFI streams,
int8_t **mem_ptr_void);
@@ -353,13 +349,16 @@ void cuda_propagate_single_carry_kb_64_inplace(
CudaStreamsFFI streams, CudaRadixCiphertextFFI *lwe_array,
CudaRadixCiphertextFFI *carry_out, const CudaRadixCiphertextFFI *carry_in,
int8_t *mem_ptr, void *const *bsks, void *const *ksks,
CudaModulusSwitchNoiseReductionKeyFFI const *ms_noise_reduction_key,
uint32_t requested_flag, uint32_t uses_carry);
void cuda_add_and_propagate_single_carry_kb_64_inplace(
CudaStreamsFFI streams, CudaRadixCiphertextFFI *lhs_array,
const CudaRadixCiphertextFFI *rhs_array, CudaRadixCiphertextFFI *carry_out,
const CudaRadixCiphertextFFI *carry_in, int8_t *mem_ptr, void *const *bsks,
void *const *ksks, uint32_t requested_flag, uint32_t uses_carry);
void *const *ksks,
CudaModulusSwitchNoiseReductionKeyFFI const *ms_noise_reduction_key,
uint32_t requested_flag, uint32_t uses_carry);
void cleanup_cuda_propagate_single_carry(CudaStreamsFFI streams,
int8_t **mem_ptr_void);
@@ -381,8 +380,9 @@ void cuda_integer_overflowing_sub_kb_64_inplace(
const CudaRadixCiphertextFFI *rhs_array,
CudaRadixCiphertextFFI *overflow_block,
const CudaRadixCiphertextFFI *input_borrow, int8_t *mem_ptr,
void *const *bsks, void *const *ksks, uint32_t compute_overflow,
uint32_t uses_input_borrow);
void *const *bsks, void *const *ksks,
CudaModulusSwitchNoiseReductionKeyFFI const *ms_noise_reduction_key,
uint32_t compute_overflow, uint32_t uses_input_borrow);
void cleanup_cuda_integer_overflowing_sub(CudaStreamsFFI streams,
int8_t **mem_ptr_void);
@@ -400,7 +400,8 @@ uint64_t scratch_cuda_integer_radix_partial_sum_ciphertexts_vec_kb_64(
void cuda_integer_radix_partial_sum_ciphertexts_vec_kb_64(
CudaStreamsFFI streams, CudaRadixCiphertextFFI *radix_lwe_out,
CudaRadixCiphertextFFI *radix_lwe_vec, int8_t *mem_ptr, void *const *bsks,
void *const *ksks);
void *const *ksks,
CudaModulusSwitchNoiseReductionKeyFFI const *ms_noise_reduction_key);
void cleanup_cuda_integer_radix_partial_sum_ciphertexts_vec(
CudaStreamsFFI streams, int8_t **mem_ptr_void);
@@ -417,6 +418,7 @@ void cuda_scalar_multiplication_integer_radix_ciphertext_64_inplace(
CudaStreamsFFI streams, CudaRadixCiphertextFFI *lwe_array,
uint64_t const *decomposed_scalar, uint64_t const *has_at_least_one_set,
int8_t *mem_ptr, void *const *bsks, void *const *ksks,
CudaModulusSwitchNoiseReductionKeyFFI const *ms_noise_reduction_key,
uint32_t polynomial_size, uint32_t message_modulus, uint32_t num_scalars);
void cleanup_cuda_integer_radix_scalar_mul(CudaStreamsFFI streams,
@@ -435,7 +437,8 @@ void cuda_integer_div_rem_radix_ciphertext_kb_64(
CudaStreamsFFI streams, CudaRadixCiphertextFFI *quotient,
CudaRadixCiphertextFFI *remainder, CudaRadixCiphertextFFI const *numerator,
CudaRadixCiphertextFFI const *divisor, bool is_signed, int8_t *mem_ptr,
void *const *bsks, void *const *ksks);
void *const *bsks, void *const *ksks,
CudaModulusSwitchNoiseReductionKeyFFI const *ms_noise_reduction_key);
void cleanup_cuda_integer_div_rem(CudaStreamsFFI streams,
int8_t **mem_ptr_void);
@@ -452,7 +455,9 @@ uint64_t scratch_cuda_integer_compute_prefix_sum_hillis_steele_64(
void cuda_integer_compute_prefix_sum_hillis_steele_64(
CudaStreamsFFI streams, CudaRadixCiphertextFFI *output_radix_lwe,
CudaRadixCiphertextFFI *generates_or_propagates, int8_t *mem_ptr,
void *const *ksks, void *const *bsks, uint32_t num_blocks);
void *const *ksks,
CudaModulusSwitchNoiseReductionKeyFFI const *ms_noise_reduction_key,
void *const *bsks, uint32_t num_blocks);
void cleanup_cuda_integer_compute_prefix_sum_hillis_steele_64(
CudaStreamsFFI streams, int8_t **mem_ptr_void);
@@ -471,7 +476,8 @@ uint64_t scratch_cuda_integer_abs_inplace_radix_ciphertext_kb_64(
void cuda_integer_abs_inplace_radix_ciphertext_kb_64(
CudaStreamsFFI streams, CudaRadixCiphertextFFI *ct, int8_t *mem_ptr,
bool is_signed, void *const *bsks, void *const *ksks);
bool is_signed, void *const *bsks, void *const *ksks,
CudaModulusSwitchNoiseReductionKeyFFI const *ms_noise_reduction_key);
void cleanup_cuda_integer_abs_inplace(CudaStreamsFFI streams,
int8_t **mem_ptr_void);
@@ -488,7 +494,9 @@ uint64_t scratch_cuda_integer_are_all_comparisons_block_true_kb_64(
void cuda_integer_are_all_comparisons_block_true_kb_64(
CudaStreamsFFI streams, CudaRadixCiphertextFFI *lwe_array_out,
CudaRadixCiphertextFFI const *lwe_array_in, int8_t *mem_ptr,
void *const *bsks, void *const *ksks, uint32_t num_radix_blocks);
void *const *bsks, void *const *ksks,
CudaModulusSwitchNoiseReductionKeyFFI const *ms_noise_reduction_key,
uint32_t num_radix_blocks);
void cleanup_cuda_integer_are_all_comparisons_block_true(CudaStreamsFFI streams,
int8_t **mem_ptr_void);
@@ -505,7 +513,9 @@ uint64_t scratch_cuda_integer_is_at_least_one_comparisons_block_true_kb_64(
void cuda_integer_is_at_least_one_comparisons_block_true_kb_64(
CudaStreamsFFI streams, CudaRadixCiphertextFFI *lwe_array_out,
CudaRadixCiphertextFFI const *lwe_array_in, int8_t *mem_ptr,
void *const *bsks, void *const *ksks, uint32_t num_radix_blocks);
void *const *bsks, void *const *ksks,
CudaModulusSwitchNoiseReductionKeyFFI const *ms_noise_reduction_key,
uint32_t num_radix_blocks);
void cleanup_cuda_integer_is_at_least_one_comparisons_block_true(
CudaStreamsFFI streams, int8_t **mem_ptr_void);
@@ -531,7 +541,9 @@ uint64_t scratch_cuda_apply_noise_squashing_kb(
void cuda_apply_noise_squashing_kb(
CudaStreamsFFI streams, CudaRadixCiphertextFFI *output_radix_lwe,
CudaRadixCiphertextFFI const *input_radix_lwe, int8_t *mem_ptr,
void *const *ksks, void *const *bsks);
void *const *ksks,
CudaModulusSwitchNoiseReductionKeyFFI const *ms_noise_reduction_key,
void *const *bsks);
void cleanup_cuda_apply_noise_squashing_kb(CudaStreamsFFI streams,
int8_t **mem_ptr_void);
@@ -549,7 +561,9 @@ void cuda_sub_and_propagate_single_carry_kb_64_inplace(
CudaStreamsFFI streams, CudaRadixCiphertextFFI *lhs_array,
const CudaRadixCiphertextFFI *rhs_array, CudaRadixCiphertextFFI *carry_out,
const CudaRadixCiphertextFFI *carry_in, int8_t *mem_ptr, void *const *bsks,
void *const *ksks, uint32_t requested_flag, uint32_t uses_carry);
void *const *ksks,
CudaModulusSwitchNoiseReductionKeyFFI const *ms_noise_reduction_key,
uint32_t requested_flag, uint32_t uses_carry);
void cleanup_cuda_sub_and_propagate_single_carry(CudaStreamsFFI streams,
int8_t **mem_ptr_void);
@@ -566,6 +580,7 @@ uint64_t scratch_cuda_integer_unsigned_scalar_div_radix_kb_64(
void cuda_integer_unsigned_scalar_div_radix_kb_64(
CudaStreamsFFI streams, CudaRadixCiphertextFFI *numerator_ct,
int8_t *mem_ptr, void *const *bsks, void *const *ksks,
const CudaModulusSwitchNoiseReductionKeyFFI *ms_noise_reduction_key,
const CudaScalarDivisorFFI *scalar_divisor_ffi);
void cleanup_cuda_integer_unsigned_scalar_div_radix_kb_64(
@@ -580,12 +595,11 @@ uint64_t scratch_cuda_extend_radix_with_sign_msb_64(
uint32_t carry_modulus, PBS_TYPE pbs_type, bool allocate_gpu_memory,
PBS_MS_REDUCTION_T noise_reduction_type);
void cuda_extend_radix_with_sign_msb_64(CudaStreamsFFI streams,
CudaRadixCiphertextFFI *output,
CudaRadixCiphertextFFI const *input,
int8_t *mem_ptr,
uint32_t num_additional_blocks,
void *const *bsks, void *const *ksks);
void cuda_extend_radix_with_sign_msb_64(
CudaStreamsFFI streams, CudaRadixCiphertextFFI *output,
CudaRadixCiphertextFFI const *input, int8_t *mem_ptr,
uint32_t num_additional_blocks, void *const *bsks, void *const *ksks,
CudaModulusSwitchNoiseReductionKeyFFI const *ms_noise_reduction_key);
void cleanup_cuda_extend_radix_with_sign_msb_64(CudaStreamsFFI streams,
int8_t **mem_ptr_void);
@@ -602,6 +616,7 @@ uint64_t scratch_cuda_integer_signed_scalar_div_radix_kb_64(
void cuda_integer_signed_scalar_div_radix_kb_64(
CudaStreamsFFI streams, CudaRadixCiphertextFFI *numerator_ct,
int8_t *mem_ptr, void *const *bsks, void *const *ksks,
const CudaModulusSwitchNoiseReductionKeyFFI *ms_noise_reduction_key,
const CudaScalarDivisorFFI *scalar_divisor_ffi, uint32_t numerator_bits);
void cleanup_cuda_integer_signed_scalar_div_radix_kb_64(CudaStreamsFFI streams,
@@ -620,7 +635,9 @@ uint64_t scratch_integer_unsigned_scalar_div_rem_radix_kb_64(
void cuda_integer_unsigned_scalar_div_rem_radix_kb_64(
CudaStreamsFFI streams, CudaRadixCiphertextFFI *quotient_ct,
CudaRadixCiphertextFFI *remainder_ct, int8_t *mem_ptr, void *const *bsks,
void *const *ksks, const CudaScalarDivisorFFI *scalar_divisor_ffi,
void *const *ksks,
const CudaModulusSwitchNoiseReductionKeyFFI *ms_noise_reduction_key,
const CudaScalarDivisorFFI *scalar_divisor_ffi,
uint64_t const *divisor_has_at_least_one_set,
uint64_t const *decomposed_divisor, uint32_t const num_scalars_divisor,
void const *clear_blocks, void const *h_clear_blocks,
@@ -642,7 +659,9 @@ uint64_t scratch_integer_signed_scalar_div_rem_radix_kb_64(
void cuda_integer_signed_scalar_div_rem_radix_kb_64(
CudaStreamsFFI streams, CudaRadixCiphertextFFI *quotient_ct,
CudaRadixCiphertextFFI *remainder_ct, int8_t *mem_ptr, void *const *bsks,
void *const *ksks, const CudaScalarDivisorFFI *scalar_divisor_ffi,
void *const *ksks,
CudaModulusSwitchNoiseReductionKeyFFI const *ms_noise_reduction_key,
const CudaScalarDivisorFFI *scalar_divisor_ffi,
uint64_t const *divisor_has_at_least_one_set,
uint64_t const *decomposed_divisor, uint32_t const num_scalars_divisor,
uint32_t numerator_bits);
@@ -662,7 +681,8 @@ uint64_t scratch_integer_count_of_consecutive_bits_kb_64(
void cuda_integer_count_of_consecutive_bits_kb_64(
CudaStreamsFFI streams, CudaRadixCiphertextFFI *output_ct,
CudaRadixCiphertextFFI const *input_ct, int8_t *mem_ptr, void *const *bsks,
void *const *ksks);
void *const *ksks,
const CudaModulusSwitchNoiseReductionKeyFFI *ms_noise_reduction_key);
void cleanup_cuda_integer_count_of_consecutive_bits_kb_64(
CudaStreamsFFI streams, int8_t **mem_ptr_void);
@@ -672,15 +692,16 @@ uint64_t scratch_cuda_integer_grouped_oprf_64(
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);
uint32_t num_blocks, 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);
void cuda_integer_grouped_oprf_async_64(CudaStreamsFFI streams,
CudaRadixCiphertextFFI *radix_lwe_out,
const void *seeded_lwe_input,
uint32_t num_blocks_to_process,
int8_t *mem, void *const *bsks);
void cuda_integer_grouped_oprf_async_64(
CudaStreamsFFI streams, CudaRadixCiphertextFFI *radix_lwe_out,
const void *seeded_lwe_input, uint32_t num_blocks_to_process, int8_t *mem,
void *const *bsks,
CudaModulusSwitchNoiseReductionKeyFFI const *ms_noise_reduction_key);
void cleanup_cuda_integer_grouped_oprf_64(CudaStreamsFFI streams,
int8_t **mem_ptr_void);
@@ -700,7 +721,8 @@ void cuda_integer_ilog2_kb_64(
CudaRadixCiphertextFFI const *trivial_ct_neg_n,
CudaRadixCiphertextFFI const *trivial_ct_2,
CudaRadixCiphertextFFI const *trivial_ct_m_minus_1_block, int8_t *mem_ptr,
void *const *bsks, void *const *ksks);
void *const *bsks, void *const *ksks,
const CudaModulusSwitchNoiseReductionKeyFFI *ms_noise_reduction_key);
void cleanup_cuda_integer_ilog2_kb_64(CudaStreamsFFI streams,
int8_t **mem_ptr_void);

View File

@@ -3,6 +3,16 @@
#include <stdint.h>
enum PBS_TYPE { MULTI_BIT = 0, CLASSICAL = 1 };
enum PBS_VARIANT { DEFAULT = 0, CG = 1, TBC = 2 };
enum PBS_MS_REDUCTION_T { NO_REDUCTION = 0, CENTERED = 1 };
enum PBS_MS_REDUCTION_T { NO_REDUCTION = 0, DRIFT = 1, CENTERED = 2 };
extern "C" {
typedef struct {
void *const *ptr;
uint32_t num_zeros;
double ms_bound;
double ms_r_sigma;
double ms_input_variance;
} CudaModulusSwitchNoiseReductionKeyFFI;
}
#endif // CUDA_PBS_ENUMS_H

View File

@@ -80,6 +80,7 @@ template <typename Torus> struct pbs_buffer<Torus, PBS_TYPE::CLASSICAL> {
Torus *global_accumulator;
double2 *global_join_buffer;
Torus *temp_lwe_array_in;
PBS_VARIANT pbs_variant;
PBS_MS_REDUCTION_T noise_reduction_type;
@@ -96,6 +97,10 @@ template <typename Torus> struct pbs_buffer<Torus, PBS_TYPE::CLASSICAL> {
this->pbs_variant = pbs_variant;
auto max_shared_memory = cuda_get_max_shared_memory(gpu_index);
this->temp_lwe_array_in = (Torus *)cuda_malloc_with_size_tracking_async(
(lwe_dimension + 1) * input_lwe_ciphertext_count * sizeof(Torus),
stream, gpu_index, size_tracker,
noise_reduction_type == PBS_MS_REDUCTION_T::DRIFT);
switch (pbs_variant) {
case PBS_VARIANT::DEFAULT: {
uint64_t full_sm_step_one =
@@ -229,6 +234,10 @@ template <typename Torus> struct pbs_buffer<Torus, PBS_TYPE::CLASSICAL> {
if (pbs_variant == DEFAULT)
cuda_drop_with_size_tracking_async(global_accumulator, stream, gpu_index,
gpu_memory_allocated);
if (noise_reduction_type == PBS_MS_REDUCTION_T::DRIFT)
cuda_drop_with_size_tracking_async(temp_lwe_array_in, stream, gpu_index,
gpu_memory_allocated);
}
};
@@ -240,6 +249,8 @@ struct pbs_buffer_128<InputTorus, PBS_TYPE::CLASSICAL> {
__uint128_t *global_accumulator;
double *global_join_buffer;
InputTorus *temp_lwe_array_in;
uint64_t *trivial_indexes;
PBS_VARIANT pbs_variant;
PBS_MS_REDUCTION_T noise_reduction_type;
@@ -257,6 +268,27 @@ struct pbs_buffer_128<InputTorus, PBS_TYPE::CLASSICAL> {
cuda_set_device(gpu_index);
this->pbs_variant = pbs_variant;
if (noise_reduction_type == PBS_MS_REDUCTION_T::DRIFT) {
this->temp_lwe_array_in =
(InputTorus *)cuda_malloc_with_size_tracking_async(
(lwe_dimension + 1) * input_lwe_ciphertext_count *
sizeof(InputTorus),
stream, gpu_index, size_tracker, allocate_gpu_memory);
this->trivial_indexes = (uint64_t *)cuda_malloc_with_size_tracking_async(
input_lwe_ciphertext_count * sizeof(uint64_t), stream, gpu_index,
size_tracker, allocate_gpu_memory);
uint64_t *h_trivial_indexes = new uint64_t[input_lwe_ciphertext_count];
for (uint32_t i = 0; i < input_lwe_ciphertext_count; i++)
h_trivial_indexes[i] = i;
cuda_memcpy_with_size_tracking_async_to_gpu(
trivial_indexes, h_trivial_indexes,
input_lwe_ciphertext_count * sizeof(uint64_t), stream, gpu_index,
allocate_gpu_memory);
cuda_synchronize_stream(stream, gpu_index);
delete[] h_trivial_indexes;
}
auto max_shared_memory = cuda_get_max_shared_memory(gpu_index);
size_t global_join_buffer_size = (glwe_dimension + 1) * level_count *
input_lwe_ciphertext_count *
@@ -392,6 +424,13 @@ struct pbs_buffer_128<InputTorus, PBS_TYPE::CLASSICAL> {
if (pbs_variant == DEFAULT)
cuda_drop_with_size_tracking_async(global_accumulator, stream, gpu_index,
gpu_memory_allocated);
if (noise_reduction_type == PBS_MS_REDUCTION_T::DRIFT) {
cuda_drop_with_size_tracking_async(temp_lwe_array_in, stream, gpu_index,
gpu_memory_allocated);
cuda_drop_with_size_tracking_async(trivial_indexes, stream, gpu_index,
gpu_memory_allocated);
}
}
};

View File

@@ -89,14 +89,18 @@ void cuda_programmable_bootstrap_lwe_ciphertext_vector_64(
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 base_log, uint32_t level_count,
uint32_t num_samples, uint32_t num_many_lut, uint32_t lut_stride);
CudaModulusSwitchNoiseReductionKeyFFI const *ms_noise_reduction_key,
void *ms_noise_reduction_ptr, int8_t *buffer, uint32_t lwe_dimension,
uint32_t glwe_dimension, uint32_t polynomial_size, uint32_t base_log,
uint32_t level_count, uint32_t num_samples, uint32_t num_many_lut,
uint32_t lut_stride);
void cuda_programmable_bootstrap_lwe_ciphertext_vector_128(
void *stream, uint32_t gpu_index, void *lwe_array_out,
void const *lut_vector, void const *lwe_array_in,
void const *bootstrapping_key, int8_t *buffer, uint32_t lwe_dimension,
void const *bootstrapping_key,
CudaModulusSwitchNoiseReductionKeyFFI const *ms_noise_reduction_key,
void const *ms_noise_reduction_ptr, int8_t *buffer, uint32_t lwe_dimension,
uint32_t glwe_dimension, uint32_t polynomial_size, uint32_t base_log,
uint32_t level_count, uint32_t num_samples);

View File

@@ -22,7 +22,8 @@ uint64_t scratch_cuda_expand_without_verification_64(
void cuda_expand_without_verification_64(
CudaStreamsFFI streams, void *lwe_array_out,
const void *lwe_flattened_compact_array_in, int8_t *mem_ptr,
void *const *bsks, void *const *computing_ksks, void *const *casting_keys);
void *const *bsks, void *const *computing_ksks, void *const *casting_keys,
CudaModulusSwitchNoiseReductionKeyFFI const *ms_noise_reduction_key);
void cleanup_expand_without_verification_64(CudaStreamsFFI streams,
int8_t **mem_ptr_void);

View File

@@ -1,88 +0,0 @@
#include "../../include/aes/aes.h"
#include "aes.cuh"
uint64_t scratch_cuda_integer_aes_encrypt_64(
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) {
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);
return scratch_cuda_integer_aes_encrypt<uint64_t>(
CudaStreams(streams), (int_aes_encrypt_buffer<uint64_t> **)mem_ptr,
params, allocate_gpu_memory, num_aes_inputs, sbox_parallelism);
}
void cuda_integer_aes_ctr_encrypt_64(CudaStreamsFFI streams,
CudaRadixCiphertextFFI *output,
CudaRadixCiphertextFFI const *iv,
CudaRadixCiphertextFFI const *round_keys,
const uint64_t *counter_bits_le_all_blocks,
uint32_t num_aes_inputs, int8_t *mem_ptr,
void *const *bsks, void *const *ksks) {
host_integer_aes_ctr_encrypt<uint64_t>(
CudaStreams(streams), output, iv, round_keys, counter_bits_le_all_blocks,
num_aes_inputs, (int_aes_encrypt_buffer<uint64_t> *)mem_ptr, bsks,
(uint64_t **)ksks);
}
void cleanup_cuda_integer_aes_encrypt_64(CudaStreamsFFI streams,
int8_t **mem_ptr_void) {
int_aes_encrypt_buffer<uint64_t> *mem_ptr =
(int_aes_encrypt_buffer<uint64_t> *)(*mem_ptr_void);
mem_ptr->release(CudaStreams(streams));
delete mem_ptr;
*mem_ptr_void = nullptr;
}
uint64_t scratch_cuda_integer_key_expansion_64(
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) {
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);
return scratch_cuda_integer_key_expansion<uint64_t>(
CudaStreams(streams), (int_key_expansion_buffer<uint64_t> **)mem_ptr,
params, allocate_gpu_memory);
}
void cuda_integer_key_expansion_64(CudaStreamsFFI streams,
CudaRadixCiphertextFFI *expanded_keys,
CudaRadixCiphertextFFI const *key,
int8_t *mem_ptr, void *const *bsks,
void *const *ksks) {
host_integer_key_expansion<uint64_t>(
CudaStreams(streams), expanded_keys, key,
(int_key_expansion_buffer<uint64_t> *)mem_ptr, bsks, (uint64_t **)ksks);
}
void cleanup_cuda_integer_key_expansion_64(CudaStreamsFFI streams,
int8_t **mem_ptr_void) {
int_key_expansion_buffer<uint64_t> *mem_ptr =
(int_key_expansion_buffer<uint64_t> *)(*mem_ptr_void);
mem_ptr->release(CudaStreams(streams));
delete mem_ptr;
*mem_ptr_void = nullptr;
}

File diff suppressed because it is too large Load Diff

View File

@@ -103,6 +103,23 @@ void cuda_centered_modulus_switch_64(void *stream, uint32_t gpu_index,
lwe_dimension, log_modulus);
}
// This end point is used only for testing purposes
// its output always follows trivial ordering
void cuda_improve_noise_modulus_switch_64(
void *stream, uint32_t gpu_index, void *lwe_array_out,
void const *lwe_array_in, void const *lwe_array_indexes,
void const *encrypted_zeros, uint32_t lwe_size, uint32_t num_lwes,
uint32_t num_zeros, double input_variance, double r_sigma, double bound,
uint32_t log_modulus) {
host_drift_modulus_switch<uint64_t>(
static_cast<cudaStream_t>(stream), gpu_index,
static_cast<uint64_t *>(lwe_array_out),
static_cast<uint64_t const *>(lwe_array_in),
static_cast<uint64_t const *>(lwe_array_indexes),
static_cast<const uint64_t *>(encrypted_zeros), lwe_size, num_lwes,
num_zeros, input_variance, r_sigma, bound, log_modulus);
}
void cuda_glwe_sample_extract_128(
void *stream, uint32_t gpu_index, void *lwe_array_out,
void const *glwe_array_in, uint32_t const *nth_array, uint32_t num_nths,

View File

@@ -36,7 +36,7 @@ __device__ Torus *get_ith_block(Torus *ksk, int i, int level,
*
*/
// Each thread in x are used to calculate one output.
// threads in y are used to parallelize the lwe_dimension_in loop.
// threads in y are used to paralelize the lwe_dimension_in loop.
// shared memory is used to store intermediate results of the reduction.
// Note: To reduce register pressure we have slightly changed the algorithm,
// the idea consists in calculating the negate value of the output. So, instead

View File

@@ -426,4 +426,31 @@ __global__ void __launch_bounds__(512)
}
}
template <typename Torus>
__host__ void host_drift_modulus_switch(
cudaStream_t stream, uint32_t gpu_index, Torus *array_out,
Torus const *array_in, uint64_t const *indexes, const Torus *zeros,
uint32_t lwe_size, uint32_t num_lwes, const uint32_t num_zeros,
const double input_variance, const double r_sigma, const double bound,
uint32_t log_modulus) {
PANIC_IF_FALSE(lwe_size >= 512,
"The lwe_size (%d) is less than 512, this is not supported\n",
lwe_size);
PANIC_IF_FALSE(
lwe_size <= 1024,
"The lwe_size (%d) is greater than 1024, this is not supported\n",
lwe_size);
cuda_set_device(gpu_index);
// This reduction requires a power of two num of threads
int num_threads = 512, num_blocks = num_lwes;
improve_noise_modulus_switch<Torus><<<num_blocks, num_threads, 0, stream>>>(
array_out, array_in, indexes, zeros, lwe_size, num_zeros, input_variance,
r_sigma, bound, log_modulus);
check_cuda_error(cudaGetLastError());
}
#endif // CNCRT_TORUS_H

View File

@@ -266,11 +266,6 @@ void cuda_memcpy_with_size_tracking_async_gpu_to_gpu(
uint32_t gpu_index, bool gpu_memory_allocated) {
if (size == 0 || !gpu_memory_allocated)
return;
GPU_ASSERT(dest != nullptr,
"Cuda error: trying to copy gpu->gpu to null ptr");
GPU_ASSERT(src != nullptr,
"Cuda error: trying to copy gpu->gpu from null ptr");
cudaPointerAttributes attr_dest;
check_cuda_error(cudaPointerGetAttributes(&attr_dest, dest));
PANIC_IF_FALSE(

View File

@@ -21,12 +21,14 @@ uint64_t scratch_cuda_integer_abs_inplace_radix_ciphertext_kb_64(
void cuda_integer_abs_inplace_radix_ciphertext_kb_64(
CudaStreamsFFI streams, CudaRadixCiphertextFFI *ct, int8_t *mem_ptr,
bool is_signed, void *const *bsks, void *const *ksks) {
bool is_signed, void *const *bsks, void *const *ksks,
CudaModulusSwitchNoiseReductionKeyFFI const *ms_noise_reduction_key) {
auto mem = (int_abs_buffer<uint64_t> *)mem_ptr;
host_integer_abs_kb<uint64_t>(CudaStreams(streams), ct, bsks,
(uint64_t **)(ksks), mem, is_signed);
(uint64_t **)(ksks), ms_noise_reduction_key,
mem, is_signed);
}
void cleanup_cuda_integer_abs_inplace(CudaStreamsFFI streams,

View File

@@ -30,10 +30,11 @@ __host__ uint64_t scratch_cuda_integer_abs_kb(
}
template <typename Torus>
__host__ void
host_integer_abs_kb(CudaStreams streams, CudaRadixCiphertextFFI *ct,
void *const *bsks, uint64_t *const *ksks,
int_abs_buffer<uint64_t> *mem_ptr, bool is_signed) {
__host__ void host_integer_abs_kb(
CudaStreams streams, CudaRadixCiphertextFFI *ct, void *const *bsks,
uint64_t *const *ksks,
CudaModulusSwitchNoiseReductionKeyFFI const *ms_noise_reduction_key,
int_abs_buffer<uint64_t> *mem_ptr, bool is_signed) {
if (!is_signed)
return;
@@ -48,19 +49,19 @@ host_integer_abs_kb(CudaStreams streams, CudaRadixCiphertextFFI *ct,
host_integer_radix_arithmetic_scalar_shift_kb_inplace<Torus>(
streams, mask, num_bits_in_ciphertext - 1,
mem_ptr->arithmetic_scalar_shift_mem, bsks, ksks);
mem_ptr->arithmetic_scalar_shift_mem, bsks, ksks, ms_noise_reduction_key);
host_addition<Torus>(streams.stream(0), streams.gpu_index(0), ct, mask, ct,
ct->num_radix_blocks, mem_ptr->params.message_modulus,
mem_ptr->params.carry_modulus);
uint32_t requested_flag = outputFlag::FLAG_NONE;
uint32_t uses_carry = 0;
host_propagate_single_carry<Torus>(streams, ct, nullptr, nullptr,
mem_ptr->scp_mem, bsks, ksks,
requested_flag, uses_carry);
host_propagate_single_carry<Torus>(
streams, ct, nullptr, nullptr, mem_ptr->scp_mem, bsks, ksks,
ms_noise_reduction_key, requested_flag, uses_carry);
host_integer_radix_bitop_kb<Torus>(streams, ct, mask, ct, mem_ptr->bitxor_mem,
bsks, ksks);
bsks, ksks, ms_noise_reduction_key);
}
#endif // TFHE_RS_ABS_CUH

View File

@@ -23,11 +23,13 @@ void cuda_bitop_integer_radix_ciphertext_kb_64(
CudaStreamsFFI streams, CudaRadixCiphertextFFI *lwe_array_out,
CudaRadixCiphertextFFI const *lwe_array_1,
CudaRadixCiphertextFFI const *lwe_array_2, int8_t *mem_ptr,
void *const *bsks, void *const *ksks) {
void *const *bsks, void *const *ksks,
CudaModulusSwitchNoiseReductionKeyFFI const *ms_noise_reduction_key) {
host_integer_radix_bitop_kb<uint64_t>(
CudaStreams(streams), lwe_array_out, lwe_array_1, lwe_array_2,
(int_bitop_buffer<uint64_t> *)mem_ptr, bsks, (uint64_t **)(ksks));
(int_bitop_buffer<uint64_t> *)mem_ptr, bsks, (uint64_t **)(ksks),
ms_noise_reduction_key);
}
void cleanup_cuda_integer_bitop(CudaStreamsFFI streams, int8_t **mem_ptr_void) {

View File

@@ -16,7 +16,8 @@ __host__ void host_integer_radix_bitop_kb(
CudaStreams streams, CudaRadixCiphertextFFI *lwe_array_out,
CudaRadixCiphertextFFI const *lwe_array_1,
CudaRadixCiphertextFFI const *lwe_array_2, int_bitop_buffer<Torus> *mem_ptr,
void *const *bsks, Torus *const *ksks) {
void *const *bsks, Torus *const *ksks,
CudaModulusSwitchNoiseReductionKeyFFI const *ms_noise_reduction_key) {
PANIC_IF_FALSE(
lwe_array_out->num_radix_blocks == lwe_array_1->num_radix_blocks &&
@@ -44,8 +45,9 @@ __host__ void host_integer_radix_bitop_kb(
}
integer_radix_apply_bivariate_lookup_table_kb<Torus>(
streams, lwe_array_out, lwe_array_1, lwe_array_2, bsks, ksks, lut,
lwe_array_out->num_radix_blocks, lut->params.message_modulus);
streams, lwe_array_out, lwe_array_1, lwe_array_2, bsks, ksks,
ms_noise_reduction_key, lut, lwe_array_out->num_radix_blocks,
lut->params.message_modulus);
memcpy(lwe_array_out->degrees, degrees,
lwe_array_out->num_radix_blocks * sizeof(uint64_t));

View File

@@ -35,17 +35,16 @@ uint64_t scratch_cuda_extend_radix_with_sign_msb_64(
num_blocks, num_additional_blocks, allocate_gpu_memory);
}
void cuda_extend_radix_with_sign_msb_64(CudaStreamsFFI streams,
CudaRadixCiphertextFFI *output,
CudaRadixCiphertextFFI const *input,
int8_t *mem_ptr,
uint32_t num_additional_blocks,
void *const *bsks, void *const *ksks) {
void cuda_extend_radix_with_sign_msb_64(
CudaStreamsFFI streams, CudaRadixCiphertextFFI *output,
CudaRadixCiphertextFFI const *input, int8_t *mem_ptr,
uint32_t num_additional_blocks, void *const *bsks, void *const *ksks,
CudaModulusSwitchNoiseReductionKeyFFI const *ms_noise_reduction_key) {
PUSH_RANGE("cast")
host_extend_radix_with_sign_msb<uint64_t>(
CudaStreams(streams), output, input,
(int_extend_radix_with_sign_msb_buffer<uint64_t> *)mem_ptr,
num_additional_blocks, bsks, (uint64_t **)ksks);
num_additional_blocks, bsks, (uint64_t **)ksks, ms_noise_reduction_key);
POP_RANGE()
}

View File

@@ -55,7 +55,8 @@ __host__ void host_extend_radix_with_sign_msb(
CudaStreams streams, CudaRadixCiphertextFFI *output,
CudaRadixCiphertextFFI const *input,
int_extend_radix_with_sign_msb_buffer<Torus> *mem_ptr,
uint32_t num_additional_blocks, void *const *bsks, Torus *const *ksks) {
uint32_t num_additional_blocks, void *const *bsks, Torus *const *ksks,
CudaModulusSwitchNoiseReductionKeyFFI const *ms_noise_reduction_key) {
if (num_additional_blocks == 0) {
PUSH_RANGE("cast/extend no addblocks")
@@ -78,7 +79,8 @@ __host__ void host_extend_radix_with_sign_msb(
input_blocks - 1, input_blocks);
host_apply_univariate_lut_kb(streams, mem_ptr->padding_block,
mem_ptr->last_block, mem_ptr->lut, ksks, bsks);
mem_ptr->last_block, mem_ptr->lut, ksks,
ms_noise_reduction_key, bsks);
for (uint32_t i = 0; i < num_additional_blocks; ++i) {
uint32_t dst_block_idx = input_blocks + i;

View File

@@ -29,12 +29,13 @@ void cuda_cmux_integer_radix_ciphertext_kb_64(
CudaRadixCiphertextFFI const *lwe_condition,
CudaRadixCiphertextFFI const *lwe_array_true,
CudaRadixCiphertextFFI const *lwe_array_false, int8_t *mem_ptr,
void *const *bsks, void *const *ksks) {
void *const *bsks, void *const *ksks,
CudaModulusSwitchNoiseReductionKeyFFI const *ms_noise_reduction_key) {
PUSH_RANGE("cmux")
host_integer_radix_cmux_kb<uint64_t>(
CudaStreams(streams), lwe_array_out, lwe_condition, lwe_array_true,
lwe_array_false, (int_cmux_buffer<uint64_t> *)mem_ptr, bsks,
(uint64_t **)(ksks));
(uint64_t **)(ksks), ms_noise_reduction_key);
POP_RANGE()
}

View File

@@ -5,13 +5,15 @@
#include "radix_ciphertext.cuh"
template <typename Torus>
__host__ void zero_out_if(CudaStreams streams,
CudaRadixCiphertextFFI *lwe_array_out,
CudaRadixCiphertextFFI const *lwe_array_input,
CudaRadixCiphertextFFI const *lwe_condition,
int_zero_out_if_buffer<Torus> *mem_ptr,
int_radix_lut<Torus> *predicate, void *const *bsks,
Torus *const *ksks, uint32_t num_radix_blocks) {
__host__ void
zero_out_if(CudaStreams streams, CudaRadixCiphertextFFI *lwe_array_out,
CudaRadixCiphertextFFI const *lwe_array_input,
CudaRadixCiphertextFFI const *lwe_condition,
int_zero_out_if_buffer<Torus> *mem_ptr,
int_radix_lut<Torus> *predicate, void *const *bsks,
Torus *const *ksks,
CudaModulusSwitchNoiseReductionKeyFFI const *ms_noise_reduction_key,
uint32_t num_radix_blocks) {
PANIC_IF_FALSE(
lwe_array_out->num_radix_blocks >= num_radix_blocks &&
lwe_array_input->num_radix_blocks >= num_radix_blocks,
@@ -31,13 +33,13 @@ __host__ void zero_out_if(CudaStreams streams,
// second operand is not an array
auto tmp_lwe_array_input = mem_ptr->tmp;
host_pack_bivariate_blocks_with_single_block<Torus>(
streams, tmp_lwe_array_input, predicate->lwe_indexes_in.get(), lwe_array_input,
lwe_condition, predicate->lwe_indexes_in.get(), params.message_modulus,
streams, tmp_lwe_array_input, predicate->lwe_indexes_in, lwe_array_input,
lwe_condition, predicate->lwe_indexes_in, params.message_modulus,
num_radix_blocks);
integer_radix_apply_univariate_lookup_table_kb<Torus>(
streams, lwe_array_out, tmp_lwe_array_input, bsks, ksks, predicate,
num_radix_blocks);
streams, lwe_array_out, tmp_lwe_array_input, bsks, ksks,
ms_noise_reduction_key, predicate, num_radix_blocks);
}
template <typename Torus>
@@ -46,7 +48,8 @@ __host__ void host_integer_radix_cmux_kb(
CudaRadixCiphertextFFI const *lwe_condition,
CudaRadixCiphertextFFI const *lwe_array_true,
CudaRadixCiphertextFFI const *lwe_array_false,
int_cmux_buffer<Torus> *mem_ptr, void *const *bsks, Torus *const *ksks) {
int_cmux_buffer<Torus> *mem_ptr, void *const *bsks, Torus *const *ksks,
CudaModulusSwitchNoiseReductionKeyFFI const *ms_noise_reduction_key) {
if (lwe_array_out->num_radix_blocks != lwe_array_true->num_radix_blocks)
PANIC("Cuda error: input and output num radix blocks must be the same")
@@ -70,8 +73,8 @@ __host__ void host_integer_radix_cmux_kb(
}
integer_radix_apply_bivariate_lookup_table_kb<Torus>(
streams, mem_ptr->buffer_out, mem_ptr->buffer_in,
mem_ptr->condition_array, bsks, ksks, mem_ptr->predicate_lut,
2 * num_radix_blocks, params.message_modulus);
mem_ptr->condition_array, bsks, ksks, ms_noise_reduction_key,
mem_ptr->predicate_lut, 2 * num_radix_blocks, params.message_modulus);
// If the condition was true, true_ct will have kept its value and false_ct
// will be 0 If the condition was false, true_ct will be 0 and false_ct will
@@ -88,7 +91,7 @@ __host__ void host_integer_radix_cmux_kb(
params.message_modulus, params.carry_modulus);
integer_radix_apply_univariate_lookup_table_kb<Torus>(
streams, lwe_array_out, &mem_true, bsks, ksks,
streams, lwe_array_out, &mem_true, bsks, ksks, ms_noise_reduction_key,
mem_ptr->message_extract_lut, num_radix_blocks);
}

View File

@@ -41,7 +41,8 @@ void cuda_comparison_integer_radix_ciphertext_kb_64(
CudaStreamsFFI streams, CudaRadixCiphertextFFI *lwe_array_out,
CudaRadixCiphertextFFI const *lwe_array_1,
CudaRadixCiphertextFFI const *lwe_array_2, int8_t *mem_ptr,
void *const *bsks, void *const *ksks) {
void *const *bsks, void *const *ksks,
CudaModulusSwitchNoiseReductionKeyFFI const *ms_noise_reduction_key) {
PUSH_RANGE("comparison")
if (lwe_array_1->num_radix_blocks != lwe_array_2->num_radix_blocks)
PANIC("Cuda error: input num radix blocks must be the same")
@@ -56,7 +57,7 @@ void cuda_comparison_integer_radix_ciphertext_kb_64(
case NE:
host_integer_radix_equality_check_kb<uint64_t>(
CudaStreams(streams), lwe_array_out, lwe_array_1, lwe_array_2, buffer,
bsks, (uint64_t **)(ksks), num_radix_blocks);
bsks, (uint64_t **)(ksks), ms_noise_reduction_key, num_radix_blocks);
break;
case GT:
case GE:
@@ -68,7 +69,7 @@ void cuda_comparison_integer_radix_ciphertext_kb_64(
host_integer_radix_difference_check_kb<uint64_t>(
CudaStreams(streams), lwe_array_out, lwe_array_1, lwe_array_2, buffer,
buffer->diff_buffer->operator_f, bsks, (uint64_t **)(ksks),
num_radix_blocks);
ms_noise_reduction_key, num_radix_blocks);
break;
case MAX:
case MIN:
@@ -76,7 +77,7 @@ void cuda_comparison_integer_radix_ciphertext_kb_64(
PANIC("Cuda error (max/min): the number of radix blocks has to be even.")
host_integer_radix_maxmin_kb<uint64_t>(
CudaStreams(streams), lwe_array_out, lwe_array_1, lwe_array_2, buffer,
bsks, (uint64_t **)(ksks), num_radix_blocks);
bsks, (uint64_t **)(ksks), ms_noise_reduction_key, num_radix_blocks);
break;
default:
PANIC("Cuda error: integer operation not supported")
@@ -117,14 +118,16 @@ uint64_t scratch_cuda_integer_are_all_comparisons_block_true_kb_64(
void cuda_integer_are_all_comparisons_block_true_kb_64(
CudaStreamsFFI streams, CudaRadixCiphertextFFI *lwe_array_out,
CudaRadixCiphertextFFI const *lwe_array_in, int8_t *mem_ptr,
void *const *bsks, void *const *ksks, uint32_t num_radix_blocks) {
void *const *bsks, void *const *ksks,
CudaModulusSwitchNoiseReductionKeyFFI const *ms_noise_reduction_key,
uint32_t num_radix_blocks) {
int_comparison_buffer<uint64_t> *buffer =
(int_comparison_buffer<uint64_t> *)mem_ptr;
host_integer_are_all_comparisons_block_true_kb<uint64_t>(
CudaStreams(streams), lwe_array_out, lwe_array_in, buffer, bsks,
(uint64_t **)(ksks), num_radix_blocks);
(uint64_t **)(ksks), ms_noise_reduction_key, num_radix_blocks);
}
void cleanup_cuda_integer_are_all_comparisons_block_true(
@@ -159,14 +162,16 @@ uint64_t scratch_cuda_integer_is_at_least_one_comparisons_block_true_kb_64(
void cuda_integer_is_at_least_one_comparisons_block_true_kb_64(
CudaStreamsFFI streams, CudaRadixCiphertextFFI *lwe_array_out,
CudaRadixCiphertextFFI const *lwe_array_in, int8_t *mem_ptr,
void *const *bsks, void *const *ksks, uint32_t num_radix_blocks) {
void *const *bsks, void *const *ksks,
CudaModulusSwitchNoiseReductionKeyFFI const *ms_noise_reduction_key,
uint32_t num_radix_blocks) {
int_comparison_buffer<uint64_t> *buffer =
(int_comparison_buffer<uint64_t> *)mem_ptr;
host_integer_is_at_least_one_comparisons_block_true_kb<uint64_t>(
CudaStreams(streams), lwe_array_out, lwe_array_in, buffer, bsks,
(uint64_t **)(ksks), num_radix_blocks);
(uint64_t **)(ksks), ms_noise_reduction_key, num_radix_blocks);
}
void cleanup_cuda_integer_is_at_least_one_comparisons_block_true(

View File

@@ -61,7 +61,9 @@ __host__ void are_all_comparisons_block_true(
CudaStreams streams, CudaRadixCiphertextFFI *lwe_array_out,
CudaRadixCiphertextFFI const *lwe_array_in,
int_comparison_buffer<Torus> *mem_ptr, void *const *bsks,
Torus *const *ksks, uint32_t num_radix_blocks) {
Torus *const *ksks,
CudaModulusSwitchNoiseReductionKeyFFI const *ms_noise_reduction_key,
uint32_t num_radix_blocks) {
if (lwe_array_out->lwe_dimension != lwe_array_in->lwe_dimension)
PANIC("Cuda error: input and output lwe dimensions must be the same")
@@ -156,7 +158,8 @@ __host__ void are_all_comparisons_block_true(
if (remaining_blocks == 1) {
// In the last iteration we copy the output to the final address
integer_radix_apply_univariate_lookup_table_kb<Torus>(
streams, lwe_array_out, accumulator, bsks, ksks, lut, 1);
streams, lwe_array_out, accumulator, bsks, ksks,
ms_noise_reduction_key, lut, 1);
// Reset max_value_lut_indexes before returning, otherwise if the lut is
// reused the lut indexes will be wrong
memset(is_max_value_lut->h_lut_indexes, 0,
@@ -173,7 +176,8 @@ __host__ void are_all_comparisons_block_true(
return;
} else {
integer_radix_apply_univariate_lookup_table_kb<Torus>(
streams, tmp_out, accumulator, bsks, ksks, lut, num_chunks);
streams, tmp_out, accumulator, bsks, ksks, ms_noise_reduction_key,
lut, num_chunks);
}
}
}
@@ -189,7 +193,9 @@ __host__ void is_at_least_one_comparisons_block_true(
CudaStreams streams, CudaRadixCiphertextFFI *lwe_array_out,
CudaRadixCiphertextFFI const *lwe_array_in,
int_comparison_buffer<Torus> *mem_ptr, void *const *bsks,
Torus *const *ksks, uint32_t num_radix_blocks) {
Torus *const *ksks,
CudaModulusSwitchNoiseReductionKeyFFI const *ms_noise_reduction_key,
uint32_t num_radix_blocks) {
if (lwe_array_out->lwe_dimension != lwe_array_in->lwe_dimension)
PANIC("Cuda error: input lwe dimensions must be the same")
@@ -243,12 +249,12 @@ __host__ void is_at_least_one_comparisons_block_true(
// In the last iteration we copy the output to the final address
integer_radix_apply_univariate_lookup_table_kb<Torus>(
streams, lwe_array_out, buffer->tmp_block_accumulated, bsks, ksks,
lut, 1);
ms_noise_reduction_key, lut, 1);
return;
} else {
integer_radix_apply_univariate_lookup_table_kb<Torus>(
streams, mem_ptr->tmp_lwe_array_out, buffer->tmp_block_accumulated,
bsks, ksks, lut, num_chunks);
bsks, ksks, ms_noise_reduction_key, lut, num_chunks);
}
}
}
@@ -258,8 +264,9 @@ __host__ void host_compare_blocks_with_zero(
CudaStreams streams, CudaRadixCiphertextFFI *lwe_array_out,
CudaRadixCiphertextFFI const *lwe_array_in,
int_comparison_buffer<Torus> *mem_ptr, void *const *bsks,
Torus *const *ksks, int32_t num_radix_blocks,
int_radix_lut<Torus> *zero_comparison) {
Torus *const *ksks,
CudaModulusSwitchNoiseReductionKeyFFI const *ms_noise_reduction_key,
int32_t num_radix_blocks, int_radix_lut<Torus> *zero_comparison) {
if (num_radix_blocks == 0)
return;
@@ -315,7 +322,8 @@ __host__ void host_compare_blocks_with_zero(
}
integer_radix_apply_univariate_lookup_table_kb<Torus>(
streams, lwe_array_out, sum, bsks, ksks, zero_comparison, num_sum_blocks);
streams, lwe_array_out, sum, bsks, ksks, ms_noise_reduction_key,
zero_comparison, num_sum_blocks);
reset_radix_ciphertext_blocks(lwe_array_out, num_sum_blocks);
}
@@ -326,7 +334,9 @@ __host__ void host_integer_radix_equality_check_kb(
CudaRadixCiphertextFFI const *lwe_array_1,
CudaRadixCiphertextFFI const *lwe_array_2,
int_comparison_buffer<Torus> *mem_ptr, void *const *bsks,
Torus *const *ksks, uint32_t num_radix_blocks) {
Torus *const *ksks,
CudaModulusSwitchNoiseReductionKeyFFI const *ms_noise_reduction_key,
uint32_t num_radix_blocks) {
if (lwe_array_out->lwe_dimension != lwe_array_1->lwe_dimension ||
lwe_array_out->lwe_dimension != lwe_array_2->lwe_dimension)
@@ -337,15 +347,16 @@ __host__ void host_integer_radix_equality_check_kb(
auto comparisons = mem_ptr->tmp_block_comparisons;
integer_radix_apply_bivariate_lookup_table_kb<Torus>(
streams, comparisons, lwe_array_1, lwe_array_2, bsks, ksks,
eq_buffer->operator_lut, num_radix_blocks,
ms_noise_reduction_key, eq_buffer->operator_lut, num_radix_blocks,
eq_buffer->operator_lut->params.message_modulus);
// This takes a Vec of blocks, where each block is either 0 or 1.
//
// It returns a block encrypting 1 if all input blocks are 1
// otherwise the block encrypts 0
are_all_comparisons_block_true<Torus>(streams, lwe_array_out, comparisons,
mem_ptr, bsks, ksks, num_radix_blocks);
are_all_comparisons_block_true<Torus>(
streams, lwe_array_out, comparisons, mem_ptr, bsks, ksks,
ms_noise_reduction_key, num_radix_blocks);
}
template <typename Torus>
@@ -354,7 +365,9 @@ __host__ void compare_radix_blocks_kb(
CudaRadixCiphertextFFI const *lwe_array_left,
CudaRadixCiphertextFFI const *lwe_array_right,
int_comparison_buffer<Torus> *mem_ptr, void *const *bsks,
Torus *const *ksks, uint32_t num_radix_blocks) {
Torus *const *ksks,
CudaModulusSwitchNoiseReductionKeyFFI const *ms_noise_reduction_key,
uint32_t num_radix_blocks) {
if (lwe_array_out->lwe_dimension != lwe_array_left->lwe_dimension ||
lwe_array_out->lwe_dimension != lwe_array_right->lwe_dimension)
@@ -387,8 +400,8 @@ __host__ void compare_radix_blocks_kb(
// Apply LUT to compare to 0
auto is_non_zero_lut = mem_ptr->eq_buffer->is_non_zero_lut;
integer_radix_apply_univariate_lookup_table_kb<Torus>(
streams, lwe_array_out, lwe_array_out, bsks, ksks, is_non_zero_lut,
num_radix_blocks);
streams, lwe_array_out, lwe_array_out, bsks, ksks, ms_noise_reduction_key,
is_non_zero_lut, num_radix_blocks);
// Add one
// Here Lhs can have the following values: (-1) % (message modulus * carry
@@ -401,13 +414,14 @@ __host__ void compare_radix_blocks_kb(
// (inferior, equal, superior) to one single shortint block containing the
// final sign
template <typename Torus>
__host__ void
tree_sign_reduction(CudaStreams streams, CudaRadixCiphertextFFI *lwe_array_out,
CudaRadixCiphertextFFI *lwe_block_comparisons,
int_tree_sign_reduction_buffer<Torus> *tree_buffer,
std::function<Torus(Torus)> sign_handler_f,
void *const *bsks, Torus *const *ksks,
uint32_t num_radix_blocks) {
__host__ void tree_sign_reduction(
CudaStreams streams, CudaRadixCiphertextFFI *lwe_array_out,
CudaRadixCiphertextFFI *lwe_block_comparisons,
int_tree_sign_reduction_buffer<Torus> *tree_buffer,
std::function<Torus(Torus)> sign_handler_f, void *const *bsks,
Torus *const *ksks,
CudaModulusSwitchNoiseReductionKeyFFI const *ms_noise_reduction_key,
uint32_t num_radix_blocks) {
if (lwe_array_out->lwe_dimension != lwe_block_comparisons->lwe_dimension)
PANIC("Cuda error: input lwe dimensions must be the same")
@@ -440,7 +454,8 @@ tree_sign_reduction(CudaStreams streams, CudaRadixCiphertextFFI *lwe_array_out,
partial_block_count, message_modulus);
integer_radix_apply_univariate_lookup_table_kb<Torus>(
streams, x, y, bsks, ksks, inner_tree_leaf, partial_block_count >> 1);
streams, x, y, bsks, ksks, ms_noise_reduction_key, inner_tree_leaf,
partial_block_count >> 1);
if ((partial_block_count % 2) != 0) {
partial_block_count >>= 1;
@@ -486,7 +501,8 @@ tree_sign_reduction(CudaStreams streams, CudaRadixCiphertextFFI *lwe_array_out,
// Last leaf
integer_radix_apply_univariate_lookup_table_kb<Torus>(
streams, lwe_array_out, y, bsks, ksks, last_lut, 1);
streams, lwe_array_out, y, bsks, ksks, ms_noise_reduction_key, last_lut,
1);
}
template <typename Torus>
@@ -496,7 +512,9 @@ __host__ void host_integer_radix_difference_check_kb(
CudaRadixCiphertextFFI const *lwe_array_right,
int_comparison_buffer<Torus> *mem_ptr,
std::function<Torus(Torus)> reduction_lut_f, void *const *bsks,
Torus *const *ksks, uint32_t num_radix_blocks) {
Torus *const *ksks,
CudaModulusSwitchNoiseReductionKeyFFI const *ms_noise_reduction_key,
uint32_t num_radix_blocks) {
if (lwe_array_out->lwe_dimension != lwe_array_left->lwe_dimension ||
lwe_array_out->lwe_dimension != lwe_array_right->lwe_dimension)
@@ -536,7 +554,7 @@ __host__ void host_integer_radix_difference_check_kb(
auto identity_lut = mem_ptr->identity_lut;
integer_radix_apply_univariate_lookup_table_kb<Torus>(
streams, diff_buffer->tmp_packed, diff_buffer->tmp_packed, bsks, ksks,
identity_lut, 2 * packed_num_radix_blocks);
ms_noise_reduction_key, identity_lut, 2 * packed_num_radix_blocks);
} else {
as_radix_ciphertext_slice<Torus>(&lhs, lwe_array_left, 0,
lwe_array_left->num_radix_blocks);
@@ -554,14 +572,16 @@ __host__ void host_integer_radix_difference_check_kb(
// Compare packed blocks, or simply the total number of radix blocks in the
// inputs
compare_radix_blocks_kb<Torus>(streams, comparisons, &lhs, &rhs, mem_ptr,
bsks, ksks, packed_num_radix_blocks);
bsks, ksks, ms_noise_reduction_key,
packed_num_radix_blocks);
num_comparisons = packed_num_radix_blocks;
} else {
// Packing is possible
if (carry_modulus >= message_modulus) {
// Compare (num_radix_blocks - 2) / 2 packed blocks
compare_radix_blocks_kb<Torus>(streams, comparisons, &lhs, &rhs, mem_ptr,
bsks, ksks, packed_num_radix_blocks);
bsks, ksks, ms_noise_reduction_key,
packed_num_radix_blocks);
// Compare the last block before the sign block separately
auto identity_lut = mem_ptr->identity_lut;
@@ -575,7 +595,7 @@ __host__ void host_integer_radix_difference_check_kb(
num_radix_blocks - 1);
integer_radix_apply_univariate_lookup_table_kb<Torus>(
streams, &last_left_block_before_sign_block, &shifted_lwe_array_left,
bsks, ksks, identity_lut, 1);
bsks, ksks, ms_noise_reduction_key, identity_lut, 1);
CudaRadixCiphertextFFI last_right_block_before_sign_block;
as_radix_ciphertext_slice<Torus>(
@@ -588,7 +608,8 @@ __host__ void host_integer_radix_difference_check_kb(
num_radix_blocks - 1);
integer_radix_apply_univariate_lookup_table_kb<Torus>(
streams, &last_right_block_before_sign_block,
&shifted_lwe_array_right, bsks, ksks, identity_lut, 1);
&shifted_lwe_array_right, bsks, ksks, ms_noise_reduction_key,
identity_lut, 1);
CudaRadixCiphertextFFI shifted_comparisons;
as_radix_ciphertext_slice<Torus>(&shifted_comparisons, comparisons,
@@ -596,7 +617,8 @@ __host__ void host_integer_radix_difference_check_kb(
packed_num_radix_blocks + 1);
compare_radix_blocks_kb<Torus>(
streams, &shifted_comparisons, &last_left_block_before_sign_block,
&last_right_block_before_sign_block, mem_ptr, bsks, ksks, 1);
&last_right_block_before_sign_block, mem_ptr, bsks, ksks,
ms_noise_reduction_key, 1);
// Compare the sign block separately
as_radix_ciphertext_slice<Torus>(&shifted_comparisons, comparisons,
@@ -610,14 +632,14 @@ __host__ void host_integer_radix_difference_check_kb(
num_radix_blocks - 1, num_radix_blocks);
integer_radix_apply_bivariate_lookup_table_kb<Torus>(
streams, &shifted_comparisons, &last_left_block, &last_right_block,
bsks, ksks, mem_ptr->signed_lut, 1,
bsks, ksks, ms_noise_reduction_key, mem_ptr->signed_lut, 1,
mem_ptr->signed_lut->params.message_modulus);
num_comparisons = packed_num_radix_blocks + 2;
} else {
compare_radix_blocks_kb<Torus>(streams, comparisons, lwe_array_left,
lwe_array_right, mem_ptr, bsks, ksks,
num_radix_blocks - 1);
compare_radix_blocks_kb<Torus>(
streams, comparisons, lwe_array_left, lwe_array_right, mem_ptr, bsks,
ksks, ms_noise_reduction_key, num_radix_blocks - 1);
// Compare the sign block separately
CudaRadixCiphertextFFI shifted_comparisons;
as_radix_ciphertext_slice<Torus>(&shifted_comparisons, comparisons,
@@ -630,7 +652,7 @@ __host__ void host_integer_radix_difference_check_kb(
num_radix_blocks - 1, num_radix_blocks);
integer_radix_apply_bivariate_lookup_table_kb<Torus>(
streams, &shifted_comparisons, &last_left_block, &last_right_block,
bsks, ksks, mem_ptr->signed_lut, 1,
bsks, ksks, ms_noise_reduction_key, mem_ptr->signed_lut, 1,
mem_ptr->signed_lut->params.message_modulus);
num_comparisons = num_radix_blocks;
}
@@ -639,9 +661,9 @@ __host__ void host_integer_radix_difference_check_kb(
// Reduces a vec containing radix blocks that encrypts a sign
// (inferior, equal, superior) to one single radix block containing the
// final sign
tree_sign_reduction<Torus>(streams, lwe_array_out, comparisons,
mem_ptr->diff_buffer->tree_buffer, reduction_lut_f,
bsks, ksks, num_comparisons);
tree_sign_reduction<Torus>(
streams, lwe_array_out, comparisons, mem_ptr->diff_buffer->tree_buffer,
reduction_lut_f, bsks, ksks, ms_noise_reduction_key, num_comparisons);
}
template <typename Torus>
@@ -663,7 +685,9 @@ __host__ void host_integer_radix_maxmin_kb(
CudaRadixCiphertextFFI const *lwe_array_left,
CudaRadixCiphertextFFI const *lwe_array_right,
int_comparison_buffer<Torus> *mem_ptr, void *const *bsks,
Torus *const *ksks, uint32_t num_radix_blocks) {
Torus *const *ksks,
CudaModulusSwitchNoiseReductionKeyFFI const *ms_noise_reduction_key,
uint32_t num_radix_blocks) {
if (lwe_array_out->lwe_dimension != lwe_array_left->lwe_dimension ||
lwe_array_out->lwe_dimension != lwe_array_right->lwe_dimension)
@@ -677,12 +701,14 @@ __host__ void host_integer_radix_maxmin_kb(
// Compute the sign
host_integer_radix_difference_check_kb<Torus>(
streams, mem_ptr->tmp_lwe_array_out, lwe_array_left, lwe_array_right,
mem_ptr, mem_ptr->identity_lut_f, bsks, ksks, num_radix_blocks);
mem_ptr, mem_ptr->identity_lut_f, bsks, ksks, ms_noise_reduction_key,
num_radix_blocks);
// Selector
host_integer_radix_cmux_kb<Torus>(
streams, lwe_array_out, mem_ptr->tmp_lwe_array_out, lwe_array_left,
lwe_array_right, mem_ptr->cmux_buffer, bsks, ksks);
host_integer_radix_cmux_kb<Torus>(streams, lwe_array_out,
mem_ptr->tmp_lwe_array_out, lwe_array_left,
lwe_array_right, mem_ptr->cmux_buffer, bsks,
ksks, ms_noise_reduction_key);
}
template <typename Torus>
@@ -690,12 +716,15 @@ __host__ void host_integer_are_all_comparisons_block_true_kb(
CudaStreams streams, CudaRadixCiphertextFFI *lwe_array_out,
CudaRadixCiphertextFFI const *lwe_array_in,
int_comparison_buffer<Torus> *mem_ptr, void *const *bsks,
Torus *const *ksks, uint32_t num_radix_blocks) {
Torus *const *ksks,
CudaModulusSwitchNoiseReductionKeyFFI const *ms_noise_reduction_key,
uint32_t num_radix_blocks) {
// It returns a block encrypting 1 if all input blocks are 1
// otherwise the block encrypts 0
are_all_comparisons_block_true<Torus>(streams, lwe_array_out, lwe_array_in,
mem_ptr, bsks, ksks, num_radix_blocks);
are_all_comparisons_block_true<Torus>(
streams, lwe_array_out, lwe_array_in, mem_ptr, bsks, ksks,
ms_noise_reduction_key, num_radix_blocks);
}
template <typename Torus>
@@ -703,12 +732,14 @@ __host__ void host_integer_is_at_least_one_comparisons_block_true_kb(
CudaStreams streams, CudaRadixCiphertextFFI *lwe_array_out,
CudaRadixCiphertextFFI const *lwe_array_in,
int_comparison_buffer<Torus> *mem_ptr, void *const *bsks,
Torus *const *ksks, uint32_t num_radix_blocks) {
Torus *const *ksks,
CudaModulusSwitchNoiseReductionKeyFFI const *ms_noise_reduction_key,
uint32_t num_radix_blocks) {
// It returns a block encrypting 1 if all input blocks are 1
// otherwise the block encrypts 0
is_at_least_one_comparisons_block_true<Torus>(streams, lwe_array_out,
lwe_array_in, mem_ptr, bsks,
ksks, num_radix_blocks);
is_at_least_one_comparisons_block_true<Torus>(
streams, lwe_array_out, lwe_array_in, mem_ptr, bsks, ksks,
ms_noise_reduction_key, num_radix_blocks);
}
#endif

View File

@@ -344,7 +344,7 @@ host_integer_decompress(CudaStreams streams,
execute_pbs_async<Torus, Torus>(
active_streams, (Torus *)d_lwe_array_out->ptr, lut->lwe_indexes_out,
lut->lut_vec, lut->lut_indexes_vec, extracted_lwe,
lut->lwe_indexes_in.get(), d_bsks, lut->buffer,
lut->lwe_indexes_in, d_bsks, nullptr, lut->buffer,
encryption_params.glwe_dimension,
compression_params.small_lwe_dimension,
encryption_params.polynomial_size, encryption_params.pbs_base_log,
@@ -359,13 +359,17 @@ host_integer_decompress(CudaStreams streams,
std::vector<Torus *> lwe_trivial_indexes_vec =
lut->lwe_trivial_indexes_vec;
lut->multi_gpu_scatter_barrier.local_streams_wait_for_stream_0(
active_streams);
/// Make sure all data that should be on GPU 0 is indeed there
cuda_event_record(lut->event_scatter_in, streams.stream(0),
streams.gpu_index(0));
for (int j = 1; j < active_streams.count(); j++) {
cuda_stream_wait_event(streams.stream(j), lut->event_scatter_in,
streams.gpu_index(j));
}
/// With multiple GPUs we push to the vectors on each GPU then when we
/// gather data to GPU 0 we can copy back to the original indexing
multi_gpu_scatter_lwe_async<Torus>(
active_streams, lwe_array_in_vec, extracted_lwe, lut->lwe_indexes_in.get(),
active_streams, lwe_array_in_vec, extracted_lwe, lut->lwe_indexes_in,
lut->using_trivial_lwe_indexes, lut->lwe_aligned_vec,
lut->active_streams.count(), num_blocks_to_decompress,
compression_params.small_lwe_dimension + 1);
@@ -374,7 +378,7 @@ host_integer_decompress(CudaStreams streams,
execute_pbs_async<Torus, Torus>(
active_streams, lwe_after_pbs_vec, lwe_trivial_indexes_vec,
lut->lut_vec, lut->lut_indexes_vec, lwe_array_in_vec,
lwe_trivial_indexes_vec, d_bsks, lut->buffer,
lwe_trivial_indexes_vec, d_bsks, nullptr, lut->buffer,
encryption_params.glwe_dimension,
compression_params.small_lwe_dimension,
encryption_params.polynomial_size, encryption_params.pbs_base_log,
@@ -391,8 +395,15 @@ host_integer_decompress(CudaStreams streams,
/// Synchronize all GPUs
// other gpus record their events
lut->multi_gpu_gather_barrier.stream_0_wait_for_local_streams(
active_streams);
for (int j = 1; j < active_streams.count(); j++) {
cuda_event_record(lut->event_scatter_out[j], active_streams.stream(j),
active_streams.gpu_index(j));
}
// GPU 0 waits for all
for (int j = 1; j < active_streams.count(); j++) {
cuda_stream_wait_event(streams.stream(0), lut->event_scatter_out[j],
streams.gpu_index(0));
}
}
} else {
static_assert(std::is_same_v<Torus, __uint128_t>,

View File

@@ -24,13 +24,14 @@ void cuda_integer_div_rem_radix_ciphertext_kb_64(
CudaStreamsFFI streams, CudaRadixCiphertextFFI *quotient,
CudaRadixCiphertextFFI *remainder, CudaRadixCiphertextFFI const *numerator,
CudaRadixCiphertextFFI const *divisor, bool is_signed, int8_t *mem_ptr,
void *const *bsks, void *const *ksks) {
void *const *bsks, void *const *ksks,
CudaModulusSwitchNoiseReductionKeyFFI const *ms_noise_reduction_key) {
PUSH_RANGE("div")
auto mem = (int_div_rem_memory<uint64_t> *)mem_ptr;
host_integer_div_rem_kb<uint64_t>(CudaStreams(streams), quotient, remainder,
numerator, divisor, is_signed, bsks,
(uint64_t **)(ksks), mem);
host_integer_div_rem_kb<uint64_t>(
CudaStreams(streams), quotient, remainder, numerator, divisor, is_signed,
bsks, (uint64_t **)(ksks), ms_noise_reduction_key, mem);
POP_RANGE()
}

View File

@@ -4,7 +4,6 @@
#include "crypto/keyswitch.cuh"
#include "device.h"
#include "integer/abs.cuh"
#include "integer/cast.cuh"
#include "integer/comparison.cuh"
#include "integer/integer.cuh"
#include "integer/integer_utilities.h"
@@ -32,455 +31,14 @@ __host__ uint64_t scratch_cuda_integer_div_rem_kb(
return size_tracker;
}
template <typename Torus>
__host__ void host_unsigned_integer_div_rem_kb_block_by_block_2_2(
CudaStreams streams, CudaRadixCiphertextFFI *quotient,
CudaRadixCiphertextFFI *remainder, CudaRadixCiphertextFFI const *numerator,
CudaRadixCiphertextFFI const *divisor, void *const *bsks,
uint64_t *const *ksks, unsigned_int_div_rem_2_2_memory<uint64_t> *mem_ptr) {
if (streams.count() < 4) {
PANIC("GPU count should be greater than 4 when using div_rem_2_2");
}
if (mem_ptr->params.message_modulus != 4 ||
mem_ptr->params.carry_modulus != 4) {
PANIC("Only message_modulus == 4 && carry_modulus == 4 parameters are "
"supported");
}
// alias
auto radix_params = mem_ptr->params;
auto num_blocks = quotient->num_radix_blocks;
auto remainder_gpu_0 = remainder;
auto remainder_gpu_1 = mem_ptr->remainder_gpu_1;
auto remainder_gpu_2 = mem_ptr->remainder_gpu_2;
auto remainder_gpu_3 = mem_ptr->remainder_gpu_3;
auto divisor_gpu_0 = divisor;
auto divisor_gpu_1 = mem_ptr->divisor_gpu_1;
auto divisor_gpu_2 = mem_ptr->divisor_gpu_2;
// gpu[0] -> gpu[0]
copy_radix_ciphertext_async<Torus>(streams.stream(0), streams.gpu_index(0),
remainder_gpu_0, numerator);
// gpu[0] -> gpu[1]
copy_radix_ciphertext_async<Torus>(streams.stream(1), streams.gpu_index(1),
remainder_gpu_1, numerator);
// gpu[0] -> gpu[1]
copy_radix_ciphertext_async<Torus>(streams.stream(1), streams.gpu_index(1),
divisor_gpu_1, divisor);
// gpu[0] -> gpu[2]
copy_radix_ciphertext_async<Torus>(streams.stream(2), streams.gpu_index(2),
remainder_gpu_2, numerator);
// gpu[0] -> gpu[3]
copy_radix_ciphertext_async<Torus>(streams.stream(3), streams.gpu_index(3),
remainder_gpu_3, numerator);
// gpu[0] -> gpu[2]
copy_radix_ciphertext_async<Torus>(streams.stream(2), streams.gpu_index(2),
divisor_gpu_2, divisor);
// gpu[0]
set_zero_radix_ciphertext_slice_async<Torus>(
streams.stream(0), streams.gpu_index(0), quotient, 0, num_blocks);
quotient->num_radix_blocks = 0;
// Copy divisor_gpu_2 into d1 gpu[2] -> gpu[2]
mem_ptr->d1->num_radix_blocks = divisor_gpu_2->num_radix_blocks;
copy_radix_ciphertext_async<Torus>(streams.stream(2), streams.gpu_index(2),
mem_ptr->d1, divisor_gpu_2);
// Computes 2*d by extending and shifting on gpu[1]
host_extend_radix_with_trivial_zero_blocks_msb<Torus>(
mem_ptr->d2, divisor_gpu_1, streams.get_ith(1));
host_integer_radix_logical_scalar_shift_kb_inplace<Torus>(
streams.get_ith(1), mem_ptr->d2, 1, mem_ptr->shift_mem, &bsks[1],
&ksks[1], mem_ptr->d2->num_radix_blocks);
// Computes 3*d = 4*d - d using block shift and subtraction on gpu[0]
host_extend_radix_with_trivial_zero_blocks_msb<Torus>(
mem_ptr->tmp_gpu_0, divisor_gpu_0, streams.get_ith(0));
host_radix_blocks_rotate_right<Torus>(streams.get_ith(0), mem_ptr->d3,
mem_ptr->tmp_gpu_0, 1,
mem_ptr->tmp_gpu_0->num_radix_blocks);
set_zero_radix_ciphertext_slice_async<Torus>(
streams.stream(0), streams.gpu_index(0), mem_ptr->d3, 0, 1);
host_sub_and_propagate_single_carry(streams.get_ith(0), mem_ptr->d3,
mem_ptr->tmp_gpu_0, nullptr, nullptr,
mem_ptr->sub_and_propagate_mem, &bsks[0],
&ksks[0], outputFlag::FLAG_NONE, 0);
// +-----------------+-----------------+-----------------+-----------------+
// | GPU[0] | GPU[1] | GPU[2] | GPU[3] |
// +-----------------+-----------------+-----------------+-----------------+
// | d3 | d2 | d1 | - |
// | low3 | low2 | low1 | - |
// | rem3 | rem2 | rem1 | rem0 |
// | sub_result_1 | sub_result_2 | sub_result_3 | - |
// | s_1_overflowed | s_2_overflowed | s_3_overflowed | - |
// | cmp_1 | cmp_2 | cmp_3 | - |
// | r3 | r2 | r1 | - |
// | o3 | o2 | o1 | - |
// | c3 = !o3 | c2 = !o2 + o3 | c1 = !o1 + o2 | c0 = o1 |
// | z_o_not_1_lut_1 | z_o_not_2_lut_1 | z_o_not_2_lut_2 | z_o_not_1_lut_2 |
// +-----------------+-----------------+-----------------+-----------------+
for (int block_index = num_blocks - 1; block_index >= 0; block_index--) {
uint32_t slice_len = num_blocks - block_index;
auto init_low_rem_f =
[&](CudaRadixCiphertextFFI *low, CudaRadixCiphertextFFI *xd,
CudaRadixCiphertextFFI *rem, CudaRadixCiphertextFFI *cur_remainder,
size_t gpu_index, bool init_low) {
rem->num_radix_blocks = slice_len;
if (init_low) {
low->num_radix_blocks = slice_len;
copy_radix_ciphertext_slice_async<Torus>(
streams.stream(gpu_index), streams.gpu_index(gpu_index), low, 0,
slice_len, xd, 0, slice_len);
}
copy_radix_ciphertext_slice_async<Torus>(
streams.stream(gpu_index), streams.gpu_index(gpu_index), rem, 0,
slice_len, cur_remainder, block_index, num_blocks);
};
init_low_rem_f(nullptr, nullptr, mem_ptr->rem0, remainder_gpu_3, 3, false);
init_low_rem_f(mem_ptr->low1, mem_ptr->d1, mem_ptr->rem1, remainder_gpu_2,
2, true);
init_low_rem_f(mem_ptr->low2, mem_ptr->d2, mem_ptr->rem2, remainder_gpu_1,
1, true);
init_low_rem_f(mem_ptr->low3, mem_ptr->d3, mem_ptr->rem3, remainder_gpu_0,
0, true);
auto sub_result_f = [&](CudaStreams streams, size_t gpu_index,
CudaRadixCiphertextFFI *sub_result,
CudaRadixCiphertextFFI *sub_overflowed,
int_borrow_prop_memory<Torus> *overflow_sub_mem,
CudaRadixCiphertextFFI *low,
CudaRadixCiphertextFFI *rem, Torus *first_indexes,
Torus *second_indexes, Torus *scalar_indexes) {
uint32_t compute_overflow = 1;
uint32_t uses_input_borrow = 0;
sub_result->num_radix_blocks = low->num_radix_blocks;
overflow_sub_mem->update_lut_indexes(
streams.get_ith(gpu_index), first_indexes, second_indexes,
scalar_indexes, rem->num_radix_blocks);
host_integer_overflowing_sub<uint64_t>(
streams.get_ith(gpu_index), sub_result, rem, low, sub_overflowed,
(const CudaRadixCiphertextFFI *)nullptr, overflow_sub_mem,
&bsks[gpu_index], &ksks[gpu_index], compute_overflow,
uses_input_borrow);
};
auto cmp_f = [&](CudaStreams streams, size_t gpu_index,
CudaRadixCiphertextFFI *out_boolean_block,
CudaRadixCiphertextFFI *comparison_blocks,
CudaRadixCiphertextFFI *d,
int_comparison_buffer<Torus> *comparison_buffer) {
CudaRadixCiphertextFFI *d_msb = new CudaRadixCiphertextFFI;
uint32_t slice_start = num_blocks - block_index;
uint32_t slice_end = d->num_radix_blocks;
as_radix_ciphertext_slice<Torus>(d_msb, d, slice_start, slice_end);
comparison_blocks->num_radix_blocks = d_msb->num_radix_blocks;
if (d_msb->num_radix_blocks == 0) {
cuda_memset_async(
(Torus *)out_boolean_block->ptr, 0,
sizeof(Torus) * (out_boolean_block->lwe_dimension + 1),
streams.stream(gpu_index), streams.gpu_index(gpu_index));
} else {
host_compare_blocks_with_zero<Torus>(
streams.get_ith(gpu_index), comparison_blocks, d_msb,
comparison_buffer, &bsks[gpu_index], &ksks[gpu_index],
d_msb->num_radix_blocks, comparison_buffer->is_zero_lut);
are_all_comparisons_block_true(
streams.get_ith(gpu_index), out_boolean_block, comparison_blocks,
comparison_buffer, &bsks[gpu_index], &ksks[gpu_index],
comparison_blocks->num_radix_blocks);
host_negation<Torus>(
streams.stream(gpu_index), streams.gpu_index(gpu_index),
(Torus *)out_boolean_block->ptr, (Torus *)out_boolean_block->ptr,
radix_params.big_lwe_dimension, 1);
// we calculate encoding because this block works only for
// message_modulus = 4 and carry_modulus = 4.
const Torus encoded_scalar = 1ULL << (sizeof(Torus) * 8 - 5);
host_addition_plaintext_scalar<Torus>(
streams.stream(gpu_index), streams.gpu_index(gpu_index),
(Torus *)out_boolean_block->ptr, (Torus *)out_boolean_block->ptr,
encoded_scalar, radix_params.big_lwe_dimension, 1);
}
delete d_msb;
};
for (uint j = 0; j < 3; j++) {
cuda_synchronize_stream(streams.stream(j), streams.gpu_index(j));
}
size_t indexes_id = mem_ptr->rem3->num_radix_blocks - 1;
sub_result_f(streams, 0, mem_ptr->sub_result_1, mem_ptr->sub_1_overflowed,
mem_ptr->overflow_sub_mem_1, mem_ptr->low3, mem_ptr->rem3,
mem_ptr->first_indexes_for_overflow_sub_gpu_0[indexes_id],
mem_ptr->second_indexes_for_overflow_sub_gpu_0[indexes_id],
mem_ptr->scalars_for_overflow_sub_gpu_0[indexes_id]);
sub_result_f(streams, 1, mem_ptr->sub_result_2, mem_ptr->sub_2_overflowed,
mem_ptr->overflow_sub_mem_2, mem_ptr->low2, mem_ptr->rem2,
mem_ptr->first_indexes_for_overflow_sub_gpu_1[indexes_id],
mem_ptr->second_indexes_for_overflow_sub_gpu_1[indexes_id],
mem_ptr->scalars_for_overflow_sub_gpu_1[indexes_id]);
sub_result_f(streams, 2, mem_ptr->sub_result_3, mem_ptr->sub_3_overflowed,
mem_ptr->overflow_sub_mem_3, mem_ptr->low1, mem_ptr->rem1,
mem_ptr->first_indexes_for_overflow_sub_gpu_2[indexes_id],
mem_ptr->second_indexes_for_overflow_sub_gpu_2[indexes_id],
mem_ptr->scalars_for_overflow_sub_gpu_2[indexes_id]);
cmp_f(mem_ptr->sub_streams_1, 0, mem_ptr->cmp_1,
mem_ptr->comparison_blocks_1, mem_ptr->d3,
mem_ptr->comparison_buffer_1);
cmp_f(mem_ptr->sub_streams_1, 1, mem_ptr->cmp_2,
mem_ptr->comparison_blocks_2, mem_ptr->d2,
mem_ptr->comparison_buffer_2);
cmp_f(mem_ptr->sub_streams_1, 2, mem_ptr->cmp_3,
mem_ptr->comparison_blocks_3, mem_ptr->d1,
mem_ptr->comparison_buffer_3);
for (uint j = 0; j < 3; j++) {
cuda_synchronize_stream(streams.stream(j), streams.gpu_index(j));
cuda_synchronize_stream(mem_ptr->sub_streams_1.stream(j),
mem_ptr->sub_streams_1.gpu_index(j));
}
auto r1 = mem_ptr->sub_result_3;
auto r2 = mem_ptr->sub_result_2;
auto r3 = mem_ptr->sub_result_1;
auto o1 = mem_ptr->sub_3_overflowed;
auto o2 = mem_ptr->sub_2_overflowed;
auto o3 = mem_ptr->sub_1_overflowed;
// used as a bitor
host_integer_radix_bitop_kb(streams.get_ith(0), o3, o3, mem_ptr->cmp_1,
mem_ptr->bitor_mem_1, &bsks[0], &ksks[0]);
// used as a bitor
host_integer_radix_bitop_kb(streams.get_ith(1), o2, o2, mem_ptr->cmp_2,
mem_ptr->bitor_mem_2, &bsks[1], &ksks[1]);
// used as a bitor
host_integer_radix_bitop_kb(streams.get_ith(2), o1, o1, mem_ptr->cmp_3,
mem_ptr->bitor_mem_3, &bsks[2], &ksks[2]);
// cmp_1, cmp_2, cmp_3 are not needed anymore, we can reuse them as c3,
// c2, c1. c0 is allocated on gpu[3], we take it from mem_ptr.
auto c3 = mem_ptr->cmp_1;
auto c2 = mem_ptr->cmp_2;
auto c1 = mem_ptr->cmp_3;
auto c0 = mem_ptr->c0;
// move all `o` so that each gpu has required `o` for calculating `c`
auto o3_gpu_1 = mem_ptr->tmp_gpu_1;
auto o2_gpu_2 = mem_ptr->tmp_gpu_2;
auto o1_gpu_3 = mem_ptr->tmp_gpu_3;
o3_gpu_1->num_radix_blocks = o3->num_radix_blocks;
o2_gpu_2->num_radix_blocks = o2->num_radix_blocks;
o1_gpu_3->num_radix_blocks = o1->num_radix_blocks;
for (uint j = 0; j < 4; j++) {
cuda_synchronize_stream(streams.stream(j), streams.gpu_index(j));
}
copy_radix_ciphertext_async<Torus>(streams.stream(1), streams.gpu_index(1),
o3_gpu_1, o3);
copy_radix_ciphertext_async<Torus>(streams.stream(2), streams.gpu_index(2),
o2_gpu_2, o2);
copy_radix_ciphertext_async<Torus>(streams.stream(3), streams.gpu_index(3),
o1_gpu_3, o1);
// c3 = !o3
copy_radix_ciphertext_slice_async<Torus>(
streams.stream(0), streams.gpu_index(0), c3, 0, 1, o3, 0, 1);
host_negation<Torus>(streams.stream(0), streams.gpu_index(0),
(Torus *)c3->ptr, (Torus *)c3->ptr,
radix_params.big_lwe_dimension, 1);
const Torus encoded_scalar = 1ULL << (sizeof(Torus) * 8 - 5);
host_addition_plaintext_scalar<Torus>(
streams.stream(0), streams.gpu_index(0), (Torus *)c3->ptr,
(Torus *)c3->ptr, encoded_scalar, radix_params.big_lwe_dimension, 1);
// c2 = !o2 + o3
copy_radix_ciphertext_slice_async<Torus>(
streams.stream(1), streams.gpu_index(1), c2, 0, 1, o2, 0, 1);
host_negation<Torus>(streams.stream(1), streams.gpu_index(1),
(Torus *)c2->ptr, (Torus *)c2->ptr,
radix_params.big_lwe_dimension, 1);
host_addition_plaintext_scalar<Torus>(
streams.stream(1), streams.gpu_index(1), (Torus *)c2->ptr,
(Torus *)c2->ptr, encoded_scalar, radix_params.big_lwe_dimension, 1);
host_addition<Torus>(streams.stream(1), streams.gpu_index(1), c2, c2,
o3_gpu_1, 1, 4, 4);
// c1 = !o1 + o2
copy_radix_ciphertext_slice_async<Torus>(
streams.stream(2), streams.gpu_index(2), c1, 0, 1, o1, 0, 1);
host_negation<Torus>(streams.stream(2), streams.gpu_index(2),
(Torus *)c1->ptr, (Torus *)c1->ptr,
radix_params.big_lwe_dimension, 1);
host_addition_plaintext_scalar<Torus>(
streams.stream(2), streams.gpu_index(2), (Torus *)c1->ptr,
(Torus *)c1->ptr, encoded_scalar, radix_params.big_lwe_dimension, 1);
host_addition<Torus>(streams.stream(2), streams.gpu_index(2), c1, c1,
o2_gpu_2, 1, 4, 4);
// c0 = o1 (direct copy)
copy_radix_ciphertext_slice_async<Torus>(streams.stream(3),
streams.gpu_index(3), mem_ptr->c0,
0, 1, o1_gpu_3, 0, 1);
auto conditional_update = [&](CudaStreams streams, size_t gpu_index,
CudaRadixCiphertextFFI *cx,
CudaRadixCiphertextFFI *rx,
int_radix_lut<Torus> *lut, Torus factor) {
auto rx_list = to_lwe_ciphertext_list(rx);
host_cleartext_multiplication<Torus>(streams.stream(gpu_index),
streams.gpu_index(gpu_index),
(Torus *)rx->ptr, &rx_list, factor);
host_add_the_same_block_to_all_blocks<Torus>(streams.stream(gpu_index),
streams.gpu_index(gpu_index),
rx, rx, cx, 4, 4);
integer_radix_apply_univariate_lookup_table_kb<Torus>(
streams.get_ith(gpu_index), rx, rx, &bsks[gpu_index],
&ksks[gpu_index], lut, rx->num_radix_blocks);
};
for (uint j = 0; j < 4; j++) {
cuda_synchronize_stream(streams.stream(j), streams.gpu_index(j));
cuda_synchronize_stream(mem_ptr->sub_streams_1.stream(j),
mem_ptr->sub_streams_1.gpu_index(j));
}
conditional_update(streams, 0, c3, r3, mem_ptr->zero_out_if_not_1_lut_1, 2);
conditional_update(streams, 1, c2, r2, mem_ptr->zero_out_if_not_2_lut_1, 3);
conditional_update(streams, 2, c1, r1, mem_ptr->zero_out_if_not_2_lut_2, 3);
conditional_update(streams, 3, c0, mem_ptr->rem0,
mem_ptr->zero_out_if_not_1_lut_2, 2);
// calculate quotient bits GPU[2]
integer_radix_apply_univariate_lookup_table_kb<Torus>(
mem_ptr->sub_streams_1.get_ith(2), mem_ptr->q1, c1, &bsks[2], &ksks[2],
mem_ptr->quotient_lut_1, 1);
// calculate quotient bits GPU[1]
integer_radix_apply_univariate_lookup_table_kb<Torus>(
mem_ptr->sub_streams_1.get_ith(1), mem_ptr->q2, c2, &bsks[1], &ksks[1],
mem_ptr->quotient_lut_2, 1);
// calculate quotient bits GPU[0]
integer_radix_apply_univariate_lookup_table_kb<Torus>(
mem_ptr->sub_streams_1.get_ith(0), mem_ptr->q3, c3, &bsks[0], &ksks[0],
mem_ptr->quotient_lut_3, 1);
for (uint j = 0; j < 4; j++) {
cuda_synchronize_stream(streams.stream(j), streams.gpu_index(j));
cuda_synchronize_stream(mem_ptr->sub_streams_1.stream(j),
mem_ptr->sub_streams_1.gpu_index(j));
}
// We need to accumulate rem, r1, r2, and r3, but each buffer currently
// lives on a different GPU. To gather them on GPU[0], well **reuse**
// buffers already allocated on GPU[0]. At this point, the contents of rem3,
// tmp_gpu_0, and low3 are no longer needed, so its safe to repurpose them.
// Aliases for the GPU[0] destinations:
auto r3_gpu_0 = r3; // reuse: destination for r3 on GPU[0]
auto r2_gpu_0 = mem_ptr->tmp_gpu_0; // reuse: destination for r2 on GPU[0]
auto r1_gpu_0 = mem_ptr->low3; // reuse: destination for r1 on GPU[0]
auto rem_gpu_0 = mem_ptr->rem3; // reuse: destination for rem on GPU[0]
r2_gpu_0->num_radix_blocks = r2->num_radix_blocks;
// r3 is already on GPU 0, so no need to copy it.
// Copy r2 from GPU[1] to GPU[0]
copy_radix_ciphertext_async<Torus>(streams.stream(0), streams.gpu_index(0),
r2_gpu_0, r2);
// Copy r1 from GPU[2] to GPU[0]
copy_radix_ciphertext_async<Torus>(streams.stream(0), streams.gpu_index(0),
r1_gpu_0, r1);
// Copy rem from GPU[3] to GPU[0]
copy_radix_ciphertext_async<Torus>(streams.stream(0), streams.gpu_index(0),
rem_gpu_0, mem_ptr->rem0);
// We do the same to accumulate quotient bits q1, q2 and q3. q3 is already
// on GPU[0]. To copy q1 and q2 we will reuse buffers allocated on GPU[0]:
// sub_1_overflowed and cmp_1.
auto q3_gpu_0 = mem_ptr->q3; // q3 is already on GPU[0]
auto q2_gpu_0 =
mem_ptr->sub_1_overflowed; // reuse: destination for q2 on GPU[0]
auto q1_gpu_0 = mem_ptr->cmp_1; // reuse: destination for q1 on GPU[0]
copy_radix_ciphertext_async<Torus>(streams.stream(0), streams.gpu_index(0),
q2_gpu_0, mem_ptr->q2);
copy_radix_ciphertext_async<Torus>(streams.stream(0), streams.gpu_index(0),
q1_gpu_0, mem_ptr->q1);
host_addition<Torus>(streams.stream(0), streams.gpu_index(0), rem_gpu_0,
rem_gpu_0, r3_gpu_0, rem_gpu_0->num_radix_blocks, 4,
4);
host_addition<Torus>(streams.stream(0), streams.gpu_index(0), rem_gpu_0,
rem_gpu_0, r2_gpu_0, rem_gpu_0->num_radix_blocks, 4,
4);
host_addition<Torus>(streams.stream(0), streams.gpu_index(0), rem_gpu_0,
rem_gpu_0, r1_gpu_0, rem_gpu_0->num_radix_blocks, 4,
4);
host_addition<Torus>(streams.stream(0), streams.gpu_index(0), q3_gpu_0,
q3_gpu_0, q2_gpu_0, 1, 4, 4);
host_addition<Torus>(streams.stream(0), streams.gpu_index(0), q3_gpu_0,
q3_gpu_0, q1_gpu_0, 1, 4, 4);
streams.synchronize();
integer_radix_apply_univariate_lookup_table_kb<Torus>(
streams, rem_gpu_0, rem_gpu_0, bsks, ksks,
mem_ptr->message_extract_lut_1, rem_gpu_0->num_radix_blocks);
integer_radix_apply_univariate_lookup_table_kb<Torus>(
mem_ptr->sub_streams_1, q3_gpu_0, q3_gpu_0, bsks, ksks,
mem_ptr->message_extract_lut_2, 1);
streams.synchronize();
mem_ptr->sub_streams_1.synchronize();
copy_radix_ciphertext_slice_async<Torus>(
streams.stream(0), streams.gpu_index(0), remainder_gpu_0, block_index,
remainder_gpu_0->num_radix_blocks, rem_gpu_0, 0,
rem_gpu_0->num_radix_blocks);
insert_block_in_radix_ciphertext_async<Torus>(
streams.stream(0), streams.gpu_index(0), q3_gpu_0, quotient, 0);
// Copy remainder_gpu_0 to all other GPUs
copy_radix_ciphertext_async<Torus>(streams.stream(0), streams.gpu_index(0),
remainder_gpu_1, remainder_gpu_0);
copy_radix_ciphertext_async<Torus>(streams.stream(0), streams.gpu_index(0),
remainder_gpu_2, remainder_gpu_0);
copy_radix_ciphertext_async<Torus>(streams.stream(0), streams.gpu_index(0),
remainder_gpu_3, remainder_gpu_0);
// non boolean blocks
for (int block_id = 0; block_id < slice_len; block_id++) {
mem_ptr->sub_result_1->degrees[block_id] =
radix_params.message_modulus - 1;
mem_ptr->rem0->degrees[block_id] = radix_params.message_modulus - 1;
}
// boolean blocks
mem_ptr->cmp_3->degrees[0] = 0;
mem_ptr->cmp_2->degrees[0] = 0;
mem_ptr->cmp_1->degrees[0] = 0;
mem_ptr->cmp_3->noise_levels[0] = 0;
streams.synchronize();
}
}
template <typename Torus>
__host__ void host_unsigned_integer_div_rem_kb(
CudaStreams streams, CudaRadixCiphertextFFI *quotient,
CudaRadixCiphertextFFI *remainder, CudaRadixCiphertextFFI const *numerator,
CudaRadixCiphertextFFI const *divisor, void *const *bsks,
uint64_t *const *ksks, unsigned_int_div_rem_memory<uint64_t> *mem_ptr) {
uint64_t *const *ksks,
CudaModulusSwitchNoiseReductionKeyFFI const *ms_noise_reduction_key,
unsigned_int_div_rem_memory<uint64_t> *mem_ptr) {
if (remainder->num_radix_blocks != numerator->num_radix_blocks ||
remainder->num_radix_blocks != divisor->num_radix_blocks ||
@@ -490,14 +48,6 @@ __host__ void host_unsigned_integer_div_rem_kb(
remainder->lwe_dimension != divisor->lwe_dimension ||
remainder->lwe_dimension != quotient->lwe_dimension)
PANIC("Cuda error: input and output lwe dimension must be equal")
if (mem_ptr->params.message_modulus == 4 &&
mem_ptr->params.carry_modulus == 4 && streams.count() >= 4) {
host_unsigned_integer_div_rem_kb_block_by_block_2_2<Torus>(
streams, quotient, remainder, numerator, divisor, bsks, ksks,
mem_ptr->div_rem_2_2_mem);
return;
}
auto radix_params = mem_ptr->params;
auto num_blocks = quotient->num_radix_blocks;
@@ -596,7 +146,7 @@ __host__ void host_unsigned_integer_div_rem_kb(
interesting_divisor->num_radix_blocks);
integer_radix_apply_univariate_lookup_table_kb<Torus>(
streams, &last_interesting_divisor_block,
&last_interesting_divisor_block, bsks, ksks,
&last_interesting_divisor_block, bsks, ksks, ms_noise_reduction_key,
mem_ptr->masking_luts_1[shifted_mask], 1);
}; // trim_last_interesting_divisor_bits
@@ -623,7 +173,7 @@ __host__ void host_unsigned_integer_div_rem_kb(
integer_radix_apply_univariate_lookup_table_kb<Torus>(
streams, divisor_ms_blocks, divisor_ms_blocks, bsks, ksks,
mem_ptr->masking_luts_2[shifted_mask], 1);
ms_noise_reduction_key, mem_ptr->masking_luts_2[shifted_mask], 1);
}; // trim_first_divisor_ms_bits
// This does
@@ -645,7 +195,7 @@ __host__ void host_unsigned_integer_div_rem_kb(
host_integer_radix_logical_scalar_shift_kb_inplace<Torus>(
streams, interesting_remainder1, 1, mem_ptr->shift_mem_1, bsks, ksks,
interesting_remainder1->num_radix_blocks);
ms_noise_reduction_key, interesting_remainder1->num_radix_blocks);
reset_radix_ciphertext_blocks(mem_ptr->tmp_radix,
interesting_remainder1->num_radix_blocks);
@@ -674,7 +224,7 @@ __host__ void host_unsigned_integer_div_rem_kb(
auto left_shift_interesting_remainder2 = [&](CudaStreams streams) {
host_integer_radix_logical_scalar_shift_kb_inplace<Torus>(
streams, interesting_remainder2, 1, mem_ptr->shift_mem_2, bsks, ksks,
interesting_remainder2->num_radix_blocks);
ms_noise_reduction_key, interesting_remainder2->num_radix_blocks);
}; // left_shift_interesting_remainder2
streams.synchronize();
@@ -747,7 +297,8 @@ __host__ void host_unsigned_integer_div_rem_kb(
streams, new_remainder, merged_interesting_remainder,
interesting_divisor, subtraction_overflowed,
(const CudaRadixCiphertextFFI *)nullptr, mem_ptr->overflow_sub_mem,
bsks, ksks, compute_borrow, uses_input_borrow);
bsks, ksks, ms_noise_reduction_key, compute_borrow,
uses_input_borrow);
};
// fills:
@@ -765,12 +316,13 @@ __host__ void host_unsigned_integer_div_rem_kb(
// So we can skip some stuff
host_compare_blocks_with_zero<Torus>(
streams, mem_ptr->tmp_1, trivial_blocks, mem_ptr->comparison_buffer,
bsks, ksks, trivial_blocks->num_radix_blocks,
bsks, ksks, ms_noise_reduction_key,
trivial_blocks->num_radix_blocks,
mem_ptr->comparison_buffer->eq_buffer->is_non_zero_lut);
is_at_least_one_comparisons_block_true<Torus>(
streams, at_least_one_upper_block_is_non_zero, mem_ptr->tmp_1,
mem_ptr->comparison_buffer, bsks, ksks,
mem_ptr->comparison_buffer, bsks, ksks, ms_noise_reduction_key,
mem_ptr->tmp_1->num_radix_blocks);
}
};
@@ -783,7 +335,7 @@ __host__ void host_unsigned_integer_div_rem_kb(
integer_radix_apply_univariate_lookup_table_kb<Torus>(
streams, cleaned_merged_interesting_remainder,
cleaned_merged_interesting_remainder, bsks, ksks,
mem_ptr->message_extract_lut_1,
ms_noise_reduction_key, mem_ptr->message_extract_lut_1,
cleaned_merged_interesting_remainder->num_radix_blocks);
};
@@ -821,7 +373,8 @@ __host__ void host_unsigned_integer_div_rem_kb(
integer_radix_apply_bivariate_lookup_table_kb<Torus>(
streams, cleaned_merged_interesting_remainder,
cleaned_merged_interesting_remainder, overflow_sum_radix, bsks,
ksks, mem_ptr->zero_out_if_overflow_did_not_happen[factor_lut_id],
ksks, ms_noise_reduction_key,
mem_ptr->zero_out_if_overflow_did_not_happen[factor_lut_id],
cleaned_merged_interesting_remainder->num_radix_blocks, factor);
};
@@ -829,7 +382,8 @@ __host__ void host_unsigned_integer_div_rem_kb(
[&](CudaStreams streams) {
integer_radix_apply_bivariate_lookup_table_kb<Torus>(
streams, new_remainder, new_remainder, overflow_sum_radix, bsks,
ksks, mem_ptr->zero_out_if_overflow_happened[factor_lut_id],
ksks, ms_noise_reduction_key,
mem_ptr->zero_out_if_overflow_happened[factor_lut_id],
new_remainder->num_radix_blocks, factor);
};
@@ -838,6 +392,7 @@ __host__ void host_unsigned_integer_div_rem_kb(
integer_radix_apply_bivariate_lookup_table_kb<Torus>(
streams, mem_ptr->did_not_overflow, subtraction_overflowed,
at_least_one_upper_block_is_non_zero, bsks, ksks,
ms_noise_reduction_key,
mem_ptr->merge_overflow_flags_luts[pos_in_block], 1,
mem_ptr->merge_overflow_flags_luts[pos_in_block]
->params.message_modulus);
@@ -896,10 +451,10 @@ __host__ void host_unsigned_integer_div_rem_kb(
integer_radix_apply_univariate_lookup_table_kb<Torus>(
mem_ptr->sub_streams_1, remainder, remainder, bsks, ksks,
mem_ptr->message_extract_lut_1, num_blocks);
ms_noise_reduction_key, mem_ptr->message_extract_lut_1, num_blocks);
integer_radix_apply_univariate_lookup_table_kb<Torus>(
mem_ptr->sub_streams_2, quotient, quotient, bsks, ksks,
mem_ptr->message_extract_lut_2, num_blocks);
ms_noise_reduction_key, mem_ptr->message_extract_lut_2, num_blocks);
mem_ptr->sub_streams_1.synchronize();
mem_ptr->sub_streams_2.synchronize();
@@ -910,7 +465,9 @@ __host__ void host_integer_div_rem_kb(
CudaStreams streams, CudaRadixCiphertextFFI *quotient,
CudaRadixCiphertextFFI *remainder, CudaRadixCiphertextFFI const *numerator,
CudaRadixCiphertextFFI const *divisor, bool is_signed, void *const *bsks,
uint64_t *const *ksks, int_div_rem_memory<uint64_t> *int_mem_ptr) {
uint64_t *const *ksks,
CudaModulusSwitchNoiseReductionKeyFFI const *ms_noise_reduction_key,
int_div_rem_memory<uint64_t> *int_mem_ptr) {
if (remainder->num_radix_blocks != numerator->num_radix_blocks ||
remainder->num_radix_blocks != divisor->num_radix_blocks ||
remainder->num_radix_blocks != quotient->num_radix_blocks)
@@ -935,16 +492,19 @@ __host__ void host_integer_div_rem_kb(
streams.synchronize();
host_integer_abs_kb<Torus>(int_mem_ptr->sub_streams_1, positive_numerator,
bsks, ksks, int_mem_ptr->abs_mem_1, true);
bsks, ksks, ms_noise_reduction_key,
int_mem_ptr->abs_mem_1, true);
host_integer_abs_kb<Torus>(int_mem_ptr->sub_streams_2, positive_divisor,
bsks, ksks, int_mem_ptr->abs_mem_2, true);
bsks, ksks, ms_noise_reduction_key,
int_mem_ptr->abs_mem_2, true);
int_mem_ptr->sub_streams_1.synchronize();
int_mem_ptr->sub_streams_2.synchronize();
host_unsigned_integer_div_rem_kb<Torus>(
int_mem_ptr->sub_streams_1, quotient, remainder, positive_numerator,
positive_divisor, bsks, ksks, int_mem_ptr->unsigned_mem);
positive_divisor, bsks, ksks, ms_noise_reduction_key,
int_mem_ptr->unsigned_mem);
CudaRadixCiphertextFFI numerator_sign;
as_radix_ciphertext_slice<Torus>(&numerator_sign, numerator, num_blocks - 1,
@@ -954,7 +514,7 @@ __host__ void host_integer_div_rem_kb(
num_blocks);
integer_radix_apply_bivariate_lookup_table_kb<Torus>(
int_mem_ptr->sub_streams_2, int_mem_ptr->sign_bits_are_different,
&numerator_sign, &divisor_sign, bsks, ksks,
&numerator_sign, &divisor_sign, bsks, ksks, ms_noise_reduction_key,
int_mem_ptr->compare_signed_bits_lut, 1,
int_mem_ptr->compare_signed_bits_lut->params.message_modulus);
@@ -967,36 +527,37 @@ __host__ void host_integer_div_rem_kb(
uint32_t requested_flag = outputFlag::FLAG_NONE;
uint32_t uses_carry = 0;
host_propagate_single_carry<Torus>(int_mem_ptr->sub_streams_1,
int_mem_ptr->negated_quotient, nullptr,
nullptr, int_mem_ptr->scp_mem_1, bsks,
ksks, requested_flag, uses_carry);
host_propagate_single_carry<Torus>(
int_mem_ptr->sub_streams_1, int_mem_ptr->negated_quotient, nullptr,
nullptr, int_mem_ptr->scp_mem_1, bsks, ksks, ms_noise_reduction_key,
requested_flag, uses_carry);
host_integer_radix_negation<Torus>(
int_mem_ptr->sub_streams_2, int_mem_ptr->negated_remainder, remainder,
radix_params.message_modulus, radix_params.carry_modulus, num_blocks);
host_propagate_single_carry<Torus>(int_mem_ptr->sub_streams_2,
int_mem_ptr->negated_remainder, nullptr,
nullptr, int_mem_ptr->scp_mem_2, bsks,
ksks, requested_flag, uses_carry);
host_propagate_single_carry<Torus>(
int_mem_ptr->sub_streams_2, int_mem_ptr->negated_remainder, nullptr,
nullptr, int_mem_ptr->scp_mem_2, bsks, ksks, ms_noise_reduction_key,
requested_flag, uses_carry);
host_integer_radix_cmux_kb<Torus>(
int_mem_ptr->sub_streams_1, quotient,
int_mem_ptr->sign_bits_are_different, int_mem_ptr->negated_quotient,
quotient, int_mem_ptr->cmux_quotient_mem, bsks, ksks);
host_integer_radix_cmux_kb<Torus>(int_mem_ptr->sub_streams_1, quotient,
int_mem_ptr->sign_bits_are_different,
int_mem_ptr->negated_quotient, quotient,
int_mem_ptr->cmux_quotient_mem, bsks,
ksks, ms_noise_reduction_key);
host_integer_radix_cmux_kb<Torus>(
int_mem_ptr->sub_streams_2, remainder, &numerator_sign,
int_mem_ptr->negated_remainder, remainder,
int_mem_ptr->cmux_remainder_mem, bsks, ksks);
int_mem_ptr->cmux_remainder_mem, bsks, ksks, ms_noise_reduction_key);
int_mem_ptr->sub_streams_1.synchronize();
int_mem_ptr->sub_streams_2.synchronize();
} else {
host_unsigned_integer_div_rem_kb<Torus>(streams, quotient, remainder,
numerator, divisor, bsks, ksks,
int_mem_ptr->unsigned_mem);
host_unsigned_integer_div_rem_kb<Torus>(
streams, quotient, remainder, numerator, divisor, bsks, ksks,
ms_noise_reduction_key, int_mem_ptr->unsigned_mem);
}
}

View File

@@ -29,12 +29,13 @@ uint64_t scratch_integer_count_of_consecutive_bits_kb_64(
void cuda_integer_count_of_consecutive_bits_kb_64(
CudaStreamsFFI streams, CudaRadixCiphertextFFI *output_ct,
CudaRadixCiphertextFFI const *input_ct, int8_t *mem_ptr, void *const *bsks,
void *const *ksks) {
void *const *ksks,
const CudaModulusSwitchNoiseReductionKeyFFI *ms_noise_reduction_key) {
host_integer_count_of_consecutive_bits<uint64_t>(
CudaStreams(streams), output_ct, input_ct,
(int_count_of_consecutive_bits_buffer<uint64_t> *)mem_ptr, bsks,
(uint64_t **)ksks);
(uint64_t **)ksks, ms_noise_reduction_key);
}
void cleanup_cuda_integer_count_of_consecutive_bits_kb_64(
@@ -80,12 +81,13 @@ void cuda_integer_ilog2_kb_64(
CudaRadixCiphertextFFI const *trivial_ct_neg_n,
CudaRadixCiphertextFFI const *trivial_ct_2,
CudaRadixCiphertextFFI const *trivial_ct_m_minus_1_block, int8_t *mem_ptr,
void *const *bsks, void *const *ksks) {
void *const *bsks, void *const *ksks,
const CudaModulusSwitchNoiseReductionKeyFFI *ms_noise_reduction_key) {
host_integer_ilog2<uint64_t>(
CudaStreams(streams), output_ct, input_ct, trivial_ct_neg_n, trivial_ct_2,
trivial_ct_m_minus_1_block, (int_ilog2_buffer<uint64_t> *)mem_ptr, bsks,
(uint64_t **)ksks);
(uint64_t **)ksks, ms_noise_reduction_key);
}
void cleanup_cuda_integer_ilog2_kb_64(CudaStreamsFFI streams,

View File

@@ -9,12 +9,14 @@ template <typename Torus>
__host__ void host_integer_prepare_count_of_consecutive_bits(
CudaStreams streams, CudaRadixCiphertextFFI *ciphertext,
int_prepare_count_of_consecutive_bits_buffer<Torus> *mem_ptr,
void *const *bsks, Torus *const *ksks) {
void *const *bsks, Torus *const *ksks,
CudaModulusSwitchNoiseReductionKeyFFI const *ms_noise_reduction_key) {
auto tmp = mem_ptr->tmp_ct;
host_apply_univariate_lut_kb<Torus>(streams, tmp, ciphertext,
mem_ptr->univ_lut_mem, ksks, bsks);
mem_ptr->univ_lut_mem, ksks,
ms_noise_reduction_key, bsks);
if (mem_ptr->direction == Leading) {
host_radix_blocks_reverse_inplace<Torus>(streams, tmp);
@@ -22,7 +24,7 @@ __host__ void host_integer_prepare_count_of_consecutive_bits(
host_compute_prefix_sum_hillis_steele<uint64_t>(
streams, ciphertext, tmp, mem_ptr->biv_lut_mem, bsks, ksks,
ciphertext->num_radix_blocks);
ms_noise_reduction_key, ciphertext->num_radix_blocks);
}
template <typename Torus>
@@ -46,7 +48,8 @@ __host__ void host_integer_count_of_consecutive_bits(
CudaStreams streams, CudaRadixCiphertextFFI *output_ct,
CudaRadixCiphertextFFI const *input_ct,
int_count_of_consecutive_bits_buffer<Torus> *mem_ptr, void *const *bsks,
Torus *const *ksks) {
Torus *const *ksks,
CudaModulusSwitchNoiseReductionKeyFFI const *ms_noise_reduction_key) {
auto params = mem_ptr->params;
auto ct_prepared = mem_ptr->ct_prepared;
@@ -57,8 +60,9 @@ __host__ void host_integer_count_of_consecutive_bits(
// Prepare count of consecutive bits
//
host_integer_prepare_count_of_consecutive_bits(
streams, ct_prepared, mem_ptr->prepare_mem, bsks, ksks);
host_integer_prepare_count_of_consecutive_bits(streams, ct_prepared,
mem_ptr->prepare_mem, bsks,
ksks, ms_noise_reduction_key);
// Perform addition and propagation of prepared cts
//
@@ -72,11 +76,12 @@ __host__ void host_integer_count_of_consecutive_bits(
}
host_integer_partial_sum_ciphertexts_vec_kb<Torus>(
streams, output_ct, cts, bsks, ksks, mem_ptr->sum_mem, counter_num_blocks,
ct_prepared->num_radix_blocks);
streams, output_ct, cts, bsks, ksks, ms_noise_reduction_key,
mem_ptr->sum_mem, counter_num_blocks, ct_prepared->num_radix_blocks);
host_propagate_single_carry<Torus>(streams, output_ct, nullptr, nullptr,
mem_ptr->propagate_mem, bsks, ksks, 0, 0);
mem_ptr->propagate_mem, bsks, ksks,
ms_noise_reduction_key, 0, 0);
}
template <typename Torus>
@@ -98,14 +103,14 @@ __host__ uint64_t scratch_integer_ilog2(CudaStreams streams,
}
template <typename Torus>
__host__ void
host_integer_ilog2(CudaStreams streams, CudaRadixCiphertextFFI *output_ct,
CudaRadixCiphertextFFI const *input_ct,
CudaRadixCiphertextFFI const *trivial_ct_neg_n,
CudaRadixCiphertextFFI const *trivial_ct_2,
CudaRadixCiphertextFFI const *trivial_ct_m_minus_1_block,
int_ilog2_buffer<Torus> *mem_ptr, void *const *bsks,
Torus *const *ksks) {
__host__ void host_integer_ilog2(
CudaStreams streams, CudaRadixCiphertextFFI *output_ct,
CudaRadixCiphertextFFI const *input_ct,
CudaRadixCiphertextFFI const *trivial_ct_neg_n,
CudaRadixCiphertextFFI const *trivial_ct_2,
CudaRadixCiphertextFFI const *trivial_ct_m_minus_1_block,
int_ilog2_buffer<Torus> *mem_ptr, void *const *bsks, Torus *const *ksks,
CudaModulusSwitchNoiseReductionKeyFFI const *ms_noise_reduction_key) {
// Prepare the input ciphertext by computing the number of consecutive
// leading zeros for each of its blocks.
@@ -113,7 +118,8 @@ host_integer_ilog2(CudaStreams streams, CudaRadixCiphertextFFI *output_ct,
copy_radix_ciphertext_async<Torus>(streams.stream(0), streams.gpu_index(0),
mem_ptr->ct_in_buffer, input_ct);
host_integer_prepare_count_of_consecutive_bits<Torus>(
streams, mem_ptr->ct_in_buffer, mem_ptr->prepare_mem, bsks, ksks);
streams, mem_ptr->ct_in_buffer, mem_ptr->prepare_mem, bsks, ksks,
ms_noise_reduction_key);
// Build the input for the sum by taking each block's leading zero count
// and placing it into a separate, zero-padded ct slot.
@@ -142,17 +148,17 @@ host_integer_ilog2(CudaStreams streams, CudaRadixCiphertextFFI *output_ct,
//
host_integer_partial_sum_ciphertexts_vec_kb<Torus>(
streams, mem_ptr->sum_output_not_propagated, mem_ptr->sum_input_cts, bsks,
ksks, mem_ptr->sum_mem, mem_ptr->counter_num_blocks,
mem_ptr->input_num_blocks + 1);
ksks, ms_noise_reduction_key, mem_ptr->sum_mem,
mem_ptr->counter_num_blocks, mem_ptr->input_num_blocks + 1);
// Apply luts to the partial sum.
//
host_apply_univariate_lut_kb<Torus>(streams, mem_ptr->message_blocks_not,
mem_ptr->sum_output_not_propagated,
mem_ptr->lut_message_not, ksks, bsks);
host_apply_univariate_lut_kb<Torus>(streams, mem_ptr->carry_blocks_not,
mem_ptr->sum_output_not_propagated,
mem_ptr->lut_carry_not, ksks, bsks);
host_apply_univariate_lut_kb<Torus>(
streams, mem_ptr->message_blocks_not, mem_ptr->sum_output_not_propagated,
mem_ptr->lut_message_not, ksks, ms_noise_reduction_key, bsks);
host_apply_univariate_lut_kb<Torus>(
streams, mem_ptr->carry_blocks_not, mem_ptr->sum_output_not_propagated,
mem_ptr->lut_carry_not, ksks, ms_noise_reduction_key, bsks);
// Left-shift the bitwise-negated carry blocks by one position.
//
@@ -190,12 +196,12 @@ host_integer_ilog2(CudaStreams streams, CudaRadixCiphertextFFI *output_ct,
trivial_ct_2, 0, mem_ptr->counter_num_blocks);
host_integer_partial_sum_ciphertexts_vec_kb<Torus>(
streams, output_ct, mem_ptr->sum_input_cts, bsks, ksks, mem_ptr->sum_mem,
mem_ptr->counter_num_blocks, 3);
streams, output_ct, mem_ptr->sum_input_cts, bsks, ksks,
ms_noise_reduction_key, mem_ptr->sum_mem, mem_ptr->counter_num_blocks, 3);
host_full_propagate_inplace<Torus>(streams, output_ct,
mem_ptr->final_propagate_mem, ksks, bsks,
mem_ptr->counter_num_blocks);
host_full_propagate_inplace<Torus>(
streams, output_ct, mem_ptr->final_propagate_mem, ksks,
ms_noise_reduction_key, bsks, mem_ptr->counter_num_blocks);
}
#endif

View File

@@ -2,17 +2,18 @@
#include "integer/negation.cuh"
#include <linear_algebra.h>
void cuda_full_propagation_64_inplace(CudaStreamsFFI streams,
CudaRadixCiphertextFFI *input_blocks,
int8_t *mem_ptr, void *const *ksks,
void *const *bsks, uint32_t num_blocks) {
void cuda_full_propagation_64_inplace(
CudaStreamsFFI streams, CudaRadixCiphertextFFI *input_blocks,
int8_t *mem_ptr, void *const *ksks,
CudaModulusSwitchNoiseReductionKeyFFI const *ms_noise_reduction_key,
void *const *bsks, uint32_t num_blocks) {
int_fullprop_buffer<uint64_t> *buffer =
(int_fullprop_buffer<uint64_t> *)mem_ptr;
host_full_propagate_inplace<uint64_t>(CudaStreams(streams), input_blocks,
buffer, (uint64_t **)(ksks), bsks,
num_blocks);
host_full_propagate_inplace<uint64_t>(
CudaStreams(streams), input_blocks, buffer, (uint64_t **)(ksks),
ms_noise_reduction_key, bsks, num_blocks);
}
uint64_t scratch_cuda_full_propagation_64(
@@ -102,24 +103,27 @@ void cuda_propagate_single_carry_kb_64_inplace(
CudaStreamsFFI streams, CudaRadixCiphertextFFI *lwe_array,
CudaRadixCiphertextFFI *carry_out, const CudaRadixCiphertextFFI *carry_in,
int8_t *mem_ptr, void *const *bsks, void *const *ksks,
CudaModulusSwitchNoiseReductionKeyFFI const *ms_noise_reduction_key,
uint32_t requested_flag, uint32_t uses_carry) {
host_propagate_single_carry<uint64_t>(
CudaStreams(streams), lwe_array, carry_out, carry_in,
(int_sc_prop_memory<uint64_t> *)mem_ptr, bsks, (uint64_t **)(ksks),
requested_flag, uses_carry);
ms_noise_reduction_key, requested_flag, uses_carry);
}
void cuda_add_and_propagate_single_carry_kb_64_inplace(
CudaStreamsFFI streams, CudaRadixCiphertextFFI *lhs_array,
const CudaRadixCiphertextFFI *rhs_array, CudaRadixCiphertextFFI *carry_out,
const CudaRadixCiphertextFFI *carry_in, int8_t *mem_ptr, void *const *bsks,
void *const *ksks, uint32_t requested_flag, uint32_t uses_carry) {
void *const *ksks,
CudaModulusSwitchNoiseReductionKeyFFI const *ms_noise_reduction_key,
uint32_t requested_flag, uint32_t uses_carry) {
host_add_and_propagate_single_carry<uint64_t>(
CudaStreams(streams), lhs_array, rhs_array, carry_out, carry_in,
(int_sc_prop_memory<uint64_t> *)mem_ptr, bsks, (uint64_t **)(ksks),
requested_flag, uses_carry);
ms_noise_reduction_key, requested_flag, uses_carry);
}
void cuda_integer_overflowing_sub_kb_64_inplace(
@@ -127,13 +131,15 @@ void cuda_integer_overflowing_sub_kb_64_inplace(
const CudaRadixCiphertextFFI *rhs_array,
CudaRadixCiphertextFFI *overflow_block,
const CudaRadixCiphertextFFI *input_borrow, int8_t *mem_ptr,
void *const *bsks, void *const *ksks, uint32_t compute_overflow,
uint32_t uses_input_borrow) {
void *const *bsks, void *const *ksks,
CudaModulusSwitchNoiseReductionKeyFFI const *ms_noise_reduction_key,
uint32_t compute_overflow, uint32_t uses_input_borrow) {
PUSH_RANGE("overflow sub")
host_integer_overflowing_sub<uint64_t>(
CudaStreams(streams), lhs_array, lhs_array, rhs_array, overflow_block,
input_borrow, (int_borrow_prop_memory<uint64_t> *)mem_ptr, bsks,
(uint64_t **)ksks, compute_overflow, uses_input_borrow);
(uint64_t **)ksks, ms_noise_reduction_key, compute_overflow,
uses_input_borrow);
POP_RANGE()
}
@@ -212,11 +218,14 @@ uint64_t scratch_cuda_apply_many_univariate_lut_kb_64(
void cuda_apply_univariate_lut_kb_64(
CudaStreamsFFI streams, CudaRadixCiphertextFFI *output_radix_lwe,
CudaRadixCiphertextFFI const *input_radix_lwe, int8_t *mem_ptr,
void *const *ksks, void *const *bsks) {
void *const *ksks,
CudaModulusSwitchNoiseReductionKeyFFI const *ms_noise_reduction_key,
void *const *bsks) {
host_apply_univariate_lut_kb<uint64_t>(
CudaStreams(streams), output_radix_lwe, input_radix_lwe,
(int_radix_lut<uint64_t> *)mem_ptr, (uint64_t **)(ksks), bsks);
(int_radix_lut<uint64_t> *)mem_ptr, (uint64_t **)(ksks),
ms_noise_reduction_key, bsks);
}
void cleanup_cuda_apply_univariate_lut_kb_64(CudaStreamsFFI streams,
@@ -232,13 +241,14 @@ void cleanup_cuda_apply_univariate_lut_kb_64(CudaStreamsFFI streams,
void cuda_apply_many_univariate_lut_kb_64(
CudaStreamsFFI streams, CudaRadixCiphertextFFI *output_radix_lwe,
CudaRadixCiphertextFFI const *input_radix_lwe, int8_t *mem_ptr,
void *const *ksks, void *const *bsks, uint32_t num_many_lut,
uint32_t lut_stride) {
void *const *ksks,
CudaModulusSwitchNoiseReductionKeyFFI const *ms_noise_reduction_key,
void *const *bsks, uint32_t num_many_lut, uint32_t lut_stride) {
host_apply_many_univariate_lut_kb<uint64_t>(
CudaStreams(streams), output_radix_lwe, input_radix_lwe,
(int_radix_lut<uint64_t> *)mem_ptr, (uint64_t **)(ksks), bsks,
num_many_lut, lut_stride);
(int_radix_lut<uint64_t> *)mem_ptr, (uint64_t **)(ksks),
ms_noise_reduction_key, bsks, num_many_lut, lut_stride);
}
uint64_t scratch_cuda_apply_bivariate_lut_kb_64(
@@ -265,13 +275,15 @@ void cuda_apply_bivariate_lut_kb_64(
CudaStreamsFFI streams, CudaRadixCiphertextFFI *output_radix_lwe,
CudaRadixCiphertextFFI const *input_radix_lwe_1,
CudaRadixCiphertextFFI const *input_radix_lwe_2, int8_t *mem_ptr,
void *const *ksks, void *const *bsks, uint32_t num_radix_blocks,
uint32_t shift) {
void *const *ksks,
CudaModulusSwitchNoiseReductionKeyFFI const *ms_noise_reduction_key,
void *const *bsks, uint32_t num_radix_blocks, uint32_t shift) {
host_apply_bivariate_lut_kb<uint64_t>(
CudaStreams(streams), output_radix_lwe, input_radix_lwe_1,
input_radix_lwe_2, (int_radix_lut<uint64_t> *)mem_ptr,
(uint64_t **)(ksks), bsks, num_radix_blocks, shift);
(uint64_t **)(ksks), ms_noise_reduction_key, bsks, num_radix_blocks,
shift);
}
void cleanup_cuda_apply_bivariate_lut_kb_64(CudaStreamsFFI streams,
@@ -308,12 +320,14 @@ uint64_t scratch_cuda_integer_compute_prefix_sum_hillis_steele_64(
void cuda_integer_compute_prefix_sum_hillis_steele_64(
CudaStreamsFFI streams, CudaRadixCiphertextFFI *output_radix_lwe,
CudaRadixCiphertextFFI *generates_or_propagates, int8_t *mem_ptr,
void *const *ksks, void *const *bsks, uint32_t num_radix_blocks) {
void *const *ksks,
CudaModulusSwitchNoiseReductionKeyFFI const *ms_noise_reduction_key,
void *const *bsks, uint32_t num_radix_blocks) {
host_compute_prefix_sum_hillis_steele<uint64_t>(
CudaStreams(streams), output_radix_lwe, generates_or_propagates,
(int_radix_lut<uint64_t> *)mem_ptr, bsks, (uint64_t **)(ksks),
num_radix_blocks);
ms_noise_reduction_key, num_radix_blocks);
}
void cleanup_cuda_integer_compute_prefix_sum_hillis_steele_64(
@@ -385,12 +399,15 @@ uint64_t scratch_cuda_apply_noise_squashing_kb(
void cuda_apply_noise_squashing_kb(
CudaStreamsFFI streams, CudaRadixCiphertextFFI *output_radix_lwe,
CudaRadixCiphertextFFI const *input_radix_lwe, int8_t *mem_ptr,
void *const *ksks, void *const *bsks) {
void *const *ksks,
CudaModulusSwitchNoiseReductionKeyFFI const *ms_noise_reduction_key,
void *const *bsks) {
PUSH_RANGE("apply noise squashing")
integer_radix_apply_noise_squashing_kb<uint64_t>(
CudaStreams(streams), output_radix_lwe, input_radix_lwe,
(int_noise_squashing_lut<uint64_t> *)mem_ptr, bsks, (uint64_t **)ksks);
(int_noise_squashing_lut<uint64_t> *)mem_ptr, bsks, (uint64_t **)ksks,
ms_noise_reduction_key);
POP_RANGE()
}

View File

@@ -507,7 +507,9 @@ template <typename Torus>
__host__ void integer_radix_apply_univariate_lookup_table_kb(
CudaStreams streams, CudaRadixCiphertextFFI *lwe_array_out,
CudaRadixCiphertextFFI const *lwe_array_in, void *const *bsks,
Torus *const *ksks, int_radix_lut<Torus> *lut, uint32_t num_radix_blocks) {
Torus *const *ksks,
CudaModulusSwitchNoiseReductionKeyFFI const *ms_noise_reduction_key,
int_radix_lut<Torus> *lut, uint32_t num_radix_blocks) {
PUSH_RANGE("apply lut")
// apply_lookup_table
auto params = lut->params;
@@ -545,30 +547,35 @@ __host__ void integer_radix_apply_univariate_lookup_table_kb(
auto active_streams = streams.active_gpu_subset(num_radix_blocks);
if (active_streams.count() == 1) {
execute_keyswitch_async<Torus>(
streams.get_ith(0), lwe_after_ks_vec[0], lwe_trivial_indexes_vec[0],
(Torus *)lwe_array_in->ptr, lut->lwe_indexes_in.get(), ksks,
big_lwe_dimension, small_lwe_dimension, ks_base_log, ks_level,
num_radix_blocks);
streams.subset_first_gpu(), lwe_after_ks_vec[0],
lwe_trivial_indexes_vec[0], (Torus *)lwe_array_in->ptr,
lut->lwe_indexes_in, ksks, big_lwe_dimension, small_lwe_dimension,
ks_base_log, ks_level, num_radix_blocks);
/// Apply PBS to apply a LUT, reduce the noise and go from a small LWE
/// dimension to a big LWE dimension
execute_pbs_async<Torus, Torus>(
streams.get_ith(0), (Torus *)lwe_array_out->ptr, lut->lwe_indexes_out,
lut->lut_vec, lut->lut_indexes_vec, lwe_after_ks_vec[0],
lwe_trivial_indexes_vec[0], bsks, lut->buffer, glwe_dimension,
streams.subset_first_gpu(), (Torus *)lwe_array_out->ptr,
lut->lwe_indexes_out, lut->lut_vec, lut->lut_indexes_vec,
lwe_after_ks_vec[0], lwe_trivial_indexes_vec[0], bsks,
ms_noise_reduction_key, lut->buffer, glwe_dimension,
small_lwe_dimension, polynomial_size, pbs_base_log, pbs_level,
grouping_factor, num_radix_blocks, pbs_type, num_many_lut, lut_stride);
} else {
/// Make sure all data that should be on GPU 0 is indeed there
lut->multi_gpu_scatter_barrier.local_streams_wait_for_stream_0(
active_streams);
cuda_event_record(lut->event_scatter_in, streams.stream(0),
streams.gpu_index(0));
for (int j = 1; j < active_streams.count(); j++) {
cuda_stream_wait_event(streams.stream(j), lut->event_scatter_in,
streams.gpu_index(j));
}
/// With multiple GPUs we push to the vectors on each GPU then when we
/// gather data to GPU 0 we can copy back to the original indexing
PUSH_RANGE("scatter")
multi_gpu_scatter_lwe_async<Torus>(
active_streams, lwe_array_in_vec, (Torus *)lwe_array_in->ptr,
lut->lwe_indexes_in.get(), lut->using_trivial_lwe_indexes,
lut->lwe_indexes_in, lut->using_trivial_lwe_indexes,
lut->lwe_aligned_vec, lut->active_streams.count(), num_radix_blocks,
big_lwe_dimension + 1);
POP_RANGE()
@@ -583,9 +590,10 @@ __host__ void integer_radix_apply_univariate_lookup_table_kb(
execute_pbs_async<Torus, Torus>(
active_streams, lwe_after_pbs_vec, lwe_trivial_indexes_vec,
lut->lut_vec, lut->lut_indexes_vec, lwe_after_ks_vec,
lwe_trivial_indexes_vec, bsks, lut->buffer, glwe_dimension,
small_lwe_dimension, polynomial_size, pbs_base_log, pbs_level,
grouping_factor, num_radix_blocks, pbs_type, num_many_lut, lut_stride);
lwe_trivial_indexes_vec, bsks, ms_noise_reduction_key, lut->buffer,
glwe_dimension, small_lwe_dimension, polynomial_size, pbs_base_log,
pbs_level, grouping_factor, num_radix_blocks, pbs_type, num_many_lut,
lut_stride);
/// Copy data back to GPU 0 and release vecs
PUSH_RANGE("gather")
@@ -594,8 +602,16 @@ __host__ void integer_radix_apply_univariate_lookup_table_kb(
lut->lwe_indexes_out, lut->using_trivial_lwe_indexes,
lut->lwe_aligned_vec, num_radix_blocks, big_lwe_dimension + 1);
POP_RANGE()
lut->multi_gpu_gather_barrier.stream_0_wait_for_local_streams(
active_streams);
// other gpus record their events
for (int j = 1; j < active_streams.count(); j++) {
cuda_event_record(lut->event_scatter_out[j], streams.stream(j),
streams.gpu_index(j));
}
// GPU 0 waits for all
for (int j = 1; j < active_streams.count(); j++) {
cuda_stream_wait_event(streams.stream(0), lut->event_scatter_out[j],
streams.gpu_index(0));
}
}
for (uint i = 0; i < num_radix_blocks; i++) {
auto degrees_index = lut->h_lut_indexes[i];
@@ -611,8 +627,9 @@ template <typename Torus>
__host__ void integer_radix_apply_many_univariate_lookup_table_kb(
CudaStreams streams, CudaRadixCiphertextFFI *lwe_array_out,
CudaRadixCiphertextFFI const *lwe_array_in, void *const *bsks,
Torus *const *ksks, int_radix_lut<Torus> *lut, uint32_t num_many_lut,
uint32_t lut_stride) {
Torus *const *ksks,
CudaModulusSwitchNoiseReductionKeyFFI const *ms_noise_reduction_key,
int_radix_lut<Torus> *lut, uint32_t num_many_lut, uint32_t lut_stride) {
PUSH_RANGE("apply many lut")
// apply_lookup_table
auto params = lut->params;
@@ -647,30 +664,34 @@ __host__ void integer_radix_apply_many_univariate_lookup_table_kb(
auto active_streams = streams.active_gpu_subset(num_radix_blocks);
if (active_streams.count() == 1) {
execute_keyswitch_async<Torus>(
streams.get_ith(0), lwe_after_ks_vec[0], lwe_trivial_indexes_vec[0],
(Torus *)lwe_array_in->ptr, lut->lwe_indexes_in.get(), ksks,
big_lwe_dimension, small_lwe_dimension, ks_base_log, ks_level,
num_radix_blocks);
streams.subset_first_gpu(), lwe_after_ks_vec[0],
lwe_trivial_indexes_vec[0], (Torus *)lwe_array_in->ptr,
lut->lwe_indexes_in, ksks, big_lwe_dimension, small_lwe_dimension,
ks_base_log, ks_level, num_radix_blocks);
/// Apply PBS to apply a LUT, reduce the noise and go from a small LWE
/// dimension to a big LWE dimension
execute_pbs_async<Torus, Torus>(
streams.get_ith(0), (Torus *)lwe_array_out->ptr, lut->lwe_indexes_out,
lut->lut_vec, lut->lut_indexes_vec, lwe_after_ks_vec[0],
lwe_trivial_indexes_vec[0], bsks, lut->buffer, glwe_dimension,
streams.subset_first_gpu(), (Torus *)lwe_array_out->ptr,
lut->lwe_indexes_out, lut->lut_vec, lut->lut_indexes_vec,
lwe_after_ks_vec[0], lwe_trivial_indexes_vec[0], bsks,
ms_noise_reduction_key, lut->buffer, glwe_dimension,
small_lwe_dimension, polynomial_size, pbs_base_log, pbs_level,
grouping_factor, num_radix_blocks, pbs_type, num_many_lut, lut_stride);
} else {
/// Make sure all data that should be on GPU 0 is indeed there
lut->multi_gpu_scatter_barrier.local_streams_wait_for_stream_0(
active_streams);
cuda_event_record(lut->event_scatter_in, streams.stream(0),
streams.gpu_index(0));
for (int j = 1; j < active_streams.count(); j++) {
cuda_stream_wait_event(streams.stream(j), lut->event_scatter_in,
streams.gpu_index(j));
}
/// With multiple GPUs we push to the vectors on each GPU then when we
/// gather data to GPU 0 we can copy back to the original indexing
PUSH_RANGE("scatter")
multi_gpu_scatter_lwe_async<Torus>(
active_streams, lwe_array_in_vec, (Torus *)lwe_array_in->ptr,
lut->lwe_indexes_in.get(), lut->using_trivial_lwe_indexes,
lut->lwe_indexes_in, lut->using_trivial_lwe_indexes,
lut->lwe_aligned_vec, lut->active_streams.count(), num_radix_blocks,
big_lwe_dimension + 1);
POP_RANGE()
@@ -685,9 +706,10 @@ __host__ void integer_radix_apply_many_univariate_lookup_table_kb(
execute_pbs_async<Torus, Torus>(
active_streams, lwe_after_pbs_vec, lwe_trivial_indexes_vec,
lut->lut_vec, lut->lut_indexes_vec, lwe_after_ks_vec,
lwe_trivial_indexes_vec, bsks, lut->buffer, glwe_dimension,
small_lwe_dimension, polynomial_size, pbs_base_log, pbs_level,
grouping_factor, num_radix_blocks, pbs_type, num_many_lut, lut_stride);
lwe_trivial_indexes_vec, bsks, ms_noise_reduction_key, lut->buffer,
glwe_dimension, small_lwe_dimension, polynomial_size, pbs_base_log,
pbs_level, grouping_factor, num_radix_blocks, pbs_type, num_many_lut,
lut_stride);
/// Copy data back to GPU 0 and release vecs
PUSH_RANGE("gather")
@@ -697,8 +719,16 @@ __host__ void integer_radix_apply_many_univariate_lookup_table_kb(
num_radix_blocks, big_lwe_dimension + 1, num_many_lut);
POP_RANGE()
lut->multi_gpu_gather_barrier.stream_0_wait_for_local_streams(
active_streams);
// other gpus record their events
for (int j = 1; j < active_streams.count(); j++) {
cuda_event_record(lut->event_scatter_out[j], streams.stream(j),
streams.gpu_index(j));
}
// GPU 0 waits for all
for (int j = 1; j < active_streams.count(); j++) {
cuda_stream_wait_event(streams.stream(0), lut->event_scatter_out[j],
streams.gpu_index(0));
}
}
for (uint i = 0; i < lwe_array_out->num_radix_blocks; i++) {
auto degrees_index = lut->h_lut_indexes[i % lut->num_blocks];
@@ -715,8 +745,9 @@ __host__ void integer_radix_apply_bivariate_lookup_table_kb(
CudaStreams streams, CudaRadixCiphertextFFI *lwe_array_out,
CudaRadixCiphertextFFI const *lwe_array_1,
CudaRadixCiphertextFFI const *lwe_array_2, void *const *bsks,
Torus *const *ksks, int_radix_lut<Torus> *lut, uint32_t num_radix_blocks,
uint32_t shift) {
Torus *const *ksks,
CudaModulusSwitchNoiseReductionKeyFFI const *ms_noise_reduction_key,
int_radix_lut<Torus> *lut, uint32_t num_radix_blocks, uint32_t shift) {
PUSH_RANGE("apply bivar lut")
if (lwe_array_out->lwe_dimension != lwe_array_1->lwe_dimension ||
lwe_array_out->lwe_dimension != lwe_array_2->lwe_dimension)
@@ -748,10 +779,10 @@ __host__ void integer_radix_apply_bivariate_lookup_table_kb(
uint32_t lut_stride = 0;
// Left message is shifted
auto lwe_array_pbs_in = lut->tmp_lwe_before_ks.get();
auto lwe_array_pbs_in = lut->tmp_lwe_before_ks;
host_pack_bivariate_blocks<Torus>(
streams, lwe_array_pbs_in, lut->lwe_trivial_indexes, lwe_array_1,
lwe_array_2, lut->lwe_indexes_in.get(), shift, num_radix_blocks,
lwe_array_2, lut->lwe_indexes_in, shift, num_radix_blocks,
params.message_modulus, params.carry_modulus);
check_cuda_error(cudaGetLastError());
@@ -765,27 +796,31 @@ __host__ void integer_radix_apply_bivariate_lookup_table_kb(
auto active_streams = streams.active_gpu_subset(num_radix_blocks);
if (active_streams.count() == 1) {
execute_keyswitch_async<Torus>(
streams.get_ith(0), lwe_after_ks_vec[0], lwe_trivial_indexes_vec[0],
(Torus *)lwe_array_pbs_in->ptr, lut->lwe_indexes_in.get(), ksks,
big_lwe_dimension, small_lwe_dimension, ks_base_log, ks_level,
num_radix_blocks);
streams.subset_first_gpu(), lwe_after_ks_vec[0],
lwe_trivial_indexes_vec[0], (Torus *)lwe_array_pbs_in->ptr,
lut->lwe_indexes_in, ksks, big_lwe_dimension, small_lwe_dimension,
ks_base_log, ks_level, num_radix_blocks);
/// Apply PBS to apply a LUT, reduce the noise and go from a small LWE
/// dimension to a big LWE dimension
execute_pbs_async<Torus, Torus>(
streams.get_ith(0), (Torus *)(lwe_array_out->ptr), lut->lwe_indexes_out,
lut->lut_vec, lut->lut_indexes_vec, lwe_after_ks_vec[0],
lwe_trivial_indexes_vec[0], bsks, lut->buffer, glwe_dimension,
streams.subset_first_gpu(), (Torus *)(lwe_array_out->ptr),
lut->lwe_indexes_out, lut->lut_vec, lut->lut_indexes_vec,
lwe_after_ks_vec[0], lwe_trivial_indexes_vec[0], bsks,
ms_noise_reduction_key, lut->buffer, glwe_dimension,
small_lwe_dimension, polynomial_size, pbs_base_log, pbs_level,
grouping_factor, num_radix_blocks, pbs_type, num_many_lut, lut_stride);
} else {
lut->multi_gpu_scatter_barrier.local_streams_wait_for_stream_0(
active_streams);
cuda_event_record(lut->event_scatter_in, streams.stream(0),
streams.gpu_index(0));
for (int j = 1; j < active_streams.count(); j++) {
cuda_stream_wait_event(streams.stream(j), lut->event_scatter_in,
streams.gpu_index(j));
}
PUSH_RANGE("scatter")
multi_gpu_scatter_lwe_async<Torus>(
active_streams, lwe_array_in_vec, (Torus *)lwe_array_pbs_in->ptr,
lut->lwe_indexes_in.get(), lut->using_trivial_lwe_indexes,
lut->lwe_indexes_in, lut->using_trivial_lwe_indexes,
lut->lwe_aligned_vec, lut->active_streams.count(), num_radix_blocks,
big_lwe_dimension + 1);
POP_RANGE()
@@ -800,9 +835,10 @@ __host__ void integer_radix_apply_bivariate_lookup_table_kb(
execute_pbs_async<Torus, Torus>(
active_streams, lwe_after_pbs_vec, lwe_trivial_indexes_vec,
lut->lut_vec, lut->lut_indexes_vec, lwe_after_ks_vec,
lwe_trivial_indexes_vec, bsks, lut->buffer, glwe_dimension,
small_lwe_dimension, polynomial_size, pbs_base_log, pbs_level,
grouping_factor, num_radix_blocks, pbs_type, num_many_lut, lut_stride);
lwe_trivial_indexes_vec, bsks, ms_noise_reduction_key, lut->buffer,
glwe_dimension, small_lwe_dimension, polynomial_size, pbs_base_log,
pbs_level, grouping_factor, num_radix_blocks, pbs_type, num_many_lut,
lut_stride);
/// Copy data back to GPU 0 and release vecs
PUSH_RANGE("gather")
@@ -811,8 +847,16 @@ __host__ void integer_radix_apply_bivariate_lookup_table_kb(
lut->lwe_indexes_out, lut->using_trivial_lwe_indexes,
lut->lwe_aligned_vec, num_radix_blocks, big_lwe_dimension + 1);
POP_RANGE()
lut->multi_gpu_gather_barrier.stream_0_wait_for_local_streams(
active_streams);
// other gpus record their events
for (int j = 1; j < active_streams.count(); j++) {
cuda_event_record(lut->event_scatter_out[j], streams.stream(j),
streams.gpu_index(j));
}
// GPU 0 waits for all
for (int j = 1; j < active_streams.count(); j++) {
cuda_stream_wait_event(streams.stream(0), lut->event_scatter_out[j],
streams.gpu_index(0));
}
}
for (uint i = 0; i < num_radix_blocks; i++) {
auto degrees_index = lut->h_lut_indexes[i];
@@ -1273,7 +1317,9 @@ template <typename Torus>
void host_compute_shifted_blocks_and_states(
CudaStreams streams, CudaRadixCiphertextFFI *lwe_array,
int_shifted_blocks_and_states_memory<Torus> *mem, void *const *bsks,
Torus *const *ksks, uint32_t lut_stride, uint32_t num_many_lut) {
Torus *const *ksks,
CudaModulusSwitchNoiseReductionKeyFFI const *ms_noise_reduction_key,
uint32_t lut_stride, uint32_t num_many_lut) {
auto num_radix_blocks = lwe_array->num_radix_blocks;
@@ -1282,7 +1328,7 @@ void host_compute_shifted_blocks_and_states(
integer_radix_apply_many_univariate_lookup_table_kb<Torus>(
streams, shifted_blocks_and_states, lwe_array, bsks, ksks,
luts_array_first_step, num_many_lut, lut_stride);
ms_noise_reduction_key, luts_array_first_step, num_many_lut, lut_stride);
auto shifted_blocks = mem->shifted_blocks;
auto block_states = mem->block_states;
@@ -1301,7 +1347,9 @@ void host_resolve_group_carries_sequentially(
CudaStreams streams, CudaRadixCiphertextFFI *resolved_carries,
CudaRadixCiphertextFFI *grouping_pgns, int_radix_params params,
int_seq_group_prop_memory<Torus> *mem, void *const *bsks,
Torus *const *ksks, uint32_t num_groups) {
Torus *const *ksks,
CudaModulusSwitchNoiseReductionKeyFFI const *ms_noise_reduction_key,
uint32_t num_groups) {
auto group_resolved_carries = mem->group_resolved_carries;
if (num_groups > 1) {
@@ -1350,8 +1398,8 @@ void host_resolve_group_carries_sequentially(
blocks_to_solve + 1);
integer_radix_apply_univariate_lookup_table_kb<Torus>(
streams, &shifted_group_resolved_carries,
&shifted_group_resolved_carries, bsks, ksks, luts_sequential,
blocks_to_solve);
&shifted_group_resolved_carries, bsks, ksks, ms_noise_reduction_key,
luts_sequential, blocks_to_solve);
// Copy the result to the resolved carries array
copy_radix_ciphertext_slice_async<Torus>(
@@ -1368,7 +1416,9 @@ template <typename Torus>
void host_compute_prefix_sum_hillis_steele(
CudaStreams streams, CudaRadixCiphertextFFI *step_output,
CudaRadixCiphertextFFI *generates_or_propagates, int_radix_lut<Torus> *luts,
void *const *bsks, Torus *const *ksks, uint32_t num_radix_blocks) {
void *const *bsks, Torus *const *ksks,
CudaModulusSwitchNoiseReductionKeyFFI const *ms_noise_reduction_key,
uint32_t num_radix_blocks) {
if (step_output->lwe_dimension != generates_or_propagates->lwe_dimension)
PANIC("Cuda error: input lwe dimensions must be the same")
@@ -1390,8 +1440,9 @@ void host_compute_prefix_sum_hillis_steele(
int cur_total_blocks = num_radix_blocks - space;
integer_radix_apply_bivariate_lookup_table_kb<Torus>(
streams, &cur_blocks, &cur_blocks, prev_blocks, bsks, ksks, luts,
cur_total_blocks, luts->params.message_modulus);
streams, &cur_blocks, &cur_blocks, prev_blocks, bsks, ksks,
ms_noise_reduction_key, luts, cur_total_blocks,
luts->params.message_modulus);
copy_radix_ciphertext_slice_async<Torus>(
streams.stream(0), streams.gpu_index(0), generates_or_propagates, space,
@@ -1411,8 +1462,9 @@ template <typename Torus>
void host_compute_propagation_simulators_and_group_carries(
CudaStreams streams, CudaRadixCiphertextFFI *block_states,
int_radix_params params, int_prop_simu_group_carries_memory<Torus> *mem,
void *const *bsks, Torus *const *ksks, uint32_t num_radix_blocks,
uint32_t num_groups) {
void *const *bsks, Torus *const *ksks,
CudaModulusSwitchNoiseReductionKeyFFI const *ms_noise_reduction_key,
uint32_t num_radix_blocks, uint32_t num_groups) {
if (num_radix_blocks > block_states->num_radix_blocks)
PANIC("Cuda error: input does not have enough radix blocks")
@@ -1429,7 +1481,7 @@ void host_compute_propagation_simulators_and_group_carries(
auto luts_array_second_step = mem->luts_array_second_step;
integer_radix_apply_univariate_lookup_table_kb<Torus>(
streams, propagation_cum_sums, propagation_cum_sums, bsks, ksks,
luts_array_second_step, num_radix_blocks);
ms_noise_reduction_key, luts_array_second_step, num_radix_blocks);
host_integer_radix_scalar_addition_inplace<Torus>(
streams, propagation_cum_sums, mem->scalar_array_cum_sum,
@@ -1448,9 +1500,10 @@ void host_compute_propagation_simulators_and_group_carries(
auto resolved_carries = mem->resolved_carries;
if (mem->use_sequential_algorithm_to_resolve_group_carries) {
// Resolve group carries sequentially
host_resolve_group_carries_sequentially(
streams, resolved_carries, grouping_pgns, params,
mem->seq_group_prop_mem, bsks, ksks, num_groups);
host_resolve_group_carries_sequentially(streams, resolved_carries,
grouping_pgns, params,
mem->seq_group_prop_mem, bsks, ksks,
ms_noise_reduction_key, num_groups);
} else {
// Resolve group carries with hillis steele
auto luts_carry_propagation_sum = mem->hs_group_prop_mem->lut_hillis_steele;
@@ -1459,7 +1512,8 @@ void host_compute_propagation_simulators_and_group_carries(
resolved_carries, 1, num_groups);
host_compute_prefix_sum_hillis_steele<Torus>(
streams, &shifted_resolved_carries, grouping_pgns,
luts_carry_propagation_sum, bsks, ksks, num_groups - 1);
luts_carry_propagation_sum, bsks, ksks, ms_noise_reduction_key,
num_groups - 1);
}
}
@@ -1473,7 +1527,9 @@ template <typename Torus>
void host_compute_shifted_blocks_and_borrow_states(
CudaStreams streams, CudaRadixCiphertextFFI *lwe_array,
int_shifted_blocks_and_borrow_states_memory<Torus> *mem, void *const *bsks,
Torus *const *ksks, uint32_t lut_stride, uint32_t num_many_lut) {
Torus *const *ksks,
CudaModulusSwitchNoiseReductionKeyFFI const *ms_noise_reduction_key,
uint32_t lut_stride, uint32_t num_many_lut) {
auto num_radix_blocks = lwe_array->num_radix_blocks;
auto shifted_blocks_and_borrow_states = mem->shifted_blocks_and_borrow_states;
@@ -1481,7 +1537,7 @@ void host_compute_shifted_blocks_and_borrow_states(
integer_radix_apply_many_univariate_lookup_table_kb<Torus>(
streams, shifted_blocks_and_borrow_states, lwe_array, bsks, ksks,
luts_array_first_step, num_many_lut, lut_stride);
ms_noise_reduction_key, luts_array_first_step, num_many_lut, lut_stride);
auto shifted_blocks = mem->shifted_blocks;
auto borrow_states = mem->borrow_states;
@@ -1503,11 +1559,11 @@ void host_compute_shifted_blocks_and_borrow_states(
* have size = 2 * (glwe_dimension * polynomial_size + 1) * sizeof(Torus)
*/
template <typename Torus>
void host_full_propagate_inplace(CudaStreams streams,
CudaRadixCiphertextFFI *input_blocks,
int_fullprop_buffer<Torus> *mem_ptr,
Torus *const *ksks, void *const *bsks,
uint32_t num_blocks) {
void host_full_propagate_inplace(
CudaStreams streams, CudaRadixCiphertextFFI *input_blocks,
int_fullprop_buffer<Torus> *mem_ptr, Torus *const *ksks,
CudaModulusSwitchNoiseReductionKeyFFI const *ms_noise_reduction_key,
void *const *bsks, uint32_t num_blocks) {
auto params = mem_ptr->lut->params;
// In the case of extracting a single LWE this parameters are dummy
@@ -1519,7 +1575,8 @@ void host_full_propagate_inplace(CudaStreams streams,
/// Since the keyswitch is done on one input only, use only 1 GPU
execute_keyswitch_async<Torus>(
streams.get_ith(0), (Torus *)(mem_ptr->tmp_small_lwe_vector->ptr),
streams.subset_first_gpu(),
(Torus *)(mem_ptr->tmp_small_lwe_vector->ptr),
mem_ptr->lut->lwe_trivial_indexes, (Torus *)cur_input_block.ptr,
mem_ptr->lut->lwe_trivial_indexes, ksks, params.big_lwe_dimension,
params.small_lwe_dimension, params.ks_base_log, params.ks_level, 1);
@@ -1529,12 +1586,12 @@ void host_full_propagate_inplace(CudaStreams streams,
1, 2, mem_ptr->tmp_small_lwe_vector, 0, 1);
execute_pbs_async<Torus, Torus>(
streams.get_ith(0), (Torus *)mem_ptr->tmp_big_lwe_vector->ptr,
streams.subset_first_gpu(), (Torus *)mem_ptr->tmp_big_lwe_vector->ptr,
mem_ptr->lut->lwe_trivial_indexes, mem_ptr->lut->lut_vec,
mem_ptr->lut->lut_indexes_vec,
(Torus *)mem_ptr->tmp_small_lwe_vector->ptr,
mem_ptr->lut->lwe_trivial_indexes, bsks, mem_ptr->lut->buffer,
params.glwe_dimension, params.small_lwe_dimension,
mem_ptr->lut->lwe_trivial_indexes, bsks, ms_noise_reduction_key,
mem_ptr->lut->buffer, params.glwe_dimension, params.small_lwe_dimension,
params.polynomial_size, params.pbs_base_log, params.pbs_level,
params.grouping_factor, 2, params.pbs_type, num_many_lut, lut_stride);
@@ -1665,12 +1722,13 @@ __host__ void scalar_pack_blocks(cudaStream_t stream, uint32_t gpu_index,
* * (lwe_dimension+1) * sizeeof(Torus) bytes
*/
template <typename Torus>
__host__ void
extract_n_bits(CudaStreams streams, CudaRadixCiphertextFFI *lwe_array_out,
const CudaRadixCiphertextFFI *lwe_array_in, void *const *bsks,
Torus *const *ksks, uint32_t effective_num_radix_blocks,
uint32_t num_radix_blocks,
int_bit_extract_luts_buffer<Torus> *bit_extract) {
__host__ void extract_n_bits(
CudaStreams streams, CudaRadixCiphertextFFI *lwe_array_out,
const CudaRadixCiphertextFFI *lwe_array_in, void *const *bsks,
Torus *const *ksks,
CudaModulusSwitchNoiseReductionKeyFFI const *ms_noise_reduction_key,
uint32_t effective_num_radix_blocks, uint32_t num_radix_blocks,
int_bit_extract_luts_buffer<Torus> *bit_extract) {
copy_radix_ciphertext_slice_async<Torus>(
streams.stream(0), streams.gpu_index(0), lwe_array_out, 0,
@@ -1684,17 +1742,19 @@ extract_n_bits(CudaStreams streams, CudaRadixCiphertextFFI *lwe_array_out,
}
}
integer_radix_apply_univariate_lookup_table_kb<Torus>(
streams, lwe_array_out, lwe_array_out, bsks, ksks, bit_extract->lut,
effective_num_radix_blocks);
streams, lwe_array_out, lwe_array_out, bsks, ksks, ms_noise_reduction_key,
bit_extract->lut, effective_num_radix_blocks);
}
template <typename Torus>
__host__ void
reduce_signs(CudaStreams streams, CudaRadixCiphertextFFI *signs_array_out,
CudaRadixCiphertextFFI *signs_array_in,
int_comparison_buffer<Torus> *mem_ptr,
std::function<Torus(Torus)> sign_handler_f, void *const *bsks,
Torus *const *ksks, uint32_t num_sign_blocks) {
__host__ void reduce_signs(
CudaStreams streams, CudaRadixCiphertextFFI *signs_array_out,
CudaRadixCiphertextFFI *signs_array_in,
int_comparison_buffer<Torus> *mem_ptr,
std::function<Torus(Torus)> sign_handler_f, void *const *bsks,
Torus *const *ksks,
CudaModulusSwitchNoiseReductionKeyFFI const *ms_noise_reduction_key,
uint32_t num_sign_blocks) {
if (signs_array_out->lwe_dimension != signs_array_in->lwe_dimension)
PANIC("Cuda error: input lwe dimensions must be the same")
@@ -1740,7 +1800,8 @@ reduce_signs(CudaStreams streams, CudaRadixCiphertextFFI *signs_array_out,
pack_blocks<Torus>(streams.stream(0), streams.gpu_index(0), signs_b,
signs_a, num_sign_blocks, message_modulus);
integer_radix_apply_univariate_lookup_table_kb<Torus>(
streams, signs_a, signs_b, bsks, ksks, lut, num_sign_blocks / 2);
streams, signs_a, signs_b, bsks, ksks, ms_noise_reduction_key, lut,
num_sign_blocks / 2);
if (num_sign_blocks % 2 == 1)
copy_radix_ciphertext_slice_async<Torus>(
@@ -1770,7 +1831,8 @@ reduce_signs(CudaStreams streams, CudaRadixCiphertextFFI *signs_array_out,
pack_blocks<Torus>(streams.stream(0), streams.gpu_index(0), signs_b,
signs_a, num_sign_blocks, message_modulus);
integer_radix_apply_univariate_lookup_table_kb<Torus>(
streams, signs_array_out, signs_b, bsks, ksks, lut, 1);
streams, signs_array_out, signs_b, bsks, ksks, ms_noise_reduction_key,
lut, 1);
} else {
@@ -1788,7 +1850,8 @@ reduce_signs(CudaStreams streams, CudaRadixCiphertextFFI *signs_array_out,
lut->broadcast_lut(lut->active_streams);
integer_radix_apply_univariate_lookup_table_kb<Torus>(
streams, signs_array_out, signs_a, bsks, ksks, lut, 1);
streams, signs_array_out, signs_a, bsks, ksks, ms_noise_reduction_key,
lut, 1);
}
}
@@ -1815,15 +1878,16 @@ uint64_t scratch_cuda_apply_univariate_lut_kb(
}
template <typename Torus>
void host_apply_univariate_lut_kb(CudaStreams streams,
CudaRadixCiphertextFFI *radix_lwe_out,
CudaRadixCiphertextFFI const *radix_lwe_in,
int_radix_lut<Torus> *mem, Torus *const *ksks,
void *const *bsks) {
void host_apply_univariate_lut_kb(
CudaStreams streams, CudaRadixCiphertextFFI *radix_lwe_out,
CudaRadixCiphertextFFI const *radix_lwe_in, int_radix_lut<Torus> *mem,
Torus *const *ksks,
CudaModulusSwitchNoiseReductionKeyFFI const *ms_noise_reduction_key,
void *const *bsks) {
integer_radix_apply_univariate_lookup_table_kb<Torus>(
streams, radix_lwe_out, radix_lwe_in, bsks, ksks, mem,
radix_lwe_out->num_radix_blocks);
streams, radix_lwe_out, radix_lwe_in, bsks, ksks, ms_noise_reduction_key,
mem, radix_lwe_out->num_radix_blocks);
}
template <typename Torus>
@@ -1853,12 +1917,13 @@ template <typename Torus>
void host_apply_many_univariate_lut_kb(
CudaStreams streams, CudaRadixCiphertextFFI *radix_lwe_out,
CudaRadixCiphertextFFI const *radix_lwe_in, int_radix_lut<Torus> *mem,
Torus *const *ksks, void *const *bsks, uint32_t num_many_lut,
uint32_t lut_stride) {
Torus *const *ksks,
CudaModulusSwitchNoiseReductionKeyFFI const *ms_noise_reduction_key,
void *const *bsks, uint32_t num_many_lut, uint32_t lut_stride) {
integer_radix_apply_many_univariate_lookup_table_kb<Torus>(
streams, radix_lwe_out, radix_lwe_in, bsks, ksks, mem, num_many_lut,
lut_stride);
streams, radix_lwe_out, radix_lwe_in, bsks, ksks, ms_noise_reduction_key,
mem, num_many_lut, lut_stride);
}
template <typename Torus>
@@ -1884,17 +1949,17 @@ uint64_t scratch_cuda_apply_bivariate_lut_kb(
}
template <typename Torus>
void host_apply_bivariate_lut_kb(CudaStreams streams,
CudaRadixCiphertextFFI *radix_lwe_out,
CudaRadixCiphertextFFI const *radix_lwe_in_1,
CudaRadixCiphertextFFI const *radix_lwe_in_2,
int_radix_lut<Torus> *mem, Torus *const *ksks,
void *const *bsks, uint32_t num_radix_blocks,
uint32_t shift) {
void host_apply_bivariate_lut_kb(
CudaStreams streams, CudaRadixCiphertextFFI *radix_lwe_out,
CudaRadixCiphertextFFI const *radix_lwe_in_1,
CudaRadixCiphertextFFI const *radix_lwe_in_2, int_radix_lut<Torus> *mem,
Torus *const *ksks,
CudaModulusSwitchNoiseReductionKeyFFI const *ms_noise_reduction_key,
void *const *bsks, uint32_t num_radix_blocks, uint32_t shift) {
integer_radix_apply_bivariate_lookup_table_kb<Torus>(
streams, radix_lwe_out, radix_lwe_in_1, radix_lwe_in_2, bsks, ksks, mem,
num_radix_blocks, shift);
streams, radix_lwe_out, radix_lwe_in_1, radix_lwe_in_2, bsks, ksks,
ms_noise_reduction_key, mem, num_radix_blocks, shift);
}
template <typename Torus>
@@ -1913,13 +1978,13 @@ uint64_t scratch_cuda_propagate_single_carry_kb_inplace(
// This function perform the three steps of Thomas' new carry propagation
// includes the logic to extract overflow when requested
template <typename Torus>
void host_propagate_single_carry(CudaStreams streams,
CudaRadixCiphertextFFI *lwe_array,
CudaRadixCiphertextFFI *carry_out,
const CudaRadixCiphertextFFI *input_carries,
int_sc_prop_memory<Torus> *mem,
void *const *bsks, Torus *const *ksks,
uint32_t requested_flag, uint32_t uses_carry) {
void host_propagate_single_carry(
CudaStreams streams, CudaRadixCiphertextFFI *lwe_array,
CudaRadixCiphertextFFI *carry_out,
const CudaRadixCiphertextFFI *input_carries, int_sc_prop_memory<Torus> *mem,
void *const *bsks, Torus *const *ksks,
CudaModulusSwitchNoiseReductionKeyFFI const *ms_noise_reduction_key,
uint32_t requested_flag, uint32_t uses_carry) {
PUSH_RANGE("propagate sc")
auto num_radix_blocks = lwe_array->num_radix_blocks;
auto params = mem->params;
@@ -1942,8 +2007,8 @@ void host_propagate_single_carry(CudaStreams streams,
// Step 1
host_compute_shifted_blocks_and_states<Torus>(
streams, lwe_array, mem->shifted_blocks_state_mem, bsks, ksks, lut_stride,
num_many_lut);
streams, lwe_array, mem->shifted_blocks_state_mem, bsks, ksks,
ms_noise_reduction_key, lut_stride, num_many_lut);
auto block_states = mem->shifted_blocks_state_mem->block_states;
if (requested_flag == outputFlag::FLAG_CARRY) {
@@ -1954,7 +2019,7 @@ void host_propagate_single_carry(CudaStreams streams,
// Step 2
host_compute_propagation_simulators_and_group_carries<Torus>(
streams, block_states, params, mem->prop_simu_group_carries_mem, bsks,
ksks, num_radix_blocks, mem->num_groups);
ksks, ms_noise_reduction_key, num_radix_blocks, mem->num_groups);
auto group_size = mem->prop_simu_group_carries_mem->group_size;
@@ -1995,7 +2060,7 @@ void host_propagate_single_carry(CudaStreams streams,
num_radix_blocks, num_radix_blocks + 1, &output_flag, 0, 1);
integer_radix_apply_univariate_lookup_table_kb<Torus>(
streams, mem->output_flag, prepared_blocks, bsks, ksks,
mem->lut_message_extract, num_radix_blocks + 1);
ms_noise_reduction_key, mem->lut_message_extract, num_radix_blocks + 1);
copy_radix_ciphertext_slice_async<Torus>(
streams.stream(0), streams.gpu_index(0), lwe_array, 0, num_radix_blocks,
@@ -2006,8 +2071,8 @@ void host_propagate_single_carry(CudaStreams streams,
} else {
auto message_extract = mem->lut_message_extract;
integer_radix_apply_univariate_lookup_table_kb<Torus>(
streams, lwe_array, prepared_blocks, bsks, ksks, message_extract,
num_radix_blocks);
streams, lwe_array, prepared_blocks, bsks, ksks, ms_noise_reduction_key,
message_extract, num_radix_blocks);
}
POP_RANGE()
}
@@ -2019,8 +2084,9 @@ void host_add_and_propagate_single_carry(
CudaStreams streams, CudaRadixCiphertextFFI *lhs_array,
const CudaRadixCiphertextFFI *rhs_array, CudaRadixCiphertextFFI *carry_out,
const CudaRadixCiphertextFFI *input_carries, int_sc_prop_memory<Torus> *mem,
void *const *bsks, Torus *const *ksks, uint32_t requested_flag,
uint32_t uses_carry) {
void *const *bsks, Torus *const *ksks,
CudaModulusSwitchNoiseReductionKeyFFI const *ms_noise_reduction_key,
uint32_t requested_flag, uint32_t uses_carry) {
PUSH_RANGE("add & propagate sc")
if (lhs_array->num_radix_blocks != rhs_array->num_radix_blocks)
PANIC("Cuda error: input and output num radix blocks must be the same")
@@ -2073,14 +2139,15 @@ void host_add_and_propagate_single_carry(
}
// Step 1
host_compute_shifted_blocks_and_states<Torus>(
streams, lhs_array, mem->shifted_blocks_state_mem, bsks, ksks, lut_stride,
num_many_lut);
streams, lhs_array, mem->shifted_blocks_state_mem, bsks, ksks,
ms_noise_reduction_key, lut_stride, num_many_lut);
auto block_states = mem->shifted_blocks_state_mem->block_states;
if (requested_flag == outputFlag::FLAG_OVERFLOW) {
auto lut_overflow_prep = mem->lut_overflow_flag_prep;
integer_radix_apply_bivariate_lookup_table_kb<Torus>(
streams, &output_flag, mem->last_lhs, mem->last_rhs, bsks, ksks,
lut_overflow_prep, 1, lut_overflow_prep->params.message_modulus);
ms_noise_reduction_key, lut_overflow_prep, 1,
lut_overflow_prep->params.message_modulus);
} else if (requested_flag == outputFlag::FLAG_CARRY) {
copy_radix_ciphertext_slice_async<Torus>(
streams.stream(0), streams.gpu_index(0), &output_flag, 0, 1,
@@ -2090,7 +2157,7 @@ void host_add_and_propagate_single_carry(
// Step 2
host_compute_propagation_simulators_and_group_carries<Torus>(
streams, block_states, params, mem->prop_simu_group_carries_mem, bsks,
ksks, num_radix_blocks, mem->num_groups);
ksks, ms_noise_reduction_key, num_radix_blocks, mem->num_groups);
auto group_size = mem->prop_simu_group_carries_mem->group_size;
@@ -2143,7 +2210,7 @@ void host_add_and_propagate_single_carry(
num_radix_blocks, num_radix_blocks + 1, &output_flag, 0, 1);
integer_radix_apply_univariate_lookup_table_kb<Torus>(
streams, mem->output_flag, prepared_blocks, bsks, ksks,
mem->lut_message_extract, num_radix_blocks + 1);
ms_noise_reduction_key, mem->lut_message_extract, num_radix_blocks + 1);
copy_radix_ciphertext_slice_async<Torus>(
streams.stream(0), streams.gpu_index(0), lhs_array, 0, num_radix_blocks,
@@ -2154,7 +2221,7 @@ void host_add_and_propagate_single_carry(
mem->output_flag, num_radix_blocks, num_radix_blocks + 1);
} else {
integer_radix_apply_univariate_lookup_table_kb<Torus>(
streams, lhs_array, prepared_blocks, bsks, ksks,
streams, lhs_array, prepared_blocks, bsks, ksks, ms_noise_reduction_key,
mem->lut_message_extract, num_radix_blocks);
}
POP_RANGE()
@@ -2177,15 +2244,14 @@ uint64_t scratch_cuda_integer_overflowing_sub(
// This function perform the three steps of Thomas' new borrow propagation
// includes the logic to extract overflow when requested
template <typename Torus>
void host_single_borrow_propagate(CudaStreams streams,
CudaRadixCiphertextFFI *lwe_array,
CudaRadixCiphertextFFI *overflow_block,
const CudaRadixCiphertextFFI *input_borrow,
int_borrow_prop_memory<Torus> *mem,
void *const *bsks, Torus *const *ksks,
uint32_t num_groups,
uint32_t compute_overflow,
uint32_t uses_input_borrow) {
void host_single_borrow_propagate(
CudaStreams streams, CudaRadixCiphertextFFI *lwe_array,
CudaRadixCiphertextFFI *overflow_block,
const CudaRadixCiphertextFFI *input_borrow,
int_borrow_prop_memory<Torus> *mem, void *const *bsks, Torus *const *ksks,
CudaModulusSwitchNoiseReductionKeyFFI const *ms_noise_reduction_key,
uint32_t num_groups, uint32_t compute_overflow,
uint32_t uses_input_borrow) {
auto num_radix_blocks = lwe_array->num_radix_blocks;
auto params = mem->params;
auto glwe_dimension = params.glwe_dimension;
@@ -2207,7 +2273,7 @@ void host_single_borrow_propagate(CudaStreams streams,
// Step 1
host_compute_shifted_blocks_and_borrow_states<Torus>(
streams, lwe_array, mem->shifted_blocks_borrow_state_mem, bsks, ksks,
lut_stride, num_many_lut);
ms_noise_reduction_key, lut_stride, num_many_lut);
auto borrow_states = mem->shifted_blocks_borrow_state_mem->borrow_states;
copy_radix_ciphertext_slice_async<Torus>(
@@ -2217,7 +2283,7 @@ void host_single_borrow_propagate(CudaStreams streams,
// Step 2
host_compute_propagation_simulators_and_group_carries<Torus>(
streams, borrow_states, params, mem->prop_simu_group_carries_mem, bsks,
ksks, num_radix_blocks, num_groups);
ksks, ms_noise_reduction_key, num_radix_blocks, num_groups);
auto shifted_blocks =
(Torus *)mem->shifted_blocks_borrow_state_mem->shifted_blocks->ptr;
@@ -2256,53 +2322,27 @@ void host_single_borrow_propagate(CudaStreams streams,
params.carry_modulus);
}
cuda_event_record(mem->incoming_events[0], streams.stream(0),
streams.gpu_index(0));
for (int j = 0; j < mem->active_streams.count(); j++) {
cuda_stream_wait_event(mem->sub_streams_1.stream(j),
mem->incoming_events[0],
mem->sub_streams_1.gpu_index(j));
cuda_stream_wait_event(mem->sub_streams_2.stream(j),
mem->incoming_events[0],
mem->sub_streams_1.gpu_index(j));
}
if (compute_overflow == outputFlag::FLAG_OVERFLOW) {
auto borrow_flag = mem->lut_borrow_flag;
integer_radix_apply_univariate_lookup_table_kb<Torus>(
mem->sub_streams_1, overflow_block, mem->overflow_block, bsks, ksks,
borrow_flag, 1);
}
for (int j = 0; j < mem->active_streams.count(); j++) {
cuda_event_record(mem->outgoing_events1[j], mem->sub_streams_1.stream(j),
mem->sub_streams_1.gpu_index(j));
streams, overflow_block, mem->overflow_block, bsks, ksks,
ms_noise_reduction_key, borrow_flag, 1);
}
// subtract borrow and cleanup prepared blocks
auto resolved_carries = mem->prop_simu_group_carries_mem->resolved_carries;
host_negation<Torus>(
mem->sub_streams_2.stream(0), mem->sub_streams_2.gpu_index(0),
(Torus *)resolved_carries->ptr, (Torus *)resolved_carries->ptr,
big_lwe_dimension, num_groups);
streams.stream(0), streams.gpu_index(0), (Torus *)resolved_carries->ptr,
(Torus *)resolved_carries->ptr, big_lwe_dimension, num_groups);
host_radix_sum_in_groups<Torus>(
mem->sub_streams_2.stream(0), mem->sub_streams_2.gpu_index(0),
prepared_blocks, prepared_blocks, resolved_carries, num_radix_blocks,
mem->group_size);
streams.stream(0), streams.gpu_index(0), prepared_blocks, prepared_blocks,
resolved_carries, num_radix_blocks, mem->group_size);
auto message_extract = mem->lut_message_extract;
integer_radix_apply_univariate_lookup_table_kb<Torus>(
mem->sub_streams_2, lwe_array, prepared_blocks, bsks, ksks,
streams, lwe_array, prepared_blocks, bsks, ksks, ms_noise_reduction_key,
message_extract, num_radix_blocks);
for (int j = 0; j < mem->active_streams.count(); j++) {
cuda_event_record(mem->outgoing_events2[j], mem->sub_streams_2.stream(j),
mem->sub_streams_2.gpu_index(j));
cuda_stream_wait_event(streams.stream(0), mem->outgoing_events1[j],
streams.gpu_index(0));
cuda_stream_wait_event(streams.stream(0), mem->outgoing_events2[j],
streams.gpu_index(0));
}
}
/// num_radix_blocks corresponds to the number of blocks on which to apply the
@@ -2313,7 +2353,8 @@ __host__ void integer_radix_apply_noise_squashing_kb(
CudaStreams streams, CudaRadixCiphertextFFI *lwe_array_out,
CudaRadixCiphertextFFI const *lwe_array_in,
int_noise_squashing_lut<InputTorus> *lut, void *const *bsks,
InputTorus *const *ksks) {
InputTorus *const *ksks,
CudaModulusSwitchNoiseReductionKeyFFI const *ms_noise_reduction_key) {
PUSH_RANGE("apply noise squashing")
auto params = lut->params;
@@ -2334,7 +2375,7 @@ __host__ void integer_radix_apply_noise_squashing_kb(
/// For multi GPU execution we create vectors of pointers for inputs and
/// outputs
auto lwe_array_pbs_in = lut->tmp_lwe_before_ks.get();
auto lwe_array_pbs_in = lut->tmp_lwe_before_ks;
std::vector<InputTorus *> lwe_array_in_vec = lut->lwe_array_in_vec;
std::vector<InputTorus *> lwe_after_ks_vec = lut->lwe_after_ks_vec;
std::vector<__uint128_t *> lwe_after_pbs_vec = lut->lwe_after_pbs_vec;
@@ -2352,10 +2393,11 @@ __host__ void integer_radix_apply_noise_squashing_kb(
streams.active_gpu_subset(lwe_array_out->num_radix_blocks);
if (active_streams.count() == 1) {
execute_keyswitch_async<InputTorus>(
streams.get_ith(0), lwe_after_ks_vec[0], lwe_trivial_indexes_vec[0],
(InputTorus *)lwe_array_pbs_in->ptr, lut->lwe_indexes_in.get(), ksks,
lut->input_big_lwe_dimension, small_lwe_dimension, ks_base_log,
ks_level, lwe_array_out->num_radix_blocks);
streams.subset_first_gpu(), lwe_after_ks_vec[0],
lwe_trivial_indexes_vec[0], (InputTorus *)lwe_array_pbs_in->ptr,
lut->lwe_indexes_in, ksks, lut->input_big_lwe_dimension,
small_lwe_dimension, ks_base_log, ks_level,
lwe_array_out->num_radix_blocks);
/// Apply PBS to apply a LUT, reduce the noise and go from a small LWE
/// dimension to a big LWE dimension
@@ -2363,12 +2405,13 @@ __host__ void integer_radix_apply_noise_squashing_kb(
/// int_noise_squashing_lut doesn't support a different output or lut
/// indexing than the trivial
execute_pbs_async<uint64_t, __uint128_t>(
streams.get_ith(0), (__uint128_t *)lwe_array_out->ptr,
streams.subset_first_gpu(), (__uint128_t *)lwe_array_out->ptr,
lwe_trivial_indexes_vec[0], lut->lut_vec, lwe_trivial_indexes_vec,
lwe_after_ks_vec[0], lwe_trivial_indexes_vec[0], bsks, lut->buffer,
glwe_dimension, small_lwe_dimension, polynomial_size, pbs_base_log,
pbs_level, grouping_factor, lwe_array_out->num_radix_blocks,
params.pbs_type, 0, 0);
lwe_after_ks_vec[0], lwe_trivial_indexes_vec[0], bsks,
ms_noise_reduction_key, lut->pbs_buffer, glwe_dimension,
small_lwe_dimension, polynomial_size, pbs_base_log, pbs_level,
grouping_factor, lwe_array_out->num_radix_blocks, params.pbs_type, 0,
0);
} else {
/// Make sure all data that should be on GPU 0 is indeed there
cuda_synchronize_stream(streams.stream(0), streams.gpu_index(0));
@@ -2377,7 +2420,7 @@ __host__ void integer_radix_apply_noise_squashing_kb(
/// gather data to GPU 0 we can copy back to the original indexing
multi_gpu_scatter_lwe_async<InputTorus>(
active_streams, lwe_array_in_vec, (InputTorus *)lwe_array_pbs_in->ptr,
lut->lwe_indexes_in.get(), lut->using_trivial_lwe_indexes,
lut->lwe_indexes_in, lut->using_trivial_lwe_indexes,
lut->lwe_aligned_scatter_vec, lut->active_streams.count(),
lwe_array_out->num_radix_blocks, lut->input_big_lwe_dimension + 1);
@@ -2392,10 +2435,10 @@ __host__ void integer_radix_apply_noise_squashing_kb(
execute_pbs_async<uint64_t, __uint128_t>(
active_streams, lwe_after_pbs_vec, lwe_trivial_indexes_vec,
lut->lut_vec, lwe_trivial_indexes_vec, lwe_after_ks_vec,
lwe_trivial_indexes_vec, bsks, lut->buffer, glwe_dimension,
small_lwe_dimension, polynomial_size, pbs_base_log, pbs_level,
grouping_factor, lwe_array_out->num_radix_blocks, params.pbs_type, 0,
0);
lwe_trivial_indexes_vec, bsks, ms_noise_reduction_key, lut->pbs_buffer,
glwe_dimension, small_lwe_dimension, polynomial_size, pbs_base_log,
pbs_level, grouping_factor, lwe_array_out->num_radix_blocks,
params.pbs_type, 0, 0);
/// Copy data back to GPU 0 and release vecs
/// In apply noise squashing we always use trivial indexes

View File

@@ -128,51 +128,59 @@ void cuda_integer_mult_radix_ciphertext_kb_64(
CudaStreamsFFI streams, CudaRadixCiphertextFFI *radix_lwe_out,
CudaRadixCiphertextFFI const *radix_lwe_left, bool const is_bool_left,
CudaRadixCiphertextFFI const *radix_lwe_right, bool const is_bool_right,
void *const *bsks, void *const *ksks, int8_t *mem_ptr,
uint32_t polynomial_size, uint32_t num_blocks) {
void *const *bsks, void *const *ksks,
CudaModulusSwitchNoiseReductionKeyFFI const *ms_noise_reduction_key,
int8_t *mem_ptr, uint32_t polynomial_size, uint32_t num_blocks) {
PUSH_RANGE("mul")
switch (polynomial_size) {
case 256:
host_integer_mult_radix_kb<uint64_t, AmortizedDegree<256>>(
CudaStreams(streams), radix_lwe_out, radix_lwe_left, is_bool_left,
radix_lwe_right, is_bool_right, bsks, (uint64_t **)(ksks),
(int_mul_memory<uint64_t> *)mem_ptr, num_blocks);
ms_noise_reduction_key, (int_mul_memory<uint64_t> *)mem_ptr,
num_blocks);
break;
case 512:
host_integer_mult_radix_kb<uint64_t, AmortizedDegree<512>>(
CudaStreams(streams), radix_lwe_out, radix_lwe_left, is_bool_left,
radix_lwe_right, is_bool_right, bsks, (uint64_t **)(ksks),
(int_mul_memory<uint64_t> *)mem_ptr, num_blocks);
ms_noise_reduction_key, (int_mul_memory<uint64_t> *)mem_ptr,
num_blocks);
break;
case 1024:
host_integer_mult_radix_kb<uint64_t, AmortizedDegree<1024>>(
CudaStreams(streams), radix_lwe_out, radix_lwe_left, is_bool_left,
radix_lwe_right, is_bool_right, bsks, (uint64_t **)(ksks),
(int_mul_memory<uint64_t> *)mem_ptr, num_blocks);
ms_noise_reduction_key, (int_mul_memory<uint64_t> *)mem_ptr,
num_blocks);
break;
case 2048:
host_integer_mult_radix_kb<uint64_t, AmortizedDegree<2048>>(
CudaStreams(streams), radix_lwe_out, radix_lwe_left, is_bool_left,
radix_lwe_right, is_bool_right, bsks, (uint64_t **)(ksks),
(int_mul_memory<uint64_t> *)mem_ptr, num_blocks);
ms_noise_reduction_key, (int_mul_memory<uint64_t> *)mem_ptr,
num_blocks);
break;
case 4096:
host_integer_mult_radix_kb<uint64_t, AmortizedDegree<4096>>(
CudaStreams(streams), radix_lwe_out, radix_lwe_left, is_bool_left,
radix_lwe_right, is_bool_right, bsks, (uint64_t **)(ksks),
(int_mul_memory<uint64_t> *)mem_ptr, num_blocks);
ms_noise_reduction_key, (int_mul_memory<uint64_t> *)mem_ptr,
num_blocks);
break;
case 8192:
host_integer_mult_radix_kb<uint64_t, AmortizedDegree<8192>>(
CudaStreams(streams), radix_lwe_out, radix_lwe_left, is_bool_left,
radix_lwe_right, is_bool_right, bsks, (uint64_t **)(ksks),
(int_mul_memory<uint64_t> *)mem_ptr, num_blocks);
ms_noise_reduction_key, (int_mul_memory<uint64_t> *)mem_ptr,
num_blocks);
break;
case 16384:
host_integer_mult_radix_kb<uint64_t, AmortizedDegree<16384>>(
CudaStreams(streams), radix_lwe_out, radix_lwe_left, is_bool_left,
radix_lwe_right, is_bool_right, bsks, (uint64_t **)(ksks),
(int_mul_memory<uint64_t> *)mem_ptr, num_blocks);
ms_noise_reduction_key, (int_mul_memory<uint64_t> *)mem_ptr,
num_blocks);
break;
default:
PANIC("Cuda error (integer multiplication): unsupported polynomial size. "
@@ -217,7 +225,8 @@ uint64_t scratch_cuda_integer_radix_partial_sum_ciphertexts_vec_kb_64(
void cuda_integer_radix_partial_sum_ciphertexts_vec_kb_64(
CudaStreamsFFI streams, CudaRadixCiphertextFFI *radix_lwe_out,
CudaRadixCiphertextFFI *radix_lwe_vec, int8_t *mem_ptr, void *const *bsks,
void *const *ksks) {
void *const *ksks,
CudaModulusSwitchNoiseReductionKeyFFI const *ms_noise_reduction_key) {
auto mem = (int_sum_ciphertexts_vec_memory<uint64_t> *)mem_ptr;
if (radix_lwe_vec->num_radix_blocks % radix_lwe_out->num_radix_blocks != 0)
@@ -225,7 +234,8 @@ void cuda_integer_radix_partial_sum_ciphertexts_vec_kb_64(
"output's number of radix blocks")
host_integer_partial_sum_ciphertexts_vec_kb<uint64_t>(
CudaStreams(streams), radix_lwe_out, radix_lwe_vec, bsks,
(uint64_t **)(ksks), mem, radix_lwe_out->num_radix_blocks,
(uint64_t **)(ksks), ms_noise_reduction_key, mem,
radix_lwe_out->num_radix_blocks,
radix_lwe_vec->num_radix_blocks / radix_lwe_out->num_radix_blocks);
}

View File

@@ -291,6 +291,7 @@ template <typename Torus>
__host__ void host_integer_partial_sum_ciphertexts_vec_kb(
CudaStreams streams, CudaRadixCiphertextFFI *radix_lwe_out,
CudaRadixCiphertextFFI *terms, void *const *bsks, uint64_t *const *ksks,
CudaModulusSwitchNoiseReductionKeyFFI const *ms_noise_reduction_key,
int_sum_ciphertexts_vec_memory<uint64_t> *mem_ptr,
uint32_t num_radix_blocks, uint32_t num_radix_in_vec) {
auto big_lwe_dimension = mem_ptr->params.big_lwe_dimension;
@@ -375,7 +376,7 @@ __host__ void host_integer_partial_sum_ciphertexts_vec_kb(
while (needs_processing) {
auto luts_message_carry = mem_ptr->luts_message_carry;
auto d_pbs_indexes_in = mem_ptr->luts_message_carry->lwe_indexes_in.get();
auto d_pbs_indexes_in = mem_ptr->luts_message_carry->lwe_indexes_in;
auto d_pbs_indexes_out = mem_ptr->luts_message_carry->lwe_indexes_out;
calculate_chunks<Torus>
<<<number_of_blocks_2d, number_of_threads, 0, streams.stream(0)>>>(
@@ -397,15 +398,17 @@ __host__ void host_integer_partial_sum_ciphertexts_vec_kb(
if (active_streams.count() == 1) {
execute_keyswitch_async<Torus>(
streams.get_ith(0), (Torus *)small_lwe_vector->ptr, d_pbs_indexes_in,
(Torus *)current_blocks->ptr, d_pbs_indexes_in, ksks,
big_lwe_dimension, small_lwe_dimension, mem_ptr->params.ks_base_log,
mem_ptr->params.ks_level, total_messages);
streams.subset_first_gpu(), (Torus *)small_lwe_vector->ptr,
d_pbs_indexes_in, (Torus *)current_blocks->ptr, d_pbs_indexes_in,
ksks, big_lwe_dimension, small_lwe_dimension,
mem_ptr->params.ks_base_log, mem_ptr->params.ks_level,
total_messages);
execute_pbs_async<Torus, Torus>(
streams.get_ith(0), (Torus *)current_blocks->ptr, d_pbs_indexes_out,
luts_message_carry->lut_vec, luts_message_carry->lut_indexes_vec,
(Torus *)small_lwe_vector->ptr, d_pbs_indexes_in, bsks,
streams.subset_first_gpu(), (Torus *)current_blocks->ptr,
d_pbs_indexes_out, luts_message_carry->lut_vec,
luts_message_carry->lut_indexes_vec, (Torus *)small_lwe_vector->ptr,
d_pbs_indexes_in, bsks, ms_noise_reduction_key,
luts_message_carry->buffer, glwe_dimension, small_lwe_dimension,
polynomial_size, mem_ptr->params.pbs_base_log,
mem_ptr->params.pbs_level, mem_ptr->params.grouping_factor,
@@ -419,7 +422,7 @@ __host__ void host_integer_partial_sum_ciphertexts_vec_kb(
integer_radix_apply_univariate_lookup_table_kb<Torus>(
streams, current_blocks, current_blocks, bsks, ksks,
luts_message_carry, total_ciphertexts);
ms_noise_reduction_key, luts_message_carry, total_ciphertexts);
}
cuda_set_device(streams.gpu_index(0));
std::swap(d_columns, d_new_columns);
@@ -433,7 +436,7 @@ __host__ void host_integer_partial_sum_ciphertexts_vec_kb(
if (mem_ptr->reduce_degrees_for_single_carry_propagation) {
auto luts_message_carry = mem_ptr->luts_message_carry;
auto d_pbs_indexes_in = mem_ptr->luts_message_carry->lwe_indexes_in.get();
auto d_pbs_indexes_in = mem_ptr->luts_message_carry->lwe_indexes_in;
auto d_pbs_indexes_out = mem_ptr->luts_message_carry->lwe_indexes_out;
prepare_final_pbs_indexes<Torus>
<<<1, 2 * num_radix_blocks, 0, streams.stream(0)>>>(
@@ -448,15 +451,16 @@ __host__ void host_integer_partial_sum_ciphertexts_vec_kb(
if (active_streams.count() == 1) {
execute_keyswitch_async<Torus>(
streams.get_ith(0), (Torus *)small_lwe_vector->ptr, d_pbs_indexes_in,
(Torus *)radix_lwe_out->ptr, d_pbs_indexes_in, ksks,
streams.subset_first_gpu(), (Torus *)small_lwe_vector->ptr,
d_pbs_indexes_in, (Torus *)radix_lwe_out->ptr, d_pbs_indexes_in, ksks,
big_lwe_dimension, small_lwe_dimension, mem_ptr->params.ks_base_log,
mem_ptr->params.ks_level, num_radix_blocks);
execute_pbs_async<Torus, Torus>(
streams.get_ith(0), (Torus *)current_blocks->ptr, d_pbs_indexes_out,
luts_message_carry->lut_vec, luts_message_carry->lut_indexes_vec,
(Torus *)small_lwe_vector->ptr, d_pbs_indexes_in, bsks,
streams.subset_first_gpu(), (Torus *)current_blocks->ptr,
d_pbs_indexes_out, luts_message_carry->lut_vec,
luts_message_carry->lut_indexes_vec, (Torus *)small_lwe_vector->ptr,
d_pbs_indexes_in, bsks, ms_noise_reduction_key,
luts_message_carry->buffer, glwe_dimension, small_lwe_dimension,
polynomial_size, mem_ptr->params.pbs_base_log,
mem_ptr->params.pbs_level, mem_ptr->params.grouping_factor,
@@ -470,7 +474,7 @@ __host__ void host_integer_partial_sum_ciphertexts_vec_kb(
integer_radix_apply_univariate_lookup_table_kb<Torus>(
active_streams, current_blocks, radix_lwe_out, bsks, ksks,
luts_message_carry, num_blocks_in_apply_lut);
ms_noise_reduction_key, luts_message_carry, num_blocks_in_apply_lut);
}
calculate_final_degrees(radix_lwe_out->degrees, terms->degrees,
num_radix_blocks, num_radix_in_vec, chunk_size,
@@ -492,8 +496,9 @@ __host__ void host_integer_mult_radix_kb(
CudaStreams streams, CudaRadixCiphertextFFI *radix_lwe_out,
CudaRadixCiphertextFFI const *radix_lwe_left, bool const is_bool_left,
CudaRadixCiphertextFFI const *radix_lwe_right, bool const is_bool_right,
void *const *bsks, uint64_t *const *ksks, int_mul_memory<Torus> *mem_ptr,
uint32_t num_blocks) {
void *const *bsks, uint64_t *const *ksks,
CudaModulusSwitchNoiseReductionKeyFFI const *ms_noise_reduction_key,
int_mul_memory<Torus> *mem_ptr, uint32_t num_blocks) {
if (radix_lwe_out->lwe_dimension != radix_lwe_left->lwe_dimension ||
radix_lwe_right->lwe_dimension != radix_lwe_left->lwe_dimension)
@@ -511,14 +516,14 @@ __host__ void host_integer_mult_radix_kb(
if (is_bool_right) {
zero_out_if<Torus>(streams, radix_lwe_out, radix_lwe_left, radix_lwe_right,
mem_ptr->zero_out_mem, mem_ptr->zero_out_predicate_lut,
bsks, ksks, num_blocks);
bsks, ksks, ms_noise_reduction_key, num_blocks);
return;
}
if (is_bool_left) {
zero_out_if<Torus>(streams, radix_lwe_out, radix_lwe_right, radix_lwe_left,
mem_ptr->zero_out_mem, mem_ptr->zero_out_predicate_lut,
bsks, ksks, num_blocks);
bsks, ksks, ms_noise_reduction_key, num_blocks);
return;
}
@@ -587,7 +592,8 @@ __host__ void host_integer_mult_radix_kb(
integer_radix_apply_bivariate_lookup_table_kb<Torus>(
streams, block_mul_res, block_mul_res, vector_result_sb, bsks, ksks,
luts_array, total_block_count, luts_array->params.message_modulus);
ms_noise_reduction_key, luts_array, total_block_count,
luts_array->params.message_modulus);
vector_result_lsb = block_mul_res;
as_radix_ciphertext_slice<Torus>(&vector_result_msb, block_mul_res,
@@ -615,14 +621,15 @@ __host__ void host_integer_mult_radix_kb(
}
host_integer_partial_sum_ciphertexts_vec_kb<Torus>(
streams, radix_lwe_out, vector_result_sb, bsks, ksks,
mem_ptr->sum_ciphertexts_mem, num_blocks, 2 * num_blocks);
ms_noise_reduction_key, mem_ptr->sum_ciphertexts_mem, num_blocks,
2 * num_blocks);
auto scp_mem_ptr = mem_ptr->sc_prop_mem;
uint32_t requested_flag = outputFlag::FLAG_NONE;
uint32_t uses_carry = 0;
host_propagate_single_carry<Torus>(streams, radix_lwe_out, nullptr, nullptr,
scp_mem_ptr, bsks, ksks, requested_flag,
uses_carry);
host_propagate_single_carry<Torus>(
streams, radix_lwe_out, nullptr, nullptr, scp_mem_ptr, bsks, ksks,
ms_noise_reduction_key, requested_flag, uses_carry);
}
template <typename Torus>

View File

@@ -134,7 +134,9 @@ __host__ void host_integer_overflowing_sub(
CudaRadixCiphertextFFI *overflow_block,
const CudaRadixCiphertextFFI *input_borrow,
int_borrow_prop_memory<uint64_t> *mem_ptr, void *const *bsks,
Torus *const *ksks, uint32_t compute_overflow, uint32_t uses_input_borrow) {
Torus *const *ksks,
CudaModulusSwitchNoiseReductionKeyFFI const *ms_noise_reduction_key,
uint32_t compute_overflow, uint32_t uses_input_borrow) {
PUSH_RANGE("overflowing sub")
if (output->num_radix_blocks != input_left->num_radix_blocks ||
output->num_radix_blocks != input_right->num_radix_blocks)
@@ -164,7 +166,7 @@ __host__ void host_integer_overflowing_sub(
host_single_borrow_propagate<Torus>(
streams, output, overflow_block, input_borrow,
(int_borrow_prop_memory<Torus> *)mem_ptr, bsks, (Torus **)(ksks),
num_groups, compute_overflow, uses_input_borrow);
ms_noise_reduction_key, num_groups, compute_overflow, uses_input_borrow);
POP_RANGE()
}

View File

@@ -5,9 +5,10 @@ uint64_t scratch_cuda_integer_grouped_oprf_64(
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) {
uint32_t num_blocks, 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,
@@ -17,19 +18,20 @@ uint64_t scratch_cuda_integer_grouped_oprf_64(
return scratch_cuda_integer_grouped_oprf<uint64_t>(
CudaStreams(streams), (int_grouped_oprf_memory<uint64_t> **)mem_ptr,
params, num_blocks_to_process, message_bits_per_block, total_random_bits,
allocate_gpu_memory);
params, num_blocks_to_process, num_blocks, message_bits_per_block,
total_random_bits, allocate_gpu_memory);
}
void cuda_integer_grouped_oprf_async_64(CudaStreamsFFI streams,
CudaRadixCiphertextFFI *radix_lwe_out,
const void *seeded_lwe_input,
uint32_t num_blocks_to_process,
int8_t *mem, void *const *bsks) {
void cuda_integer_grouped_oprf_async_64(
CudaStreamsFFI streams, CudaRadixCiphertextFFI *radix_lwe_out,
const void *seeded_lwe_input, uint32_t num_blocks_to_process, int8_t *mem,
void *const *bsks,
CudaModulusSwitchNoiseReductionKeyFFI const *ms_noise_reduction_key) {
host_integer_grouped_oprf<uint64_t>(
CudaStreams(streams), radix_lwe_out, (const uint64_t *)seeded_lwe_input,
num_blocks_to_process, (int_grouped_oprf_memory<uint64_t> *)mem, bsks);
num_blocks_to_process, (int_grouped_oprf_memory<uint64_t> *)mem, bsks,
ms_noise_reduction_key);
}
void cleanup_cuda_integer_grouped_oprf_64(CudaStreamsFFI streams,

View File

@@ -8,34 +8,34 @@ template <typename Torus>
uint64_t scratch_cuda_integer_grouped_oprf(
CudaStreams streams, int_grouped_oprf_memory<Torus> **mem_ptr,
int_radix_params params, uint32_t num_blocks_to_process,
uint32_t message_bits_per_block, uint64_t total_random_bits,
bool allocate_gpu_memory) {
uint32_t num_blocks, uint32_t message_bits_per_block,
uint64_t total_random_bits, bool allocate_gpu_memory) {
uint64_t size_tracker = 0;
*mem_ptr = new int_grouped_oprf_memory<Torus>(
streams, params, num_blocks_to_process, message_bits_per_block,
total_random_bits, allocate_gpu_memory, size_tracker);
streams, params, num_blocks_to_process, num_blocks,
message_bits_per_block, total_random_bits, allocate_gpu_memory,
size_tracker);
return size_tracker;
}
template <typename Torus>
void host_integer_grouped_oprf(CudaStreams streams,
CudaRadixCiphertextFFI *radix_lwe_out,
const Torus *seeded_lwe_input,
uint32_t num_blocks_to_process,
int_grouped_oprf_memory<Torus> *mem_ptr,
void *const *bsks) {
void host_integer_grouped_oprf(
CudaStreams streams, CudaRadixCiphertextFFI *radix_lwe_out,
const Torus *seeded_lwe_input, uint32_t num_blocks_to_process,
int_grouped_oprf_memory<Torus> *mem_ptr, void *const *bsks,
CudaModulusSwitchNoiseReductionKeyFFI const *ms_noise_reduction_key) {
auto active_streams = streams.active_gpu_subset(num_blocks_to_process);
auto lut = mem_ptr->luts;
if (active_streams.count() == 1) {
execute_pbs_async<Torus, Torus>(
streams.get_ith(0), (Torus *)(radix_lwe_out->ptr), lut->lwe_indexes_out,
streams, (Torus *)(radix_lwe_out->ptr), lut->lwe_indexes_out,
lut->lut_vec, lut->lut_indexes_vec,
const_cast<Torus *>(seeded_lwe_input), lut->lwe_indexes_in.get(), bsks,
lut->buffer, mem_ptr->params.glwe_dimension,
const_cast<Torus *>(seeded_lwe_input), lut->lwe_indexes_in, bsks,
ms_noise_reduction_key, lut->buffer, mem_ptr->params.glwe_dimension,
mem_ptr->params.small_lwe_dimension, mem_ptr->params.polynomial_size,
mem_ptr->params.pbs_base_log, mem_ptr->params.pbs_level,
mem_ptr->params.grouping_factor, num_blocks_to_process,
@@ -45,35 +45,48 @@ void host_integer_grouped_oprf(CudaStreams streams,
std::vector<Torus *> lwe_after_pbs_vec = lut->lwe_after_pbs_vec;
std::vector<Torus *> lwe_trivial_indexes_vec = lut->lwe_trivial_indexes_vec;
lut->multi_gpu_scatter_barrier.local_streams_wait_for_stream_0(
active_streams);
cuda_event_record(lut->event_scatter_in, streams.stream(0),
streams.gpu_index(0));
for (int j = 1; j < active_streams.count(); j++) {
cuda_stream_wait_event(streams.stream(j), lut->event_scatter_in,
streams.gpu_index(j));
}
if (!lut->using_trivial_lwe_indexes) {
PANIC("lut->using_trivial_lwe_indexes should be true");
}
PUSH_RANGE("scatter")
multi_gpu_scatter_lwe_async<Torus>(
active_streams, lwe_array_in_vec, seeded_lwe_input, lut->lwe_indexes_in.get(),
active_streams, lwe_array_in_vec, seeded_lwe_input, lut->lwe_indexes_in,
lut->using_trivial_lwe_indexes, lut->lwe_aligned_vec,
active_streams.count(), num_blocks_to_process,
mem_ptr->params.small_lwe_dimension + 1);
POP_RANGE()
execute_pbs_async<Torus, Torus>(
active_streams, lwe_after_pbs_vec, lwe_trivial_indexes_vec,
lut->lut_vec, lut->lut_indexes_vec, lwe_array_in_vec,
lwe_trivial_indexes_vec, bsks, lut->buffer,
lwe_trivial_indexes_vec, bsks, ms_noise_reduction_key, lut->buffer,
mem_ptr->params.glwe_dimension, mem_ptr->params.small_lwe_dimension,
mem_ptr->params.polynomial_size, mem_ptr->params.pbs_base_log,
mem_ptr->params.pbs_level, mem_ptr->params.grouping_factor,
num_blocks_to_process, mem_ptr->params.pbs_type, 1, 0);
PUSH_RANGE("gather")
multi_gpu_gather_lwe_async<Torus>(
active_streams, (Torus *)radix_lwe_out->ptr, lwe_after_pbs_vec,
lut->lwe_indexes_out, lut->using_trivial_lwe_indexes,
lut->lwe_aligned_vec, num_blocks_to_process,
mem_ptr->params.big_lwe_dimension + 1);
POP_RANGE()
lut->multi_gpu_gather_barrier.stream_0_wait_for_local_streams(
active_streams);
// other gpus record their events
for (int j = 1; j < active_streams.count(); j++) {
cuda_event_record(lut->event_scatter_out[j], streams.stream(j),
streams.gpu_index(j));
}
// GPU 0 waits for all
for (int j = 1; j < active_streams.count(); j++) {
cuda_stream_wait_event(streams.stream(0), lut->event_scatter_out[j],
streams.gpu_index(0));
}
}
for (uint32_t i = 0; i < num_blocks_to_process; i++) {

View File

@@ -7,13 +7,6 @@
#include "utils/helper_profile.cuh"
#include "utils/kernel_dimensions.cuh"
inline CudaLweCiphertextListFFI
to_lwe_ciphertext_list(CudaRadixCiphertextFFI *radix) {
return {.ptr = radix->ptr,
.num_radix_blocks = radix->num_radix_blocks,
.lwe_dimension = radix->lwe_dimension};
}
template <typename Torus>
void create_zero_radix_ciphertext_async(cudaStream_t const stream,
uint32_t const gpu_index,

View File

@@ -4,13 +4,15 @@ void cuda_scalar_bitop_integer_radix_ciphertext_kb_64(
CudaStreamsFFI streams, CudaRadixCiphertextFFI *lwe_array_out,
CudaRadixCiphertextFFI const *lwe_array_input, void const *clear_blocks,
void const *h_clear_blocks, uint32_t num_clear_blocks, int8_t *mem_ptr,
void *const *bsks, void *const *ksks) {
void *const *bsks, void *const *ksks,
CudaModulusSwitchNoiseReductionKeyFFI const *ms_noise_reduction_key) {
host_integer_radix_scalar_bitop_kb<uint64_t>(
CudaStreams(streams), lwe_array_out, lwe_array_input,
static_cast<const uint64_t *>(clear_blocks),
static_cast<const uint64_t *>(h_clear_blocks), num_clear_blocks,
(int_bitop_buffer<uint64_t> *)mem_ptr, bsks, (uint64_t **)(ksks));
(int_bitop_buffer<uint64_t> *)mem_ptr, bsks, (uint64_t **)(ksks),
ms_noise_reduction_key);
}
void update_degrees_after_scalar_bitand(uint64_t *output_degrees,

View File

@@ -9,7 +9,8 @@ __host__ void host_integer_radix_scalar_bitop_kb(
CudaStreams streams, CudaRadixCiphertextFFI *output,
CudaRadixCiphertextFFI const *input, Torus const *clear_blocks,
Torus const *h_clear_blocks, uint32_t num_clear_blocks,
int_bitop_buffer<Torus> *mem_ptr, void *const *bsks, Torus *const *ksks) {
int_bitop_buffer<Torus> *mem_ptr, void *const *bsks, Torus *const *ksks,
CudaModulusSwitchNoiseReductionKeyFFI const *ms_noise_reduction_key) {
if (output->num_radix_blocks != input->num_radix_blocks)
PANIC("Cuda error: input and output num radix blocks must be equal")
@@ -49,7 +50,8 @@ __host__ void host_integer_radix_scalar_bitop_kb(
lut->broadcast_lut(active_streams, false);
integer_radix_apply_univariate_lookup_table_kb<Torus>(
streams, output, input, bsks, ksks, lut, num_clear_blocks);
streams, output, input, bsks, ksks, ms_noise_reduction_key, lut,
num_clear_blocks);
memcpy(output->degrees, degrees, num_clear_blocks * sizeof(uint64_t));
if (op == SCALAR_BITAND && num_clear_blocks < num_radix_blocks) {

View File

@@ -35,7 +35,9 @@ void cuda_scalar_comparison_integer_radix_ciphertext_kb_64(
CudaStreamsFFI streams, CudaRadixCiphertextFFI *lwe_array_out,
CudaRadixCiphertextFFI const *lwe_array_in, void const *scalar_blocks,
void const *h_scalar_blocks, int8_t *mem_ptr, void *const *bsks,
void *const *ksks, uint32_t num_scalar_blocks) {
void *const *ksks,
CudaModulusSwitchNoiseReductionKeyFFI const *ms_noise_reduction_key,
uint32_t num_scalar_blocks) {
// The output ciphertext might be a boolean block or a radix ciphertext
// depending on the case (eq/gt vs max/min) so the amount of blocks to
@@ -49,7 +51,8 @@ void cuda_scalar_comparison_integer_radix_ciphertext_kb_64(
host_integer_radix_scalar_equality_check_kb<uint64_t>(
CudaStreams(streams), lwe_array_out, lwe_array_in,
static_cast<const uint64_t *>(scalar_blocks), buffer, bsks,
(uint64_t **)(ksks), num_radix_blocks, num_scalar_blocks);
(uint64_t **)(ksks), ms_noise_reduction_key, num_radix_blocks,
num_scalar_blocks);
break;
case GT:
case GE:
@@ -63,7 +66,7 @@ void cuda_scalar_comparison_integer_radix_ciphertext_kb_64(
static_cast<const uint64_t *>(scalar_blocks),
static_cast<const uint64_t *>(h_scalar_blocks), buffer,
buffer->diff_buffer->operator_f, bsks, (uint64_t **)(ksks),
num_radix_blocks, num_scalar_blocks);
ms_noise_reduction_key, num_radix_blocks, num_scalar_blocks);
break;
case MAX:
case MIN:
@@ -74,7 +77,8 @@ void cuda_scalar_comparison_integer_radix_ciphertext_kb_64(
CudaStreams(streams), lwe_array_out, lwe_array_in,
static_cast<const uint64_t *>(scalar_blocks),
static_cast<const uint64_t *>(h_scalar_blocks), buffer, bsks,
(uint64_t **)(ksks), num_radix_blocks, num_scalar_blocks);
(uint64_t **)(ksks), ms_noise_reduction_key, num_radix_blocks,
num_scalar_blocks);
break;
default:
PANIC("Cuda error: integer operation not supported")

View File

@@ -29,7 +29,9 @@ __host__ void scalar_compare_radix_blocks_kb(
CudaStreams streams, CudaRadixCiphertextFFI *lwe_array_out,
CudaRadixCiphertextFFI *lwe_array_in, Torus *scalar_blocks,
int_comparison_buffer<Torus> *mem_ptr, void *const *bsks,
Torus *const *ksks, uint32_t num_radix_blocks) {
Torus *const *ksks,
CudaModulusSwitchNoiseReductionKeyFFI const *ms_noise_reduction_key,
uint32_t num_radix_blocks) {
if (num_radix_blocks == 0)
return;
@@ -69,8 +71,8 @@ __host__ void scalar_compare_radix_blocks_kb(
// Apply LUT to compare to 0
auto sign_lut = mem_ptr->eq_buffer->is_non_zero_lut;
integer_radix_apply_univariate_lookup_table_kb<Torus>(
streams, lwe_array_out, subtracted_blocks, bsks, ksks, sign_lut,
num_radix_blocks);
streams, lwe_array_out, subtracted_blocks, bsks, ksks,
ms_noise_reduction_key, sign_lut, num_radix_blocks);
// FIXME: without this sync signed scalar eq tests fail, I don't understand
// the reason
@@ -88,7 +90,9 @@ __host__ void integer_radix_unsigned_scalar_difference_check_kb(
CudaRadixCiphertextFFI const *lwe_array_in, Torus const *scalar_blocks,
Torus const *h_scalar_blocks, int_comparison_buffer<Torus> *mem_ptr,
std::function<Torus(Torus)> sign_handler_f, void *const *bsks,
Torus *const *ksks, uint32_t num_radix_blocks, uint32_t num_scalar_blocks) {
Torus *const *ksks,
CudaModulusSwitchNoiseReductionKeyFFI const *ms_noise_reduction_key,
uint32_t num_radix_blocks, uint32_t num_scalar_blocks) {
if (lwe_array_out->lwe_dimension != lwe_array_in->lwe_dimension)
PANIC("Cuda error: input lwe dimensions must be the same")
if (lwe_array_in->num_radix_blocks < num_radix_blocks)
@@ -128,10 +132,11 @@ __host__ void integer_radix_unsigned_scalar_difference_check_kb(
// means scalar is zero
host_compare_blocks_with_zero<Torus>(
streams, mem_ptr->tmp_lwe_array_out, lwe_array_in, mem_ptr, bsks, ksks,
num_radix_blocks, mem_ptr->is_zero_lut);
ms_noise_reduction_key, num_radix_blocks, mem_ptr->is_zero_lut);
are_all_comparisons_block_true<Torus>(
streams, mem_ptr->tmp_lwe_array_out, mem_ptr->tmp_lwe_array_out,
mem_ptr, bsks, ksks, mem_ptr->tmp_lwe_array_out->num_radix_blocks);
mem_ptr, bsks, ksks, ms_noise_reduction_key,
mem_ptr->tmp_lwe_array_out->num_radix_blocks);
auto scalar_last_leaf_lut_f = [sign_handler_f](Torus x) -> Torus {
x = (x == 1 ? IS_EQUAL : IS_SUPERIOR);
@@ -149,7 +154,8 @@ __host__ void integer_radix_unsigned_scalar_difference_check_kb(
lut->broadcast_lut(active_streams);
integer_radix_apply_univariate_lookup_table_kb<Torus>(
streams, lwe_array_out, mem_ptr->tmp_lwe_array_out, bsks, ksks, lut, 1);
streams, lwe_array_out, mem_ptr->tmp_lwe_array_out, bsks, ksks,
ms_noise_reduction_key, lut, 1);
} else if (num_scalar_blocks < num_radix_blocks) {
// We have to handle both part of the work described above
@@ -201,7 +207,7 @@ __host__ void integer_radix_unsigned_scalar_difference_check_kb(
auto comparisons = mem_ptr->tmp_block_comparisons;
scalar_compare_radix_blocks_kb<Torus>(
lsb_streams, comparisons, diff_buffer->tmp_packed, (Torus *)rhs.ptr,
mem_ptr, bsks, ksks, num_lsb_radix_blocks);
mem_ptr, bsks, ksks, ms_noise_reduction_key, num_lsb_radix_blocks);
// Reduces a vec containing radix blocks that encrypts a sign
// (inferior, equal, superior) to one single radix block containing the
@@ -209,15 +215,15 @@ __host__ void integer_radix_unsigned_scalar_difference_check_kb(
tree_sign_reduction<Torus>(lsb_streams, lwe_array_lsb_out, comparisons,
mem_ptr->diff_buffer->tree_buffer,
mem_ptr->identity_lut_f, bsks, ksks,
num_lsb_radix_blocks);
ms_noise_reduction_key, num_lsb_radix_blocks);
//////////////
// msb
host_compare_blocks_with_zero<Torus>(
msb_streams, &lwe_array_msb_out, &msb, mem_ptr, bsks, ksks,
num_msb_radix_blocks, mem_ptr->is_zero_lut);
ms_noise_reduction_key, num_msb_radix_blocks, mem_ptr->is_zero_lut);
are_all_comparisons_block_true<Torus>(
msb_streams, &lwe_array_msb_out, &lwe_array_msb_out, mem_ptr, bsks,
ksks, lwe_array_msb_out.num_radix_blocks);
ksks, ms_noise_reduction_key, lwe_array_msb_out.num_radix_blocks);
lsb_streams.synchronize();
msb_streams.synchronize();
@@ -244,7 +250,7 @@ __host__ void integer_radix_unsigned_scalar_difference_check_kb(
integer_radix_apply_bivariate_lookup_table_kb<Torus>(
streams, lwe_array_out, lwe_array_lsb_out, &lwe_array_msb_out, bsks,
ksks, lut, 1, lut->params.message_modulus);
ksks, ms_noise_reduction_key, lut, 1, lut->params.message_modulus);
} else {
if (num_radix_blocks == 1) {
@@ -277,7 +283,8 @@ __host__ void integer_radix_unsigned_scalar_difference_check_kb(
one_block_lut->broadcast_lut(active_streams);
integer_radix_apply_univariate_lookup_table_kb<Torus>(
streams, lwe_array_out, lwe_array_in, bsks, ksks, one_block_lut, 1);
streams, lwe_array_out, lwe_array_in, bsks, ksks,
ms_noise_reduction_key, one_block_lut, 1);
one_block_lut->release(streams);
delete one_block_lut;
} else {
@@ -307,7 +314,7 @@ __host__ void integer_radix_unsigned_scalar_difference_check_kb(
auto comparisons = mem_ptr->tmp_lwe_array_out;
scalar_compare_radix_blocks_kb<Torus>(
streams, comparisons, diff_buffer->tmp_packed, (Torus *)rhs.ptr,
mem_ptr, bsks, ksks, num_lsb_radix_blocks);
mem_ptr, bsks, ksks, ms_noise_reduction_key, num_lsb_radix_blocks);
// Reduces a vec containing radix blocks that encrypts a sign
// (inferior, equal, superior) to one single radix block containing the
@@ -315,7 +322,7 @@ __host__ void integer_radix_unsigned_scalar_difference_check_kb(
tree_sign_reduction<Torus>(streams, lwe_array_out, comparisons,
mem_ptr->diff_buffer->tree_buffer,
sign_handler_f, bsks, ksks,
num_lsb_radix_blocks);
ms_noise_reduction_key, num_lsb_radix_blocks);
}
}
}
@@ -326,7 +333,9 @@ __host__ void integer_radix_signed_scalar_difference_check_kb(
CudaRadixCiphertextFFI const *lwe_array_in, Torus const *scalar_blocks,
Torus const *h_scalar_blocks, int_comparison_buffer<Torus> *mem_ptr,
std::function<Torus(Torus)> sign_handler_f, void *const *bsks,
Torus *const *ksks, uint32_t num_radix_blocks, uint32_t num_scalar_blocks) {
Torus *const *ksks,
CudaModulusSwitchNoiseReductionKeyFFI const *ms_noise_reduction_key,
uint32_t num_radix_blocks, uint32_t num_scalar_blocks) {
if (lwe_array_out->lwe_dimension != lwe_array_in->lwe_dimension)
PANIC("Cuda error: input lwe dimensions must be the same")
@@ -367,10 +376,10 @@ __host__ void integer_radix_signed_scalar_difference_check_kb(
auto are_all_msb_zeros = mem_ptr->tmp_lwe_array_out;
host_compare_blocks_with_zero<Torus>(
streams, are_all_msb_zeros, lwe_array_in, mem_ptr, bsks, ksks,
num_radix_blocks, mem_ptr->is_zero_lut);
ms_noise_reduction_key, num_radix_blocks, mem_ptr->is_zero_lut);
are_all_comparisons_block_true<Torus>(
streams, are_all_msb_zeros, are_all_msb_zeros, mem_ptr, bsks, ksks,
are_all_msb_zeros->num_radix_blocks);
ms_noise_reduction_key, are_all_msb_zeros->num_radix_blocks);
CudaRadixCiphertextFFI sign_block;
as_radix_ciphertext_slice<Torus>(&sign_block, lwe_array_in,
num_radix_blocks - 1, num_radix_blocks);
@@ -421,8 +430,8 @@ __host__ void integer_radix_signed_scalar_difference_check_kb(
lut->broadcast_lut(active_streams);
integer_radix_apply_bivariate_lookup_table_kb<Torus>(
streams, lwe_array_out, are_all_msb_zeros, &sign_block, bsks, ksks, lut,
1, lut->params.message_modulus);
streams, lwe_array_out, are_all_msb_zeros, &sign_block, bsks, ksks,
ms_noise_reduction_key, lut, 1, lut->params.message_modulus);
} else if (num_scalar_blocks < num_radix_blocks) {
// We have to handle both part of the work described above
@@ -468,7 +477,7 @@ __host__ void integer_radix_signed_scalar_difference_check_kb(
auto comparisons = mem_ptr->tmp_block_comparisons;
scalar_compare_radix_blocks_kb<Torus>(
lsb_streams, comparisons, diff_buffer->tmp_packed, (Torus *)rhs.ptr,
mem_ptr, bsks, ksks, num_lsb_radix_blocks);
mem_ptr, bsks, ksks, ms_noise_reduction_key, num_lsb_radix_blocks);
// Reduces a vec containing radix blocks that encrypts a sign
// (inferior, equal, superior) to one single radix block containing the
@@ -476,17 +485,17 @@ __host__ void integer_radix_signed_scalar_difference_check_kb(
tree_sign_reduction<Torus>(lsb_streams, lwe_array_lsb_out, comparisons,
mem_ptr->diff_buffer->tree_buffer,
mem_ptr->identity_lut_f, bsks, ksks,
num_lsb_radix_blocks);
ms_noise_reduction_key, num_lsb_radix_blocks);
//////////////
// msb
// We remove the last block (which is the sign)
auto are_all_msb_zeros = lwe_array_msb_out;
host_compare_blocks_with_zero<Torus>(
msb_streams, &are_all_msb_zeros, &msb, mem_ptr, bsks, ksks,
num_msb_radix_blocks, mem_ptr->is_zero_lut);
ms_noise_reduction_key, num_msb_radix_blocks, mem_ptr->is_zero_lut);
are_all_comparisons_block_true<Torus>(
msb_streams, &are_all_msb_zeros, &are_all_msb_zeros, mem_ptr, bsks,
ksks, are_all_msb_zeros.num_radix_blocks);
ksks, ms_noise_reduction_key, are_all_msb_zeros.num_radix_blocks);
auto sign_bit_pos = (int)log2(message_modulus) - 1;
@@ -527,14 +536,15 @@ __host__ void integer_radix_signed_scalar_difference_check_kb(
&sign_block, &msb, num_msb_radix_blocks - 1, num_msb_radix_blocks);
integer_radix_apply_bivariate_lookup_table_kb<Torus>(
msb_streams, &lwe_array_msb_out, &sign_block, &are_all_msb_zeros, bsks,
ksks, signed_msb_lut, 1, signed_msb_lut->params.message_modulus);
ksks, ms_noise_reduction_key, signed_msb_lut, 1,
signed_msb_lut->params.message_modulus);
lsb_streams.synchronize();
msb_streams.synchronize();
//////////////
// Reduce the two blocks into one final
reduce_signs<Torus>(streams, lwe_array_out, lwe_array_lsb_out, mem_ptr,
sign_handler_f, bsks, ksks, 2);
sign_handler_f, bsks, ksks, ms_noise_reduction_key, 2);
} else {
if (num_radix_blocks == 1) {
@@ -569,7 +579,8 @@ __host__ void integer_radix_signed_scalar_difference_check_kb(
one_block_lut->broadcast_lut(active_streams);
integer_radix_apply_univariate_lookup_table_kb<Torus>(
streams, lwe_array_out, lwe_array_in, bsks, ksks, one_block_lut, 1);
streams, lwe_array_out, lwe_array_in, bsks, ksks,
ms_noise_reduction_key, one_block_lut, 1);
one_block_lut->release(streams);
delete one_block_lut;
} else {
@@ -608,7 +619,8 @@ __host__ void integer_radix_signed_scalar_difference_check_kb(
// - 2 if lhs > rhs
scalar_compare_radix_blocks_kb<Torus>(
lsb_streams, lwe_array_ct_out, diff_buffer->tmp_packed,
(Torus *)rhs.ptr, mem_ptr, bsks, ksks, num_lsb_radix_blocks);
(Torus *)rhs.ptr, mem_ptr, bsks, ksks, ms_noise_reduction_key,
num_lsb_radix_blocks);
CudaRadixCiphertextFFI encrypted_sign_block;
as_radix_ciphertext_slice<Torus>(&encrypted_sign_block, lwe_array_in,
num_radix_blocks - 1, num_radix_blocks);
@@ -624,8 +636,8 @@ __host__ void integer_radix_signed_scalar_difference_check_kb(
integer_radix_apply_bivariate_lookup_table_kb<Torus>(
msb_streams, &lwe_array_sign_out, &encrypted_sign_block,
trivial_sign_block, bsks, ksks, mem_ptr->signed_lut, 1,
mem_ptr->signed_lut->params.message_modulus);
trivial_sign_block, bsks, ksks, ms_noise_reduction_key,
mem_ptr->signed_lut, 1, mem_ptr->signed_lut->params.message_modulus);
lsb_streams.synchronize();
msb_streams.synchronize();
@@ -633,7 +645,8 @@ __host__ void integer_radix_signed_scalar_difference_check_kb(
// (inferior, equal, superior) to one single radix block containing the
// final sign
reduce_signs<Torus>(streams, lwe_array_out, lwe_array_ct_out, mem_ptr,
sign_handler_f, bsks, ksks, num_lsb_radix_blocks + 1);
sign_handler_f, bsks, ksks, ms_noise_reduction_key,
num_lsb_radix_blocks + 1);
}
}
}
@@ -644,7 +657,9 @@ __host__ void host_integer_radix_scalar_difference_check_kb(
CudaRadixCiphertextFFI const *lwe_array_in, Torus const *scalar_blocks,
Torus const *h_scalar_blocks, int_comparison_buffer<Torus> *mem_ptr,
std::function<Torus(Torus)> sign_handler_f, void *const *bsks,
Torus *const *ksks, uint32_t num_radix_blocks, uint32_t num_scalar_blocks) {
Torus *const *ksks,
CudaModulusSwitchNoiseReductionKeyFFI const *ms_noise_reduction_key,
uint32_t num_radix_blocks, uint32_t num_scalar_blocks) {
if (lwe_array_out->lwe_dimension != lwe_array_in->lwe_dimension)
PANIC("Cuda error: input lwe dimensions must be the same")
@@ -656,13 +671,13 @@ __host__ void host_integer_radix_scalar_difference_check_kb(
// is signed and scalar is positive
integer_radix_signed_scalar_difference_check_kb<Torus>(
streams, lwe_array_out, lwe_array_in, scalar_blocks, h_scalar_blocks,
mem_ptr, sign_handler_f, bsks, ksks, num_radix_blocks,
num_scalar_blocks);
mem_ptr, sign_handler_f, bsks, ksks, ms_noise_reduction_key,
num_radix_blocks, num_scalar_blocks);
} else {
integer_radix_unsigned_scalar_difference_check_kb<Torus>(
streams, lwe_array_out, lwe_array_in, scalar_blocks, h_scalar_blocks,
mem_ptr, sign_handler_f, bsks, ksks, num_radix_blocks,
num_scalar_blocks);
mem_ptr, sign_handler_f, bsks, ksks, ms_noise_reduction_key,
num_radix_blocks, num_scalar_blocks);
}
}
@@ -671,8 +686,9 @@ __host__ void host_integer_radix_scalar_maxmin_kb(
CudaStreams streams, CudaRadixCiphertextFFI *lwe_array_out,
CudaRadixCiphertextFFI const *lwe_array_in, Torus const *scalar_blocks,
Torus const *h_scalar_blocks, int_comparison_buffer<Torus> *mem_ptr,
void *const *bsks, Torus *const *ksks, uint32_t num_radix_blocks,
uint32_t num_scalar_blocks) {
void *const *bsks, Torus *const *ksks,
CudaModulusSwitchNoiseReductionKeyFFI const *ms_noise_reduction_key,
uint32_t num_radix_blocks, uint32_t num_scalar_blocks) {
if (lwe_array_out->lwe_dimension != lwe_array_in->lwe_dimension)
PANIC("Cuda error: input and output lwe dimensions must be the same")
@@ -690,7 +706,8 @@ __host__ void host_integer_radix_scalar_maxmin_kb(
auto sign = mem_ptr->tmp_lwe_array_out;
host_integer_radix_scalar_difference_check_kb<Torus>(
streams, sign, lwe_array_in, scalar_blocks, h_scalar_blocks, mem_ptr,
mem_ptr->identity_lut_f, bsks, ksks, num_radix_blocks, num_scalar_blocks);
mem_ptr->identity_lut_f, bsks, ksks, ms_noise_reduction_key,
num_radix_blocks, num_scalar_blocks);
// There is no optimized CMUX for scalars, so we convert to a trivial
// ciphertext
@@ -704,9 +721,10 @@ __host__ void host_integer_radix_scalar_maxmin_kb(
// Selector
// CMUX for Max or Min
host_integer_radix_cmux_kb<Torus>(
streams, lwe_array_out, mem_ptr->tmp_lwe_array_out, lwe_array_left,
lwe_array_right, mem_ptr->cmux_buffer, bsks, ksks);
host_integer_radix_cmux_kb<Torus>(streams, lwe_array_out,
mem_ptr->tmp_lwe_array_out, lwe_array_left,
lwe_array_right, mem_ptr->cmux_buffer, bsks,
ksks, ms_noise_reduction_key);
}
template <typename Torus>
@@ -714,7 +732,9 @@ __host__ void host_integer_radix_scalar_equality_check_kb(
CudaStreams streams, CudaRadixCiphertextFFI *lwe_array_out,
CudaRadixCiphertextFFI const *lwe_array_in, Torus const *scalar_blocks,
int_comparison_buffer<Torus> *mem_ptr, void *const *bsks,
Torus *const *ksks, uint32_t num_radix_blocks, uint32_t num_scalar_blocks) {
Torus *const *ksks,
CudaModulusSwitchNoiseReductionKeyFFI const *ms_noise_reduction_key,
uint32_t num_radix_blocks, uint32_t num_scalar_blocks) {
if (lwe_array_out->lwe_dimension != lwe_array_in->lwe_dimension)
PANIC("Cuda error: input and output lwe dimensions must be the same")
@@ -787,7 +807,8 @@ __host__ void host_integer_radix_scalar_equality_check_kb(
integer_radix_apply_univariate_lookup_table_kb<Torus>(
lsb_streams, mem_ptr->tmp_lwe_array_out, mem_ptr->tmp_packed_input,
bsks, ksks, scalar_comparison_luts, num_halved_lsb_radix_blocks);
bsks, ksks, ms_noise_reduction_key, scalar_comparison_luts,
num_halved_lsb_radix_blocks);
}
//////////////
// msb_in
@@ -804,12 +825,12 @@ __host__ void host_integer_radix_scalar_equality_check_kb(
PANIC("Cuda error: integer operation not supported")
}
host_compare_blocks_with_zero<Torus>(msb_streams, &msb_out, &msb_in,
mem_ptr, bsks, ksks,
num_msb_radix_blocks, msb_lut);
are_all_comparisons_block_true<Torus>(msb_streams, &msb_out, &msb_out,
mem_ptr, bsks, ksks,
msb_out.num_radix_blocks);
host_compare_blocks_with_zero<Torus>(
msb_streams, &msb_out, &msb_in, mem_ptr, bsks, ksks,
ms_noise_reduction_key, num_msb_radix_blocks, msb_lut);
are_all_comparisons_block_true<Torus>(
msb_streams, &msb_out, &msb_out, mem_ptr, bsks, ksks,
ms_noise_reduction_key, msb_out.num_radix_blocks);
}
lsb_streams.synchronize();
@@ -819,11 +840,13 @@ __host__ void host_integer_radix_scalar_equality_check_kb(
case COMPARISON_TYPE::EQ:
are_all_comparisons_block_true<Torus>(
streams, lwe_array_out, mem_ptr->tmp_lwe_array_out, mem_ptr, bsks, ksks,
ms_noise_reduction_key,
num_halved_scalar_blocks + (num_msb_radix_blocks > 0));
break;
case COMPARISON_TYPE::NE:
is_at_least_one_comparisons_block_true<Torus>(
streams, lwe_array_out, mem_ptr->tmp_lwe_array_out, mem_ptr, bsks, ksks,
ms_noise_reduction_key,
num_halved_scalar_blocks + (num_msb_radix_blocks > 0));
break;
default:

View File

@@ -24,12 +24,13 @@ uint64_t scratch_cuda_integer_unsigned_scalar_div_radix_kb_64(
void cuda_integer_unsigned_scalar_div_radix_kb_64(
CudaStreamsFFI streams, CudaRadixCiphertextFFI *numerator_ct,
int8_t *mem_ptr, void *const *bsks, void *const *ksks,
const CudaModulusSwitchNoiseReductionKeyFFI *ms_noise_reduction_key,
const CudaScalarDivisorFFI *scalar_divisor_ffi) {
host_integer_unsigned_scalar_div_radix<uint64_t>(
CudaStreams(streams), numerator_ct,
(int_unsigned_scalar_div_mem<uint64_t> *)mem_ptr, bsks, (uint64_t **)ksks,
scalar_divisor_ffi);
ms_noise_reduction_key, scalar_divisor_ffi);
}
void cleanup_cuda_integer_unsigned_scalar_div_radix_kb_64(
@@ -68,12 +69,13 @@ uint64_t scratch_cuda_integer_signed_scalar_div_radix_kb_64(
void cuda_integer_signed_scalar_div_radix_kb_64(
CudaStreamsFFI streams, CudaRadixCiphertextFFI *numerator_ct,
int8_t *mem_ptr, void *const *bsks, void *const *ksks,
const CudaModulusSwitchNoiseReductionKeyFFI *ms_noise_reduction_key,
const CudaScalarDivisorFFI *scalar_divisor_ffi, uint32_t numerator_bits) {
host_integer_signed_scalar_div_radix_kb<uint64_t>(
CudaStreams(streams), numerator_ct,
(int_signed_scalar_div_mem<uint64_t> *)mem_ptr, bsks, (uint64_t **)ksks,
scalar_divisor_ffi, numerator_bits);
ms_noise_reduction_key, scalar_divisor_ffi, numerator_bits);
}
void cleanup_cuda_integer_signed_scalar_div_radix_kb_64(CudaStreamsFFI streams,
@@ -113,7 +115,9 @@ uint64_t scratch_integer_unsigned_scalar_div_rem_radix_kb_64(
void cuda_integer_unsigned_scalar_div_rem_radix_kb_64(
CudaStreamsFFI streams, CudaRadixCiphertextFFI *quotient_ct,
CudaRadixCiphertextFFI *remainder_ct, int8_t *mem_ptr, void *const *bsks,
void *const *ksks, const CudaScalarDivisorFFI *scalar_divisor_ffi,
void *const *ksks,
const CudaModulusSwitchNoiseReductionKeyFFI *ms_noise_reduction_key,
const CudaScalarDivisorFFI *scalar_divisor_ffi,
uint64_t const *divisor_has_at_least_one_set,
uint64_t const *decomposed_divisor, uint32_t const num_scalars_divisor,
void const *clear_blocks, void const *h_clear_blocks,
@@ -122,9 +126,9 @@ void cuda_integer_unsigned_scalar_div_rem_radix_kb_64(
host_integer_unsigned_scalar_div_rem_radix<uint64_t>(
CudaStreams(streams), quotient_ct, remainder_ct,
(int_unsigned_scalar_div_rem_buffer<uint64_t> *)mem_ptr, bsks,
(uint64_t **)ksks, scalar_divisor_ffi, divisor_has_at_least_one_set,
decomposed_divisor, num_scalars_divisor, (uint64_t *)clear_blocks,
(uint64_t *)h_clear_blocks, num_clear_blocks);
(uint64_t **)ksks, ms_noise_reduction_key, scalar_divisor_ffi,
divisor_has_at_least_one_set, decomposed_divisor, num_scalars_divisor,
(uint64_t *)clear_blocks, (uint64_t *)h_clear_blocks, num_clear_blocks);
}
void cleanup_cuda_integer_unsigned_scalar_div_rem_radix_kb_64(
@@ -164,7 +168,9 @@ uint64_t scratch_integer_signed_scalar_div_rem_radix_kb_64(
void cuda_integer_signed_scalar_div_rem_radix_kb_64(
CudaStreamsFFI streams, CudaRadixCiphertextFFI *quotient_ct,
CudaRadixCiphertextFFI *remainder_ct, int8_t *mem_ptr, void *const *bsks,
void *const *ksks, const CudaScalarDivisorFFI *scalar_divisor_ffi,
void *const *ksks,
CudaModulusSwitchNoiseReductionKeyFFI const *ms_noise_reduction_key,
const CudaScalarDivisorFFI *scalar_divisor_ffi,
uint64_t const *divisor_has_at_least_one_set,
uint64_t const *decomposed_divisor, uint32_t const num_scalars_divisor,
uint32_t numerator_bits) {
@@ -172,8 +178,9 @@ void cuda_integer_signed_scalar_div_rem_radix_kb_64(
host_integer_signed_scalar_div_rem_radix<uint64_t>(
CudaStreams(streams), quotient_ct, remainder_ct,
(int_signed_scalar_div_rem_buffer<uint64_t> *)mem_ptr, bsks,
(uint64_t **)ksks, scalar_divisor_ffi, divisor_has_at_least_one_set,
decomposed_divisor, num_scalars_divisor, numerator_bits);
(uint64_t **)ksks, ms_noise_reduction_key, scalar_divisor_ffi,
divisor_has_at_least_one_set, decomposed_divisor, num_scalars_divisor,
numerator_bits);
}
void cleanup_cuda_integer_signed_scalar_div_rem_radix_kb_64(

View File

@@ -27,7 +27,9 @@ template <typename Torus>
__host__ void host_integer_unsigned_scalar_div_radix(
CudaStreams streams, CudaRadixCiphertextFFI *numerator_ct,
int_unsigned_scalar_div_mem<Torus> *mem_ptr, void *const *bsks,
Torus *const *ksks, const CudaScalarDivisorFFI *scalar_divisor_ffi) {
Torus *const *ksks,
CudaModulusSwitchNoiseReductionKeyFFI const *ms_noise_reduction_key,
const CudaScalarDivisorFFI *scalar_divisor_ffi) {
if (scalar_divisor_ffi->is_abs_divisor_one) {
return;
@@ -36,7 +38,7 @@ __host__ void host_integer_unsigned_scalar_div_radix(
if (scalar_divisor_ffi->is_divisor_pow2) {
host_integer_radix_logical_scalar_shift_kb_inplace<Torus>(
streams, numerator_ct, scalar_divisor_ffi->ilog2_divisor,
mem_ptr->logical_scalar_shift_mem, bsks, ksks,
mem_ptr->logical_scalar_shift_mem, bsks, ksks, ms_noise_reduction_key,
numerator_ct->num_radix_blocks);
return;
}
@@ -63,24 +65,26 @@ __host__ void host_integer_unsigned_scalar_div_radix(
numerator_cpy, numerator_ct);
host_integer_radix_scalar_mul_high_kb<Torus>(
streams, numerator_cpy, mem_ptr->scalar_mul_high_mem, ksks, bsks,
scalar_divisor_ffi);
streams, numerator_cpy, mem_ptr->scalar_mul_high_mem, ksks,
ms_noise_reduction_key, bsks, scalar_divisor_ffi);
host_sub_and_propagate_single_carry<Torus>(
streams, numerator_ct, numerator_cpy, nullptr, nullptr,
mem_ptr->sub_and_propagate_mem, bsks, ksks, FLAG_NONE, (uint32_t)0);
mem_ptr->sub_and_propagate_mem, bsks, ksks, ms_noise_reduction_key,
FLAG_NONE, (uint32_t)0);
host_integer_radix_logical_scalar_shift_kb_inplace<Torus>(
streams, numerator_ct, (uint32_t)1, mem_ptr->logical_scalar_shift_mem,
bsks, ksks, numerator_ct->num_radix_blocks);
bsks, ksks, ms_noise_reduction_key, numerator_ct->num_radix_blocks);
host_add_and_propagate_single_carry<Torus>(
streams, numerator_ct, numerator_cpy, nullptr, nullptr,
mem_ptr->scp_mem, bsks, ksks, FLAG_NONE, (uint32_t)0);
mem_ptr->scp_mem, bsks, ksks, ms_noise_reduction_key, FLAG_NONE,
(uint32_t)0);
host_integer_radix_logical_scalar_shift_kb_inplace<Torus>(
streams, numerator_ct, scalar_divisor_ffi->shift_post - (uint32_t)1,
mem_ptr->logical_scalar_shift_mem, bsks, ksks,
mem_ptr->logical_scalar_shift_mem, bsks, ksks, ms_noise_reduction_key,
numerator_ct->num_radix_blocks);
return;
@@ -88,16 +92,16 @@ __host__ void host_integer_unsigned_scalar_div_radix(
host_integer_radix_logical_scalar_shift_kb_inplace<Torus>(
streams, numerator_ct, scalar_divisor_ffi->shift_pre,
mem_ptr->logical_scalar_shift_mem, bsks, ksks,
mem_ptr->logical_scalar_shift_mem, bsks, ksks, ms_noise_reduction_key,
numerator_ct->num_radix_blocks);
host_integer_radix_scalar_mul_high_kb<Torus>(streams, numerator_ct,
mem_ptr->scalar_mul_high_mem,
ksks, bsks, scalar_divisor_ffi);
host_integer_radix_scalar_mul_high_kb<Torus>(
streams, numerator_ct, mem_ptr->scalar_mul_high_mem, ksks,
ms_noise_reduction_key, bsks, scalar_divisor_ffi);
host_integer_radix_logical_scalar_shift_kb_inplace<Torus>(
streams, numerator_ct, scalar_divisor_ffi->shift_post,
mem_ptr->logical_scalar_shift_mem, bsks, ksks,
mem_ptr->logical_scalar_shift_mem, bsks, ksks, ms_noise_reduction_key,
numerator_ct->num_radix_blocks);
}
@@ -121,8 +125,9 @@ template <typename Torus>
__host__ void host_integer_signed_scalar_div_radix_kb(
CudaStreams streams, CudaRadixCiphertextFFI *numerator_ct,
int_signed_scalar_div_mem<Torus> *mem_ptr, void *const *bsks,
Torus *const *ksks, const CudaScalarDivisorFFI *scalar_divisor_ffi,
uint32_t numerator_bits) {
Torus *const *ksks,
CudaModulusSwitchNoiseReductionKeyFFI const *ms_noise_reduction_key,
const CudaScalarDivisorFFI *scalar_divisor_ffi, uint32_t numerator_bits) {
if (scalar_divisor_ffi->is_abs_divisor_one) {
if (scalar_divisor_ffi->is_divisor_negative) {
@@ -153,20 +158,23 @@ __host__ void host_integer_signed_scalar_div_radix_kb(
host_integer_radix_arithmetic_scalar_shift_kb_inplace<Torus>(
streams, tmp, scalar_divisor_ffi->chosen_multiplier_num_bits - 1,
mem_ptr->arithmetic_scalar_shift_mem, bsks, ksks);
mem_ptr->arithmetic_scalar_shift_mem, bsks, ksks,
ms_noise_reduction_key);
host_integer_radix_logical_scalar_shift_kb_inplace<Torus>(
streams, tmp,
numerator_bits - scalar_divisor_ffi->chosen_multiplier_num_bits,
mem_ptr->logical_scalar_shift_mem, bsks, ksks, tmp->num_radix_blocks);
mem_ptr->logical_scalar_shift_mem, bsks, ksks, ms_noise_reduction_key,
tmp->num_radix_blocks);
host_add_and_propagate_single_carry<Torus>(
streams, tmp, numerator_ct, nullptr, nullptr, mem_ptr->scp_mem, bsks,
ksks, FLAG_NONE, (uint32_t)0);
ksks, ms_noise_reduction_key, FLAG_NONE, (uint32_t)0);
host_integer_radix_arithmetic_scalar_shift_kb_inplace<Torus>(
streams, tmp, scalar_divisor_ffi->chosen_multiplier_num_bits,
mem_ptr->arithmetic_scalar_shift_mem, bsks, ksks);
mem_ptr->arithmetic_scalar_shift_mem, bsks, ksks,
ms_noise_reduction_key);
} else if (!scalar_divisor_ffi->is_chosen_multiplier_geq_two_pow_numerator) {
copy_radix_ciphertext_async<Torus>(streams.stream(0), streams.gpu_index(0),
@@ -174,11 +182,12 @@ __host__ void host_integer_signed_scalar_div_radix_kb(
host_integer_radix_signed_scalar_mul_high_kb<Torus>(
streams, tmp, mem_ptr->scalar_mul_high_mem, ksks, scalar_divisor_ffi,
bsks);
ms_noise_reduction_key, bsks);
host_integer_radix_arithmetic_scalar_shift_kb_inplace<Torus>(
streams, tmp, scalar_divisor_ffi->shift_post,
mem_ptr->arithmetic_scalar_shift_mem, bsks, ksks);
mem_ptr->arithmetic_scalar_shift_mem, bsks, ksks,
ms_noise_reduction_key);
CudaRadixCiphertextFFI *xsign = mem_ptr->xsign_ffi;
copy_radix_ciphertext_async<Torus>(streams.stream(0), streams.gpu_index(0),
@@ -186,11 +195,12 @@ __host__ void host_integer_signed_scalar_div_radix_kb(
host_integer_radix_arithmetic_scalar_shift_kb_inplace<Torus>(
streams, xsign, numerator_bits - 1,
mem_ptr->arithmetic_scalar_shift_mem, bsks, ksks);
mem_ptr->arithmetic_scalar_shift_mem, bsks, ksks,
ms_noise_reduction_key);
host_sub_and_propagate_single_carry<Torus>(
streams, tmp, xsign, nullptr, nullptr, mem_ptr->sub_and_propagate_mem,
bsks, ksks, FLAG_NONE, (uint32_t)0);
bsks, ksks, ms_noise_reduction_key, FLAG_NONE, (uint32_t)0);
} else {
@@ -199,15 +209,16 @@ __host__ void host_integer_signed_scalar_div_radix_kb(
host_integer_radix_signed_scalar_mul_high_kb<Torus>(
streams, tmp, mem_ptr->scalar_mul_high_mem, ksks, scalar_divisor_ffi,
bsks);
ms_noise_reduction_key, bsks);
host_add_and_propagate_single_carry<Torus>(
streams, tmp, numerator_ct, nullptr, nullptr, mem_ptr->scp_mem, bsks,
ksks, FLAG_NONE, (uint32_t)0);
ksks, ms_noise_reduction_key, FLAG_NONE, (uint32_t)0);
host_integer_radix_arithmetic_scalar_shift_kb_inplace<Torus>(
streams, tmp, scalar_divisor_ffi->shift_post,
mem_ptr->arithmetic_scalar_shift_mem, bsks, ksks);
mem_ptr->arithmetic_scalar_shift_mem, bsks, ksks,
ms_noise_reduction_key);
CudaRadixCiphertextFFI *xsign = mem_ptr->xsign_ffi;
copy_radix_ciphertext_async<Torus>(streams.stream(0), streams.gpu_index(0),
@@ -215,11 +226,12 @@ __host__ void host_integer_signed_scalar_div_radix_kb(
host_integer_radix_arithmetic_scalar_shift_kb_inplace<Torus>(
streams, xsign, numerator_bits - 1,
mem_ptr->arithmetic_scalar_shift_mem, bsks, ksks);
mem_ptr->arithmetic_scalar_shift_mem, bsks, ksks,
ms_noise_reduction_key);
host_sub_and_propagate_single_carry<Torus>(
streams, tmp, xsign, nullptr, nullptr, mem_ptr->sub_and_propagate_mem,
bsks, ksks, FLAG_NONE, (uint32_t)0);
bsks, ksks, ms_noise_reduction_key, FLAG_NONE, (uint32_t)0);
}
if (scalar_divisor_ffi->is_divisor_negative) {
@@ -251,7 +263,9 @@ __host__ void host_integer_unsigned_scalar_div_rem_radix(
CudaStreams streams, CudaRadixCiphertextFFI *quotient_ct,
CudaRadixCiphertextFFI *remainder_ct,
int_unsigned_scalar_div_rem_buffer<Torus> *mem_ptr, void *const *bsks,
Torus *const *ksks, const CudaScalarDivisorFFI *scalar_divisor_ffi,
Torus *const *ksks,
CudaModulusSwitchNoiseReductionKeyFFI const *ms_noise_reduction_key,
const CudaScalarDivisorFFI *scalar_divisor_ffi,
uint64_t const *divisor_has_at_least_one_set,
uint64_t const *decomposed_divisor, uint32_t const num_scalars_divisor,
Torus const *clear_blocks, Torus const *h_clear_blocks,
@@ -261,17 +275,18 @@ __host__ void host_integer_unsigned_scalar_div_rem_radix(
copy_radix_ciphertext_async<Torus>(streams.stream(0), streams.gpu_index(0),
numerator_ct, quotient_ct);
host_integer_unsigned_scalar_div_radix(streams, quotient_ct,
mem_ptr->unsigned_div_mem, bsks, ksks,
scalar_divisor_ffi);
host_integer_unsigned_scalar_div_radix(
streams, quotient_ct, mem_ptr->unsigned_div_mem, bsks, ksks,
ms_noise_reduction_key, scalar_divisor_ffi);
if (scalar_divisor_ffi->is_divisor_pow2) {
copy_radix_ciphertext_async<Torus>(streams.stream(0), streams.gpu_index(0),
remainder_ct, numerator_ct);
host_integer_radix_scalar_bitop_kb(
streams, remainder_ct, remainder_ct, clear_blocks, h_clear_blocks,
num_clear_blocks, mem_ptr->bitop_mem, bsks, ksks);
host_integer_radix_scalar_bitop_kb(streams, remainder_ct, remainder_ct,
clear_blocks, h_clear_blocks,
num_clear_blocks, mem_ptr->bitop_mem,
bsks, ksks, ms_noise_reduction_key);
} else {
if (!scalar_divisor_ffi->is_divisor_zero) {
@@ -284,13 +299,15 @@ __host__ void host_integer_unsigned_scalar_div_rem_radix(
host_integer_scalar_mul_radix<Torus>(
streams, remainder_ct, decomposed_divisor,
divisor_has_at_least_one_set, mem_ptr->scalar_mul_mem, bsks, ksks,
mem_ptr->params.message_modulus, num_scalars_divisor);
ms_noise_reduction_key, mem_ptr->params.message_modulus,
num_scalars_divisor);
}
}
host_sub_and_propagate_single_carry(
streams, numerator_ct, remainder_ct, nullptr, nullptr,
mem_ptr->sub_and_propagate_mem, bsks, ksks, FLAG_NONE, (uint32_t)0);
mem_ptr->sub_and_propagate_mem, bsks, ksks, ms_noise_reduction_key,
FLAG_NONE, (uint32_t)0);
copy_radix_ciphertext_async<Torus>(streams.stream(0), streams.gpu_index(0),
remainder_ct, numerator_ct);
@@ -318,7 +335,9 @@ __host__ void host_integer_signed_scalar_div_rem_radix(
CudaStreams streams, CudaRadixCiphertextFFI *quotient_ct,
CudaRadixCiphertextFFI *remainder_ct,
int_signed_scalar_div_rem_buffer<Torus> *mem_ptr, void *const *bsks,
Torus *const *ksks, const CudaScalarDivisorFFI *scalar_divisor_ffi,
Torus *const *ksks,
CudaModulusSwitchNoiseReductionKeyFFI const *ms_noise_reduction_key,
const CudaScalarDivisorFFI *scalar_divisor_ffi,
uint64_t const *divisor_has_at_least_one_set,
uint64_t const *decomposed_divisor, uint32_t const num_scalars_divisor,
uint32_t numerator_bits) {
@@ -327,13 +346,13 @@ __host__ void host_integer_signed_scalar_div_rem_radix(
copy_radix_ciphertext_async<Torus>(streams.stream(0), streams.gpu_index(0),
numerator_ct, quotient_ct);
host_integer_signed_scalar_div_radix_kb(streams, quotient_ct,
mem_ptr->signed_div_mem, bsks, ksks,
scalar_divisor_ffi, numerator_bits);
host_integer_signed_scalar_div_radix_kb(
streams, quotient_ct, mem_ptr->signed_div_mem, bsks, ksks,
ms_noise_reduction_key, scalar_divisor_ffi, numerator_bits);
host_propagate_single_carry<Torus>(streams, quotient_ct, nullptr, nullptr,
mem_ptr->scp_mem, bsks, ksks, FLAG_NONE,
(uint32_t)0);
host_propagate_single_carry<Torus>(
streams, quotient_ct, nullptr, nullptr, mem_ptr->scp_mem, bsks, ksks,
ms_noise_reduction_key, FLAG_NONE, (uint32_t)0);
if (!scalar_divisor_ffi->is_divisor_negative &&
scalar_divisor_ffi->is_divisor_pow2) {
@@ -342,7 +361,7 @@ __host__ void host_integer_signed_scalar_div_rem_radix(
host_integer_radix_logical_scalar_shift_kb_inplace(
streams, remainder_ct, scalar_divisor_ffi->ilog2_divisor,
mem_ptr->logical_scalar_shift_mem, bsks, ksks,
mem_ptr->logical_scalar_shift_mem, bsks, ksks, ms_noise_reduction_key,
remainder_ct->num_radix_blocks);
} else if (!scalar_divisor_ffi->is_divisor_zero) {
@@ -356,13 +375,15 @@ __host__ void host_integer_signed_scalar_div_rem_radix(
host_integer_scalar_mul_radix<Torus>(
streams, remainder_ct, decomposed_divisor,
divisor_has_at_least_one_set, mem_ptr->scalar_mul_mem, bsks, ksks,
mem_ptr->params.message_modulus, num_scalars_divisor);
ms_noise_reduction_key, mem_ptr->params.message_modulus,
num_scalars_divisor);
}
}
host_sub_and_propagate_single_carry(
streams, numerator_ct, remainder_ct, nullptr, nullptr,
mem_ptr->sub_and_propagate_mem, bsks, ksks, FLAG_NONE, (uint32_t)0);
mem_ptr->sub_and_propagate_mem, bsks, ksks, ms_noise_reduction_key,
FLAG_NONE, (uint32_t)0);
copy_radix_ciphertext_async<Torus>(streams.stream(0), streams.gpu_index(0),
remainder_ct, numerator_ct);

View File

@@ -22,13 +22,15 @@ uint64_t scratch_cuda_integer_scalar_mul_kb_64(
void cuda_scalar_multiplication_integer_radix_ciphertext_64_inplace(
CudaStreamsFFI streams, CudaRadixCiphertextFFI *lwe_array,
uint64_t const *decomposed_scalar, uint64_t const *has_at_least_one_set,
int8_t *mem, void *const *bsks, void *const *ksks, uint32_t polynomial_size,
uint32_t message_modulus, uint32_t num_scalars) {
int8_t *mem, void *const *bsks, void *const *ksks,
CudaModulusSwitchNoiseReductionKeyFFI const *ms_noise_reduction_key,
uint32_t polynomial_size, uint32_t message_modulus, uint32_t num_scalars) {
host_integer_scalar_mul_radix<uint64_t>(
CudaStreams(streams), lwe_array, decomposed_scalar, has_at_least_one_set,
reinterpret_cast<int_scalar_mul_buffer<uint64_t> *>(mem), bsks,
(uint64_t **)(ksks), message_modulus, num_scalars);
(uint64_t **)(ksks), ms_noise_reduction_key, message_modulus,
num_scalars);
}
void cleanup_cuda_integer_radix_scalar_mul(CudaStreamsFFI streams,

View File

@@ -46,6 +46,7 @@ __host__ void host_integer_scalar_mul_radix(
CudaStreams streams, CudaRadixCiphertextFFI *lwe_array,
T const *decomposed_scalar, T const *has_at_least_one_set,
int_scalar_mul_buffer<T> *mem, void *const *bsks, T *const *ksks,
CudaModulusSwitchNoiseReductionKeyFFI const *ms_noise_reduction_key,
uint32_t message_modulus, uint32_t num_scalars) {
auto num_radix_blocks = lwe_array->num_radix_blocks;
@@ -68,7 +69,7 @@ __host__ void host_integer_scalar_mul_radix(
num_radix_blocks, lwe_array, 0, num_radix_blocks);
host_integer_radix_logical_scalar_shift_kb_inplace<T>(
streams, &shift_input, shift_amount, mem->logical_scalar_shift_buffer,
bsks, ksks, num_radix_blocks);
bsks, ksks, ms_noise_reduction_key, num_radix_blocks);
} else {
// create trivial assign for value = 0
set_zero_radix_ciphertext_slice_async<T>(
@@ -112,14 +113,15 @@ __host__ void host_integer_scalar_mul_radix(
} else {
host_integer_partial_sum_ciphertexts_vec_kb<T>(
streams, lwe_array, all_shifted_buffer, bsks, ksks,
mem->sum_ciphertexts_vec_mem, num_radix_blocks, j);
ms_noise_reduction_key, mem->sum_ciphertexts_vec_mem, num_radix_blocks,
j);
auto scp_mem_ptr = mem->sc_prop_mem;
uint32_t requested_flag = outputFlag::FLAG_NONE;
uint32_t uses_carry = 0;
host_propagate_single_carry<T>(streams, lwe_array, nullptr, nullptr,
scp_mem_ptr, bsks, ksks, requested_flag,
uses_carry);
host_propagate_single_carry<T>(
streams, lwe_array, nullptr, nullptr, scp_mem_ptr, bsks, ksks,
ms_noise_reduction_key, requested_flag, uses_carry);
}
}
@@ -168,6 +170,7 @@ template <typename Torus>
__host__ void host_integer_radix_scalar_mul_high_kb(
CudaStreams streams, CudaRadixCiphertextFFI *ct,
int_scalar_mul_high_buffer<Torus> *mem_ptr, Torus *const *ksks,
CudaModulusSwitchNoiseReductionKeyFFI const *ms_noise_reduction_key,
void *const *bsks, const CudaScalarDivisorFFI *scalar_divisor_ffi) {
if (scalar_divisor_ffi->is_chosen_multiplier_zero) {
@@ -188,7 +191,7 @@ __host__ void host_integer_radix_scalar_mul_high_kb(
host_integer_radix_logical_scalar_shift_kb_inplace<Torus>(
streams, tmp_ffi, scalar_divisor_ffi->ilog2_chosen_multiplier,
mem_ptr->logical_scalar_shift_mem, bsks, (uint64_t **)ksks,
tmp_ffi->num_radix_blocks);
ms_noise_reduction_key, tmp_ffi->num_radix_blocks);
} else {
@@ -196,7 +199,8 @@ __host__ void host_integer_radix_scalar_mul_high_kb(
streams, tmp_ffi, scalar_divisor_ffi->decomposed_chosen_multiplier,
scalar_divisor_ffi->chosen_multiplier_has_at_least_one_set,
mem_ptr->scalar_mul_mem, bsks, (uint64_t **)ksks,
mem_ptr->params.message_modulus, scalar_divisor_ffi->num_scalars);
ms_noise_reduction_key, mem_ptr->params.message_modulus,
scalar_divisor_ffi->num_scalars);
}
}
@@ -207,7 +211,9 @@ template <typename Torus>
__host__ void host_integer_radix_signed_scalar_mul_high_kb(
CudaStreams streams, CudaRadixCiphertextFFI *ct,
int_signed_scalar_mul_high_buffer<Torus> *mem_ptr, Torus *const *ksks,
const CudaScalarDivisorFFI *scalar_divisor_ffi, void *const *bsks) {
const CudaScalarDivisorFFI *scalar_divisor_ffi,
CudaModulusSwitchNoiseReductionKeyFFI const *ms_noise_reduction_key,
void *const *bsks) {
if (scalar_divisor_ffi->is_chosen_multiplier_zero) {
set_zero_radix_ciphertext_slice_async<Torus>(
@@ -219,7 +225,7 @@ __host__ void host_integer_radix_signed_scalar_mul_high_kb(
host_extend_radix_with_sign_msb<Torus>(
streams, tmp_ffi, ct, mem_ptr->extend_radix_mem, ct->num_radix_blocks,
bsks, (uint64_t **)ksks);
bsks, (uint64_t **)ksks, ms_noise_reduction_key);
if (scalar_divisor_ffi->active_bits != (uint32_t)0 &&
!scalar_divisor_ffi->is_abs_chosen_multiplier_one &&
@@ -229,13 +235,14 @@ __host__ void host_integer_radix_signed_scalar_mul_high_kb(
host_integer_radix_logical_scalar_shift_kb_inplace<Torus>(
streams, tmp_ffi, scalar_divisor_ffi->ilog2_chosen_multiplier,
mem_ptr->logical_scalar_shift_mem, bsks, (uint64_t **)ksks,
tmp_ffi->num_radix_blocks);
ms_noise_reduction_key, tmp_ffi->num_radix_blocks);
} else {
host_integer_scalar_mul_radix<Torus>(
streams, tmp_ffi, scalar_divisor_ffi->decomposed_chosen_multiplier,
scalar_divisor_ffi->chosen_multiplier_has_at_least_one_set,
mem_ptr->scalar_mul_mem, bsks, (uint64_t **)ksks,
mem_ptr->params.message_modulus, scalar_divisor_ffi->num_scalars);
ms_noise_reduction_key, mem_ptr->params.message_modulus,
scalar_divisor_ffi->num_scalars);
}
}

View File

@@ -22,12 +22,13 @@ uint64_t scratch_cuda_integer_radix_scalar_rotate_kb_64(
void cuda_integer_radix_scalar_rotate_kb_64_inplace(
CudaStreamsFFI streams, CudaRadixCiphertextFFI *lwe_array, uint32_t n,
int8_t *mem_ptr, void *const *bsks, void *const *ksks) {
int8_t *mem_ptr, void *const *bsks, void *const *ksks,
CudaModulusSwitchNoiseReductionKeyFFI const *ms_noise_reduction_key) {
host_integer_radix_scalar_rotate_kb_inplace<uint64_t>(
CudaStreams(streams), lwe_array, n,
(int_logical_scalar_shift_buffer<uint64_t> *)mem_ptr, bsks,
(uint64_t **)(ksks));
(uint64_t **)(ksks), ms_noise_reduction_key);
}
void cleanup_cuda_integer_radix_scalar_rotate(CudaStreamsFFI streams,

View File

@@ -28,7 +28,8 @@ template <typename Torus>
__host__ void host_integer_radix_scalar_rotate_kb_inplace(
CudaStreams streams, CudaRadixCiphertextFFI *lwe_array, uint32_t n,
int_logical_scalar_shift_buffer<Torus> *mem, void *const *bsks,
Torus *const *ksks) {
Torus *const *ksks,
CudaModulusSwitchNoiseReductionKeyFFI const *ms_noise_reduction_key) {
auto num_blocks = lwe_array->num_radix_blocks;
auto params = mem->params;
@@ -73,7 +74,8 @@ __host__ void host_integer_radix_scalar_rotate_kb_inplace(
integer_radix_apply_bivariate_lookup_table_kb<Torus>(
streams, lwe_array, receiver_blocks, giver_blocks, bsks, ksks,
lut_bivariate, num_blocks, lut_bivariate->params.message_modulus);
ms_noise_reduction_key, lut_bivariate, num_blocks,
lut_bivariate->params.message_modulus);
} else {
// rotate left as the blocks are from LSB to MSB
@@ -97,7 +99,8 @@ __host__ void host_integer_radix_scalar_rotate_kb_inplace(
integer_radix_apply_bivariate_lookup_table_kb<Torus>(
streams, lwe_array, receiver_blocks, giver_blocks, bsks, ksks,
lut_bivariate, num_blocks, lut_bivariate->params.message_modulus);
ms_noise_reduction_key, lut_bivariate, num_blocks,
lut_bivariate->params.message_modulus);
}
}

View File

@@ -26,12 +26,13 @@ uint64_t scratch_cuda_integer_radix_logical_scalar_shift_kb_64(
/// rotations - 1 The remaining blocks are padded with zeros
void cuda_integer_radix_logical_scalar_shift_kb_64_inplace(
CudaStreamsFFI streams, CudaRadixCiphertextFFI *lwe_array, uint32_t shift,
int8_t *mem_ptr, void *const *bsks, void *const *ksks) {
int8_t *mem_ptr, void *const *bsks, void *const *ksks,
CudaModulusSwitchNoiseReductionKeyFFI const *ms_noise_reduction_key) {
host_integer_radix_logical_scalar_shift_kb_inplace<uint64_t>(
CudaStreams(streams), lwe_array, shift,
(int_logical_scalar_shift_buffer<uint64_t> *)mem_ptr, bsks,
(uint64_t **)(ksks), lwe_array->num_radix_blocks);
(uint64_t **)(ksks), ms_noise_reduction_key, lwe_array->num_radix_blocks);
}
uint64_t scratch_cuda_integer_radix_arithmetic_scalar_shift_kb_64(
@@ -63,12 +64,13 @@ uint64_t scratch_cuda_integer_radix_arithmetic_scalar_shift_kb_64(
/// zeros as would be done in the logical shift.
void cuda_integer_radix_arithmetic_scalar_shift_kb_64_inplace(
CudaStreamsFFI streams, CudaRadixCiphertextFFI *lwe_array, uint32_t shift,
int8_t *mem_ptr, void *const *bsks, void *const *ksks) {
int8_t *mem_ptr, void *const *bsks, void *const *ksks,
CudaModulusSwitchNoiseReductionKeyFFI const *ms_noise_reduction_key) {
host_integer_radix_arithmetic_scalar_shift_kb_inplace<uint64_t>(
CudaStreams(streams), lwe_array, shift,
(int_arithmetic_scalar_shift_buffer<uint64_t> *)mem_ptr, bsks,
(uint64_t **)(ksks));
(uint64_t **)(ksks), ms_noise_reduction_key);
}
void cleanup_cuda_integer_radix_logical_scalar_shift(CudaStreamsFFI streams,

View File

@@ -28,7 +28,9 @@ template <typename Torus>
__host__ void host_integer_radix_logical_scalar_shift_kb_inplace(
CudaStreams streams, CudaRadixCiphertextFFI *lwe_array, uint32_t shift,
int_logical_scalar_shift_buffer<Torus> *mem, void *const *bsks,
Torus *const *ksks, uint32_t num_blocks) {
Torus *const *ksks,
CudaModulusSwitchNoiseReductionKeyFFI const *ms_noise_reduction_key,
uint32_t num_blocks) {
if (lwe_array->num_radix_blocks < num_blocks)
PANIC("Cuda error: input does not have enough blocks")
@@ -79,8 +81,9 @@ __host__ void host_integer_radix_logical_scalar_shift_kb_inplace(
integer_radix_apply_bivariate_lookup_table_kb<Torus>(
streams, &partial_current_blocks, &partial_current_blocks,
&partial_previous_blocks, bsks, ksks, lut_bivariate,
partial_block_count, lut_bivariate->params.message_modulus);
&partial_previous_blocks, bsks, ksks, ms_noise_reduction_key,
lut_bivariate, partial_block_count,
lut_bivariate->params.message_modulus);
} else {
// right shift
@@ -110,8 +113,8 @@ __host__ void host_integer_radix_logical_scalar_shift_kb_inplace(
integer_radix_apply_bivariate_lookup_table_kb<Torus>(
streams, partial_current_blocks, partial_current_blocks,
&partial_next_blocks, bsks, ksks, lut_bivariate, partial_block_count,
lut_bivariate->params.message_modulus);
&partial_next_blocks, bsks, ksks, ms_noise_reduction_key, lut_bivariate,
partial_block_count, lut_bivariate->params.message_modulus);
}
}
@@ -132,7 +135,8 @@ template <typename Torus>
__host__ void host_integer_radix_arithmetic_scalar_shift_kb_inplace(
CudaStreams streams, CudaRadixCiphertextFFI *lwe_array, uint32_t shift,
int_arithmetic_scalar_shift_buffer<Torus> *mem, void *const *bsks,
Torus *const *ksks) {
Torus *const *ksks,
CudaModulusSwitchNoiseReductionKeyFFI const *ms_noise_reduction_key) {
auto num_blocks = lwe_array->num_radix_blocks;
auto params = mem->params;
@@ -201,8 +205,9 @@ __host__ void host_integer_radix_arithmetic_scalar_shift_kb_inplace(
integer_radix_apply_bivariate_lookup_table_kb<Torus>(
streams, partial_current_blocks, partial_current_blocks,
&partial_next_blocks, bsks, ksks, lut_bivariate,
partial_block_count, lut_bivariate->params.message_modulus);
&partial_next_blocks, bsks, ksks, ms_noise_reduction_key,
lut_bivariate, partial_block_count,
lut_bivariate->params.message_modulus);
}
// Since our CPU threads will be working on different streams we shall
// Ensure the work in the main stream is completed
@@ -211,7 +216,7 @@ __host__ void host_integer_radix_arithmetic_scalar_shift_kb_inplace(
mem->lut_buffers_univariate[num_bits_in_block - 1];
integer_radix_apply_univariate_lookup_table_kb<Torus>(
mem->local_streams_1, &padding_block, &last_block_copy, bsks, ksks,
lut_univariate_padding_block, 1);
ms_noise_reduction_key, lut_univariate_padding_block, 1);
// Replace blocks 'pulled' from the left with the correct padding
// block
for (uint i = 0; i < rotations; i++) {
@@ -225,7 +230,7 @@ __host__ void host_integer_radix_arithmetic_scalar_shift_kb_inplace(
mem->lut_buffers_univariate[shift_within_block - 1];
integer_radix_apply_univariate_lookup_table_kb<Torus>(
mem->local_streams_2, &last_block, &last_block_copy, bsks, ksks,
lut_univariate_shift_last_block, 1);
ms_noise_reduction_key, lut_univariate_shift_last_block, 1);
}
mem->local_streams_1.synchronize();

View File

@@ -22,12 +22,13 @@ uint64_t scratch_cuda_integer_radix_shift_and_rotate_kb_64(
void cuda_integer_radix_shift_and_rotate_kb_64_inplace(
CudaStreamsFFI streams, CudaRadixCiphertextFFI *lwe_array,
CudaRadixCiphertextFFI const *lwe_shift, int8_t *mem_ptr, void *const *bsks,
void *const *ksks) {
void *const *ksks,
CudaModulusSwitchNoiseReductionKeyFFI const *ms_noise_reduction_key) {
host_integer_radix_shift_and_rotate_kb_inplace<uint64_t>(
CudaStreams(streams), lwe_array, lwe_shift,
(int_shift_and_rotate_buffer<uint64_t> *)mem_ptr, bsks,
(uint64_t **)(ksks));
(uint64_t **)(ksks), ms_noise_reduction_key);
}
void cleanup_cuda_integer_radix_shift_and_rotate(CudaStreamsFFI streams,

View File

@@ -29,7 +29,8 @@ __host__ void host_integer_radix_shift_and_rotate_kb_inplace(
CudaStreams streams, CudaRadixCiphertextFFI *lwe_array,
CudaRadixCiphertextFFI const *lwe_shift,
int_shift_and_rotate_buffer<Torus> *mem, void *const *bsks,
Torus *const *ksks) {
Torus *const *ksks,
CudaModulusSwitchNoiseReductionKeyFFI const *ms_noise_reduction_key) {
cuda_set_device(streams.gpu_index(0));
if (lwe_array->num_radix_blocks != lwe_shift->num_radix_blocks)
@@ -56,6 +57,7 @@ __host__ void host_integer_radix_shift_and_rotate_kb_inplace(
// Extract all bits
auto bits = mem->tmp_bits;
extract_n_bits<Torus>(streams, bits, lwe_array, bsks, ksks,
ms_noise_reduction_key,
num_radix_blocks * bits_per_block, num_radix_blocks,
mem->bit_extract_luts);
@@ -77,8 +79,8 @@ __host__ void host_integer_radix_shift_and_rotate_kb_inplace(
// so that it is already aligned to the correct position of the cmux input
// and we reduce noise growth
extract_n_bits<Torus>(streams, shift_bits, lwe_shift, bsks, ksks,
max_num_bits_that_tell_shift, num_radix_blocks,
mem->bit_extract_luts_with_offset_2);
ms_noise_reduction_key, max_num_bits_that_tell_shift,
num_radix_blocks, mem->bit_extract_luts_with_offset_2);
// If signed, do an "arithmetic shift" by padding with the sign bit
CudaRadixCiphertextFFI last_bit;
@@ -150,7 +152,7 @@ __host__ void host_integer_radix_shift_and_rotate_kb_inplace(
// control_bit|b|a
host_pack_bivariate_blocks<Torus>(
streams, mux_inputs, mux_lut->lwe_indexes_out, rotated_input,
input_bits_a, mux_lut->lwe_indexes_in.get(), 2, total_nb_bits,
input_bits_a, mux_lut->lwe_indexes_in, 2, total_nb_bits,
mem->params.message_modulus, mem->params.carry_modulus);
// The shift bit is already properly aligned/positioned
@@ -161,7 +163,8 @@ __host__ void host_integer_radix_shift_and_rotate_kb_inplace(
// we have
// control_bit|b|a
integer_radix_apply_univariate_lookup_table_kb<Torus>(
streams, input_bits_a, mux_inputs, bsks, ksks, mux_lut, total_nb_bits);
streams, input_bits_a, mux_inputs, bsks, ksks, ms_noise_reduction_key,
mux_lut, total_nb_bits);
}
// Initializes the output
@@ -193,8 +196,8 @@ __host__ void host_integer_radix_shift_and_rotate_kb_inplace(
// To give back a clean ciphertext
auto cleaning_lut = mem->cleaning_lut;
integer_radix_apply_univariate_lookup_table_kb<Torus>(
streams, lwe_array, lwe_array, bsks, ksks, cleaning_lut,
num_radix_blocks);
streams, lwe_array, lwe_array, bsks, ksks, ms_noise_reduction_key,
cleaning_lut, num_radix_blocks);
}
}
#endif

View File

@@ -23,12 +23,14 @@ void cuda_sub_and_propagate_single_carry_kb_64_inplace(
CudaStreamsFFI streams, CudaRadixCiphertextFFI *lhs_array,
const CudaRadixCiphertextFFI *rhs_array, CudaRadixCiphertextFFI *carry_out,
const CudaRadixCiphertextFFI *carry_in, int8_t *mem_ptr, void *const *bsks,
void *const *ksks, uint32_t requested_flag, uint32_t uses_carry) {
void *const *ksks,
CudaModulusSwitchNoiseReductionKeyFFI const *ms_noise_reduction_key,
uint32_t requested_flag, uint32_t uses_carry) {
PUSH_RANGE("sub")
host_sub_and_propagate_single_carry<uint64_t>(
CudaStreams(streams), lhs_array, rhs_array, carry_out, carry_in,
(int_sub_and_propagate<uint64_t> *)mem_ptr, bsks, (uint64_t **)(ksks),
requested_flag, uses_carry);
ms_noise_reduction_key, requested_flag, uses_carry);
POP_RANGE()
}

View File

@@ -33,6 +33,7 @@ void host_sub_and_propagate_single_carry(
const CudaRadixCiphertextFFI *rhs_array, CudaRadixCiphertextFFI *carry_out,
const CudaRadixCiphertextFFI *input_carries,
int_sub_and_propagate<Torus> *mem, void *const *bsks, Torus *const *ksks,
CudaModulusSwitchNoiseReductionKeyFFI const *ms_noise_reduction_key,
uint32_t requested_flag, uint32_t uses_carry) {
host_integer_radix_negation<Torus>(
@@ -41,7 +42,8 @@ void host_sub_and_propagate_single_carry(
host_add_and_propagate_single_carry<Torus>(
streams, lhs_array, mem->neg_rhs_array, carry_out, input_carries,
mem->sc_prop_mem, bsks, ksks, requested_flag, uses_carry);
mem->sc_prop_mem, bsks, ksks, ms_noise_reduction_key, requested_flag,
uses_carry);
}
template <typename Torus>

View File

@@ -204,20 +204,20 @@ __device__ void mul_ggsw_glwe_in_fourier_domain_2_2_params(
}
template <typename InputTorus, typename OutputTorus>
void execute_pbs_async(CudaStreams streams,
const LweArrayVariant<OutputTorus> &lwe_array_out,
const LweArrayVariant<InputTorus> &lwe_output_indexes,
const std::vector<OutputTorus *> lut_vec,
const std::vector<InputTorus *> lut_indexes_vec,
const LweArrayVariant<InputTorus> &lwe_array_in,
const LweArrayVariant<InputTorus> &lwe_input_indexes,
void *const *bootstrapping_keys,
std::vector<int8_t *> pbs_buffer,
uint32_t glwe_dimension, uint32_t lwe_dimension,
uint32_t polynomial_size, uint32_t base_log,
uint32_t level_count, uint32_t grouping_factor,
uint32_t input_lwe_ciphertext_count, PBS_TYPE pbs_type,
uint32_t num_many_lut, uint32_t lut_stride) {
void execute_pbs_async(
CudaStreams streams, const LweArrayVariant<OutputTorus> &lwe_array_out,
const LweArrayVariant<InputTorus> &lwe_output_indexes,
const std::vector<OutputTorus *> lut_vec,
const std::vector<InputTorus *> lut_indexes_vec,
const LweArrayVariant<InputTorus> &lwe_array_in,
const LweArrayVariant<InputTorus> &lwe_input_indexes,
void *const *bootstrapping_keys,
CudaModulusSwitchNoiseReductionKeyFFI const *ms_noise_reduction_key,
std::vector<int8_t *> pbs_buffer, uint32_t glwe_dimension,
uint32_t lwe_dimension, uint32_t polynomial_size, uint32_t base_log,
uint32_t level_count, uint32_t grouping_factor,
uint32_t input_lwe_ciphertext_count, PBS_TYPE pbs_type,
uint32_t num_many_lut, uint32_t lut_stride) {
if constexpr (std::is_same_v<OutputTorus, uint32_t>) {
// 32 bits
@@ -310,13 +310,17 @@ void execute_pbs_async(CudaStreams streams,
auto d_lut_vector_indexes =
lut_indexes_vec[i] + (ptrdiff_t)(gpu_offset);
void *zeros = nullptr;
if (ms_noise_reduction_key != nullptr &&
ms_noise_reduction_key->ptr != nullptr)
zeros = ms_noise_reduction_key->ptr[i];
cuda_programmable_bootstrap_lwe_ciphertext_vector_64(
streams.stream(i), streams.gpu_index(i), current_lwe_array_out,
current_lwe_output_indexes, lut_vec[i], d_lut_vector_indexes,
current_lwe_array_in, current_lwe_input_indexes,
bootstrapping_keys[i], pbs_buffer[i], lwe_dimension, glwe_dimension,
polynomial_size, base_log, level_count, num_inputs_on_gpu,
num_many_lut, lut_stride);
bootstrapping_keys[i], ms_noise_reduction_key, zeros, pbs_buffer[i],
lwe_dimension, glwe_dimension, polynomial_size, base_log,
level_count, num_inputs_on_gpu, num_many_lut, lut_stride);
}
break;
default:
@@ -370,11 +374,16 @@ void execute_pbs_async(CudaStreams streams,
auto d_lut_vector_indexes =
lut_indexes_vec[i] + (ptrdiff_t)(gpu_offset);
void *zeros = nullptr;
if (ms_noise_reduction_key != nullptr &&
ms_noise_reduction_key->ptr != nullptr)
zeros = ms_noise_reduction_key->ptr[i];
cuda_programmable_bootstrap_lwe_ciphertext_vector_128(
streams.stream(i), streams.gpu_index(i), current_lwe_array_out,
lut_vec[i], current_lwe_array_in, bootstrapping_keys[i],
pbs_buffer[i], lwe_dimension, glwe_dimension, polynomial_size,
base_log, level_count, num_inputs_on_gpu);
ms_noise_reduction_key, zeros, pbs_buffer[i], lwe_dimension,
glwe_dimension, polynomial_size, base_log, level_count,
num_inputs_on_gpu);
}
break;
default:

View File

@@ -80,7 +80,9 @@ __global__ void device_programmable_bootstrap_cg(
// The third dimension of the block is used to determine on which ciphertext
// this block is operating, in the case of batch bootstraps
const Torus *block_lwe_array_in =
&lwe_array_in[lwe_input_indexes[blockIdx.x] * (lwe_dimension + 1)];
(noise_reduction_type == PBS_MS_REDUCTION_T::DRIFT)
? &lwe_array_in[blockIdx.x * (lwe_dimension + 1)]
: &lwe_array_in[lwe_input_indexes[blockIdx.x] * (lwe_dimension + 1)];
const Torus *block_lut_vector =
&lut_vector[lut_vector_indexes[blockIdx.x] * params::degree *

View File

@@ -650,15 +650,33 @@ void cuda_programmable_bootstrap_lwe_ciphertext_vector_64(
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 base_log, uint32_t level_count,
uint32_t num_samples, uint32_t num_many_lut, uint32_t lut_stride) {
CudaModulusSwitchNoiseReductionKeyFFI const *ms_noise_reduction_key,
void *ms_drift_noise_reduction_ptr, int8_t *mem_ptr, uint32_t lwe_dimension,
uint32_t glwe_dimension, uint32_t polynomial_size, uint32_t base_log,
uint32_t level_count, uint32_t num_samples, uint32_t num_many_lut,
uint32_t lut_stride) {
if (base_log > 64)
PANIC("Cuda error (classical PBS): base log should be <= 64")
pbs_buffer<uint64_t, CLASSICAL> *buffer =
(pbs_buffer<uint64_t, CLASSICAL> *)mem_ptr;
// If the parameters contain drift noise reduction key, then apply it
if (buffer->noise_reduction_type == PBS_MS_REDUCTION_T::DRIFT) {
uint32_t log_modulus = log2(polynomial_size) + 1;
host_drift_modulus_switch<uint64_t>(
static_cast<cudaStream_t>(stream), gpu_index, buffer->temp_lwe_array_in,
static_cast<uint64_t const *>(lwe_array_in),
static_cast<uint64_t const *>(lwe_input_indexes),
static_cast<uint64_t *>(ms_drift_noise_reduction_ptr),
lwe_dimension + 1, num_samples, ms_noise_reduction_key->num_zeros,
ms_noise_reduction_key->ms_input_variance,
ms_noise_reduction_key->ms_r_sigma, ms_noise_reduction_key->ms_bound,
log_modulus);
} else {
buffer->temp_lwe_array_in =
const_cast<uint64_t *>(static_cast<const uint64_t *>(lwe_array_in));
}
check_cuda_error(cudaGetLastError());
switch (buffer->pbs_variant) {
@@ -669,7 +687,7 @@ void cuda_programmable_bootstrap_lwe_ciphertext_vector_64(
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 *>(buffer->temp_lwe_array_in),
static_cast<const uint64_t *>(lwe_input_indexes),
static_cast<const double2 *>(bootstrapping_key), buffer, lwe_dimension,
glwe_dimension, polynomial_size, base_log, level_count, num_samples,
@@ -684,7 +702,7 @@ void cuda_programmable_bootstrap_lwe_ciphertext_vector_64(
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 *>(buffer->temp_lwe_array_in),
static_cast<const uint64_t *>(lwe_input_indexes),
static_cast<const double2 *>(bootstrapping_key), buffer, lwe_dimension,
glwe_dimension, polynomial_size, base_log, level_count, num_samples,
@@ -696,7 +714,7 @@ void cuda_programmable_bootstrap_lwe_ciphertext_vector_64(
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 *>(buffer->temp_lwe_array_in),
static_cast<const uint64_t *>(lwe_input_indexes),
static_cast<const double2 *>(bootstrapping_key), buffer, lwe_dimension,
glwe_dimension, polynomial_size, base_log, level_count, num_samples,

View File

@@ -56,7 +56,9 @@ __global__ void __launch_bounds__(params::degree / params::opt)
// The third dimension of the block is used to determine on which ciphertext
// this block is operating, in the case of batch bootstraps
const Torus *block_lwe_array_in =
&lwe_array_in[lwe_input_indexes[blockIdx.x] * (lwe_dimension + 1)];
(noise_reduction_type == PBS_MS_REDUCTION_T::DRIFT)
? &lwe_array_in[blockIdx.x * (lwe_dimension + 1)]
: &lwe_array_in[lwe_input_indexes[blockIdx.x] * (lwe_dimension + 1)];
const Torus *block_lut_vector =
&lut_vector[lut_vector_indexes[blockIdx.x] * params::degree *

View File

@@ -36,7 +36,7 @@ uint64_t scratch_cuda_programmable_bootstrap_128(
template <typename InputTorus>
void executor_cuda_programmable_bootstrap_lwe_ciphertext_vector_128(
void *stream, uint32_t gpu_index, __uint128_t *lwe_array_out,
__uint128_t const *lut_vector, InputTorus const *lwe_array_in,
__uint128_t const *lut_vector, InputTorus *lwe_array_in,
double const *bootstrapping_key,
pbs_buffer_128<InputTorus, PBS_TYPE::CLASSICAL> *buffer,
uint32_t lwe_dimension, uint32_t glwe_dimension, uint32_t polynomial_size,
@@ -83,7 +83,7 @@ void executor_cuda_programmable_bootstrap_lwe_ciphertext_vector_128(
template <typename InputTorus>
void executor_cuda_programmable_bootstrap_cg_lwe_ciphertext_vector_128(
void *stream, uint32_t gpu_index, __uint128_t *lwe_array_out,
__uint128_t const *lut_vector, InputTorus const *lwe_array_in,
__uint128_t const *lut_vector, InputTorus *lwe_array_in,
double const *bootstrapping_key,
pbs_buffer_128<InputTorus, PBS_TYPE::CLASSICAL> *buffer,
uint32_t lwe_dimension, uint32_t glwe_dimension, uint32_t polynomial_size,
@@ -132,17 +132,36 @@ void host_programmable_bootstrap_lwe_ciphertext_vector_128(
void *stream, uint32_t gpu_index, void *lwe_array_out,
__uint128_t const *lut_vector, void const *lwe_array_in,
void const *bootstrapping_key,
CudaModulusSwitchNoiseReductionKeyFFI const *ms_drift_noise_reduction_ptr,
void const *ms_noise_reduction_ptr,
pbs_buffer_128<InputTorus, PBS_TYPE::CLASSICAL> *buffer,
uint32_t lwe_dimension, uint32_t glwe_dimension, uint32_t polynomial_size,
uint32_t base_log, uint32_t level_count, uint32_t num_samples) {
if (base_log > 64)
PANIC("Cuda error (classical PBS): base log should be <= 64")
// If the parameters contain drift noise reduction key, then apply it
if (buffer->noise_reduction_type == PBS_MS_REDUCTION_T::DRIFT) {
uint32_t log_modulus = log2(polynomial_size) + 1;
host_drift_modulus_switch<InputTorus>(
static_cast<cudaStream_t>(stream), gpu_index,
static_cast<InputTorus *>(buffer->temp_lwe_array_in),
static_cast<InputTorus const *>(lwe_array_in),
static_cast<uint64_t const *>(buffer->trivial_indexes),
static_cast<const InputTorus *>(ms_noise_reduction_ptr),
lwe_dimension + 1, num_samples, ms_drift_noise_reduction_ptr->num_zeros,
ms_drift_noise_reduction_ptr->ms_input_variance,
ms_drift_noise_reduction_ptr->ms_r_sigma,
ms_drift_noise_reduction_ptr->ms_bound, log_modulus);
} else {
buffer->temp_lwe_array_in =
const_cast<InputTorus *>(static_cast<const InputTorus *>(lwe_array_in));
}
switch (buffer->pbs_variant) {
case DEFAULT:
executor_cuda_programmable_bootstrap_lwe_ciphertext_vector_128<InputTorus>(
stream, gpu_index, static_cast<__uint128_t *>(lwe_array_out),
lut_vector, static_cast<InputTorus const *>(lwe_array_in),
lut_vector, static_cast<InputTorus *>(buffer->temp_lwe_array_in),
static_cast<const double *>(bootstrapping_key), buffer, lwe_dimension,
glwe_dimension, polynomial_size, base_log, level_count, num_samples);
break;
@@ -150,7 +169,7 @@ void host_programmable_bootstrap_lwe_ciphertext_vector_128(
executor_cuda_programmable_bootstrap_cg_lwe_ciphertext_vector_128<
InputTorus>(
stream, gpu_index, static_cast<__uint128_t *>(lwe_array_out),
lut_vector, static_cast<InputTorus const *>(lwe_array_in),
lut_vector, static_cast<InputTorus *>(buffer->temp_lwe_array_in),
static_cast<const double *>(bootstrapping_key), buffer, lwe_dimension,
glwe_dimension, polynomial_size, base_log, level_count, num_samples);
break;
@@ -215,7 +234,9 @@ void host_programmable_bootstrap_lwe_ciphertext_vector_128(
void cuda_programmable_bootstrap_lwe_ciphertext_vector_128(
void *streams, uint32_t gpu_index, void *lwe_array_out,
void const *lut_vector, void const *lwe_array_in,
void const *bootstrapping_key, int8_t *mem_ptr, uint32_t lwe_dimension,
void const *bootstrapping_key,
CudaModulusSwitchNoiseReductionKeyFFI const *ms_noise_reduction_key,
void const *ms_noise_reduction_ptr, int8_t *mem_ptr, uint32_t lwe_dimension,
uint32_t glwe_dimension, uint32_t polynomial_size, uint32_t base_log,
uint32_t level_count, uint32_t num_samples) {
pbs_buffer_128<uint64_t, PBS_TYPE::CLASSICAL> *buffer =
@@ -224,8 +245,9 @@ void cuda_programmable_bootstrap_lwe_ciphertext_vector_128(
host_programmable_bootstrap_lwe_ciphertext_vector_128<uint64_t>(
streams, gpu_index, lwe_array_out,
static_cast<const __uint128_t *>(lut_vector), lwe_array_in,
bootstrapping_key, buffer, lwe_dimension, glwe_dimension, polynomial_size,
base_log, level_count, num_samples);
bootstrapping_key, ms_noise_reduction_key, ms_noise_reduction_ptr, buffer,
lwe_dimension, glwe_dimension, polynomial_size, base_log, level_count,
num_samples);
}
/*

View File

@@ -668,7 +668,7 @@ uint64_t scratch_cuda_programmable_bootstrap_128_vector(
template <typename InputTorus, class params, bool first_iter>
__host__ void execute_step_one_128(
cudaStream_t stream, uint32_t gpu_index, __uint128_t const *lut_vector,
InputTorus const *lwe_array_in, double const *bootstrapping_key,
InputTorus *lwe_array_in, double const *bootstrapping_key,
__uint128_t *global_accumulator, double *global_join_buffer,
PBS_MS_REDUCTION_T noise_reduction_type,
uint32_t input_lwe_ciphertext_count, uint32_t lwe_dimension,
@@ -752,7 +752,7 @@ __host__ void execute_step_two_128(
template <typename InputTorus, class params>
__host__ void host_programmable_bootstrap_128(
cudaStream_t stream, uint32_t gpu_index, __uint128_t *lwe_array_out,
__uint128_t const *lut_vector, InputTorus const *lwe_array_in,
__uint128_t const *lut_vector, InputTorus *lwe_array_in,
double const *bootstrapping_key,
pbs_buffer_128<InputTorus, PBS_TYPE::CLASSICAL> *pbs_buffer,
uint32_t glwe_dimension, uint32_t lwe_dimension, uint32_t polynomial_size,

View File

@@ -84,7 +84,9 @@ __global__ void device_programmable_bootstrap_tbc(
// The third dimension of the block is used to determine on which ciphertext
// this block is operating, in the case of batch bootstraps
const Torus *block_lwe_array_in =
&lwe_array_in[lwe_input_indexes[blockIdx.x] * (lwe_dimension + 1)];
(noise_reduction_type == PBS_MS_REDUCTION_T::DRIFT)
? &lwe_array_in[blockIdx.x * (lwe_dimension + 1)]
: &lwe_array_in[lwe_input_indexes[blockIdx.x] * (lwe_dimension + 1)];
const Torus *block_lut_vector =
&lut_vector[lut_vector_indexes[blockIdx.x] * params::degree *

View File

@@ -43,7 +43,8 @@ uint64_t scratch_cuda_expand_without_verification_64(
void cuda_expand_without_verification_64(
CudaStreamsFFI streams, void *lwe_array_out,
const void *lwe_flattened_compact_array_in, int8_t *mem_ptr,
void *const *bsks, void *const *computing_ksks, void *const *casting_keys) {
void *const *bsks, void *const *computing_ksks, void *const *casting_keys,
CudaModulusSwitchNoiseReductionKeyFFI const *ms_noise_reduction_key) {
auto expand_buffer = reinterpret_cast<zk_expand_mem<uint64_t> *>(mem_ptr);
@@ -53,49 +54,49 @@ void cuda_expand_without_verification_64(
streams, static_cast<uint64_t *>(lwe_array_out),
static_cast<const uint64_t *>(lwe_flattened_compact_array_in),
expand_buffer, (uint64_t **)casting_keys, bsks,
(uint64_t **)(computing_ksks));
(uint64_t **)(computing_ksks), ms_noise_reduction_key);
break;
case 512:
host_expand_without_verification<uint64_t, AmortizedDegree<512>>(
streams, static_cast<uint64_t *>(lwe_array_out),
static_cast<const uint64_t *>(lwe_flattened_compact_array_in),
expand_buffer, (uint64_t **)casting_keys, bsks,
(uint64_t **)(computing_ksks));
(uint64_t **)(computing_ksks), ms_noise_reduction_key);
break;
case 1024:
host_expand_without_verification<uint64_t, AmortizedDegree<1024>>(
streams, static_cast<uint64_t *>(lwe_array_out),
static_cast<const uint64_t *>(lwe_flattened_compact_array_in),
expand_buffer, (uint64_t **)casting_keys, bsks,
(uint64_t **)(computing_ksks));
(uint64_t **)(computing_ksks), ms_noise_reduction_key);
break;
case 2048:
host_expand_without_verification<uint64_t, AmortizedDegree<2048>>(
streams, static_cast<uint64_t *>(lwe_array_out),
static_cast<const uint64_t *>(lwe_flattened_compact_array_in),
expand_buffer, (uint64_t **)casting_keys, bsks,
(uint64_t **)(computing_ksks));
(uint64_t **)(computing_ksks), ms_noise_reduction_key);
break;
case 4096:
host_expand_without_verification<uint64_t, AmortizedDegree<4096>>(
streams, static_cast<uint64_t *>(lwe_array_out),
static_cast<const uint64_t *>(lwe_flattened_compact_array_in),
expand_buffer, (uint64_t **)casting_keys, bsks,
(uint64_t **)(computing_ksks));
(uint64_t **)(computing_ksks), ms_noise_reduction_key);
break;
case 8192:
host_expand_without_verification<uint64_t, AmortizedDegree<8192>>(
streams, static_cast<uint64_t *>(lwe_array_out),
static_cast<const uint64_t *>(lwe_flattened_compact_array_in),
expand_buffer, (uint64_t **)casting_keys, bsks,
(uint64_t **)(computing_ksks));
(uint64_t **)(computing_ksks), ms_noise_reduction_key);
break;
case 16384:
host_expand_without_verification<uint64_t, AmortizedDegree<16384>>(
streams, static_cast<uint64_t *>(lwe_array_out),
static_cast<const uint64_t *>(lwe_flattened_compact_array_in),
expand_buffer, (uint64_t **)casting_keys, bsks,
(uint64_t **)(computing_ksks));
(uint64_t **)(computing_ksks), ms_noise_reduction_key);
break;
default:
PANIC("CUDA error: lwe_dimension not supported."

View File

@@ -19,7 +19,8 @@ template <typename Torus, class params>
__host__ void host_expand_without_verification(
CudaStreams streams, Torus *lwe_array_out,
const Torus *lwe_flattened_compact_array_in, zk_expand_mem<Torus> *mem_ptr,
Torus *const *casting_keys, void *const *bsks, Torus *const *compute_ksks) {
Torus *const *casting_keys, void *const *bsks, Torus *const *compute_ksks,
CudaModulusSwitchNoiseReductionKeyFFI const *ms_noise_reduction_key) {
// Expand
auto casting_key_type = mem_ptr->casting_key_type;
auto expanded_lwes = mem_ptr->tmp_expanded_lwes;
@@ -76,7 +77,7 @@ __host__ void host_expand_without_verification(
// apply keyswitch to BIG
execute_keyswitch_async<Torus>(
streams.get_ith(0), ksed_small_to_big_expanded_lwes,
streams.subset_first_gpu(), 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);
@@ -95,8 +96,8 @@ __host__ void host_expand_without_verification(
auto input = new CudaRadixCiphertextFFI;
into_radix_ciphertext(input, lwe_array_input, 2 * num_lwes, lwe_dimension);
integer_radix_apply_univariate_lookup_table_kb<Torus>(
streams, output, input, bsks, ksks, message_and_carry_extract_luts,
2 * num_lwes);
streams, output, input, bsks, ksks, ms_noise_reduction_key,
message_and_carry_extract_luts, 2 * num_lwes);
}
template <typename Torus>

View File

@@ -191,9 +191,9 @@ TEST_P(ClassicalProgrammableBootstrapTestPrimitives_u64, bootstrap) {
stream, gpu_index, (void *)d_lwe_ct_out_array,
(void *)d_lwe_output_indexes, (void *)d_lut_pbs_identity,
(void *)d_lut_pbs_indexes, (void *)d_lwe_ct_in,
(void *)d_lwe_input_indexes, (void *)d_fourier_bsk, pbs_buffer,
lwe_dimension, glwe_dimension, polynomial_size, pbs_base_log,
pbs_level, number_of_inputs, num_many_lut, lut_stride);
(void *)d_lwe_input_indexes, (void *)d_fourier_bsk, nullptr, nullptr,
pbs_buffer, lwe_dimension, glwe_dimension, polynomial_size,
pbs_base_log, pbs_level, number_of_inputs, num_many_lut, lut_stride);
// Copy result back
cuda_memcpy_async_to_cpu(lwe_ct_out_array, d_lwe_ct_out_array,
(glwe_dimension * polynomial_size + 1) *

View File

@@ -98,8 +98,37 @@ pub const PBS_TYPE_MULTI_BIT: PBS_TYPE = 0;
pub const PBS_TYPE_CLASSICAL: PBS_TYPE = 1;
pub type PBS_TYPE = ffi::c_uint;
pub const PBS_MS_REDUCTION_T_NO_REDUCTION: PBS_MS_REDUCTION_T = 0;
pub const PBS_MS_REDUCTION_T_CENTERED: PBS_MS_REDUCTION_T = 1;
pub const PBS_MS_REDUCTION_T_DRIFT: PBS_MS_REDUCTION_T = 1;
pub const PBS_MS_REDUCTION_T_CENTERED: PBS_MS_REDUCTION_T = 2;
pub type PBS_MS_REDUCTION_T = ffi::c_uint;
#[repr(C)]
#[derive(Debug, Copy, Clone)]
pub struct CudaModulusSwitchNoiseReductionKeyFFI {
pub ptr: *const *mut ffi::c_void,
pub num_zeros: u32,
pub ms_bound: f64,
pub ms_r_sigma: f64,
pub ms_input_variance: f64,
}
#[allow(clippy::unnecessary_operation, clippy::identity_op)]
const _: () = {
["Size of CudaModulusSwitchNoiseReductionKeyFFI"]
[::std::mem::size_of::<CudaModulusSwitchNoiseReductionKeyFFI>() - 40usize];
["Alignment of CudaModulusSwitchNoiseReductionKeyFFI"]
[::std::mem::align_of::<CudaModulusSwitchNoiseReductionKeyFFI>() - 8usize];
["Offset of field: CudaModulusSwitchNoiseReductionKeyFFI::ptr"]
[::std::mem::offset_of!(CudaModulusSwitchNoiseReductionKeyFFI, ptr) - 0usize];
["Offset of field: CudaModulusSwitchNoiseReductionKeyFFI::num_zeros"]
[::std::mem::offset_of!(CudaModulusSwitchNoiseReductionKeyFFI, num_zeros) - 8usize];
["Offset of field: CudaModulusSwitchNoiseReductionKeyFFI::ms_bound"]
[::std::mem::offset_of!(CudaModulusSwitchNoiseReductionKeyFFI, ms_bound) - 16usize];
["Offset of field: CudaModulusSwitchNoiseReductionKeyFFI::ms_r_sigma"]
[::std::mem::offset_of!(CudaModulusSwitchNoiseReductionKeyFFI, ms_r_sigma) - 24usize];
["Offset of field: CudaModulusSwitchNoiseReductionKeyFFI::ms_input_variance"][::std::mem::offset_of!(
CudaModulusSwitchNoiseReductionKeyFFI,
ms_input_variance
) - 32usize];
};
pub const SHIFT_OR_ROTATE_TYPE_LEFT_SHIFT: SHIFT_OR_ROTATE_TYPE = 0;
pub const SHIFT_OR_ROTATE_TYPE_RIGHT_SHIFT: SHIFT_OR_ROTATE_TYPE = 1;
pub const SHIFT_OR_ROTATE_TYPE_LEFT_ROTATE: SHIFT_OR_ROTATE_TYPE = 2;
@@ -252,55 +281,6 @@ const _: () = {
divisor_has_more_bits_than_numerator
) - 60usize];
};
#[repr(C)]
#[derive(Debug, Copy, Clone)]
pub struct CudaLweCiphertextListFFI {
pub ptr: *mut ffi::c_void,
pub num_radix_blocks: u32,
pub lwe_dimension: u32,
}
#[allow(clippy::unnecessary_operation, clippy::identity_op)]
const _: () = {
["Size of CudaLweCiphertextListFFI"]
[::std::mem::size_of::<CudaLweCiphertextListFFI>() - 16usize];
["Alignment of CudaLweCiphertextListFFI"]
[::std::mem::align_of::<CudaLweCiphertextListFFI>() - 8usize];
["Offset of field: CudaLweCiphertextListFFI::ptr"]
[::std::mem::offset_of!(CudaLweCiphertextListFFI, ptr) - 0usize];
["Offset of field: CudaLweCiphertextListFFI::num_radix_blocks"]
[::std::mem::offset_of!(CudaLweCiphertextListFFI, num_radix_blocks) - 8usize];
["Offset of field: CudaLweCiphertextListFFI::lwe_dimension"]
[::std::mem::offset_of!(CudaLweCiphertextListFFI, lwe_dimension) - 12usize];
};
#[repr(C)]
#[derive(Debug, Copy, Clone)]
pub struct CudaPackedGlweCiphertextListFFI {
pub ptr: *mut ffi::c_void,
pub storage_log_modulus: u32,
pub lwe_per_glwe: u32,
pub total_lwe_bodies_count: u32,
pub glwe_dimension: u32,
pub polynomial_size: u32,
}
#[allow(clippy::unnecessary_operation, clippy::identity_op)]
const _: () = {
["Size of CudaPackedGlweCiphertextListFFI"]
[::std::mem::size_of::<CudaPackedGlweCiphertextListFFI>() - 32usize];
["Alignment of CudaPackedGlweCiphertextListFFI"]
[::std::mem::align_of::<CudaPackedGlweCiphertextListFFI>() - 8usize];
["Offset of field: CudaPackedGlweCiphertextListFFI::ptr"]
[::std::mem::offset_of!(CudaPackedGlweCiphertextListFFI, ptr) - 0usize];
["Offset of field: CudaPackedGlweCiphertextListFFI::storage_log_modulus"]
[::std::mem::offset_of!(CudaPackedGlweCiphertextListFFI, storage_log_modulus) - 8usize];
["Offset of field: CudaPackedGlweCiphertextListFFI::lwe_per_glwe"]
[::std::mem::offset_of!(CudaPackedGlweCiphertextListFFI, lwe_per_glwe) - 12usize];
["Offset of field: CudaPackedGlweCiphertextListFFI::total_lwe_bodies_count"]
[::std::mem::offset_of!(CudaPackedGlweCiphertextListFFI, total_lwe_bodies_count) - 16usize];
["Offset of field: CudaPackedGlweCiphertextListFFI::glwe_dimension"]
[::std::mem::offset_of!(CudaPackedGlweCiphertextListFFI, glwe_dimension) - 20usize];
["Offset of field: CudaPackedGlweCiphertextListFFI::polynomial_size"]
[::std::mem::offset_of!(CudaPackedGlweCiphertextListFFI, polynomial_size) - 24usize];
};
unsafe extern "C" {
pub fn scratch_cuda_apply_univariate_lut_kb_64(
streams: CudaStreamsFFI,
@@ -353,6 +333,7 @@ unsafe extern "C" {
input_radix_lwe: *const CudaRadixCiphertextFFI,
mem_ptr: *mut i8,
ksks: *const *mut ffi::c_void,
ms_noise_reduction_key: *const CudaModulusSwitchNoiseReductionKeyFFI,
bsks: *const *mut ffi::c_void,
);
}
@@ -392,6 +373,7 @@ unsafe extern "C" {
input_radix_lwe_2: *const CudaRadixCiphertextFFI,
mem_ptr: *mut i8,
ksks: *const *mut ffi::c_void,
ms_noise_reduction_key: *const CudaModulusSwitchNoiseReductionKeyFFI,
bsks: *const *mut ffi::c_void,
num_radix_blocks: u32,
shift: u32,
@@ -410,6 +392,7 @@ unsafe extern "C" {
input_radix_lwe: *const CudaRadixCiphertextFFI,
mem_ptr: *mut i8,
ksks: *const *mut ffi::c_void,
ms_noise_reduction_key: *const CudaModulusSwitchNoiseReductionKeyFFI,
bsks: *const *mut ffi::c_void,
num_luts: u32,
lut_stride: u32,
@@ -440,6 +423,7 @@ unsafe extern "C" {
input_blocks: *mut CudaRadixCiphertextFFI,
mem_ptr: *mut i8,
ksks: *const *mut ffi::c_void,
ms_noise_reduction_key: *const CudaModulusSwitchNoiseReductionKeyFFI,
bsks: *const *mut ffi::c_void,
num_blocks: u32,
);
@@ -479,6 +463,7 @@ unsafe extern "C" {
is_bool_right: bool,
bsks: *const *mut ffi::c_void,
ksks: *const *mut ffi::c_void,
ms_noise_reduction_key: *const CudaModulusSwitchNoiseReductionKeyFFI,
mem_ptr: *mut i8,
polynomial_size: u32,
num_blocks: u32,
@@ -538,6 +523,7 @@ unsafe extern "C" {
mem_ptr: *mut i8,
bsks: *const *mut ffi::c_void,
ksks: *const *mut ffi::c_void,
ms_noise_reduction_key: *const CudaModulusSwitchNoiseReductionKeyFFI,
);
}
unsafe extern "C" {
@@ -570,6 +556,7 @@ unsafe extern "C" {
mem_ptr: *mut i8,
bsks: *const *mut ffi::c_void,
ksks: *const *mut ffi::c_void,
ms_noise_reduction_key: *const CudaModulusSwitchNoiseReductionKeyFFI,
);
}
unsafe extern "C" {
@@ -615,6 +602,7 @@ unsafe extern "C" {
mem_ptr: *mut i8,
bsks: *const *mut ffi::c_void,
ksks: *const *mut ffi::c_void,
ms_noise_reduction_key: *const CudaModulusSwitchNoiseReductionKeyFFI,
);
}
unsafe extern "C" {
@@ -655,6 +643,7 @@ unsafe extern "C" {
mem_ptr: *mut i8,
bsks: *const *mut ffi::c_void,
ksks: *const *mut ffi::c_void,
ms_noise_reduction_key: *const CudaModulusSwitchNoiseReductionKeyFFI,
);
}
unsafe extern "C" {
@@ -667,6 +656,7 @@ unsafe extern "C" {
mem_ptr: *mut i8,
bsks: *const *mut ffi::c_void,
ksks: *const *mut ffi::c_void,
ms_noise_reduction_key: *const CudaModulusSwitchNoiseReductionKeyFFI,
num_scalar_blocks: u32,
);
}
@@ -704,6 +694,7 @@ unsafe extern "C" {
mem_ptr: *mut i8,
bsks: *const *mut ffi::c_void,
ksks: *const *mut ffi::c_void,
ms_noise_reduction_key: *const CudaModulusSwitchNoiseReductionKeyFFI,
);
}
unsafe extern "C" {
@@ -717,6 +708,7 @@ unsafe extern "C" {
mem_ptr: *mut i8,
bsks: *const *mut ffi::c_void,
ksks: *const *mut ffi::c_void,
ms_noise_reduction_key: *const CudaModulusSwitchNoiseReductionKeyFFI,
);
}
unsafe extern "C" {
@@ -753,6 +745,7 @@ unsafe extern "C" {
mem_ptr: *mut i8,
bsks: *const *mut ffi::c_void,
ksks: *const *mut ffi::c_void,
ms_noise_reduction_key: *const CudaModulusSwitchNoiseReductionKeyFFI,
);
}
unsafe extern "C" {
@@ -788,6 +781,7 @@ unsafe extern "C" {
mem_ptr: *mut i8,
bsks: *const *mut ffi::c_void,
ksks: *const *mut ffi::c_void,
ms_noise_reduction_key: *const CudaModulusSwitchNoiseReductionKeyFFI,
);
}
unsafe extern "C" {
@@ -849,6 +843,7 @@ unsafe extern "C" {
mem_ptr: *mut i8,
bsks: *const *mut ffi::c_void,
ksks: *const *mut ffi::c_void,
ms_noise_reduction_key: *const CudaModulusSwitchNoiseReductionKeyFFI,
requested_flag: u32,
uses_carry: u32,
);
@@ -863,6 +858,7 @@ unsafe extern "C" {
mem_ptr: *mut i8,
bsks: *const *mut ffi::c_void,
ksks: *const *mut ffi::c_void,
ms_noise_reduction_key: *const CudaModulusSwitchNoiseReductionKeyFFI,
requested_flag: u32,
uses_carry: u32,
);
@@ -908,6 +904,7 @@ unsafe extern "C" {
mem_ptr: *mut i8,
bsks: *const *mut ffi::c_void,
ksks: *const *mut ffi::c_void,
ms_noise_reduction_key: *const CudaModulusSwitchNoiseReductionKeyFFI,
compute_overflow: u32,
uses_input_borrow: u32,
);
@@ -948,6 +945,7 @@ unsafe extern "C" {
mem_ptr: *mut i8,
bsks: *const *mut ffi::c_void,
ksks: *const *mut ffi::c_void,
ms_noise_reduction_key: *const CudaModulusSwitchNoiseReductionKeyFFI,
);
}
unsafe extern "C" {
@@ -986,6 +984,7 @@ unsafe extern "C" {
mem_ptr: *mut i8,
bsks: *const *mut ffi::c_void,
ksks: *const *mut ffi::c_void,
ms_noise_reduction_key: *const CudaModulusSwitchNoiseReductionKeyFFI,
polynomial_size: u32,
message_modulus: u32,
num_scalars: u32,
@@ -1030,6 +1029,7 @@ unsafe extern "C" {
mem_ptr: *mut i8,
bsks: *const *mut ffi::c_void,
ksks: *const *mut ffi::c_void,
ms_noise_reduction_key: *const CudaModulusSwitchNoiseReductionKeyFFI,
);
}
unsafe extern "C" {
@@ -1064,6 +1064,7 @@ unsafe extern "C" {
generates_or_propagates: *mut CudaRadixCiphertextFFI,
mem_ptr: *mut i8,
ksks: *const *mut ffi::c_void,
ms_noise_reduction_key: *const CudaModulusSwitchNoiseReductionKeyFFI,
bsks: *const *mut ffi::c_void,
num_blocks: u32,
);
@@ -1110,6 +1111,7 @@ unsafe extern "C" {
is_signed: bool,
bsks: *const *mut ffi::c_void,
ksks: *const *mut ffi::c_void,
ms_noise_reduction_key: *const CudaModulusSwitchNoiseReductionKeyFFI,
);
}
unsafe extern "C" {
@@ -1144,6 +1146,7 @@ unsafe extern "C" {
mem_ptr: *mut i8,
bsks: *const *mut ffi::c_void,
ksks: *const *mut ffi::c_void,
ms_noise_reduction_key: *const CudaModulusSwitchNoiseReductionKeyFFI,
num_radix_blocks: u32,
);
}
@@ -1182,6 +1185,7 @@ unsafe extern "C" {
mem_ptr: *mut i8,
bsks: *const *mut ffi::c_void,
ksks: *const *mut ffi::c_void,
ms_noise_reduction_key: *const CudaModulusSwitchNoiseReductionKeyFFI,
num_radix_blocks: u32,
);
}
@@ -1235,6 +1239,7 @@ unsafe extern "C" {
input_radix_lwe: *const CudaRadixCiphertextFFI,
mem_ptr: *mut i8,
ksks: *const *mut ffi::c_void,
ms_noise_reduction_key: *const CudaModulusSwitchNoiseReductionKeyFFI,
bsks: *const *mut ffi::c_void,
);
}
@@ -1276,6 +1281,7 @@ unsafe extern "C" {
mem_ptr: *mut i8,
bsks: *const *mut ffi::c_void,
ksks: *const *mut ffi::c_void,
ms_noise_reduction_key: *const CudaModulusSwitchNoiseReductionKeyFFI,
requested_flag: u32,
uses_carry: u32,
);
@@ -1314,6 +1320,7 @@ unsafe extern "C" {
mem_ptr: *mut i8,
bsks: *const *mut ffi::c_void,
ksks: *const *mut ffi::c_void,
ms_noise_reduction_key: *const CudaModulusSwitchNoiseReductionKeyFFI,
scalar_divisor_ffi: *const CudaScalarDivisorFFI,
);
}
@@ -1353,6 +1360,7 @@ unsafe extern "C" {
num_additional_blocks: u32,
bsks: *const *mut ffi::c_void,
ksks: *const *mut ffi::c_void,
ms_noise_reduction_key: *const CudaModulusSwitchNoiseReductionKeyFFI,
);
}
unsafe extern "C" {
@@ -1389,6 +1397,7 @@ unsafe extern "C" {
mem_ptr: *mut i8,
bsks: *const *mut ffi::c_void,
ksks: *const *mut ffi::c_void,
ms_noise_reduction_key: *const CudaModulusSwitchNoiseReductionKeyFFI,
scalar_divisor_ffi: *const CudaScalarDivisorFFI,
numerator_bits: u32,
);
@@ -1429,6 +1438,7 @@ unsafe extern "C" {
mem_ptr: *mut i8,
bsks: *const *mut ffi::c_void,
ksks: *const *mut ffi::c_void,
ms_noise_reduction_key: *const CudaModulusSwitchNoiseReductionKeyFFI,
scalar_divisor_ffi: *const CudaScalarDivisorFFI,
divisor_has_at_least_one_set: *const u64,
decomposed_divisor: *const u64,
@@ -1474,6 +1484,7 @@ unsafe extern "C" {
mem_ptr: *mut i8,
bsks: *const *mut ffi::c_void,
ksks: *const *mut ffi::c_void,
ms_noise_reduction_key: *const CudaModulusSwitchNoiseReductionKeyFFI,
scalar_divisor_ffi: *const CudaScalarDivisorFFI,
divisor_has_at_least_one_set: *const u64,
decomposed_divisor: *const u64,
@@ -1518,6 +1529,7 @@ unsafe extern "C" {
mem_ptr: *mut i8,
bsks: *const *mut ffi::c_void,
ksks: *const *mut ffi::c_void,
ms_noise_reduction_key: *const CudaModulusSwitchNoiseReductionKeyFFI,
);
}
unsafe extern "C" {
@@ -1539,6 +1551,7 @@ unsafe extern "C" {
pbs_base_log: u32,
grouping_factor: u32,
num_blocks_to_process: u32,
num_blocks: u32,
message_modulus: u32,
carry_modulus: u32,
pbs_type: PBS_TYPE,
@@ -1556,6 +1569,7 @@ unsafe extern "C" {
num_blocks_to_process: u32,
mem: *mut i8,
bsks: *const *mut ffi::c_void,
ms_noise_reduction_key: *const CudaModulusSwitchNoiseReductionKeyFFI,
);
}
unsafe extern "C" {
@@ -1597,11 +1611,61 @@ unsafe extern "C" {
mem_ptr: *mut i8,
bsks: *const *mut ffi::c_void,
ksks: *const *mut ffi::c_void,
ms_noise_reduction_key: *const CudaModulusSwitchNoiseReductionKeyFFI,
);
}
unsafe extern "C" {
pub fn cleanup_cuda_integer_ilog2_kb_64(streams: CudaStreamsFFI, mem_ptr_void: *mut *mut i8);
}
#[repr(C)]
#[derive(Debug, Copy, Clone)]
pub struct CudaLweCiphertextListFFI {
pub ptr: *mut ffi::c_void,
pub num_radix_blocks: u32,
pub lwe_dimension: u32,
}
#[allow(clippy::unnecessary_operation, clippy::identity_op)]
const _: () = {
["Size of CudaLweCiphertextListFFI"]
[::std::mem::size_of::<CudaLweCiphertextListFFI>() - 16usize];
["Alignment of CudaLweCiphertextListFFI"]
[::std::mem::align_of::<CudaLweCiphertextListFFI>() - 8usize];
["Offset of field: CudaLweCiphertextListFFI::ptr"]
[::std::mem::offset_of!(CudaLweCiphertextListFFI, ptr) - 0usize];
["Offset of field: CudaLweCiphertextListFFI::num_radix_blocks"]
[::std::mem::offset_of!(CudaLweCiphertextListFFI, num_radix_blocks) - 8usize];
["Offset of field: CudaLweCiphertextListFFI::lwe_dimension"]
[::std::mem::offset_of!(CudaLweCiphertextListFFI, lwe_dimension) - 12usize];
};
#[repr(C)]
#[derive(Debug, Copy, Clone)]
pub struct CudaPackedGlweCiphertextListFFI {
pub ptr: *mut ffi::c_void,
pub storage_log_modulus: u32,
pub lwe_per_glwe: u32,
pub total_lwe_bodies_count: u32,
pub glwe_dimension: u32,
pub polynomial_size: u32,
}
#[allow(clippy::unnecessary_operation, clippy::identity_op)]
const _: () = {
["Size of CudaPackedGlweCiphertextListFFI"]
[::std::mem::size_of::<CudaPackedGlweCiphertextListFFI>() - 32usize];
["Alignment of CudaPackedGlweCiphertextListFFI"]
[::std::mem::align_of::<CudaPackedGlweCiphertextListFFI>() - 8usize];
["Offset of field: CudaPackedGlweCiphertextListFFI::ptr"]
[::std::mem::offset_of!(CudaPackedGlweCiphertextListFFI, ptr) - 0usize];
["Offset of field: CudaPackedGlweCiphertextListFFI::storage_log_modulus"]
[::std::mem::offset_of!(CudaPackedGlweCiphertextListFFI, storage_log_modulus) - 8usize];
["Offset of field: CudaPackedGlweCiphertextListFFI::lwe_per_glwe"]
[::std::mem::offset_of!(CudaPackedGlweCiphertextListFFI, lwe_per_glwe) - 12usize];
["Offset of field: CudaPackedGlweCiphertextListFFI::total_lwe_bodies_count"]
[::std::mem::offset_of!(CudaPackedGlweCiphertextListFFI, total_lwe_bodies_count) - 16usize];
["Offset of field: CudaPackedGlweCiphertextListFFI::glwe_dimension"]
[::std::mem::offset_of!(CudaPackedGlweCiphertextListFFI, glwe_dimension) - 20usize];
["Offset of field: CudaPackedGlweCiphertextListFFI::polynomial_size"]
[::std::mem::offset_of!(CudaPackedGlweCiphertextListFFI, polynomial_size) - 24usize];
};
unsafe extern "C" {
pub fn scratch_cuda_integer_compress_radix_ciphertext_64(
streams: CudaStreamsFFI,
@@ -1729,78 +1793,6 @@ unsafe extern "C" {
mem_ptr_void: *mut *mut i8,
);
}
unsafe extern "C" {
pub fn scratch_cuda_integer_aes_encrypt_64(
streams: CudaStreamsFFI,
mem_ptr: *mut *mut i8,
glwe_dimension: u32,
polynomial_size: u32,
lwe_dimension: u32,
ks_level: u32,
ks_base_log: u32,
pbs_level: u32,
pbs_base_log: u32,
grouping_factor: u32,
message_modulus: u32,
carry_modulus: u32,
pbs_type: PBS_TYPE,
allocate_gpu_memory: bool,
noise_reduction_type: PBS_MS_REDUCTION_T,
num_aes_inputs: u32,
sbox_parallelism: u32,
) -> u64;
}
unsafe extern "C" {
pub fn cuda_integer_aes_ctr_encrypt_64(
streams: CudaStreamsFFI,
output: *mut CudaRadixCiphertextFFI,
iv: *const CudaRadixCiphertextFFI,
round_keys: *const CudaRadixCiphertextFFI,
counter_bits_le_all_blocks: *const u64,
num_aes_inputs: u32,
mem_ptr: *mut i8,
bsks: *const *mut ffi::c_void,
ksks: *const *mut ffi::c_void,
);
}
unsafe extern "C" {
pub fn cleanup_cuda_integer_aes_encrypt_64(streams: CudaStreamsFFI, mem_ptr_void: *mut *mut i8);
}
unsafe extern "C" {
pub fn scratch_cuda_integer_key_expansion_64(
streams: CudaStreamsFFI,
mem_ptr: *mut *mut i8,
glwe_dimension: u32,
polynomial_size: u32,
lwe_dimension: u32,
ks_level: u32,
ks_base_log: u32,
pbs_level: u32,
pbs_base_log: u32,
grouping_factor: u32,
message_modulus: u32,
carry_modulus: u32,
pbs_type: PBS_TYPE,
allocate_gpu_memory: bool,
noise_reduction_type: PBS_MS_REDUCTION_T,
) -> u64;
}
unsafe extern "C" {
pub fn cuda_integer_key_expansion_64(
streams: CudaStreamsFFI,
expanded_keys: *mut CudaRadixCiphertextFFI,
key: *const CudaRadixCiphertextFFI,
mem_ptr: *mut i8,
bsks: *const *mut ffi::c_void,
ksks: *const *mut ffi::c_void,
);
}
unsafe extern "C" {
pub fn cleanup_cuda_integer_key_expansion_64(
streams: CudaStreamsFFI,
mem_ptr_void: *mut *mut i8,
);
}
pub const KS_TYPE_BIG_TO_SMALL: KS_TYPE = 0;
pub const KS_TYPE_SMALL_TO_BIG: KS_TYPE = 1;
pub type KS_TYPE = ffi::c_uint;
@@ -1841,6 +1833,7 @@ unsafe extern "C" {
bsks: *const *mut ffi::c_void,
computing_ksks: *const *mut ffi::c_void,
casting_keys: *const *mut ffi::c_void,
ms_noise_reduction_key: *const CudaModulusSwitchNoiseReductionKeyFFI,
);
}
unsafe extern "C" {
@@ -2308,6 +2301,8 @@ unsafe extern "C" {
lwe_array_in: *const ffi::c_void,
lwe_input_indexes: *const ffi::c_void,
bootstrapping_key: *const ffi::c_void,
ms_noise_reduction_key: *const CudaModulusSwitchNoiseReductionKeyFFI,
ms_noise_reduction_ptr: *mut ffi::c_void,
buffer: *mut i8,
lwe_dimension: u32,
glwe_dimension: u32,
@@ -2327,6 +2322,8 @@ unsafe extern "C" {
lut_vector: *const ffi::c_void,
lwe_array_in: *const ffi::c_void,
bootstrapping_key: *const ffi::c_void,
ms_noise_reduction_key: *const CudaModulusSwitchNoiseReductionKeyFFI,
ms_noise_reduction_ptr: *const ffi::c_void,
buffer: *mut i8,
lwe_dimension: u32,
glwe_dimension: u32,

View File

@@ -2,7 +2,6 @@
#include "cuda/include/ciphertext.h"
#include "cuda/include/integer/compression/compression.h"
#include "cuda/include/integer/integer.h"
#include "cuda/include/aes/aes.h"
#include "cuda/include/zk/zk.h"
#include "cuda/include/keyswitch/keyswitch.h"
#include "cuda/include/keyswitch/ks_enums.h"

View File

@@ -1,6 +1,6 @@
[package]
name = "tfhe-hpu-backend"
version = "0.3.0"
version = "0.2.0"
edition = "2021"
license = "BSD-3-Clause-Clear"
description = "HPU implementation on FPGA of TFHE-rs primitives."
@@ -33,7 +33,7 @@ serde = { version = "1", features = ["derive"] }
toml = { version = "0.8", features = [] }
paste = "1.0.15"
thiserror = "1.0.61"
bytemuck = { workspace = true }
bytemuck = "1.16.0"
anyhow = "1.0.82"
lazy_static = "1.4.0"
rand = "0.8.5"

View File

@@ -65,12 +65,9 @@ HPU configuration knobs are gathered in a TOML configuration file. This file des
"${HPU_BACKEND_DIR}/config_store/${HPU_CONFIG}/hpu_regif_core_cfg_3in3.toml",
"${HPU_BACKEND_DIR}/config_store/${HPU_CONFIG}/hpu_regif_core_prc_1in3.toml",
"${HPU_BACKEND_DIR}/config_store/${HPU_CONFIG}/hpu_regif_core_prc_3in3.toml"]
polling_us=2
polling_us=10
[fpga.ffi.V80] # Hardware properties
id="${V80_PCIE_DEV}"
board_sn="${V80_SERIAL_NUMBER}"
hpu_path="${HPU_BACKEND_DIR}/config_store/v80_archives/psi64.hpu"
ami_path="${AMI_PATH}/ami.ko"
ami_dev="/dev/ami1" # Name of ami device
qdma_h2c="/dev/qdma${V80_PCIE_DEV}001-MM-0" # QDma host to card device
qdma_c2h="/dev/qdma${V80_PCIE_DEV}001-MM-1" # QDma card to host device
@@ -210,26 +207,11 @@ In order to run those applications on hardware, user must build from the project
> ```
``` bash
$ cargo build --release --features="hpu-v80" --example hpu_hlapi --example hpu_bench
cargo build --release --features="hpu-v80" --example hpu_hlapi --example hpu_bench
# Correctly setup environment with setup_hpu.sh script
$ source setup_hpu.sh --config v80 -p
# Source Xilinx environment (2024 or 2025 version)
$ source /opt/xilinx/Vivado/2024.2/settings64.sh
$ xsdb -eval "connect;puts [lsort -unique [regex -all -inline {( XFL[A-Z0-9]*)} [targets -target-properties]]]"
****** Xilinx hw_server v2024.2
**** Build date : Oct 29 2024 at 10:16:47
** Copyright 1986-2022 Xilinx, Inc. All Rights Reserved.
** Copyright 2022-2024 Advanced Micro Devices, Inc. All Rights Reserved.
INFO: hw_server application started
INFO: Use Ctrl-C to exit hw_server application
INFO: To connect to this hw_server instance use url: TCP:127.0.0.1:3121
{ XFL12E5XJHWLA}
$ export V80_SERIAL_NUMBER=XFL12E5XJHWL
$ ./target/release/examples/hpu_bench --integer-w 64 --integer-w 32 --iop MUL --iter 10
$ ./target/release/examples/hpu_hlapi
source setup_hpu.sh --config v80
./target/release/examples/hpu_bench --integer-w 64 --integer-w 32 --iop MUL --iter 10
./target/release/examples/hpu_hlapi
```
> NB: Error that occurred when ".hpu" files weren't correctly fetch could be a bit enigmatic: `memory allocation of ... bytes failed`
@@ -238,31 +220,6 @@ $ ./target/release/examples/hpu_hlapi
> make pull_hpu_files
> ```
> NB: tfhe-hpu-backend can only use one V80 board at this time but if you have several boards on your server you can do
> ```bash
> $ . setup_hpu.sh --config v80 -p
> getopt: option requires an argument -- 'p'
> Please select a device in following list (1st two digits):
> 24:00.1 Processing accelerators: Xilinx Corporation Device 50b5
> 61:00.1 Processing accelerators: Xilinx Corporation Device 50b5
> $ . setup_hpu.sh --config v80 -p 61
> $ source /opt/xilinx/Vivado/2024.2/settings64.sh
> # if AMI driver is loaded and AMC version running is the expected one
> $ cat /sys/module/ami/drivers/pci\:ami/0000\:61\:00.0/board_serial
> XFL1UKRD42KW
> # list serial number available on USB JTAG
> $ xsdb -eval "connect;puts [lsort -unique [regex -all -inline {( XFL[A-Z0-9]*)} [targets -target-properties]]]"
> ...
> { XFL12E5XJHWLA} { XFL1UKRD42KWA}
> $ export V80_SERIAL_NUMBER=XFL1UKRD42KW
> $ ./target/release/examples/hpu_hlapi
> ```
> NB: By default setup_hpu.sh will set AMI_PATH to something like /opt/v80/ami/e55d02d where e55d02d is the git revision of AMI driver.
> To run properly, You need to either place a compiled ami.ko from this revision in this directory or set AMI_PATH to your AVED extraction:
> ```bash
> export AMI_PATH=/home/user/AVED/sw/AMI/driver/
> ```
## Test framework
There is also a set of tests backed in tfhe-rs. Tests are gather in testbundle over various integer width.
@@ -278,7 +235,7 @@ Those tests have 5 sub-kind:
Snippets below give some example of command that could be used for testing:
``` bash
# Correctly setup environment with setup_hpu.sh script
source setup_hpu.sh --config v80 -p
source setup_hpu.sh --config v80 --init-qdma
# Run all sub-kind for 64b integer width
cargo test --release --features="hpu-v80" --test hpu -- u64
@@ -292,7 +249,7 @@ HPU is completely integrated in tfhe benchmark system. Performances results coul
Three benchmarks could be started, through the following Makefile target for simplicity:
``` bash
# Do not forget to correctly set environment before hand
source setup_hpu.sh --config v80 -p
source setup_hpu.sh --config v80 --init-qdma
# Run hlapi benches
make test_high_level_api_hpu

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