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25 Commits

Author SHA1 Message Date
Loris
03635afa8f toolchain changed 2024-05-16 11:36:40 +02:00
J-B Orfila
4c659b5c70 Artifacts CCS2024 2024-04-23 11:00:00 +02:00
Arthur Meyre
b80e09f9d2 chore(tfhe): bump version 2024-02-29 09:28:28 +01:00
Arthur Meyre
aae5b45047 chore(tfhe): update toolchain to avoid SIMD breakage, fix lints 2024-02-29 09:28:28 +01:00
tmontaigu
c0240af4ca chore(integer): use Arc<ServerKey> for executor
The goal is to avoid holding the key twice in memory
when both the executor and the test case needs the key
2024-02-28 14:59:13 +01:00
Arthur Meyre
0578c2ab1d chore(ci): fix doctest by using parameters with enough precision 2024-02-28 14:59:13 +01:00
Arthur Meyre
d1abdc081d chore(ci): fix test runs by moving panic to its own test file
- investigate what goes wrong in the panic hook leading to multiple use of
the same object from the js side
2024-02-28 14:59:13 +01:00
Arthur Meyre
44ff195704 chore(tfhe): bump version to 0.4.3 2024-02-28 14:59:13 +01:00
Arthur Meyre
1fb65f1f6e fix(shortint): use proper noise value during compact list encryption 2024-02-28 14:59:13 +01:00
Arthur Meyre
e1f54981bf chore(tfhe): pin bytemuck to avoid nightly stdsimd breakage 2024-02-28 14:59:13 +01:00
Arthur Meyre
621cbcb14a chore(doc): correct some typos and wrong phrasing on data migration 2024-01-24 19:46:00 +01:00
Arthur Meyre
0898268733 chore(tfhe): bump version to 0.4.2 2024-01-23 19:48:36 +01:00
Arthur Meyre
6ec7f7e405 feat(forward_compatibility): add code to upgrade to TFHE-rs 0.5
- add tfhe-c-api-dynamic-buffer to be able to work with 0.5 buffers
- add a script to symlink the dependency lib to a fixed name
- the rust build system adds a fingerprint to the lib name which is not
practical when we are linking our C test executable
- link the most recent artifacts corresponding to the dependency we have
2024-01-23 19:48:36 +01:00
tmontaigu
16ad67ace3 chore(wasm): update dependencies of wasm tests 2024-01-23 19:48:36 +01:00
Arthur Meyre
c949256323 doc(data_migration): add documentation on how to migrate data for TFHE-rs
co-authored-by: jborfila
2024-01-22 13:43:10 +01:00
Arthur Meyre
7ae5f65909 feat(boolean): add raw parts methods to the ClientKey
- into_raw_parts allows to deconstruct a ClientKey
- new_from_raw_parts allows to construct a ClientKey
2024-01-08 17:17:27 +01:00
Arthur Meyre
4a2e9e5064 chore(c_api): add the c_api code from the docs as a test 2024-01-03 14:26:57 +01:00
Arthur Meyre
3ae27e79d0 doc(c_api): Add an output for the users compiling the C API example 2024-01-03 14:26:57 +01:00
tmontaigu
2332f89aa0 docs(capi): fix C API example 2024-01-03 14:26:57 +01:00
Arthur Meyre
3f9603a75c chore(ci): fix trivium clippy target 2023-11-28 19:23:29 +01:00
Arthur Meyre
848cc37300 chore(ci): update Makefile for semver trick 2023-11-28 19:23:29 +01:00
tmontaigu
2f4d00b13a chore(tfhe): bump version to 0.4.1 2023-10-23 15:00:39 +02:00
tmontaigu
2f295ea467 fix(integer): fix unsigned_overflowing_sub on trivials
unsigned_overflowing_sub does an independant subtraction
on each blocks with a correcting term being added to avoid
trashing the padding bit (lhs - rhs + correction).

The correction depended on rhs's degree.
e.g. if rhs's degree was in range 1..(msg_mod-1) -> correction =
     msg_mod

However if rhs's degree was zero (so rhs is a trivial 0), the correction
was also 0, however the borrow propagation rely on that correction to
always be added.
2023-10-23 15:00:39 +02:00
tmontaigu
fa54a02c01 chore(ci): set node version 2023-10-23 15:00:39 +02:00
tmontaigu
646b644728 chore(ci): tell nvm to use node version 20 in wasm parallel tests 2023-10-23 15:00:39 +02:00
1084 changed files with 52935 additions and 152937 deletions

View File

@@ -1,6 +1,6 @@
---
name: Bug report
about: Report a problem with TFHE-rs
about: Report a problem with concrete
title: ''
labels: triage_required
assignees: ''

View File

@@ -1,6 +1,6 @@
---
name: Feature request
about: Suggest an idea for TFHE-rs
about: Suggest an idea for concrete
title: ''
labels: feature_request
assignees: ''

View File

@@ -1,9 +0,0 @@
self-hosted-runner:
# Labels of self-hosted runner in array of strings.
labels:
- m1mac
- 4090-desktop
# 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.
config-variables: null

View File

@@ -1,34 +0,0 @@
# Manage approved label in pull request
name: PR approved label manager
on:
pull_request:
pull_request_review:
types: [submitted]
jobs:
trigger-tests:
runs-on: ubuntu-latest
permissions:
pull-requests: write
steps:
- name: Get current labels
uses: snnaplab/get-labels-action@f426df40304808ace3b5282d4f036515f7609576
# Remove label if a push is performed after an approval
- name: Remove approved label
if: ${{ github.event_name == 'pull_request' && contains(fromJSON(env.LABELS), 'approved') }}
uses: actions-ecosystem/action-remove-labels@2ce5d41b4b6aa8503e285553f75ed56e0a40bae0
with:
# We use a PAT to have the same user (zama-bot) for label deletion as for creation.
github_token: ${{ secrets.FHE_ACTIONS_TOKEN }}
labels: approved
# Add label only if the review is approved and if the label doesn't already exist
- name: Add approved label
uses: actions-ecosystem/action-add-labels@18f1af5e3544586314bbe15c0273249c770b2daf
if: ${{ github.event_name == 'pull_request_review' && github.event.review.state == 'approved' && !contains(fromJSON(env.LABELS), 'approved') }}
with:
# We need to use a PAT to be able to trigger `labeled` event for the other workflow.
github_token: ${{ secrets.FHE_ACTIONS_TOKEN }}
labels: approved

View File

@@ -5,64 +5,71 @@ env:
CARGO_TERM_COLOR: always
ACTION_RUN_URL: ${{ github.server_url }}/${{ github.repository }}/actions/runs/${{ github.run_id }}
RUSTFLAGS: "-C target-cpu=native"
RUST_BACKTRACE: "full"
RUST_MIN_STACK: "8388608"
SLACK_CHANNEL: ${{ secrets.SLACK_CHANNEL }}
SLACK_ICON: https://pbs.twimg.com/profile_images/1274014582265298945/OjBKP9kn_400x400.png
SLACK_USERNAME: ${{ secrets.BOT_USERNAME }}
SLACK_WEBHOOK: ${{ secrets.SLACK_WEBHOOK }}
on:
# Allows you to run this workflow manually from the Actions tab as an alternative.
workflow_dispatch:
pull_request:
# All the inputs are provided by Slab
inputs:
instance_id:
description: "AWS instance ID"
type: string
instance_image_id:
description: "AWS instance AMI ID"
type: string
instance_type:
description: "AWS instance product type"
type: string
runner_name:
description: "Action runner name"
type: string
request_id:
description: 'Slab request ID'
type: string
fork_repo:
description: 'Name of forked repo as user/repo'
type: string
fork_git_sha:
description: 'Git SHA to checkout from fork'
type: string
jobs:
setup-ec2:
name: Setup EC2 instance (fast-tests)
runs-on: ubuntu-latest
outputs:
runner-name: ${{ steps.start-instance.outputs.label }}
steps:
- name: Start instance
id: start-instance
uses: zama-ai/slab-github-runner@1dced74825027fe3d481392163ed8fc56813fb5d
with:
mode: start
github-token: ${{ secrets.SLAB_ACTION_TOKEN }}
slab-url: ${{ secrets.SLAB_BASE_URL }}
job-secret: ${{ secrets.JOB_SECRET }}
backend: aws
profile: cpu-big
fast-tests:
name: Fast CPU tests
needs: setup-ec2
concurrency:
group: ${{ github.workflow }}_${{ github.ref }}
group: ${{ github.workflow }}_${{ github.ref }}_${{ inputs.instance_image_id }}_${{ inputs.instance_type }}
cancel-in-progress: true
runs-on: ${{ needs.setup-ec2.outputs.runner-name }}
runs-on: ${{ inputs.runner_name }}
steps:
# Step used for log purpose.
- name: Instance configuration used
run: |
echo "ID: ${{ inputs.instance_id }}"
echo "AMI: ${{ inputs.instance_image_id }}"
echo "Type: ${{ inputs.instance_type }}"
echo "Request ID: ${{ inputs.request_id }}"
echo "Fork repo: ${{ inputs.fork_repo }}"
echo "Fork git sha: ${{ inputs.fork_git_sha }}"
- name: Checkout tfhe-rs
uses: actions/checkout@9bb56186c3b09b4f86b1c65136769dd318469633
uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608
with:
repository: ${{ inputs.fork_repo }}
ref: ${{ inputs.fork_git_sha }}
- name: Set up home
run: |
echo "HOME=/home/ubuntu" >> "${GITHUB_ENV}"
- name: Install latest stable
uses: dtolnay/rust-toolchain@dc6353516c68da0f06325f42ad880f76a5e77ec9
uses: actions-rs/toolchain@16499b5e05bf2e26879000db0c1d13f7e13fa3af
with:
toolchain: stable
default: true
- name: Run concrete-csprng tests
run: |
make test_concrete_csprng
- name: Run tfhe-zk-pok tests
run: |
make test_zk_pok
- name: Run core tests
run: |
AVX512_SUPPORT=ON make test_core_crypto
@@ -107,34 +114,18 @@ jobs:
run: |
make test_safe_deserialization
- name: Run forward compatibility tests
run: |
make test_forward_compatibility
- name: Slack Notification
if: ${{ always() }}
continue-on-error: true
uses: rtCamp/action-slack-notify@4e5fb42d249be6a45a298f3c9543b111b02f7907
uses: rtCamp/action-slack-notify@b24d75fe0e728a4bf9fc42ee217caa686d141ee8
env:
SLACK_COLOR: ${{ job.status }}
SLACK_CHANNEL: ${{ secrets.SLACK_CHANNEL }}
SLACK_ICON: https://pbs.twimg.com/profile_images/1274014582265298945/OjBKP9kn_400x400.png
SLACK_MESSAGE: "Fast AWS tests finished with status: ${{ job.status }}. (${{ env.ACTION_RUN_URL }})"
teardown-ec2:
name: Teardown EC2 instance (fast-tests)
if: ${{ always() && needs.setup-ec2.result != 'skipped' }}
needs: [ setup-ec2, fast-tests ]
runs-on: ubuntu-latest
steps:
- name: Stop instance
id: stop-instance
uses: zama-ai/slab-github-runner@1dced74825027fe3d481392163ed8fc56813fb5d
with:
mode: stop
github-token: ${{ secrets.SLAB_ACTION_TOKEN }}
slab-url: ${{ secrets.SLAB_BASE_URL }}
job-secret: ${{ secrets.JOB_SECRET }}
label: ${{ needs.setup-ec2.outputs.runner-name }}
- name: Slack Notification
if: ${{ failure() }}
continue-on-error: true
uses: rtCamp/action-slack-notify@4e5fb42d249be6a45a298f3c9543b111b02f7907
env:
SLACK_COLOR: ${{ job.status }}
SLACK_MESSAGE: "EC2 teardown (fast-tests) finished with status: ${{ job.status }}. (${{ env.ACTION_RUN_URL }})"
SLACK_USERNAME: ${{ secrets.BOT_USERNAME }}
SLACK_WEBHOOK: ${{ secrets.SLACK_WEBHOOK }}

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@@ -1,75 +0,0 @@
# Compile and test tfhe-cuda-backend on an RTX 4090 machine
name: TFHE Cuda Backend - 4090 full tests
env:
CARGO_TERM_COLOR: always
ACTION_RUN_URL: ${{ github.server_url }}/${{ github.repository }}/actions/runs/${{ github.run_id }}
RUSTFLAGS: "-C target-cpu=native"
RUST_BACKTRACE: "full"
RUST_MIN_STACK: "8388608"
SLACK_CHANNEL: ${{ secrets.SLACK_CHANNEL }}
SLACK_ICON: https://pbs.twimg.com/profile_images/1274014582265298945/OjBKP9kn_400x400.png
SLACK_USERNAME: ${{ secrets.BOT_USERNAME }}
SLACK_WEBHOOK: ${{ secrets.SLACK_WEBHOOK }}
on:
# Allows you to run this workflow manually from the Actions tab as an alternative.
workflow_dispatch:
pull_request:
types: [labeled]
jobs:
cuda-tests-linux:
name: CUDA tests (RTX 4090)
if: ${{ github.event_name == 'workflow_dispatch' || contains(github.event.label.name, '4090_test') }}
concurrency:
group: ${{ github.workflow }}_${{ github.ref }}
cancel-in-progress: true
runs-on: ["self-hosted", "4090-desktop"]
steps:
- name: Checkout tfhe-rs
uses: actions/checkout@9bb56186c3b09b4f86b1c65136769dd318469633
- name: Install latest stable
uses: dtolnay/rust-toolchain@dc6353516c68da0f06325f42ad880f76a5e77ec9
with:
toolchain: stable
- name: Run fmt checks
run: |
make check_fmt_gpu
- name: Run clippy checks
run: |
make pcc_gpu
- name: Run core crypto, integer and internal CUDA backend tests
run: |
make test_gpu
- name: Run user docs tests
run: |
make test_user_doc_gpu
- name: Test C API
run: |
make test_c_api_gpu
- name: Run High Level API Tests
run: |
make test_high_level_api_gpu
- uses: actions-ecosystem/action-remove-labels@2ce5d41b4b6aa8503e285553f75ed56e0a40bae0
if: ${{ always() && github.event_name == 'pull_request' }}
with:
labels: 4090_test
github_token: ${{ secrets.GITHUB_TOKEN }}
- name: Slack Notification
if: ${{ always() }}
continue-on-error: true
uses: rtCamp/action-slack-notify@4e5fb42d249be6a45a298f3c9543b111b02f7907
env:
SLACK_COLOR: ${{ job.status }}
SLACK_MESSAGE: "CUDA RTX 4090 tests finished with status: ${{ job.status }}. (${{ env.ACTION_RUN_URL }})"

View File

@@ -1,142 +0,0 @@
# Compile and test tfhe-cuda-backend on an AWS instance
name: TFHE Cuda Backend - Full tests
env:
CARGO_TERM_COLOR: always
ACTION_RUN_URL: ${{ github.server_url }}/${{ github.repository }}/actions/runs/${{ github.run_id }}
RUSTFLAGS: "-C target-cpu=native"
RUST_BACKTRACE: "full"
RUST_MIN_STACK: "8388608"
SLACK_CHANNEL: ${{ secrets.SLACK_CHANNEL }}
SLACK_ICON: https://pbs.twimg.com/profile_images/1274014582265298945/OjBKP9kn_400x400.png
SLACK_USERNAME: ${{ secrets.BOT_USERNAME }}
SLACK_WEBHOOK: ${{ secrets.SLACK_WEBHOOK }}
on:
# Allows you to run this workflow manually from the Actions tab as an alternative.
workflow_dispatch:
pull_request:
jobs:
setup-ec2:
name: Setup EC2 instance (cuda-tests)
runs-on: ubuntu-latest
outputs:
runner-name: ${{ steps.start-instance.outputs.label }}
steps:
- name: Start instance
id: start-instance
uses: zama-ai/slab-github-runner@1dced74825027fe3d481392163ed8fc56813fb5d
with:
mode: start
github-token: ${{ secrets.SLAB_ACTION_TOKEN }}
slab-url: ${{ secrets.SLAB_BASE_URL_PRE_PROD }}
job-secret: ${{ secrets.JOB_SECRET }}
backend: aws
profile: gpu-test
cuda-tests-linux:
name: CUDA tests
needs: setup-ec2
concurrency:
group: ${{ github.workflow }}_${{ github.ref }}
cancel-in-progress: ${{ github.ref != 'refs/heads/main' }}
runs-on: ${{ needs.setup-ec2.outputs.runner-name }}
strategy:
fail-fast: false
# explicit include-based build matrix, of known valid options
matrix:
include:
- os: ubuntu-22.04
cuda: "12.2"
gcc: 9
env:
CUDA_PATH: /usr/local/cuda-${{ matrix.cuda }}
steps:
- name: Checkout tfhe-rs
uses: actions/checkout@9bb56186c3b09b4f86b1c65136769dd318469633
- name: Set up home
run: |
echo "HOME=/home/ubuntu" >> "${GITHUB_ENV}"
- name: Install latest stable
uses: dtolnay/rust-toolchain@be73d7920c329f220ce78e0234b8f96b7ae60248
with:
toolchain: stable
- name: Export CUDA variables
if: ${{ !cancelled() }}
run: |
echo "CUDA_PATH=$CUDA_PATH" >> "${GITHUB_ENV}"
echo "$CUDA_PATH/bin" >> "${GITHUB_PATH}"
echo "LD_LIBRARY_PATH=$CUDA_PATH/lib:$LD_LIBRARY_PATH" >> "${GITHUB_ENV}"
echo "CUDACXX=/usr/local/cuda-${{ matrix.cuda }}/bin/nvcc" >> "${GITHUB_ENV}"
# Specify the correct host compilers
- name: Export gcc and g++ variables
if: ${{ !cancelled() }}
run: |
{
echo "CC=/usr/bin/gcc-${{ matrix.gcc }}";
echo "CXX=/usr/bin/g++-${{ matrix.gcc }}";
echo "CUDAHOSTCXX=/usr/bin/g++-${{ matrix.gcc }}";
echo "HOME=/home/ubuntu";
} >> "${GITHUB_ENV}"
- name: Run fmt checks
run: |
make check_fmt_gpu
- name: Run clippy checks
run: |
make pcc_gpu
- name: Run core crypto, integer and internal CUDA backend tests
run: |
make test_gpu
- name: Run user docs tests
run: |
make test_user_doc_gpu
- name: Test C API
run: |
make test_c_api_gpu
- name: Run High Level API Tests
run: |
make test_high_level_api_gpu
- name: Slack Notification
if: ${{ always() }}
continue-on-error: true
uses: rtCamp/action-slack-notify@4e5fb42d249be6a45a298f3c9543b111b02f7907
env:
SLACK_COLOR: ${{ job.status }}
SLACK_MESSAGE: "CUDA AWS tests finished with status: ${{ job.status }}. (${{ env.ACTION_RUN_URL }})"
teardown-ec2:
name: Teardown EC2 instance (cuda-tests)
if: ${{ always() && needs.setup-ec2.result != 'skipped' }}
needs: [ setup-ec2, cuda-tests-linux ]
runs-on: ubuntu-latest
steps:
- name: Stop instance
id: stop-instance
uses: zama-ai/slab-github-runner@1dced74825027fe3d481392163ed8fc56813fb5d
with:
mode: stop
github-token: ${{ secrets.SLAB_ACTION_TOKEN }}
slab-url: ${{ secrets.SLAB_BASE_URL_PRE_PROD }}
job-secret: ${{ secrets.JOB_SECRET }}
label: ${{ needs.setup-ec2.outputs.runner-name }}
- name: Slack Notification
if: ${{ failure() }}
continue-on-error: true
uses: rtCamp/action-slack-notify@4e5fb42d249be6a45a298f3c9543b111b02f7907
env:
SLACK_COLOR: ${{ job.status }}
SLACK_MESSAGE: "EC2 teardown (cuda-tests) finished with status: ${{ job.status }}. (${{ env.ACTION_RUN_URL }})"

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@@ -1,105 +1,86 @@
name: AWS Unsigned Integer Tests on CPU
name: AWS Integer Tests on CPU
env:
CARGO_TERM_COLOR: always
ACTION_RUN_URL: ${{ github.server_url }}/${{ github.repository }}/actions/runs/${{ github.run_id }}
RUSTFLAGS: "-C target-cpu=native"
RUST_BACKTRACE: "full"
RUST_MIN_STACK: "8388608"
SLACK_CHANNEL: ${{ secrets.SLACK_CHANNEL }}
SLACK_ICON: https://pbs.twimg.com/profile_images/1274014582265298945/OjBKP9kn_400x400.png
SLACK_USERNAME: ${{ secrets.BOT_USERNAME }}
SLACK_WEBHOOK: ${{ secrets.SLACK_WEBHOOK }}
on:
# Allows you to run this workflow manually from the Actions tab as an alternative.
workflow_dispatch:
pull_request:
types: [ labeled ]
# All the inputs are provided by Slab
inputs:
instance_id:
description: "AWS instance ID"
type: string
instance_image_id:
description: "AWS instance AMI ID"
type: string
instance_type:
description: "AWS instance product type"
type: string
runner_name:
description: "Action runner name"
type: string
request_id:
description: 'Slab request ID'
type: string
fork_repo:
description: 'Name of forked repo as user/repo'
type: string
fork_git_sha:
description: 'Git SHA to checkout from fork'
type: string
jobs:
setup-ec2:
name: Setup EC2 instance (unsigned-integer-tests)
if: ${{ github.event_name == 'workflow_dispatch' || contains(github.event.label.name, 'approved') }}
runs-on: ubuntu-latest
outputs:
runner-name: ${{ steps.start-instance.outputs.label }}
steps:
- name: Start instance
id: start-instance
uses: zama-ai/slab-github-runner@1dced74825027fe3d481392163ed8fc56813fb5d
with:
mode: start
github-token: ${{ secrets.SLAB_ACTION_TOKEN }}
slab-url: ${{ secrets.SLAB_BASE_URL }}
job-secret: ${{ secrets.JOB_SECRET }}
backend: aws
profile: cpu-big
unsigned-integer-tests:
name: Unsigned integer tests
needs: setup-ec2
integer-tests:
concurrency:
group: ${{ github.workflow }}_${{ github.ref }}
group: ${{ github.workflow }}_${{ github.ref }}_${{ inputs.instance_image_id }}_${{ inputs.instance_type }}
cancel-in-progress: true
runs-on: ${{ needs.setup-ec2.outputs.runner-name }}
runs-on: ${{ inputs.runner_name }}
steps:
# Step used for log purpose.
- name: Instance configuration used
run: |
echo "ID: ${{ inputs.instance_id }}"
echo "AMI: ${{ inputs.instance_image_id }}"
echo "Type: ${{ inputs.instance_type }}"
echo "Request ID: ${{ inputs.request_id }}"
echo "Fork repo: ${{ inputs.fork_repo }}"
echo "Fork git sha: ${{ inputs.fork_git_sha }}"
- name: Checkout tfhe-rs
uses: actions/checkout@9bb56186c3b09b4f86b1c65136769dd318469633
uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608
with:
repository: ${{ inputs.fork_repo }}
ref: ${{ inputs.fork_git_sha }}
- name: Set up home
run: |
echo "HOME=/home/ubuntu" >> "${GITHUB_ENV}"
- name: Install latest stable
uses: dtolnay/rust-toolchain@dc6353516c68da0f06325f42ad880f76a5e77ec9
uses: actions-rs/toolchain@16499b5e05bf2e26879000db0c1d13f7e13fa3af
with:
toolchain: stable
- name: Gen Keys if required
run: |
make GEN_KEY_CACHE_MULTI_BIT_ONLY=TRUE gen_key_cache
- name: Run unsigned integer multi-bit tests
run: |
AVX512_SUPPORT=ON make test_unsigned_integer_multi_bit_ci
default: true
- name: Gen Keys if required
run: |
make gen_key_cache
- name: Run unsigned integer tests
- name: Run integer tests
run: |
AVX512_SUPPORT=ON BIG_TESTS_INSTANCE=TRUE make test_unsigned_integer_ci
BIG_TESTS_INSTANCE=TRUE make test_integer_ci
- name: Slack Notification
if: ${{ always() }}
continue-on-error: true
uses: rtCamp/action-slack-notify@4e5fb42d249be6a45a298f3c9543b111b02f7907
uses: rtCamp/action-slack-notify@b24d75fe0e728a4bf9fc42ee217caa686d141ee8
env:
SLACK_COLOR: ${{ job.status }}
SLACK_MESSAGE: "Unsigned Integer tests finished with status: ${{ job.status }}. (${{ env.ACTION_RUN_URL }})"
teardown-ec2:
name: Teardown EC2 instance (unsigned-integer-tests)
if: ${{ always() && needs.setup-ec2.result != 'skipped' }}
needs: [ setup-ec2, unsigned-integer-tests ]
runs-on: ubuntu-latest
steps:
- name: Stop instance
id: stop-instance
uses: zama-ai/slab-github-runner@1dced74825027fe3d481392163ed8fc56813fb5d
with:
mode: stop
github-token: ${{ secrets.SLAB_ACTION_TOKEN }}
slab-url: ${{ secrets.SLAB_BASE_URL }}
job-secret: ${{ secrets.JOB_SECRET }}
label: ${{ needs.setup-ec2.outputs.runner-name }}
- name: Slack Notification
if: ${{ failure() }}
continue-on-error: true
uses: rtCamp/action-slack-notify@4e5fb42d249be6a45a298f3c9543b111b02f7907
env:
SLACK_COLOR: ${{ job.status }}
SLACK_MESSAGE: "EC2 teardown (unsigned-integer-tests) finished with status: ${{ job.status }}. (${{ env.ACTION_RUN_URL }})"
SLACK_CHANNEL: ${{ secrets.SLACK_CHANNEL }}
SLACK_ICON: https://pbs.twimg.com/profile_images/1274014582265298945/OjBKP9kn_400x400.png
SLACK_MESSAGE: "Integer tests finished with status: ${{ job.status }}. (${{ env.ACTION_RUN_URL }})"
SLACK_USERNAME: ${{ secrets.BOT_USERNAME }}
SLACK_WEBHOOK: ${{ secrets.SLACK_WEBHOOK }}

View File

@@ -0,0 +1,90 @@
name: AWS Multi Bit Tests on CPU
env:
CARGO_TERM_COLOR: always
ACTION_RUN_URL: ${{ github.server_url }}/${{ github.repository }}/actions/runs/${{ github.run_id }}
RUSTFLAGS: "-C target-cpu=native"
on:
# Allows you to run this workflow manually from the Actions tab as an alternative.
workflow_dispatch:
# All the inputs are provided by Slab
inputs:
instance_id:
description: "AWS instance ID"
type: string
instance_image_id:
description: "AWS instance AMI ID"
type: string
instance_type:
description: "AWS instance product type"
type: string
runner_name:
description: "Action runner name"
type: string
request_id:
description: 'Slab request ID'
type: string
fork_repo:
description: 'Name of forked repo as user/repo'
type: string
fork_git_sha:
description: 'Git SHA to checkout from fork'
type: string
jobs:
multi-bit-tests:
concurrency:
group: ${{ github.workflow }}_${{ github.ref }}_${{ inputs.instance_image_id }}_${{ inputs.instance_type }}
cancel-in-progress: true
runs-on: ${{ inputs.runner_name }}
steps:
# Step used for log purpose.
- name: Instance configuration used
run: |
echo "ID: ${{ inputs.instance_id }}"
echo "AMI: ${{ inputs.instance_image_id }}"
echo "Type: ${{ inputs.instance_type }}"
echo "Request ID: ${{ inputs.request_id }}"
echo "Fork repo: ${{ inputs.fork_repo }}"
echo "Fork git sha: ${{ inputs.fork_git_sha }}"
- name: Checkout tfhe-rs
uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608
with:
repository: ${{ inputs.fork_repo }}
ref: ${{ inputs.fork_git_sha }}
- name: Set up home
run: |
echo "HOME=/home/ubuntu" >> "${GITHUB_ENV}"
- name: Install latest stable
uses: actions-rs/toolchain@16499b5e05bf2e26879000db0c1d13f7e13fa3af
with:
toolchain: stable
default: true
- name: Gen Keys if required
run: |
make GEN_KEY_CACHE_MULTI_BIT_ONLY=TRUE gen_key_cache
- name: Run shortint multi-bit tests
run: |
make test_shortint_multi_bit_ci
- name: Run integer multi-bit tests
run: |
make test_integer_multi_bit_ci
- name: Slack Notification
if: ${{ always() }}
continue-on-error: true
uses: rtCamp/action-slack-notify@b24d75fe0e728a4bf9fc42ee217caa686d141ee8
env:
SLACK_COLOR: ${{ job.status }}
SLACK_CHANNEL: ${{ secrets.SLACK_CHANNEL }}
SLACK_ICON: https://pbs.twimg.com/profile_images/1274014582265298945/OjBKP9kn_400x400.png
SLACK_MESSAGE: "Shortint tests finished with status: ${{ job.status }}. (${{ env.ACTION_RUN_URL }})"
SLACK_USERNAME: ${{ secrets.BOT_USERNAME }}
SLACK_WEBHOOK: ${{ secrets.SLACK_WEBHOOK }}

View File

@@ -1,109 +0,0 @@
name: AWS Signed Integer Tests on CPU
env:
CARGO_TERM_COLOR: always
ACTION_RUN_URL: ${{ github.server_url }}/${{ github.repository }}/actions/runs/${{ github.run_id }}
RUSTFLAGS: "-C target-cpu=native"
RUST_BACKTRACE: "full"
RUST_MIN_STACK: "8388608"
SLACK_CHANNEL: ${{ secrets.SLACK_CHANNEL }}
SLACK_ICON: https://pbs.twimg.com/profile_images/1274014582265298945/OjBKP9kn_400x400.png
SLACK_USERNAME: ${{ secrets.BOT_USERNAME }}
SLACK_WEBHOOK: ${{ secrets.SLACK_WEBHOOK }}
on:
# Allows you to run this workflow manually from the Actions tab as an alternative.
workflow_dispatch:
pull_request:
types: [ labeled ]
jobs:
setup-ec2:
name: Setup EC2 instance (signed-integer-tests)
if: ${{ github.event_name == 'workflow_dispatch' || contains(github.event.label.name, 'approved') }}
runs-on: ubuntu-latest
outputs:
runner-name: ${{ steps.start-instance.outputs.label }}
steps:
- name: Start instance
id: start-instance
uses: zama-ai/slab-github-runner@1dced74825027fe3d481392163ed8fc56813fb5d
with:
mode: start
github-token: ${{ secrets.SLAB_ACTION_TOKEN }}
slab-url: ${{ secrets.SLAB_BASE_URL }}
job-secret: ${{ secrets.JOB_SECRET }}
backend: aws
profile: cpu-big
signed-integer-tests:
name: Signed integer tests
needs: setup-ec2
concurrency:
group: ${{ github.workflow }}_${{ github.ref }}
cancel-in-progress: true
runs-on: ${{ needs.setup-ec2.outputs.runner-name }}
steps:
- name: Checkout tfhe-rs
uses: actions/checkout@9bb56186c3b09b4f86b1c65136769dd318469633
- name: Set up home
run: |
echo "HOME=/home/ubuntu" >> "${GITHUB_ENV}"
- name: Install latest stable
uses: dtolnay/rust-toolchain@dc6353516c68da0f06325f42ad880f76a5e77ec9
with:
toolchain: stable
- name: Gen Keys if required
run: |
make GEN_KEY_CACHE_MULTI_BIT_ONLY=TRUE gen_key_cache
- name: Run shortint multi-bit tests
run: |
make test_shortint_multi_bit_ci
- name: Run signed integer multi-bit tests
run: |
AVX512_SUPPORT=ON make test_signed_integer_multi_bit_ci
- name: Gen Keys if required
run: |
make gen_key_cache
- name: Run signed integer tests
run: |
AVX512_SUPPORT=ON BIG_TESTS_INSTANCE=TRUE make test_signed_integer_ci
- name: Slack Notification
if: ${{ always() }}
continue-on-error: true
uses: rtCamp/action-slack-notify@4e5fb42d249be6a45a298f3c9543b111b02f7907
env:
SLACK_COLOR: ${{ job.status }}
SLACK_MESSAGE: "Signed Integer tests finished with status: ${{ job.status }}. (${{ env.ACTION_RUN_URL }})"
teardown-ec2:
name: Teardown EC2 instance (signed-integer-tests)
if: ${{ always() && needs.setup-ec2.result != 'skipped' }}
needs: [ setup-ec2, signed-integer-tests ]
runs-on: ubuntu-latest
steps:
- name: Stop instance
id: stop-instance
uses: zama-ai/slab-github-runner@1dced74825027fe3d481392163ed8fc56813fb5d
with:
mode: stop
github-token: ${{ secrets.SLAB_ACTION_TOKEN }}
slab-url: ${{ secrets.SLAB_BASE_URL }}
job-secret: ${{ secrets.JOB_SECRET }}
label: ${{ needs.setup-ec2.outputs.runner-name }}
- name: Slack Notification
if: ${{ failure() }}
continue-on-error: true
uses: rtCamp/action-slack-notify@4e5fb42d249be6a45a298f3c9543b111b02f7907
env:
SLACK_COLOR: ${{ job.status }}
SLACK_MESSAGE: "EC2 teardown (signed-integer-tests) finished with status: ${{ job.status }}. (${{ env.ACTION_RUN_URL }})"

View File

@@ -4,66 +4,71 @@ env:
CARGO_TERM_COLOR: always
ACTION_RUN_URL: ${{ github.server_url }}/${{ github.repository }}/actions/runs/${{ github.run_id }}
RUSTFLAGS: "-C target-cpu=native"
RUST_BACKTRACE: "full"
RUST_MIN_STACK: "8388608"
SLACK_CHANNEL: ${{ secrets.SLACK_CHANNEL }}
SLACK_ICON: https://pbs.twimg.com/profile_images/1274014582265298945/OjBKP9kn_400x400.png
SLACK_USERNAME: ${{ secrets.BOT_USERNAME }}
SLACK_WEBHOOK: ${{ secrets.SLACK_WEBHOOK }}
on:
# Allows you to run this workflow manually from the Actions tab as an alternative.
workflow_dispatch:
pull_request:
types: [ labeled ]
# All the inputs are provided by Slab
inputs:
instance_id:
description: "AWS instance ID"
type: string
instance_image_id:
description: "AWS instance AMI ID"
type: string
instance_type:
description: "AWS instance product type"
type: string
runner_name:
description: "Action runner name"
type: string
request_id:
description: 'Slab request ID'
type: string
fork_repo:
description: 'Name of forked repo as user/repo'
type: string
fork_git_sha:
description: 'Git SHA to checkout from fork'
type: string
jobs:
setup-ec2:
name: Setup EC2 instance (cpu-tests)
if: ${{ github.event_name == 'workflow_dispatch' || contains(github.event.label.name, 'approved') }}
runs-on: ubuntu-latest
outputs:
runner-name: ${{ steps.start-instance.outputs.label }}
steps:
- name: Start instance
id: start-instance
uses: zama-ai/slab-github-runner@1dced74825027fe3d481392163ed8fc56813fb5d
with:
mode: start
github-token: ${{ secrets.SLAB_ACTION_TOKEN }}
slab-url: ${{ secrets.SLAB_BASE_URL }}
job-secret: ${{ secrets.JOB_SECRET }}
backend: aws
profile: cpu-big
cpu-tests:
name: CPU tests
needs: setup-ec2
shortint-tests:
concurrency:
group: ${{ github.workflow }}_${{ github.ref }}
group: ${{ github.workflow }}_${{ github.ref }}_${{ inputs.instance_image_id }}_${{ inputs.instance_type }}
cancel-in-progress: true
runs-on: ${{ needs.setup-ec2.outputs.runner-name }}
runs-on: ${{ inputs.runner_name }}
steps:
# Step used for log purpose.
- name: Instance configuration used
run: |
echo "ID: ${{ inputs.instance_id }}"
echo "AMI: ${{ inputs.instance_image_id }}"
echo "Type: ${{ inputs.instance_type }}"
echo "Request ID: ${{ inputs.request_id }}"
echo "Fork repo: ${{ inputs.fork_repo }}"
echo "Fork git sha: ${{ inputs.fork_git_sha }}"
- name: Checkout tfhe-rs
uses: actions/checkout@9bb56186c3b09b4f86b1c65136769dd318469633
uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608
with:
repository: ${{ inputs.fork_repo }}
ref: ${{ inputs.fork_git_sha }}
- name: Set up home
run: |
echo "HOME=/home/ubuntu" >> "${GITHUB_ENV}"
- name: Install latest stable
uses: dtolnay/rust-toolchain@dc6353516c68da0f06325f42ad880f76a5e77ec9
uses: actions-rs/toolchain@16499b5e05bf2e26879000db0c1d13f7e13fa3af
with:
toolchain: stable
default: true
- name: Run concrete-csprng tests
run: |
make test_concrete_csprng
- name: Run tfhe-zk-pok tests
run: |
make test_zk_pok
- name: Run core tests
run: |
AVX512_SUPPORT=ON make test_core_crypto
@@ -76,6 +81,10 @@ jobs:
run: |
make test_c_api
- name: Run C API tests with forward_compatibility
run: |
FORWARD_COMPAT=ON make test_c_api
- name: Run user docs tests
run: |
make test_user_doc
@@ -95,41 +104,15 @@ jobs:
- name: Run example tests
run: |
make test_examples
make dark_market
- name: Run apps tests
run: |
make test_trivium
make test_kreyvium
- name: Slack Notification
if: ${{ always() }}
continue-on-error: true
uses: rtCamp/action-slack-notify@4e5fb42d249be6a45a298f3c9543b111b02f7907
uses: rtCamp/action-slack-notify@b24d75fe0e728a4bf9fc42ee217caa686d141ee8
env:
SLACK_COLOR: ${{ job.status }}
SLACK_MESSAGE: "CPU tests finished with status: ${{ job.status }}. (${{ env.ACTION_RUN_URL }})"
teardown-ec2:
name: Teardown EC2 instance (cpu-tests)
if: ${{ always() && needs.setup-ec2.result != 'skipped' }}
needs: [ setup-ec2, cpu-tests ]
runs-on: ubuntu-latest
steps:
- name: Stop instance
id: stop-instance
uses: zama-ai/slab-github-runner@1dced74825027fe3d481392163ed8fc56813fb5d
with:
mode: stop
github-token: ${{ secrets.SLAB_ACTION_TOKEN }}
slab-url: ${{ secrets.SLAB_BASE_URL }}
job-secret: ${{ secrets.JOB_SECRET }}
label: ${{ needs.setup-ec2.outputs.runner-name }}
- name: Slack Notification
if: ${{ failure() }}
continue-on-error: true
uses: rtCamp/action-slack-notify@4e5fb42d249be6a45a298f3c9543b111b02f7907
env:
SLACK_COLOR: ${{ job.status }}
SLACK_MESSAGE: "EC2 teardown (cpu-tests) finished with status: ${{ job.status }}. (${{ env.ACTION_RUN_URL }})"
SLACK_CHANNEL: ${{ secrets.SLACK_CHANNEL }}
SLACK_ICON: https://pbs.twimg.com/profile_images/1274014582265298945/OjBKP9kn_400x400.png
SLACK_MESSAGE: "Shortint tests finished with status: ${{ job.status }}. (${{ env.ACTION_RUN_URL }})"
SLACK_USERNAME: ${{ secrets.BOT_USERNAME }}
SLACK_WEBHOOK: ${{ secrets.SLACK_WEBHOOK }}

View File

@@ -4,65 +4,66 @@ env:
CARGO_TERM_COLOR: always
ACTION_RUN_URL: ${{ github.server_url }}/${{ github.repository }}/actions/runs/${{ github.run_id }}
RUSTFLAGS: "-C target-cpu=native"
RUST_BACKTRACE: "full"
RUST_MIN_STACK: "8388608"
SLACK_CHANNEL: ${{ secrets.SLACK_CHANNEL }}
SLACK_ICON: https://pbs.twimg.com/profile_images/1274014582265298945/OjBKP9kn_400x400.png
SLACK_USERNAME: ${{ secrets.BOT_USERNAME }}
SLACK_WEBHOOK: ${{ secrets.SLACK_WEBHOOK }}
on:
# Allows you to run this workflow manually from the Actions tab as an alternative.
workflow_dispatch:
pull_request:
types: [ labeled ]
# All the inputs are provided by Slab
inputs:
instance_id:
description: "AWS instance ID"
type: string
instance_image_id:
description: "AWS instance AMI ID"
type: string
instance_type:
description: "AWS instance product type"
type: string
runner_name:
description: "Action runner name"
type: string
request_id:
description: 'Slab request ID'
type: string
fork_repo:
description: 'Name of forked repo as user/repo'
type: string
fork_git_sha:
description: 'Git SHA to checkout from fork'
type: string
jobs:
setup-ec2:
name: Setup EC2 instance (wasm-tests)
if: ${{ github.event_name == 'workflow_dispatch' || contains(github.event.label.name, 'approved') }}
runs-on: ubuntu-latest
outputs:
runner-name: ${{ steps.start-instance.outputs.label }}
steps:
- name: Start instance
id: start-instance
uses: zama-ai/slab-github-runner@1dced74825027fe3d481392163ed8fc56813fb5d
with:
mode: start
github-token: ${{ secrets.SLAB_ACTION_TOKEN }}
slab-url: ${{ secrets.SLAB_BASE_URL }}
job-secret: ${{ secrets.JOB_SECRET }}
backend: aws
profile: cpu-small
wasm-tests:
name: WASM tests
needs: setup-ec2
concurrency:
group: ${{ github.workflow }}_${{ github.ref }}
group: ${{ github.workflow }}_${{ github.ref }}_${{ inputs.instance_image_id }}_${{ inputs.instance_type }}
cancel-in-progress: true
runs-on: ${{ needs.setup-ec2.outputs.runner-name }}
runs-on: ${{ inputs.runner_name }}
steps:
# Step used for log purpose.
- name: Instance configuration used
run: |
echo "ID: ${{ inputs.instance_id }}"
echo "AMI: ${{ inputs.instance_image_id }}"
echo "Type: ${{ inputs.instance_type }}"
echo "Request ID: ${{ inputs.request_id }}"
echo "Fork repo: ${{ inputs.fork_repo }}"
echo "Fork git sha: ${{ inputs.fork_git_sha }}"
- name: Checkout tfhe-rs
uses: actions/checkout@9bb56186c3b09b4f86b1c65136769dd318469633
uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608
with:
repository: ${{ inputs.fork_repo }}
ref: ${{ inputs.fork_git_sha }}
- name: Set up home
run: |
echo "HOME=/home/ubuntu" >> "${GITHUB_ENV}"
- name: Install latest stable
uses: dtolnay/rust-toolchain@dc6353516c68da0f06325f42ad880f76a5e77ec9
uses: actions-rs/toolchain@16499b5e05bf2e26879000db0c1d13f7e13fa3af
with:
toolchain: stable
- name: Install Node
run: |
make install_node
- name: Run fmt checks
run: |
make check_fmt_js
default: true
- name: Run js on wasm API tests
run: |
@@ -70,36 +71,17 @@ jobs:
- name: Run parallel wasm tests
run: |
make install_node
make ci_test_web_js_api_parallel
- name: Slack Notification
if: ${{ always() }}
continue-on-error: true
uses: rtCamp/action-slack-notify@4e5fb42d249be6a45a298f3c9543b111b02f7907
uses: rtCamp/action-slack-notify@b24d75fe0e728a4bf9fc42ee217caa686d141ee8
env:
SLACK_COLOR: ${{ job.status }}
SLACK_CHANNEL: ${{ secrets.SLACK_CHANNEL }}
SLACK_ICON: https://pbs.twimg.com/profile_images/1274014582265298945/OjBKP9kn_400x400.png
SLACK_MESSAGE: "WASM tests finished with status: ${{ job.status }}. (${{ env.ACTION_RUN_URL }})"
teardown-ec2:
name: Teardown EC2 instance (wasm-tests)
if: ${{ always() && needs.setup-ec2.result != 'skipped' }}
needs: [ setup-ec2, wasm-tests ]
runs-on: ubuntu-latest
steps:
- name: Stop instance
id: stop-instance
uses: zama-ai/slab-github-runner@1dced74825027fe3d481392163ed8fc56813fb5d
with:
mode: stop
github-token: ${{ secrets.SLAB_ACTION_TOKEN }}
slab-url: ${{ secrets.SLAB_BASE_URL }}
job-secret: ${{ secrets.JOB_SECRET }}
label: ${{ needs.setup-ec2.outputs.runner-name }}
- name: Slack Notification
if: ${{ failure() }}
continue-on-error: true
uses: rtCamp/action-slack-notify@4e5fb42d249be6a45a298f3c9543b111b02f7907
env:
SLACK_COLOR: ${{ job.status }}
SLACK_MESSAGE: "EC2 teardown (wasm-tests) finished with status: ${{ job.status }}. (${{ env.ACTION_RUN_URL }})"
SLACK_USERNAME: ${{ secrets.BOT_USERNAME }}
SLACK_WEBHOOK: ${{ secrets.SLACK_WEBHOOK }}

View File

@@ -32,8 +32,6 @@ env:
CARGO_TERM_COLOR: always
RESULTS_FILENAME: parsed_benchmark_results_${{ github.sha }}.json
ACTION_RUN_URL: ${{ github.server_url }}/${{ github.repository }}/actions/runs/${{ github.run_id }}
RUST_BACKTRACE: "full"
RUST_MIN_STACK: "8388608"
jobs:
run-boolean-benchmarks:
@@ -53,7 +51,7 @@ jobs:
echo "BENCH_DATE=$(date --iso-8601=seconds)" >> "${GITHUB_ENV}"
- name: Checkout tfhe-rs repo with tags
uses: actions/checkout@9bb56186c3b09b4f86b1c65136769dd318469633
uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608
with:
fetch-depth: 0
@@ -63,13 +61,14 @@ jobs:
echo "HOME=/home/ubuntu" >> "${GITHUB_ENV}"
- name: Install rust
uses: dtolnay/rust-toolchain@dc6353516c68da0f06325f42ad880f76a5e77ec9
uses: actions-rs/toolchain@16499b5e05bf2e26879000db0c1d13f7e13fa3af
with:
toolchain: nightly
override: true
- name: Run benchmarks with AVX512
run: |
make bench_boolean
make AVX512_SUPPORT=ON bench_boolean
- name: Parse results
run: |
@@ -97,17 +96,17 @@ jobs:
--append-results
- name: Upload parsed results artifact
uses: actions/upload-artifact@5d5d22a31266ced268874388b861e4b58bb5c2f3
uses: actions/upload-artifact@a8a3f3ad30e3422c9c7b888a15615d19a852ae32
with:
name: ${{ github.sha }}_boolean
path: ${{ env.RESULTS_FILENAME }}
- name: Checkout Slab repo
uses: actions/checkout@9bb56186c3b09b4f86b1c65136769dd318469633
uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608
with:
repository: zama-ai/slab
path: slab
token: ${{ secrets.FHE_ACTIONS_TOKEN }}
token: ${{ secrets.CONCRETE_ACTIONS_TOKEN }}
- name: Send data to Slab
shell: bash
@@ -126,11 +125,11 @@ jobs:
- name: Slack Notification
if: ${{ failure() }}
continue-on-error: true
uses: rtCamp/action-slack-notify@4e5fb42d249be6a45a298f3c9543b111b02f7907
uses: rtCamp/action-slack-notify@b24d75fe0e728a4bf9fc42ee217caa686d141ee8
env:
SLACK_COLOR: ${{ job.status }}
SLACK_CHANNEL: ${{ secrets.SLACK_CHANNEL }}
SLACK_ICON: https://pbs.twimg.com/profile_images/1274014582265298945/OjBKP9kn_400x400.png
SLACK_MESSAGE: "Boolean benchmarks finished with status: ${{ job.status }}. (${{ env.ACTION_RUN_URL }})"
SLACK_MESSAGE: "Boolean benchmarks failed. (${{ env.ACTION_RUN_URL }})"
SLACK_USERNAME: ${{ secrets.BOT_USERNAME }}
SLACK_WEBHOOK: ${{ secrets.SLACK_WEBHOOK }}

View File

@@ -6,8 +6,6 @@ on:
env:
CARGO_TERM_COLOR: always
RUSTFLAGS: "-C target-cpu=native"
RUST_BACKTRACE: "full"
RUST_MIN_STACK: "8388608"
concurrency:
group: ${{ github.workflow }}-${{ github.head_ref }}
@@ -19,11 +17,11 @@ jobs:
strategy:
matrix:
os: [ubuntu-latest, macos-latest-large, windows-latest]
os: [ubuntu-latest, macos-latest, windows-latest]
fail-fast: false
steps:
- uses: actions/checkout@9bb56186c3b09b4f86b1c65136769dd318469633
- uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608
- name: Install and run newline linter checks
if: matrix.os == 'ubuntu-latest'
@@ -68,9 +66,5 @@ jobs:
run: |
make build_c_api
- name: Build coverage tests
run: |
make build_tfhe_coverage
# The wasm build check is a bit annoying to set-up here and is done during the tests in
# aws_tfhe_tests.yml

View File

@@ -1,27 +0,0 @@
# Lint and check CI
name: CI Lint and Checks
on:
pull_request:
env:
ACTIONLINT_VERSION: 1.6.27
jobs:
lint-check:
name: Lint and checks
runs-on: ubuntu-latest
steps:
- name: Checkout tfhe-rs
uses: actions/checkout@9bb56186c3b09b4f86b1c65136769dd318469633
- name: Get actionlint
run: |
bash <(curl https://raw.githubusercontent.com/rhysd/actionlint/main/scripts/download-actionlint.bash) ${{ env.ACTIONLINT_VERSION }}
echo "f2ee6d561ce00fa93aab62a7791c1a0396ec7e8876b2a8f2057475816c550782 actionlint" > checksum
sha256sum -c checksum
ln -s "$(pwd)/actionlint" /usr/local/bin/
- name: Lint workflows
run: |
make lint_workflow

View File

@@ -4,8 +4,6 @@ env:
CARGO_TERM_COLOR: always
ACTION_RUN_URL: ${{ github.server_url }}/${{ github.repository }}/actions/runs/${{ github.run_id }}
RUSTFLAGS: "-C target-cpu=native"
RUST_BACKTRACE: "full"
RUST_MIN_STACK: "8388608"
on:
# Allows you to run this workflow manually from the Actions tab as an alternative.
@@ -40,7 +38,6 @@ jobs:
group: ${{ github.workflow }}_${{ github.ref }}_${{ inputs.instance_image_id }}_${{ inputs.instance_type }}
cancel-in-progress: true
runs-on: ${{ inputs.runner_name }}
timeout-minutes: 11520 # 8 days
steps:
# Step used for log purpose.
- name: Instance configuration used
@@ -53,7 +50,7 @@ jobs:
echo "Fork git sha: ${{ inputs.fork_git_sha }}"
- name: Checkout tfhe-rs
uses: actions/checkout@9bb56186c3b09b4f86b1c65136769dd318469633
uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608
with:
repository: ${{ inputs.fork_repo }}
ref: ${{ inputs.fork_git_sha }}
@@ -63,13 +60,14 @@ jobs:
echo "HOME=/home/ubuntu" >> "${GITHUB_ENV}"
- name: Install latest stable
uses: dtolnay/rust-toolchain@dc6353516c68da0f06325f42ad880f76a5e77ec9
uses: actions-rs/toolchain@16499b5e05bf2e26879000db0c1d13f7e13fa3af
with:
toolchain: stable
default: true
- name: Check for file changes
id: changed-files
uses: tj-actions/changed-files@2d756ea4c53f7f6b397767d8723b3a10a9f35bf2
uses: tj-actions/changed-files@408093d9ff9c134c33b974e0722ce06b9d6e8263
with:
files_yaml: |
tfhe:
@@ -81,12 +79,6 @@ jobs:
if: steps.changed-files.outputs.tfhe_any_changed == 'true'
run: |
make GEN_KEY_CACHE_COVERAGE_ONLY=TRUE gen_key_cache
make gen_key_cache_core_crypto
- name: Run coverage for core_crypto
if: steps.changed-files.outputs.tfhe_any_changed == 'true'
run: |
make test_core_crypto_cov AVX512_SUPPORT=ON
- name: Run coverage for boolean
if: steps.changed-files.outputs.tfhe_any_changed == 'true'
@@ -99,32 +91,18 @@ jobs:
make test_shortint_cov
- name: Upload tfhe coverage to Codecov
uses: codecov/codecov-action@7afa10ed9b269c561c2336fd862446844e0cbf71
uses: codecov/codecov-action@eaaf4bedf32dbdc6b720b63067d99c4d77d6047d
if: steps.changed-files.outputs.tfhe_any_changed == 'true'
with:
token: ${{ secrets.CODECOV_TOKEN }}
directory: ./coverage/
fail_ci_if_error: true
files: shortint/cobertura.xml,boolean/cobertura.xml,core_crypto/cobertura.xml,core_crypto_avx512/cobertura.xml
- name: Run integer coverage
if: steps.changed-files.outputs.tfhe_any_changed == 'true'
run: |
make test_integer_cov
- name: Upload tfhe coverage to Codecov
uses: codecov/codecov-action@7afa10ed9b269c561c2336fd862446844e0cbf71
if: steps.changed-files.outputs.tfhe_any_changed == 'true'
with:
token: ${{ secrets.CODECOV_TOKEN }}
directory: ./coverage/
fail_ci_if_error: true
files: integer/cobertura.xml
files: shortint/cobertura.xml,boolean/cobertura.xml
- name: Slack Notification
if: ${{ failure() }}
continue-on-error: true
uses: rtCamp/action-slack-notify@4e5fb42d249be6a45a298f3c9543b111b02f7907
uses: rtCamp/action-slack-notify@b24d75fe0e728a4bf9fc42ee217caa686d141ee8
env:
SLACK_COLOR: ${{ job.status }}
SLACK_CHANNEL: ${{ secrets.SLACK_CHANNEL }}

View File

@@ -1,182 +0,0 @@
# Run core crypto benchmarks on an AWS instance with CUDA and return parsed results to Slab CI bot.
name: Core crypto GPU benchmarks
on:
# Allows you to run this workflow manually from the Actions tab as an alternative.
workflow_dispatch:
env:
CARGO_TERM_COLOR: always
RESULTS_FILENAME: parsed_benchmark_results_${{ github.sha }}.json
ACTION_RUN_URL: ${{ github.server_url }}/${{ github.repository }}/actions/runs/${{ github.run_id }}
jobs:
setup-ec2:
name: Setup EC2 instance (cuda-benchmarks)
runs-on: ubuntu-latest
outputs:
runner-name: ${{ steps.start-instance.outputs.label }}
steps:
- name: Start instance
id: start-instance
uses: zama-ai/slab-github-runner@1dced74825027fe3d481392163ed8fc56813fb5d
with:
mode: start
github-token: ${{ secrets.SLAB_ACTION_TOKEN }}
slab-url: ${{ secrets.SLAB_BASE_URL_PRE_PROD }}
job-secret: ${{ secrets.JOB_SECRET }}
backend: hyperstack
profile: gpu-bench
core-crypto-benchmarks:
name: CUDA core crypto benchmarks
needs: setup-ec2
runs-on: ${{ needs.setup-ec2.outputs.runner-name }}
strategy:
fail-fast: false
# explicit include-based build matrix, of known valid options
matrix:
include:
- os: ubuntu-22.04
cuda: "12.2"
gcc: 11
env:
CUDA_PATH: /usr/local/cuda-${{ matrix.cuda }}
CMAKE_VERSION: 3.29.1
steps:
- name: Install dependencies
run: |
sudo apt update
sudo apt install -y checkinstall zlib1g-dev libssl-dev
wget https://github.com/Kitware/CMake/releases/download/v${{ env.CMAKE_VERSION }}/cmake-${{ env.CMAKE_VERSION }}.tar.gz
tar -zxvf cmake-${{ env.CMAKE_VERSION }}.tar.gz
cd cmake-${{ env.CMAKE_VERSION }}
./bootstrap
make -j"$(nproc)"
sudo make install
- name: Get benchmark date
run: |
echo "BENCH_DATE=$(date --iso-8601=seconds)" >> "${GITHUB_ENV}"
- name: Checkout tfhe-rs repo with tags
uses: actions/checkout@9bb56186c3b09b4f86b1c65136769dd318469633
with:
fetch-depth: 0
- name: Set up home
# "Install rust" step require root user to have a HOME directory which is not set.
run: |
echo "HOME=/home/ubuntu" >> "${GITHUB_ENV}"
- name: Install rust
uses: dtolnay/rust-toolchain@dc6353516c68da0f06325f42ad880f76a5e77ec9
with:
toolchain: nightly
- name: Export CUDA variables
if: ${{ !cancelled() }}
run: |
{
echo "CUDA_PATH=$CUDA_PATH";
echo "LD_LIBRARY_PATH=$CUDA_PATH/lib:$LD_LIBRARY_PATH";
echo "CUDACXX=/usr/local/cuda-${{ matrix.cuda }}/bin/nvcc";
} >> "${GITHUB_ENV}"
echo "$CUDA_PATH/bin" >> "${GITHUB_PATH}"
# Specify the correct host compilers
- name: Export gcc and g++ variables
if: ${{ !cancelled() }}
run: |
{
echo "CC=/usr/bin/gcc-${{ matrix.gcc }}";
echo "CXX=/usr/bin/g++-${{ matrix.gcc }}";
echo "CUDAHOSTCXX=/usr/bin/g++-${{ matrix.gcc }}";
echo "HOME=/home/ubuntu";
} >> "${GITHUB_ENV}"
- name: Run benchmarks with AVX512
run: |
make bench_pbs_gpu
make bench_ks_gpu
- name: Parse results
run: |
COMMIT_DATE="$(git --no-pager show -s --format=%cd --date=iso8601-strict ${{ github.sha }})"
COMMIT_HASH="$(git describe --tags --dirty)"
python3 ./ci/benchmark_parser.py target/criterion ${{ env.RESULTS_FILENAME }} \
--database tfhe_rs \
--hardware ${{ inputs.instance_type }} \
--backend gpu \
--project-version "${COMMIT_HASH}" \
--branch ${{ github.ref_name }} \
--commit-date "${COMMIT_DATE}" \
--bench-date "${{ env.BENCH_DATE }}" \
--name-suffix avx512 \
--walk-subdirs \
--throughput
- name: Upload parsed results artifact
uses: actions/upload-artifact@5d5d22a31266ced268874388b861e4b58bb5c2f3
with:
name: ${{ github.sha }}_core_crypto
path: ${{ env.RESULTS_FILENAME }}
- name: Checkout Slab repo
uses: actions/checkout@9bb56186c3b09b4f86b1c65136769dd318469633
with:
repository: zama-ai/slab
path: slab
token: ${{ secrets.FHE_ACTIONS_TOKEN }}
- name: Send data to Slab
shell: bash
run: |
echo "Computing HMac on downloaded artifact"
SIGNATURE="$(slab/scripts/hmac_calculator.sh ${{ env.RESULTS_FILENAME }} '${{ secrets.JOB_SECRET }}')"
echo "Sending results to Slab..."
curl -v -k \
-H "Content-Type: application/json" \
-H "X-Slab-Repository: ${{ github.repository }}" \
-H "X-Slab-Command: store_data_v2" \
-H "X-Hub-Signature-256: sha256=${SIGNATURE}" \
-d @${{ env.RESULTS_FILENAME }} \
${{ secrets.SLAB_URL }}
# FIXME This action needs docker to be installed on the machine beforehand.
# - name: Slack Notification
# if: ${{ failure() }}
# continue-on-error: true
# uses: rtCamp/action-slack-notify@4e5fb42d249be6a45a298f3c9543b111b02f7907
# env:
# SLACK_COLOR: ${{ job.status }}
# SLACK_CHANNEL: ${{ secrets.SLACK_CHANNEL }}
# SLACK_ICON: https://pbs.twimg.com/profile_images/1274014582265298945/OjBKP9kn_400x400.png
# SLACK_MESSAGE: "PBS GPU benchmarks finished with status: ${{ job.status }}. (${{ env.ACTION_RUN_URL }})"
# SLACK_USERNAME: ${{ secrets.BOT_USERNAME }}
# SLACK_WEBHOOK: ${{ secrets.SLACK_WEBHOOK }}
teardown-ec2:
name: Teardown EC2 instance (cuda-benchmarks)
if: ${{ always() && needs.setup-ec2.result != 'skipped' }}
needs: [ setup-ec2, core-crypto-benchmarks ]
runs-on: ubuntu-latest
steps:
- name: Stop instance
id: stop-instance
uses: zama-ai/slab-github-runner@1dced74825027fe3d481392163ed8fc56813fb5d
with:
mode: stop
github-token: ${{ secrets.SLAB_ACTION_TOKEN }}
slab-url: ${{ secrets.SLAB_BASE_URL_PRE_PROD }}
job-secret: ${{ secrets.JOB_SECRET }}
label: ${{ needs.setup-ec2.outputs.runner-name }}
- name: Slack Notification
if: ${{ failure() }}
continue-on-error: true
uses: rtCamp/action-slack-notify@4e5fb42d249be6a45a298f3c9543b111b02f7907
env:
SLACK_COLOR: ${{ job.status }}
SLACK_MESSAGE: "EC2 teardown (cuda-benchmarks) finished with status: ${{ job.status }}. (${{ env.ACTION_RUN_URL }})"

View File

@@ -0,0 +1,74 @@
name: CSPRNG randomness testing Workflow
env:
CARGO_TERM_COLOR: always
ACTION_RUN_URL: ${{ github.server_url }}/${{ github.repository }}/actions/runs/${{ github.run_id }}
RUSTFLAGS: "-C target-cpu=native"
on:
# Allows you to run this workflow manually from the Actions tab as an alternative.
workflow_dispatch:
# All the inputs are provided by Slab
inputs:
instance_id:
description: "AWS instance ID"
type: string
instance_image_id:
description: "AWS instance AMI ID"
type: string
instance_type:
description: "AWS instance product type"
type: string
runner_name:
description: "Action runner name"
type: string
request_id:
description: 'Slab request ID'
type: string
fork_repo:
description: 'Name of forked repo as user/repo'
type: string
fork_git_sha:
description: 'Git SHA to checkout from fork'
type: string
jobs:
csprng-randomness-teting:
name: CSPRNG randomness testing
concurrency:
group: ${{ github.workflow }}_${{ github.ref }}_${{ inputs.instance_image_id }}_${{ inputs.instance_type }}
cancel-in-progress: true
runs-on: ${{ inputs.runner_name }}
steps:
- name: Checkout tfhe-rs
uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608
with:
repository: ${{ inputs.fork_repo }}
ref: ${{ inputs.fork_git_sha }}
- name: Set up home
run: |
echo "HOME=/home/ubuntu" >> "${GITHUB_ENV}"
- name: Install latest stable
uses: actions-rs/toolchain@16499b5e05bf2e26879000db0c1d13f7e13fa3af
with:
toolchain: stable
default: true
- name: Dieharder randomness test suite
run: |
make dieharder_csprng
- name: Slack Notification
if: ${{ failure() }}
continue-on-error: true
uses: rtCamp/action-slack-notify@b24d75fe0e728a4bf9fc42ee217caa686d141ee8
env:
SLACK_COLOR: ${{ job.status }}
SLACK_CHANNEL: ${{ secrets.SLACK_CHANNEL }}
SLACK_ICON: https://pbs.twimg.com/profile_images/1274014582265298945/OjBKP9kn_400x400.png
SLACK_MESSAGE: "concrete-csprng randomness check finished with status: ${{ job.status }}. (${{ env.ACTION_RUN_URL }})"
SLACK_USERNAME: ${{ secrets.BOT_USERNAME }}
SLACK_WEBHOOK: ${{ secrets.SLACK_WEBHOOK }}

View File

@@ -1,94 +0,0 @@
name: CSPRNG randomness testing Workflow
env:
CARGO_TERM_COLOR: always
ACTION_RUN_URL: ${{ github.server_url }}/${{ github.repository }}/actions/runs/${{ github.run_id }}
RUSTFLAGS: "-C target-cpu=native"
RUST_BACKTRACE: "full"
RUST_MIN_STACK: "8388608"
SLACK_CHANNEL: ${{ secrets.SLACK_CHANNEL }}
SLACK_ICON: https://pbs.twimg.com/profile_images/1274014582265298945/OjBKP9kn_400x400.png
SLACK_USERNAME: ${{ secrets.BOT_USERNAME }}
SLACK_WEBHOOK: ${{ secrets.SLACK_WEBHOOK }}
on:
# Allows you to run this workflow manually from the Actions tab as an alternative.
workflow_dispatch:
pull_request:
types: [ labeled ]
jobs:
setup-ec2:
name: Setup EC2 instance (csprng-randomness-tests)
if: ${{ github.event_name == 'workflow_dispatch' || contains(github.event.label.name, 'approved') }}
runs-on: ubuntu-latest
outputs:
runner-name: ${{ steps.start-instance.outputs.label }}
steps:
- name: Start instance
id: start-instance
uses: zama-ai/slab-github-runner@1dced74825027fe3d481392163ed8fc56813fb5d
with:
mode: start
github-token: ${{ secrets.SLAB_ACTION_TOKEN }}
slab-url: ${{ secrets.SLAB_BASE_URL }}
job-secret: ${{ secrets.JOB_SECRET }}
backend: aws
profile: cpu-small
csprng-randomness-tests:
name: CSPRNG randomness tests
needs: setup-ec2
concurrency:
group: ${{ github.workflow }}_${{ github.ref }}
cancel-in-progress: true
runs-on: ${{ needs.setup-ec2.outputs.runner-name }}
steps:
- name: Checkout tfhe-rs
uses: actions/checkout@9bb56186c3b09b4f86b1c65136769dd318469633
- name: Set up home
run: |
echo "HOME=/home/ubuntu" >> "${GITHUB_ENV}"
- name: Install latest stable
uses: dtolnay/rust-toolchain@dc6353516c68da0f06325f42ad880f76a5e77ec9
with:
toolchain: stable
- name: Dieharder randomness test suite
run: |
make dieharder_csprng
- name: Slack Notification
if: ${{ failure() }}
continue-on-error: true
uses: rtCamp/action-slack-notify@4e5fb42d249be6a45a298f3c9543b111b02f7907
env:
SLACK_COLOR: ${{ job.status }}
SLACK_MESSAGE: "concrete-csprng randomness check finished with status: ${{ job.status }}. (${{ env.ACTION_RUN_URL }})"
teardown-ec2:
name: Teardown EC2 instance (csprng-randomness-tests)
if: ${{ always() && needs.setup-ec2.result != 'skipped' }}
needs: [ setup-ec2, csprng-randomness-tests ]
runs-on: ubuntu-latest
steps:
- name: Stop instance
id: stop-instance
uses: zama-ai/slab-github-runner@1dced74825027fe3d481392163ed8fc56813fb5d
with:
mode: stop
github-token: ${{ secrets.SLAB_ACTION_TOKEN }}
slab-url: ${{ secrets.SLAB_BASE_URL }}
job-secret: ${{ secrets.JOB_SECRET }}
label: ${{ needs.setup-ec2.outputs.runner-name }}
- name: Slack Notification
if: ${{ failure() }}
continue-on-error: true
uses: rtCamp/action-slack-notify@4e5fb42d249be6a45a298f3c9543b111b02f7907
env:
SLACK_COLOR: ${{ job.status }}
SLACK_MESSAGE: "EC2 teardown (csprng-randomness-tests) finished with status: ${{ job.status }}. (${{ env.ACTION_RUN_URL }})"

View File

@@ -1,202 +0,0 @@
# Run all benchmarks on an RTX 4090 machine and return parsed results to Slab CI bot.
name: TFHE Cuda Backend - 4090 full benchmarks
env:
CARGO_TERM_COLOR: always
RESULTS_FILENAME: parsed_benchmark_results_${{ github.sha }}.json
ACTION_RUN_URL: ${{ github.server_url }}/${{ github.repository }}/actions/runs/${{ github.run_id }}
RUST_BACKTRACE: "full"
RUST_MIN_STACK: "8388608"
SLACK_CHANNEL: ${{ secrets.SLACK_CHANNEL }}
SLACK_ICON: https://pbs.twimg.com/profile_images/1274014582265298945/OjBKP9kn_400x400.png
SLACK_USERNAME: ${{ secrets.BOT_USERNAME }}
SLACK_WEBHOOK: ${{ secrets.SLACK_WEBHOOK }}
on:
# Allows you to run this workflow manually from the Actions tab as an alternative.
workflow_dispatch:
pull_request:
types: [labeled]
schedule:
# Weekly benchmarks will be triggered each Friday at 9p.m.
- cron: "0 21 * * 5"
jobs:
cuda-integer-benchmarks:
name: Cuda integer benchmarks for all operations flavor (RTX 4090)
if: ${{ github.event_name == 'workflow_dispatch' || github.event_name == 'schedule' || contains(github.event.label.name, '4090_bench') }}
concurrency:
group: ${{ github.workflow }}_${{ github.ref }}_cuda_integer_bench
cancel-in-progress: true
runs-on: ["self-hosted", "4090-desktop"]
timeout-minutes: 1440 # 24 hours
strategy:
fail-fast: false
max-parallel: 1
matrix:
command: [integer, integer_multi_bit]
op_flavor: [default, unchecked]
steps:
- name: Checkout tfhe-rs
uses: actions/checkout@9bb56186c3b09b4f86b1c65136769dd318469633
with:
fetch-depth: 0
- name: Get benchmark details
run: |
{
echo "BENCH_DATE=$(date --iso-8601=seconds)";
echo "COMMIT_DATE=$(git --no-pager show -s --format=%cd --date=iso8601-strict ${{ github.sha }})";
echo "COMMIT_HASH=$(git describe --tags --dirty)";
} >> "${GITHUB_ENV}"
- name: Install rust
uses: dtolnay/rust-toolchain@dc6353516c68da0f06325f42ad880f76a5e77ec9
with:
toolchain: nightly
- name: Checkout Slab repo
uses: actions/checkout@9bb56186c3b09b4f86b1c65136769dd318469633
with:
repository: zama-ai/slab
path: slab
token: ${{ secrets.FHE_ACTIONS_TOKEN }}
- name: Run integer benchmarks
run: |
make BENCH_OP_FLAVOR=${{ matrix.op_flavor }} bench_${{ matrix.command }}_gpu
- name: Parse results
run: |
python3 ./ci/benchmark_parser.py target/criterion ${{ env.RESULTS_FILENAME }} \
--database tfhe_rs \
--hardware "rtx4090" \
--backend gpu \
--project-version "${{ env.COMMIT_HASH }}" \
--branch ${{ github.ref_name }} \
--commit-date "${{ env.COMMIT_DATE }}" \
--bench-date "${{ env.BENCH_DATE }}" \
--walk-subdirs \
--throughput
- name: Upload parsed results artifact
uses: actions/upload-artifact@5d5d22a31266ced268874388b861e4b58bb5c2f3
with:
name: ${{ github.sha }}_${{ matrix.command }}_${{ matrix.op_flavor }}
path: ${{ env.RESULTS_FILENAME }}
- name: Send data to Slab
shell: bash
run: |
echo "Computing HMac on results file"
SIGNATURE="$(slab/scripts/hmac_calculator.sh ${{ env.RESULTS_FILENAME }} '${{ secrets.JOB_SECRET }}')"
echo "Sending results to Slab..."
curl -v -k \
-H "Content-Type: application/json" \
-H "X-Slab-Repository: ${{ github.repository }}" \
-H "X-Slab-Command: store_data_v2" \
-H "X-Hub-Signature-256: sha256=${SIGNATURE}" \
-d @${{ env.RESULTS_FILENAME }} \
${{ secrets.SLAB_URL }}
- name: Slack Notification
if: ${{ always() }}
continue-on-error: true
uses: rtCamp/action-slack-notify@4e5fb42d249be6a45a298f3c9543b111b02f7907
env:
SLACK_COLOR: ${{ job.status }}
SLACK_MESSAGE: "Integer RTX 4090 full benchmarks finished with status: ${{ job.status }}. (${{ env.ACTION_RUN_URL }})"
cuda-core-crypto-benchmarks:
name: Cuda core crypto benchmarks (RTX 4090)
if: ${{ github.event_name == 'workflow_dispatch' || github.event_name == 'schedule' || contains(github.event.label.name, '4090_bench') }}
needs: cuda-integer-benchmarks
concurrency:
group: ${{ github.workflow }}_${{ github.ref }}_cuda_core_crypto_bench
cancel-in-progress: true
runs-on: ["self-hosted", "4090-desktop"]
timeout-minutes: 1440 # 24 hours
steps:
- name: Checkout tfhe-rs
uses: actions/checkout@9bb56186c3b09b4f86b1c65136769dd318469633
with:
fetch-depth: 0
- name: Get benchmark details
run: |
{
echo "BENCH_DATE=$(date --iso-8601=seconds)";
echo "COMMIT_DATE=$(git --no-pager show -s --format=%cd --date=iso8601-strict ${{ github.sha }})";
echo "COMMIT_HASH=$(git describe --tags --dirty)";
} >> "${GITHUB_ENV}"
- name: Install rust
uses: dtolnay/rust-toolchain@dc6353516c68da0f06325f42ad880f76a5e77ec9
with:
toolchain: nightly
- name: Checkout Slab repo
uses: actions/checkout@9bb56186c3b09b4f86b1c65136769dd318469633
with:
repository: zama-ai/slab
path: slab
token: ${{ secrets.FHE_ACTIONS_TOKEN }}
- name: Run integer benchmarks
run: |
make bench_pbs_gpu
make bench_ks_gpu
- name: Parse results
run: |
python3 ./ci/benchmark_parser.py target/criterion ${{ env.RESULTS_FILENAME }} \
--database tfhe_rs \
--hardware "rtx4090" \
--backend gpu \
--project-version "${{ env.COMMIT_HASH }}" \
--branch ${{ github.ref_name }} \
--commit-date "${{ env.COMMIT_DATE }}" \
--bench-date "${{ env.BENCH_DATE }}" \
--walk-subdirs \
--throughput
- name: Upload parsed results artifact
uses: actions/upload-artifact@5d5d22a31266ced268874388b861e4b58bb5c2f3
with:
name: ${{ github.sha }}_core_crypto
path: ${{ env.RESULTS_FILENAME }}
- name: Send data to Slab
shell: bash
run: |
echo "Computing HMac on results file"
SIGNATURE="$(slab/scripts/hmac_calculator.sh ${{ env.RESULTS_FILENAME }} '${{ secrets.JOB_SECRET }}')"
echo "Sending results to Slab..."
curl -v -k \
-H "Content-Type: application/json" \
-H "X-Slab-Repository: ${{ github.repository }}" \
-H "X-Slab-Command: store_data_v2" \
-H "X-Hub-Signature-256: sha256=${SIGNATURE}" \
-d @${{ env.RESULTS_FILENAME }} \
${{ secrets.SLAB_URL }}
- name: Slack Notification
if: ${{ !success() && !cancelled() }}
continue-on-error: true
uses: rtCamp/action-slack-notify@4e5fb42d249be6a45a298f3c9543b111b02f7907
env:
SLACK_COLOR: ${{ job.status }}
SLACK_MESSAGE: "Core crypto RTX 4090 full benchmarks finished with status: ${{ job.status }}. (${{ env.ACTION_RUN_URL }})"
remove_github_label:
name: Remove 4090 bench label
if: ${{ always() && github.event_name == 'pull_request' }}
needs: [cuda-integer-benchmarks, cuda-core-crypto-benchmarks]
runs-on: ["self-hosted", "4090-desktop"]
steps:
- uses: actions-ecosystem/action-remove-labels@2ce5d41b4b6aa8503e285553f75ed56e0a40bae0
with:
labels: 4090_bench
github_token: ${{ secrets.GITHUB_TOKEN }}

View File

@@ -25,8 +25,6 @@ env:
RESULTS_FILENAME: parsed_benchmark_results_${{ github.sha }}.json
PARSE_INTEGER_BENCH_CSV_FILE: tfhe_rs_integer_benches_${{ github.sha }}.csv
ACTION_RUN_URL: ${{ github.server_url }}/${{ github.repository }}/actions/runs/${{ github.run_id }}
RUST_BACKTRACE: "full"
RUST_MIN_STACK: "8388608"
jobs:
run-integer-benchmarks:
@@ -46,7 +44,7 @@ jobs:
echo "BENCH_DATE=$(date --iso-8601=seconds)" >> "${GITHUB_ENV}"
- name: Checkout tfhe-rs repo with tags
uses: actions/checkout@9bb56186c3b09b4f86b1c65136769dd318469633
uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608
with:
fetch-depth: 0
@@ -56,13 +54,14 @@ jobs:
echo "HOME=/home/ubuntu" >> "${GITHUB_ENV}"
- name: Install rust
uses: dtolnay/rust-toolchain@dc6353516c68da0f06325f42ad880f76a5e77ec9
uses: actions-rs/toolchain@16499b5e05bf2e26879000db0c1d13f7e13fa3af
with:
toolchain: nightly
override: true
- name: Run benchmarks with AVX512
run: |
make FAST_BENCH=TRUE bench_integer
make AVX512_SUPPORT=ON FAST_BENCH=TRUE bench_integer
- name: Parse benchmarks to csv
run: |
@@ -70,7 +69,7 @@ jobs:
parse_integer_benches
- name: Upload csv results artifact
uses: actions/upload-artifact@5d5d22a31266ced268874388b861e4b58bb5c2f3
uses: actions/upload-artifact@a8a3f3ad30e3422c9c7b888a15615d19a852ae32
with:
name: ${{ github.sha }}_csv_integer
path: ${{ env.PARSE_INTEGER_BENCH_CSV_FILE }}
@@ -91,17 +90,17 @@ jobs:
--throughput
- name: Upload parsed results artifact
uses: actions/upload-artifact@5d5d22a31266ced268874388b861e4b58bb5c2f3
uses: actions/upload-artifact@a8a3f3ad30e3422c9c7b888a15615d19a852ae32
with:
name: ${{ github.sha }}_integer
path: ${{ env.RESULTS_FILENAME }}
- name: Checkout Slab repo
uses: actions/checkout@9bb56186c3b09b4f86b1c65136769dd318469633
uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608
with:
repository: zama-ai/slab
path: slab
token: ${{ secrets.FHE_ACTIONS_TOKEN }}
token: ${{ secrets.CONCRETE_ACTIONS_TOKEN }}
- name: Send data to Slab
shell: bash
@@ -120,11 +119,11 @@ jobs:
- name: Slack Notification
if: ${{ failure() }}
continue-on-error: true
uses: rtCamp/action-slack-notify@4e5fb42d249be6a45a298f3c9543b111b02f7907
uses: rtCamp/action-slack-notify@b24d75fe0e728a4bf9fc42ee217caa686d141ee8
env:
SLACK_COLOR: ${{ job.status }}
SLACK_CHANNEL: ${{ secrets.SLACK_CHANNEL }}
SLACK_ICON: https://pbs.twimg.com/profile_images/1274014582265298945/OjBKP9kn_400x400.png
SLACK_MESSAGE: "Integer benchmarks finished with status: ${{ job.status }}. (${{ env.ACTION_RUN_URL }})"
SLACK_MESSAGE: "Integer benchmarks failed. (${{ env.ACTION_RUN_URL }})"
SLACK_USERNAME: ${{ secrets.BOT_USERNAME }}
SLACK_WEBHOOK: ${{ secrets.SLACK_WEBHOOK }}

View File

@@ -28,8 +28,6 @@ env:
CARGO_TERM_COLOR: always
RESULTS_FILENAME: parsed_benchmark_results_${{ github.sha }}.json
ACTION_RUN_URL: ${{ github.server_url }}/${{ github.repository }}/actions/runs/${{ github.run_id }}
RUST_BACKTRACE: "full"
RUST_MIN_STACK: "8388608"
jobs:
prepare-matrix:
@@ -41,17 +39,20 @@ jobs:
- name: Weekly benchmarks
if: ${{ github.event.inputs.user_inputs == 'weekly_benchmarks' }}
run: |
echo "OP_FLAVOR=[\"default\"]" >> "${GITHUB_ENV}"
echo "OP_FLAVOR=[\"default\", \"default_comp\", \"default_scalar\", \"default_scalar_comp\"]" >> ${GITHUB_ENV}
- name: Quarterly benchmarks
if: ${{ github.event.inputs.user_inputs == 'quarterly_benchmarks' }}
run: |
echo "OP_FLAVOR=[\"default\", \"smart\", \"unchecked\", \"misc\"]" >> "${GITHUB_ENV}"
echo "OP_FLAVOR=[\"default\", \"default_comp\", \"default_scalar\", \"default_scalar_comp\", \
\"smart\", \"smart_comp\", \"smart_scalar\", \"smart_parallelized\", \"smart_parallelized_comp\", \"smart_scalar_parallelized\", \"smart_scalar_parallelized_comp\", \
\"unchecked\", \"unchecked_comp\", \"unchecked_scalar\", \"unchecked_scalar_comp\", \
\"misc\"]" >> ${GITHUB_ENV}
- name: Set operation flavor output
id: set_op_flavor
run: |
echo "op_flavor=${{ toJSON(env.OP_FLAVOR) }}" >> "${GITHUB_OUTPUT}"
echo "op_flavor=${{ toJSON(env.OP_FLAVOR) }}" >> ${GITHUB_OUTPUT}
integer-benchmarks:
name: Execute integer benchmarks for all operations flavor
@@ -59,7 +60,6 @@ jobs:
runs-on: ${{ github.event.inputs.runner_name }}
if: ${{ !cancelled() }}
continue-on-error: true
timeout-minutes: 1440 # 24 hours
strategy:
max-parallel: 1
matrix:
@@ -74,17 +74,15 @@ jobs:
echo "Request ID: ${{ inputs.request_id }}"
- name: Checkout tfhe-rs repo with tags
uses: actions/checkout@9bb56186c3b09b4f86b1c65136769dd318469633
uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608
with:
fetch-depth: 0
- name: Get benchmark details
run: |
{
echo "BENCH_DATE=$(date --iso-8601=seconds)";
echo "COMMIT_DATE=$(git --no-pager show -s --format=%cd --date=iso8601-strict ${{ github.sha }})";
echo "COMMIT_HASH=$(git describe --tags --dirty)";
} >> "${GITHUB_ENV}"
echo "BENCH_DATE=$(date --iso-8601=seconds)" >> "${GITHUB_ENV}"
echo "COMMIT_DATE=$(git --no-pager show -s --format=%cd --date=iso8601-strict ${{ github.sha }})" >> "${GITHUB_ENV}"
echo "COMMIT_HASH=$(git describe --tags --dirty)" >> "${GITHUB_ENV}"
- name: Set up home
# "Install rust" step require root user to have a HOME directory which is not set.
@@ -92,20 +90,21 @@ jobs:
echo "HOME=/home/ubuntu" >> "${GITHUB_ENV}"
- name: Install rust
uses: dtolnay/rust-toolchain@dc6353516c68da0f06325f42ad880f76a5e77ec9
uses: actions-rs/toolchain@16499b5e05bf2e26879000db0c1d13f7e13fa3af
with:
toolchain: nightly
override: true
- name: Checkout Slab repo
uses: actions/checkout@9bb56186c3b09b4f86b1c65136769dd318469633
uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608
with:
repository: zama-ai/slab
path: slab
token: ${{ secrets.FHE_ACTIONS_TOKEN }}
token: ${{ secrets.CONCRETE_ACTIONS_TOKEN }}
- name: Run benchmarks with AVX512
run: |
make BENCH_OP_FLAVOR=${{ matrix.op_flavor }} bench_${{ matrix.command }}
make AVX512_SUPPORT=ON BENCH_OP_FLAVOR=${{ matrix.op_flavor }} bench_${{ matrix.command }}
- name: Parse results
run: |
@@ -121,7 +120,7 @@ jobs:
--throughput
- name: Upload parsed results artifact
uses: actions/upload-artifact@5d5d22a31266ced268874388b861e4b58bb5c2f3
uses: actions/upload-artifact@a8a3f3ad30e3422c9c7b888a15615d19a852ae32
with:
name: ${{ github.sha }}_${{ matrix.command }}_${{ matrix.op_flavor }}
path: ${{ env.RESULTS_FILENAME }}
@@ -148,11 +147,11 @@ jobs:
steps:
- name: Notify
continue-on-error: true
uses: rtCamp/action-slack-notify@4e5fb42d249be6a45a298f3c9543b111b02f7907
uses: rtCamp/action-slack-notify@b24d75fe0e728a4bf9fc42ee217caa686d141ee8
env:
SLACK_COLOR: ${{ job.status }}
SLACK_CHANNEL: ${{ secrets.SLACK_CHANNEL }}
SLACK_ICON: https://pbs.twimg.com/profile_images/1274014582265298945/OjBKP9kn_400x400.png
SLACK_MESSAGE: "Integer full benchmarks finished with status: ${{ job.status }}. (${{ env.ACTION_RUN_URL }})"
SLACK_MESSAGE: "Integer full benchmarks failed. (${{ env.ACTION_RUN_URL }})"
SLACK_USERNAME: ${{ secrets.BOT_USERNAME }}
SLACK_WEBHOOK: ${{ secrets.SLACK_WEBHOOK }}

View File

@@ -1,195 +0,0 @@
# Run integer benchmarks on an AWS instance with CUDA and return parsed results to Slab CI bot.
name: Integer GPU benchmarks
on:
# Allows you to run this workflow manually from the Actions tab as an alternative.
workflow_dispatch:
pull_request:
env:
CARGO_TERM_COLOR: always
RESULTS_FILENAME: parsed_benchmark_results_${{ github.sha }}.json
PARSE_INTEGER_BENCH_CSV_FILE: tfhe_rs_integer_benches_${{ github.sha }}.csv
ACTION_RUN_URL: ${{ github.server_url }}/${{ github.repository }}/actions/runs/${{ github.run_id }}
RUST_BACKTRACE: "full"
RUST_MIN_STACK: "8388608"
jobs:
setup-ec2:
name: Setup EC2 instance (cuda-benchmarks)
runs-on: ubuntu-latest
outputs:
runner-name: ${{ steps.start-instance.outputs.label }}
steps:
- name: Start instance
id: start-instance
uses: zama-ai/slab-github-runner@1dced74825027fe3d481392163ed8fc56813fb5d
with:
mode: start
github-token: ${{ secrets.SLAB_ACTION_TOKEN }}
slab-url: ${{ secrets.SLAB_BASE_URL_PRE_PROD }}
job-secret: ${{ secrets.JOB_SECRET }}
backend: hyperstack
profile: gpu-bench
cuda-integer-benchmarks:
name: CUDA integer benchmarks
needs: setup-ec2
runs-on: ${{ needs.setup-ec2.outputs.runner-name }}
strategy:
fail-fast: false
# explicit include-based build matrix, of known valid options
matrix:
include:
- os: ubuntu-22.04
cuda: "12.2"
gcc: 11
env:
CUDA_PATH: /usr/local/cuda-${{ matrix.cuda }}
CMAKE_VERSION: 3.29.1
steps:
- name: Install dependencies
run: |
sudo apt update
sudo apt install -y checkinstall zlib1g-dev libssl-dev
wget https://github.com/Kitware/CMake/releases/download/v${{ env.CMAKE_VERSION }}/cmake-${{ env.CMAKE_VERSION }}.tar.gz
tar -zxvf cmake-${{ env.CMAKE_VERSION }}.tar.gz
cd cmake-${{ env.CMAKE_VERSION }}
./bootstrap
make -j"$(nproc)"
sudo make install
- name: Get benchmark date
run: |
echo "BENCH_DATE=$(date --iso-8601=seconds)" >> "${GITHUB_ENV}"
- name: Checkout tfhe-rs repo with tags
uses: actions/checkout@9bb56186c3b09b4f86b1c65136769dd318469633
with:
fetch-depth: 0
- name: Set up home
# "Install rust" step require root user to have a HOME directory which is not set.
run: |
echo "HOME=/home/ubuntu" >> "${GITHUB_ENV}"
- name: Install rust
uses: dtolnay/rust-toolchain@dc6353516c68da0f06325f42ad880f76a5e77ec9
with:
toolchain: nightly
- name: Export CUDA variables
if: ${{ !cancelled() }}
run: |
{
echo "CUDA_PATH=$CUDA_PATH";
echo "LD_LIBRARY_PATH=$CUDA_PATH/lib:$LD_LIBRARY_PATH";
echo "CUDACXX=/usr/local/cuda-${{ matrix.cuda }}/bin/nvcc";
} >> "${GITHUB_ENV}"
echo "$CUDA_PATH/bin" >> "${GITHUB_PATH}"
# Specify the correct host compilers
- name: Export gcc and g++ variables
if: ${{ !cancelled() }}
run: |
{
echo "CC=/usr/bin/gcc-${{ matrix.gcc }}";
echo "CXX=/usr/bin/g++-${{ matrix.gcc }}";
echo "CUDAHOSTCXX=/usr/bin/g++-${{ matrix.gcc }}";
} >> "${GITHUB_ENV}"
- name: Run benchmarks with AVX512
run: |
make FAST_BENCH=TRUE BENCH_OP_FLAVOR=default bench_integer_gpu
- name: Parse benchmarks to csv
run: |
make PARSE_INTEGER_BENCH_CSV_FILE=${{ env.PARSE_INTEGER_BENCH_CSV_FILE }} \
parse_integer_benches
- name: Upload csv results artifact
uses: actions/upload-artifact@5d5d22a31266ced268874388b861e4b58bb5c2f3
with:
name: ${{ github.sha }}_csv_integer
path: ${{ env.PARSE_INTEGER_BENCH_CSV_FILE }}
- name: Parse results
run: |
COMMIT_DATE="$(git --no-pager show -s --format=%cd --date=iso8601-strict ${{ github.sha }})"
COMMIT_HASH="$(git describe --tags --dirty)"
python3 ./ci/benchmark_parser.py target/criterion ${{ env.RESULTS_FILENAME }} \
--database tfhe_rs \
--hardware "n2-H100x1" \
--backend gpu \
--project-version "${COMMIT_HASH}" \
--branch ${{ github.ref_name }} \
--commit-date "${COMMIT_DATE}" \
--bench-date "${{ env.BENCH_DATE }}" \
--walk-subdirs \
--name-suffix avx512 \
--throughput
- name: Upload parsed results artifact
uses: actions/upload-artifact@5d5d22a31266ced268874388b861e4b58bb5c2f3
with:
name: ${{ github.sha }}_integer
path: ${{ env.RESULTS_FILENAME }}
- name: Checkout Slab repo
uses: actions/checkout@9bb56186c3b09b4f86b1c65136769dd318469633
with:
repository: zama-ai/slab
path: slab
token: ${{ secrets.FHE_ACTIONS_TOKEN }}
- name: Send data to Slab
shell: bash
run: |
echo "Computing HMac on results file"
SIGNATURE="$(slab/scripts/hmac_calculator.sh ${{ env.RESULTS_FILENAME }} '${{ secrets.JOB_SECRET }}')"
echo "Sending results to Slab..."
curl -v -k \
-H "Content-Type: application/json" \
-H "X-Slab-Repository: ${{ github.repository }}" \
-H "X-Slab-Command: store_data_v2" \
-H "X-Hub-Signature-256: sha256=${SIGNATURE}" \
-d @${{ env.RESULTS_FILENAME }} \
${{ secrets.SLAB_URL }}
# FIXME This action needs docker to be installed on the machine beforehand.
# - name: Slack Notification
# if: ${{ !success() && !cancelled() }}
# continue-on-error: true
# uses: rtCamp/action-slack-notify@4e5fb42d249be6a45a298f3c9543b111b02f7907
# env:
# SLACK_COLOR: ${{ job.status }}
# SLACK_CHANNEL: ${{ secrets.SLACK_CHANNEL }}
# SLACK_ICON: https://pbs.twimg.com/profile_images/1274014582265298945/OjBKP9kn_400x400.png
# SLACK_MESSAGE: "Integer GPU benchmarks finished with status: ${{ job.status }}. (${{ env.ACTION_RUN_URL }})"
# SLACK_USERNAME: ${{ secrets.BOT_USERNAME }}
# SLACK_WEBHOOK: ${{ secrets.SLACK_WEBHOOK }}
teardown-ec2:
name: Teardown EC2 instance (cuda-benchmarks)
if: ${{ always() && needs.setup-ec2.result != 'skipped' }}
needs: [ setup-ec2, cuda-integer-benchmarks ]
runs-on: ubuntu-latest
steps:
- name: Stop instance
id: stop-instance
uses: zama-ai/slab-github-runner@1dced74825027fe3d481392163ed8fc56813fb5d
with:
mode: stop
github-token: ${{ secrets.SLAB_ACTION_TOKEN }}
slab-url: ${{ secrets.SLAB_BASE_URL_PRE_PROD }}
job-secret: ${{ secrets.JOB_SECRET }}
label: ${{ needs.setup-ec2.outputs.runner-name }}
- name: Slack Notification
if: ${{ failure() }}
continue-on-error: true
uses: rtCamp/action-slack-notify@4e5fb42d249be6a45a298f3c9543b111b02f7907
env:
SLACK_COLOR: ${{ job.status }}
SLACK_MESSAGE: "EC2 teardown (cuda-benchmarks) finished with status: ${{ job.status }}. (${{ env.ACTION_RUN_URL }})"

View File

@@ -1,190 +0,0 @@
# Run all integer benchmarks on an AWS instance with CUDA and return parsed results to Slab CI bot.
name: Integer GPU full benchmarks
on:
# Allows you to run this workflow manually from the Actions tab as an alternative.
workflow_dispatch:
pull_request:
env:
CARGO_TERM_COLOR: always
RESULTS_FILENAME: parsed_benchmark_results_${{ github.sha }}.json
ACTION_RUN_URL: ${{ github.server_url }}/${{ github.repository }}/actions/runs/${{ github.run_id }}
RUST_BACKTRACE: "full"
RUST_MIN_STACK: "8388608"
jobs:
setup-ec2:
name: Setup EC2 instance (cuda-full-benchmarks)
runs-on: ubuntu-latest
outputs:
runner-name: ${{ steps.start-instance.outputs.label }}
steps:
- name: Start instance
id: start-instance
uses: zama-ai/slab-github-runner@1dced74825027fe3d481392163ed8fc56813fb5d
with:
mode: start
github-token: ${{ secrets.SLAB_ACTION_TOKEN }}
slab-url: ${{ secrets.SLAB_BASE_URL_PRE_PROD }}
job-secret: ${{ secrets.JOB_SECRET }}
backend: hyperstack
profile: gpu-bench
cuda-integer-full-benchmarks:
name: CUDA integer full benchmarks
needs: setup-ec2
runs-on: ${{ needs.setup-ec2.outputs.runner-name }}
timeout-minutes: 1440 # 24 hours
continue-on-error: true
strategy:
fail-fast: false
max-parallel: 1
matrix:
command: [integer, integer_multi_bit]
op_flavor: [default, unchecked]
# explicit include-based build matrix, of known valid options
include:
- os: ubuntu-22.04
cuda: "12.2"
gcc: 11
env:
CUDA_PATH: /usr/local/cuda-${{ matrix.cuda }}
CMAKE_VERSION: 3.29.1
steps:
- name: Install dependencies
run: |
sudo apt update
sudo apt install -y checkinstall zlib1g-dev libssl-dev
wget https://github.com/Kitware/CMake/releases/download/v${{ env.CMAKE_VERSION }}/cmake-${{ env.CMAKE_VERSION }}.tar.gz
tar -zxvf cmake-${{ env.CMAKE_VERSION }}.tar.gz
cd cmake-${{ env.CMAKE_VERSION }}
./bootstrap
make -j"$(nproc)"
sudo make install
- name: Checkout tfhe-rs repo with tags
uses: actions/checkout@9bb56186c3b09b4f86b1c65136769dd318469633
with:
fetch-depth: 0
- name: Get benchmark details
run: |
{
echo "BENCH_DATE=$(date --iso-8601=seconds)";
echo "COMMIT_DATE=$(git --no-pager show -s --format=%cd --date=iso8601-strict ${{ github.sha }})";
echo "COMMIT_HASH=$(git describe --tags --dirty)";
} >> "${GITHUB_ENV}"
- name: Set up home
# "Install rust" step require root user to have a HOME directory which is not set.
run: |
echo "HOME=/home/ubuntu" >> "${GITHUB_ENV}"
- name: Install rust
uses: dtolnay/rust-toolchain@dc6353516c68da0f06325f42ad880f76a5e77ec9
with:
toolchain: nightly
- name: Export CUDA variables
if: ${{ !cancelled() }}
run: |
{
echo "CUDA_PATH=$CUDA_PATH";
echo "LD_LIBRARY_PATH=$CUDA_PATH/lib:$LD_LIBRARY_PATH";
echo "CUDACXX=/usr/local/cuda-${{ matrix.cuda }}/bin/nvcc";
} >> "${GITHUB_ENV}"
echo "$CUDA_PATH/bin" >> "${GITHUB_PATH}"
# Specify the correct host compilers
- name: Export gcc and g++ variables
if: ${{ !cancelled() }}
run: |
{
echo "CC=/usr/bin/gcc-${{ matrix.gcc }}";
echo "CXX=/usr/bin/g++-${{ matrix.gcc }}";
echo "CUDAHOSTCXX=/usr/bin/g++-${{ matrix.gcc }}";
} >> "${GITHUB_ENV}"
- name: Checkout Slab repo
uses: actions/checkout@9bb56186c3b09b4f86b1c65136769dd318469633
with:
repository: zama-ai/slab
path: slab
token: ${{ secrets.FHE_ACTIONS_TOKEN }}
- name: Run benchmarks with AVX512
run: |
make BENCH_OP_FLAVOR=${{ matrix.op_flavor }} bench_${{ matrix.command }}_gpu
- name: Parse results
run: |
python3 ./ci/benchmark_parser.py target/criterion ${{ env.RESULTS_FILENAME }} \
--database tfhe_rs \
--hardware "n2-H100x1" \
--backend gpu \
--project-version "${{ env.COMMIT_HASH }}" \
--branch ${{ github.ref_name }} \
--commit-date "${{ env.COMMIT_DATE }}" \
--bench-date "${{ env.BENCH_DATE }}" \
--walk-subdirs \
--name-suffix avx512 \
--throughput
- name: Upload parsed results artifact
uses: actions/upload-artifact@5d5d22a31266ced268874388b861e4b58bb5c2f3
with:
name: ${{ github.sha }}_${{ matrix.command }}_${{ matrix.op_flavor }}
path: ${{ env.RESULTS_FILENAME }}
- name: Send data to Slab
shell: bash
run: |
echo "Computing HMac on results file"
SIGNATURE="$(slab/scripts/hmac_calculator.sh ${{ env.RESULTS_FILENAME }} '${{ secrets.JOB_SECRET }}')"
echo "Sending results to Slab..."
curl -v -k \
-H "Content-Type: application/json" \
-H "X-Slab-Repository: ${{ github.repository }}" \
-H "X-Slab-Command: store_data_v2" \
-H "X-Hub-Signature-256: sha256=${SIGNATURE}" \
-d @${{ env.RESULTS_FILENAME }} \
${{ secrets.SLAB_URL }}
# FIXME This action needs docker to be installed on the machine beforehand.
# - name: Slack Notification
# if: ${{ !success() && !cancelled() }}
# continue-on-error: true
# uses: rtCamp/action-slack-notify@4e5fb42d249be6a45a298f3c9543b111b02f7907
# env:
# SLACK_COLOR: ${{ job.status }}
# SLACK_CHANNEL: ${{ secrets.SLACK_CHANNEL }}
# SLACK_ICON: https://pbs.twimg.com/profile_images/1274014582265298945/OjBKP9kn_400x400.png
# SLACK_MESSAGE: "Integer GPU full benchmarks finished with status: ${{ job.status }}. (${{ env.ACTION_RUN_URL }})"
# SLACK_USERNAME: ${{ secrets.BOT_USERNAME }}
# SLACK_WEBHOOK: ${{ secrets.SLACK_WEBHOOK }}
teardown-ec2:
name: Teardown EC2 instance (cuda-full-benchmarks)
if: ${{ always() && needs.setup-ec2.result != 'skipped' }}
needs: [ setup-ec2, cuda-integer-full-benchmarks ]
runs-on: ubuntu-latest
steps:
- name: Stop instance
id: stop-instance
uses: zama-ai/slab-github-runner@1dced74825027fe3d481392163ed8fc56813fb5d
with:
mode: stop
github-token: ${{ secrets.SLAB_ACTION_TOKEN }}
slab-url: ${{ secrets.SLAB_BASE_URL_PRE_PROD }}
job-secret: ${{ secrets.JOB_SECRET }}
label: ${{ needs.setup-ec2.outputs.runner-name }}
- name: Slack Notification
if: ${{ failure() }}
continue-on-error: true
uses: rtCamp/action-slack-notify@4e5fb42d249be6a45a298f3c9543b111b02f7907
env:
SLACK_COLOR: ${{ job.status }}
SLACK_MESSAGE: "EC2 teardown (cuda-full-benchmarks) finished with status: ${{ job.status }}. (${{ env.ACTION_RUN_URL }})"

View File

@@ -25,8 +25,6 @@ env:
RESULTS_FILENAME: parsed_benchmark_results_${{ github.sha }}.json
PARSE_INTEGER_BENCH_CSV_FILE: tfhe_rs_integer_benches_${{ github.sha }}.csv
ACTION_RUN_URL: ${{ github.server_url }}/${{ github.repository }}/actions/runs/${{ github.run_id }}
RUST_BACKTRACE: "full"
RUST_MIN_STACK: "8388608"
jobs:
run-integer-benchmarks:
@@ -46,7 +44,7 @@ jobs:
echo "BENCH_DATE=$(date --iso-8601=seconds)" >> "${GITHUB_ENV}"
- name: Checkout tfhe-rs repo with tags
uses: actions/checkout@9bb56186c3b09b4f86b1c65136769dd318469633
uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608
with:
fetch-depth: 0
@@ -56,13 +54,14 @@ jobs:
echo "HOME=/home/ubuntu" >> "${GITHUB_ENV}"
- name: Install rust
uses: dtolnay/rust-toolchain@dc6353516c68da0f06325f42ad880f76a5e77ec9
uses: actions-rs/toolchain@16499b5e05bf2e26879000db0c1d13f7e13fa3af
with:
toolchain: nightly
override: true
- name: Run multi-bit benchmarks with AVX512
run: |
make FAST_BENCH=TRUE bench_integer_multi_bit
make AVX512_SUPPORT=ON FAST_BENCH=TRUE bench_integer_multi_bit
- name: Parse benchmarks to csv
run: |
@@ -70,7 +69,7 @@ jobs:
parse_integer_benches
- name: Upload csv results artifact
uses: actions/upload-artifact@5d5d22a31266ced268874388b861e4b58bb5c2f3
uses: actions/upload-artifact@a8a3f3ad30e3422c9c7b888a15615d19a852ae32
with:
name: ${{ github.sha }}_csv_integer
path: ${{ env.PARSE_INTEGER_BENCH_CSV_FILE }}
@@ -91,17 +90,17 @@ jobs:
--throughput
- name: Upload parsed results artifact
uses: actions/upload-artifact@5d5d22a31266ced268874388b861e4b58bb5c2f3
uses: actions/upload-artifact@a8a3f3ad30e3422c9c7b888a15615d19a852ae32
with:
name: ${{ github.sha }}_integer
path: ${{ env.RESULTS_FILENAME }}
- name: Checkout Slab repo
uses: actions/checkout@9bb56186c3b09b4f86b1c65136769dd318469633
uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608
with:
repository: zama-ai/slab
path: slab
token: ${{ secrets.FHE_ACTIONS_TOKEN }}
token: ${{ secrets.CONCRETE_ACTIONS_TOKEN }}
- name: Send data to Slab
shell: bash
@@ -120,11 +119,11 @@ jobs:
- name: Slack Notification
if: ${{ failure() }}
continue-on-error: true
uses: rtCamp/action-slack-notify@4e5fb42d249be6a45a298f3c9543b111b02f7907
uses: rtCamp/action-slack-notify@b24d75fe0e728a4bf9fc42ee217caa686d141ee8
env:
SLACK_COLOR: ${{ job.status }}
SLACK_CHANNEL: ${{ secrets.SLACK_CHANNEL }}
SLACK_ICON: https://pbs.twimg.com/profile_images/1274014582265298945/OjBKP9kn_400x400.png
SLACK_MESSAGE: "Integer benchmarks finished with status: ${{ job.status }}. (${{ env.ACTION_RUN_URL }})"
SLACK_MESSAGE: "Integer benchmarks failed. (${{ env.ACTION_RUN_URL }})"
SLACK_USERNAME: ${{ secrets.BOT_USERNAME }}
SLACK_WEBHOOK: ${{ secrets.SLACK_WEBHOOK }}

View File

@@ -1,196 +0,0 @@
# Run integer benchmarks with multi-bit cryptographic parameters on an AWS instance and return parsed results to Slab CI bot.
name: Integer GPU Multi-bit benchmarks
on:
# Allows you to run this workflow manually from the Actions tab as an alternative.
workflow_dispatch:
pull_request:
env:
CARGO_TERM_COLOR: always
RESULTS_FILENAME: parsed_benchmark_results_${{ github.sha }}.json
PARSE_INTEGER_BENCH_CSV_FILE: tfhe_rs_integer_benches_${{ github.sha }}.csv
ACTION_RUN_URL: ${{ github.server_url }}/${{ github.repository }}/actions/runs/${{ github.run_id }}
RUST_BACKTRACE: "full"
RUST_MIN_STACK: "8388608"
jobs:
setup-ec2:
name: Setup EC2 instance (cuda-multi-bit-benchmarks)
runs-on: ubuntu-latest
outputs:
runner-name: ${{ steps.start-instance.outputs.label }}
steps:
- name: Start instance
id: start-instance
uses: zama-ai/slab-github-runner@1dced74825027fe3d481392163ed8fc56813fb5d
with:
mode: start
github-token: ${{ secrets.SLAB_ACTION_TOKEN }}
slab-url: ${{ secrets.SLAB_BASE_URL_PRE_PROD }}
job-secret: ${{ secrets.JOB_SECRET }}
backend: hyperstack
profile: gpu-bench
cuda-integer-multi-bit-benchmarks:
name: CUDA integer multi-bit benchmarks
needs: setup-ec2
runs-on: ${{ needs.setup-ec2.outputs.runner-name }}
timeout-minutes: 1440 # 24 hours
strategy:
fail-fast: false
# explicit include-based build matrix, of known valid options
matrix:
include:
- os: ubuntu-22.04
cuda: "12.2"
gcc: 11
env:
CUDA_PATH: /usr/local/cuda-${{ matrix.cuda }}
CMAKE_VERSION: 3.29.1
steps:
- name: Install dependencies
run: |
sudo apt update
sudo apt install -y checkinstall zlib1g-dev libssl-dev
wget https://github.com/Kitware/CMake/releases/download/v${{ env.CMAKE_VERSION }}/cmake-${{ env.CMAKE_VERSION }}.tar.gz
tar -zxvf cmake-${{ env.CMAKE_VERSION }}.tar.gz
cd cmake-${{ env.CMAKE_VERSION }}
./bootstrap
make -j"$(nproc)"
sudo make install
- name: Get benchmark date
run: |
echo "BENCH_DATE=$(date --iso-8601=seconds)" >> "${GITHUB_ENV}"
- name: Checkout tfhe-rs repo with tags
uses: actions/checkout@9bb56186c3b09b4f86b1c65136769dd318469633
with:
fetch-depth: 0
- name: Set up home
# "Install rust" step require root user to have a HOME directory which is not set.
run: |
echo "HOME=/home/ubuntu" >> "${GITHUB_ENV}"
- name: Install rust
uses: dtolnay/rust-toolchain@dc6353516c68da0f06325f42ad880f76a5e77ec9
with:
toolchain: nightly
- name: Export CUDA variables
if: ${{ !cancelled() }}
run: |
{
echo "CUDA_PATH=$CUDA_PATH";
echo "LD_LIBRARY_PATH=$CUDA_PATH/lib:$LD_LIBRARY_PATH";
echo "CUDACXX=/usr/local/cuda-${{ matrix.cuda }}/bin/nvcc";
} >> "${GITHUB_ENV}"
echo "$CUDA_PATH/bin" >> "${GITHUB_PATH}"
# Specify the correct host compilers
- name: Export gcc and g++ variables
if: ${{ !cancelled() }}
run: |
{
echo "CC=/usr/bin/gcc-${{ matrix.gcc }}";
echo "CXX=/usr/bin/g++-${{ matrix.gcc }}";
echo "CUDAHOSTCXX=/usr/bin/g++-${{ matrix.gcc }}";
} >> "${GITHUB_ENV}"
- name: Run multi-bit benchmarks with AVX512
run: |
make FAST_BENCH=TRUE BENCH_OP_FLAVOR=default bench_integer_multi_bit_gpu
- name: Parse benchmarks to csv
run: |
make PARSE_INTEGER_BENCH_CSV_FILE=${{ env.PARSE_INTEGER_BENCH_CSV_FILE }} \
parse_integer_benches
- name: Upload csv results artifact
uses: actions/upload-artifact@5d5d22a31266ced268874388b861e4b58bb5c2f3
with:
name: ${{ github.sha }}_csv_integer
path: ${{ env.PARSE_INTEGER_BENCH_CSV_FILE }}
- name: Parse results
run: |
COMMIT_DATE="$(git --no-pager show -s --format=%cd --date=iso8601-strict ${{ github.sha }})"
COMMIT_HASH="$(git describe --tags --dirty)"
python3 ./ci/benchmark_parser.py target/criterion ${{ env.RESULTS_FILENAME }} \
--database tfhe_rs \
--hardware "n2-H100x1" \
--backend gpu \
--project-version "${COMMIT_HASH}" \
--branch ${{ github.ref_name }} \
--commit-date "${COMMIT_DATE}" \
--bench-date "${{ env.BENCH_DATE }}" \
--walk-subdirs \
--name-suffix avx512 \
--throughput
- name: Upload parsed results artifact
uses: actions/upload-artifact@5d5d22a31266ced268874388b861e4b58bb5c2f3
with:
name: ${{ github.sha }}_integer
path: ${{ env.RESULTS_FILENAME }}
- name: Checkout Slab repo
uses: actions/checkout@9bb56186c3b09b4f86b1c65136769dd318469633
with:
repository: zama-ai/slab
path: slab
token: ${{ secrets.FHE_ACTIONS_TOKEN }}
- name: Send data to Slab
shell: bash
run: |
echo "Computing HMac on results file"
SIGNATURE="$(slab/scripts/hmac_calculator.sh ${{ env.RESULTS_FILENAME }} '${{ secrets.JOB_SECRET }}')"
echo "Sending results to Slab..."
curl -v -k \
-H "Content-Type: application/json" \
-H "X-Slab-Repository: ${{ github.repository }}" \
-H "X-Slab-Command: store_data_v2" \
-H "X-Hub-Signature-256: sha256=${SIGNATURE}" \
-d @${{ env.RESULTS_FILENAME }} \
${{ secrets.SLAB_URL }}
# FIXME This action needs docker to be installed on the machine beforehand.
# - name: Slack Notification
# if: ${{ !success() && !cancelled() }}
# continue-on-error: true
# uses: rtCamp/action-slack-notify@4e5fb42d249be6a45a298f3c9543b111b02f7907
# env:
# SLACK_COLOR: ${{ job.status }}
# SLACK_CHANNEL: ${{ secrets.SLACK_CHANNEL }}
# SLACK_ICON: https://pbs.twimg.com/profile_images/1274014582265298945/OjBKP9kn_400x400.png
# SLACK_MESSAGE: "Integer GPU benchmarks finished with status: ${{ job.status }}. (${{ env.ACTION_RUN_URL }})"
# SLACK_USERNAME: ${{ secrets.BOT_USERNAME }}
# SLACK_WEBHOOK: ${{ secrets.SLACK_WEBHOOK }}
teardown-ec2:
name: Teardown EC2 instance (cuda-multi-bit-benchmarks)
if: ${{ always() && needs.setup-ec2.result != 'skipped' }}
needs: [ setup-ec2, cuda-integer-multi-bit-benchmarks ]
runs-on: ubuntu-latest
steps:
- name: Stop instance
id: stop-instance
uses: zama-ai/slab-github-runner@1dced74825027fe3d481392163ed8fc56813fb5d
with:
mode: stop
github-token: ${{ secrets.SLAB_ACTION_TOKEN }}
slab-url: ${{ secrets.SLAB_BASE_URL_PRE_PROD }}
job-secret: ${{ secrets.JOB_SECRET }}
label: ${{ needs.setup-ec2.outputs.runner-name }}
- name: Slack Notification
if: ${{ failure() }}
continue-on-error: true
uses: rtCamp/action-slack-notify@4e5fb42d249be6a45a298f3c9543b111b02f7907
env:
SLACK_COLOR: ${{ job.status }}
SLACK_MESSAGE: "EC2 teardown (cuda-multi-bit-benchmarks) finished with status: ${{ job.status }}. (${{ env.ACTION_RUN_URL }})"

View File

@@ -14,9 +14,8 @@ on:
env:
CARGO_TERM_COLOR: always
RUSTFLAGS: "-C target-cpu=native"
RUST_BACKTRACE: "full"
RUST_MIN_STACK: "8388608"
ACTION_RUN_URL: ${{ github.server_url }}/${{ github.repository }}/actions/runs/${{ github.run_id }}
CARGO_PROFILE: release_lto_off
FAST_TESTS: "TRUE"
concurrency:
@@ -27,16 +26,15 @@ jobs:
cargo-builds:
if: ${{ (github.event_name == 'schedule' && github.repository == 'zama-ai/tfhe-rs') || github.event_name == 'workflow_dispatch' || contains(github.event.label.name, 'm1_test') }}
runs-on: ["self-hosted", "m1mac"]
# 12 hours, default is 6 hours, hopefully this is more than enough
timeout-minutes: 720
steps:
- uses: actions/checkout@9bb56186c3b09b4f86b1c65136769dd318469633
- uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608
- name: Install latest stable
uses: dtolnay/rust-toolchain@dc6353516c68da0f06325f42ad880f76a5e77ec9
uses: actions-rs/toolchain@16499b5e05bf2e26879000db0c1d13f7e13fa3af
with:
toolchain: stable
default: true
- name: Run pcc checks
run: |
@@ -74,10 +72,6 @@ jobs:
run: |
make test_concrete_csprng
- name: Run tfhe-zk-pok tests
run: |
make test_zk_pok
- name: Run core tests
run: |
make test_core_crypto
@@ -117,9 +111,10 @@ jobs:
run: |
make test_shortint_multi_bit_ci
- name: Run integer multi bit tests
run: |
make test_integer_multi_bit_ci
# # These multi bit integer tests are too slow on M1 with low core count and low RAM
# - name: Run integer multi bit tests
# run: |
# make test_integer_multi_bit_ci
remove_label:
name: Remove m1_test label
@@ -137,7 +132,7 @@ jobs:
- name: Slack Notification
if: ${{ needs.cargo-builds.result != 'skipped' }}
continue-on-error: true
uses: rtCamp/action-slack-notify@4e5fb42d249be6a45a298f3c9543b111b02f7907
uses: rtCamp/action-slack-notify@b24d75fe0e728a4bf9fc42ee217caa686d141ee8
env:
SLACK_COLOR: ${{ needs.cargo-builds.result }}
SLACK_CHANNEL: ${{ secrets.SLACK_CHANNEL }}

View File

@@ -30,7 +30,7 @@ jobs:
runs-on: ubuntu-latest
steps:
- name: Checkout
uses: actions/checkout@9bb56186c3b09b4f86b1c65136769dd318469633
uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608
with:
fetch-depth: 0
@@ -49,7 +49,7 @@ jobs:
- name: Publish web package
if: ${{ inputs.push_web_package }}
uses: JS-DevTools/npm-publish@19c28f1ef146469e409470805ea4279d47c3d35c
uses: JS-DevTools/npm-publish@fe72237be0920f7a0cafd6a966c9b929c9466e9b
with:
token: ${{ secrets.NPM_TOKEN }}
package: tfhe/pkg/package.json
@@ -65,7 +65,7 @@ jobs:
- name: Publish Node package
if: ${{ inputs.push_node_package }}
uses: JS-DevTools/npm-publish@19c28f1ef146469e409470805ea4279d47c3d35c
uses: JS-DevTools/npm-publish@fe72237be0920f7a0cafd6a966c9b929c9466e9b
with:
token: ${{ secrets.NPM_TOKEN }}
package: tfhe/pkg/package.json
@@ -74,7 +74,7 @@ jobs:
- name: Slack Notification
if: ${{ failure() }}
continue-on-error: true
uses: rtCamp/action-slack-notify@4e5fb42d249be6a45a298f3c9543b111b02f7907
uses: rtCamp/action-slack-notify@b24d75fe0e728a4bf9fc42ee217caa686d141ee8
env:
SLACK_COLOR: ${{ job.status }}
SLACK_CHANNEL: ${{ secrets.SLACK_CHANNEL }}

View File

@@ -18,7 +18,7 @@ jobs:
runs-on: ubuntu-latest
steps:
- name: Checkout
uses: actions/checkout@9bb56186c3b09b4f86b1c65136769dd318469633
uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608
with:
fetch-depth: 0
@@ -32,7 +32,7 @@ jobs:
- name: Slack Notification
if: ${{ failure() }}
continue-on-error: true
uses: rtCamp/action-slack-notify@4e5fb42d249be6a45a298f3c9543b111b02f7907
uses: rtCamp/action-slack-notify@b24d75fe0e728a4bf9fc42ee217caa686d141ee8
env:
SLACK_COLOR: ${{ job.status }}
SLACK_CHANNEL: ${{ secrets.SLACK_CHANNEL }}

View File

@@ -1,129 +0,0 @@
# Publish new release of tfhe-cuda-backend on crates.io.
name: Publish CUDA release
on:
workflow_dispatch:
inputs:
dry_run:
description: "Dry-run"
type: boolean
default: true
push_to_crates:
description: "Push to crate"
type: boolean
default: true
env:
ACTION_RUN_URL: ${{ github.server_url }}/${{ github.repository }}/actions/runs/${{ github.run_id }}
SLACK_CHANNEL: ${{ secrets.SLACK_CHANNEL }}
SLACK_ICON: https://pbs.twimg.com/profile_images/1274014582265298945/OjBKP9kn_400x400.png
SLACK_USERNAME: ${{ secrets.BOT_USERNAME }}
SLACK_WEBHOOK: ${{ secrets.SLACK_WEBHOOK }}
jobs:
setup-ec2:
name: Setup EC2 instance (publish-cuda-release)
runs-on: ubuntu-latest
outputs:
runner-name: ${{ steps.start-instance.outputs.label }}
steps:
- name: Start instance
id: start-instance
uses: zama-ai/slab-github-runner@1dced74825027fe3d481392163ed8fc56813fb5d
with:
mode: start
github-token: ${{ secrets.SLAB_ACTION_TOKEN }}
slab-url: ${{ secrets.SLAB_BASE_URL }}
job-secret: ${{ secrets.JOB_SECRET }}
backend: aws
profile: gpu-test
publish-cuda-release:
name: Publish CUDA Release
needs: setup-ec2
runs-on: ${{ needs.setup-ec2.outputs.runner-name }}
strategy:
fail-fast: false
# explicit include-based build matrix, of known valid options
matrix:
include:
- os: ubuntu-22.04
cuda: "12.2"
gcc: 9
env:
CUDA_PATH: /usr/local/cuda-${{ matrix.cuda }}
steps:
- name: Checkout
uses: actions/checkout@9bb56186c3b09b4f86b1c65136769dd318469633
with:
fetch-depth: 0
- name: Set up home
run: |
echo "HOME=/home/ubuntu" >> "${GITHUB_ENV}"
- name: Install latest stable
uses: dtolnay/rust-toolchain@dc6353516c68da0f06325f42ad880f76a5e77ec9
with:
toolchain: stable
- name: Export CUDA variables
if: ${{ !cancelled() }}
run: |
echo "$CUDA_PATH/bin" >> "${GITHUB_PATH}"
{
echo "CUDA_PATH=$CUDA_PATH";
echo "LD_LIBRARY_PATH=$CUDA_PATH/lib:$LD_LIBRARY_PATH";
echo "CUDACXX=/usr/local/cuda-${{ matrix.cuda }}/bin/nvcc";
} >> "${GITHUB_ENV}"
# Specify the correct host compilers
- name: Export gcc and g++ variables
if: ${{ !cancelled() }}
run: |
{
echo "CC=/usr/bin/gcc-${{ matrix.gcc }}";
echo "CXX=/usr/bin/g++-${{ matrix.gcc }}";
echo "CUDAHOSTCXX=/usr/bin/g++-${{ matrix.gcc }}";
echo "HOME=/home/ubuntu";
} >> "${GITHUB_ENV}"
- name: Publish crate.io package
if: ${{ inputs.push_to_crates }}
env:
CRATES_TOKEN: ${{ secrets.CARGO_REGISTRY_TOKEN }}
DRY_RUN: ${{ inputs.dry_run && '--dry-run' || '' }}
run: |
cargo publish -p tfhe-cuda-backend --token ${{ env.CRATES_TOKEN }} ${{ env.DRY_RUN }}
- name: Slack Notification
if: ${{ failure() }}
continue-on-error: true
uses: rtCamp/action-slack-notify@4e5fb42d249be6a45a298f3c9543b111b02f7907
env:
SLACK_COLOR: ${{ job.status }}
SLACK_MESSAGE: "tfhe-cuda-backend release finished with status: ${{ job.status }}. (${{ env.ACTION_RUN_URL }})"
teardown-ec2:
name: Teardown EC2 instance (publish-release)
if: ${{ always() && needs.setup-ec2.result != 'skipped' }}
needs: [ setup-ec2, publish-cuda-release ]
runs-on: ubuntu-latest
steps:
- name: Stop instance
id: stop-instance
uses: zama-ai/slab-github-runner@1dced74825027fe3d481392163ed8fc56813fb5d
with:
mode: stop
github-token: ${{ secrets.SLAB_ACTION_TOKEN }}
slab-url: ${{ secrets.SLAB_BASE_URL }}
job-secret: ${{ secrets.JOB_SECRET }}
label: ${{ needs.setup-ec2.outputs.runner-name }}
- name: Slack Notification
if: ${{ failure() }}
continue-on-error: true
uses: rtCamp/action-slack-notify@4e5fb42d249be6a45a298f3c9543b111b02f7907
env:
SLACK_COLOR: ${{ job.status }}
SLACK_MESSAGE: "EC2 teardown (publish-cuda-release) finished with status: ${{ job.status }}. (${{ env.ACTION_RUN_URL }})"

View File

@@ -17,14 +17,13 @@ jobs:
runs-on: ubuntu-latest
steps:
- name: Checkout tfhe-rs
uses: actions/checkout@9bb56186c3b09b4f86b1c65136769dd318469633
uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608
- name: Checkout lattice-estimator
uses: actions/checkout@9bb56186c3b09b4f86b1c65136769dd318469633
uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608
with:
repository: malb/lattice-estimator
path: lattice_estimator
ref: '53508253629d3b5d31a2ad110e85dc69391ccb95'
- name: Install Sage
run: |
@@ -42,7 +41,7 @@ jobs:
- name: Slack Notification
if: ${{ always() }}
continue-on-error: true
uses: rtCamp/action-slack-notify@4e5fb42d249be6a45a298f3c9543b111b02f7907
uses: rtCamp/action-slack-notify@b24d75fe0e728a4bf9fc42ee217caa686d141ee8
env:
SLACK_COLOR: ${{ job.status }}
SLACK_CHANNEL: ${{ secrets.SLACK_CHANNEL }}

View File

@@ -1,5 +1,5 @@
# Run core crypto benchmarks on an AWS instance and return parsed results to Slab CI bot.
name: Core crypto benchmarks
# Run PBS benchmarks on an AWS instance and return parsed results to Slab CI bot.
name: PBS benchmarks
on:
workflow_dispatch:
@@ -32,12 +32,10 @@ env:
CARGO_TERM_COLOR: always
RESULTS_FILENAME: parsed_benchmark_results_${{ github.sha }}.json
ACTION_RUN_URL: ${{ github.server_url }}/${{ github.repository }}/actions/runs/${{ github.run_id }}
RUST_BACKTRACE: "full"
RUST_MIN_STACK: "8388608"
jobs:
run-core-crypto-benchmarks:
name: Execute core crypto benchmarks in EC2
run-pbs-benchmarks:
name: Execute PBS benchmarks in EC2
runs-on: ${{ github.event.inputs.runner_name }}
if: ${{ !cancelled() }}
steps:
@@ -53,7 +51,7 @@ jobs:
echo "BENCH_DATE=$(date --iso-8601=seconds)" >> "${GITHUB_ENV}"
- name: Checkout tfhe-rs repo with tags
uses: actions/checkout@9bb56186c3b09b4f86b1c65136769dd318469633
uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608
with:
fetch-depth: 0
@@ -63,14 +61,22 @@ jobs:
echo "HOME=/home/ubuntu" >> "${GITHUB_ENV}"
- name: Install rust
uses: dtolnay/rust-toolchain@dc6353516c68da0f06325f42ad880f76a5e77ec9
uses: actions-rs/toolchain@16499b5e05bf2e26879000db0c1d13f7e13fa3af
with:
toolchain: nightly
override: true
- name: Run benchmarks with AVX512
- name: bench_ac2023_CJP
run: |
make bench_pbs
make bench_ks
make AVX512_SUPPORT=ON bench_ac2023_CJP
- name: bench_ac2023_stairKS
run: |
make AVX512_SUPPORT=ON bench_ac2023_stairKS
- name: bench_ac2023_fastKS
run: |
make AVX512_SUPPORT=ON bench_ac2023_fastKS
- name: Parse results
run: |
@@ -88,17 +94,17 @@ jobs:
--throughput
- name: Upload parsed results artifact
uses: actions/upload-artifact@5d5d22a31266ced268874388b861e4b58bb5c2f3
uses: actions/upload-artifact@a8a3f3ad30e3422c9c7b888a15615d19a852ae32
with:
name: ${{ github.sha }}_core_crypto
name: ${{ github.sha }}_pbs
path: ${{ env.RESULTS_FILENAME }}
- name: Checkout Slab repo
uses: actions/checkout@9bb56186c3b09b4f86b1c65136769dd318469633
uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608
with:
repository: zama-ai/slab
path: slab
token: ${{ secrets.FHE_ACTIONS_TOKEN }}
token: ${{ secrets.CONCRETE_ACTIONS_TOKEN }}
- name: Send data to Slab
shell: bash
@@ -117,11 +123,11 @@ jobs:
- name: Slack Notification
if: ${{ failure() }}
continue-on-error: true
uses: rtCamp/action-slack-notify@4e5fb42d249be6a45a298f3c9543b111b02f7907
uses: rtCamp/action-slack-notify@b24d75fe0e728a4bf9fc42ee217caa686d141ee8
env:
SLACK_COLOR: ${{ job.status }}
SLACK_CHANNEL: ${{ secrets.SLACK_CHANNEL }}
SLACK_ICON: https://pbs.twimg.com/profile_images/1274014582265298945/OjBKP9kn_400x400.png
SLACK_MESSAGE: "PBS benchmarks finished with status: ${{ job.status }}. (${{ env.ACTION_RUN_URL }})"
SLACK_MESSAGE: "PBS benchmarks failed. (${{ env.ACTION_RUN_URL }})"
SLACK_USERNAME: ${{ secrets.BOT_USERNAME }}
SLACK_WEBHOOK: ${{ secrets.SLACK_WEBHOOK }}

View File

@@ -24,8 +24,6 @@ env:
CARGO_TERM_COLOR: always
RESULTS_FILENAME: parsed_benchmark_results_${{ github.sha }}.json
ACTION_RUN_URL: ${{ github.server_url }}/${{ github.repository }}/actions/runs/${{ github.run_id }}
RUST_BACKTRACE: "full"
RUST_MIN_STACK: "8388608"
jobs:
run-shortint-benchmarks:
@@ -45,7 +43,7 @@ jobs:
echo "BENCH_DATE=$(date --iso-8601=seconds)" >> "${GITHUB_ENV}"
- name: Checkout tfhe-rs repo with tags
uses: actions/checkout@9bb56186c3b09b4f86b1c65136769dd318469633
uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608
with:
fetch-depth: 0
@@ -55,13 +53,14 @@ jobs:
echo "HOME=/home/ubuntu" >> "${GITHUB_ENV}"
- name: Install rust
uses: dtolnay/rust-toolchain@dc6353516c68da0f06325f42ad880f76a5e77ec9
uses: actions-rs/toolchain@16499b5e05bf2e26879000db0c1d13f7e13fa3af
with:
toolchain: nightly
override: true
- name: Run benchmarks with AVX512
run: |
make bench_shortint
make AVX512_SUPPORT=ON bench_shortint
- name: Parse results
run: |
@@ -89,17 +88,17 @@ jobs:
--append-results
- name: Upload parsed results artifact
uses: actions/upload-artifact@5d5d22a31266ced268874388b861e4b58bb5c2f3
uses: actions/upload-artifact@a8a3f3ad30e3422c9c7b888a15615d19a852ae32
with:
name: ${{ github.sha }}_shortint
path: ${{ env.RESULTS_FILENAME }}
- name: Checkout Slab repo
uses: actions/checkout@9bb56186c3b09b4f86b1c65136769dd318469633
uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608
with:
repository: zama-ai/slab
path: slab
token: ${{ secrets.FHE_ACTIONS_TOKEN }}
token: ${{ secrets.CONCRETE_ACTIONS_TOKEN }}
- name: Send data to Slab
shell: bash
@@ -118,11 +117,11 @@ jobs:
- name: Slack Notification
if: ${{ failure() }}
continue-on-error: true
uses: rtCamp/action-slack-notify@4e5fb42d249be6a45a298f3c9543b111b02f7907
uses: rtCamp/action-slack-notify@b24d75fe0e728a4bf9fc42ee217caa686d141ee8
env:
SLACK_COLOR: ${{ job.status }}
SLACK_CHANNEL: ${{ secrets.SLACK_CHANNEL }}
SLACK_ICON: https://pbs.twimg.com/profile_images/1274014582265298945/OjBKP9kn_400x400.png
SLACK_MESSAGE: "Shortint benchmarks finished with status: ${{ job.status }}. (${{ env.ACTION_RUN_URL }})"
SLACK_MESSAGE: "Shortint benchmarks failed. (${{ env.ACTION_RUN_URL }})"
SLACK_USERNAME: ${{ secrets.BOT_USERNAME }}
SLACK_WEBHOOK: ${{ secrets.SLACK_WEBHOOK }}

View File

@@ -32,8 +32,6 @@ env:
CARGO_TERM_COLOR: always
RESULTS_FILENAME: parsed_benchmark_results_${{ github.sha }}.json
ACTION_RUN_URL: ${{ github.server_url }}/${{ github.repository }}/actions/runs/${{ github.run_id }}
RUST_BACKTRACE: "full"
RUST_MIN_STACK: "8388608"
jobs:
shortint-benchmarks:
@@ -53,17 +51,15 @@ jobs:
echo "Request ID: ${{ inputs.request_id }}"
- name: Checkout tfhe-rs repo with tags
uses: actions/checkout@9bb56186c3b09b4f86b1c65136769dd318469633
uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608
with:
fetch-depth: 0
- name: Get benchmark details
run: |
{
echo "BENCH_DATE=$(date --iso-8601=seconds)";
echo "COMMIT_DATE=$(git --no-pager show -s --format=%cd --date=iso8601-strict ${{ github.sha }})";
echo "COMMIT_HASH=$(git describe --tags --dirty)";
} >> "${GITHUB_ENV}"
echo "BENCH_DATE=$(date --iso-8601=seconds)" >> "${GITHUB_ENV}"
echo "COMMIT_DATE=$(git --no-pager show -s --format=%cd --date=iso8601-strict ${{ github.sha }})" >> "${GITHUB_ENV}"
echo "COMMIT_HASH=$(git describe --tags --dirty)" >> "${GITHUB_ENV}"
- name: Set up home
# "Install rust" step require root user to have a HOME directory which is not set.
@@ -71,20 +67,21 @@ jobs:
echo "HOME=/home/ubuntu" >> "${GITHUB_ENV}"
- name: Install rust
uses: dtolnay/rust-toolchain@dc6353516c68da0f06325f42ad880f76a5e77ec9
uses: actions-rs/toolchain@16499b5e05bf2e26879000db0c1d13f7e13fa3af
with:
toolchain: nightly
override: true
- name: Checkout Slab repo
uses: actions/checkout@9bb56186c3b09b4f86b1c65136769dd318469633
uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608
with:
repository: zama-ai/slab
path: slab
token: ${{ secrets.FHE_ACTIONS_TOKEN }}
token: ${{ secrets.CONCRETE_ACTIONS_TOKEN }}
- name: Run benchmarks with AVX512
run: |
make BENCH_OP_FLAVOR=${{ matrix.op_flavor }} bench_shortint
make AVX512_SUPPORT=ON BENCH_OP_FLAVOR=${{ matrix.op_flavor }} bench_shortint
- name: Parse results
run: |
@@ -115,7 +112,7 @@ jobs:
--append-results
- name: Upload parsed results artifact
uses: actions/upload-artifact@5d5d22a31266ced268874388b861e4b58bb5c2f3
uses: actions/upload-artifact@a8a3f3ad30e3422c9c7b888a15615d19a852ae32
with:
name: ${{ github.sha }}_shortint_${{ matrix.op_flavor }}
path: ${{ env.RESULTS_FILENAME }}
@@ -142,11 +139,11 @@ jobs:
steps:
- name: Notify
continue-on-error: true
uses: rtCamp/action-slack-notify@4e5fb42d249be6a45a298f3c9543b111b02f7907
uses: rtCamp/action-slack-notify@b24d75fe0e728a4bf9fc42ee217caa686d141ee8
env:
SLACK_COLOR: ${{ job.status }}
SLACK_CHANNEL: ${{ secrets.SLACK_CHANNEL }}
SLACK_ICON: https://pbs.twimg.com/profile_images/1274014582265298945/OjBKP9kn_400x400.png
SLACK_MESSAGE: "Shortint full benchmarks finished with status: ${{ job.status }}. (${{ env.ACTION_RUN_URL }})"
SLACK_MESSAGE: "Shortint full benchmarks failed. (${{ env.ACTION_RUN_URL }})"
SLACK_USERNAME: ${{ secrets.BOT_USERNAME }}
SLACK_WEBHOOK: ${{ secrets.SLACK_WEBHOOK }}

View File

@@ -1,130 +0,0 @@
# Run signed integer benchmarks on an AWS instance and return parsed results to Slab CI bot.
name: Signed Integer benchmarks
on:
workflow_dispatch:
inputs:
instance_id:
description: "Instance ID"
type: string
instance_image_id:
description: "Instance AMI ID"
type: string
instance_type:
description: "Instance product type"
type: string
runner_name:
description: "Action runner name"
type: string
request_id:
description: "Slab request ID"
type: string
env:
CARGO_TERM_COLOR: always
RESULTS_FILENAME: parsed_benchmark_results_${{ github.sha }}.json
PARSE_INTEGER_BENCH_CSV_FILE: tfhe_rs_integer_benches_${{ github.sha }}.csv
ACTION_RUN_URL: ${{ github.server_url }}/${{ github.repository }}/actions/runs/${{ github.run_id }}
RUST_BACKTRACE: "full"
RUST_MIN_STACK: "8388608"
jobs:
run-integer-benchmarks:
name: Execute signed integer benchmarks in EC2
runs-on: ${{ github.event.inputs.runner_name }}
if: ${{ !cancelled() }}
steps:
- name: Instance configuration used
run: |
echo "IDs: ${{ inputs.instance_id }}"
echo "AMI: ${{ inputs.instance_image_id }}"
echo "Type: ${{ inputs.instance_type }}"
echo "Request ID: ${{ inputs.request_id }}"
- name: Get benchmark date
run: |
echo "BENCH_DATE=$(date --iso-8601=seconds)" >> "${GITHUB_ENV}"
- name: Checkout tfhe-rs repo with tags
uses: actions/checkout@9bb56186c3b09b4f86b1c65136769dd318469633
with:
fetch-depth: 0
- name: Set up home
# "Install rust" step require root user to have a HOME directory which is not set.
run: |
echo "HOME=/home/ubuntu" >> "${GITHUB_ENV}"
- name: Install rust
uses: dtolnay/rust-toolchain@dc6353516c68da0f06325f42ad880f76a5e77ec9
with:
toolchain: nightly
- name: Run benchmarks with AVX512
run: |
make FAST_BENCH=TRUE bench_signed_integer
- name: Parse benchmarks to csv
run: |
make PARSE_INTEGER_BENCH_CSV_FILE=${{ env.PARSE_INTEGER_BENCH_CSV_FILE }} \
parse_integer_benches
- name: Upload csv results artifact
uses: actions/upload-artifact@5d5d22a31266ced268874388b861e4b58bb5c2f3
with:
name: ${{ github.sha }}_csv_integer
path: ${{ env.PARSE_INTEGER_BENCH_CSV_FILE }}
- name: Parse results
run: |
COMMIT_DATE="$(git --no-pager show -s --format=%cd --date=iso8601-strict ${{ github.sha }})"
COMMIT_HASH="$(git describe --tags --dirty)"
python3 ./ci/benchmark_parser.py target/criterion ${{ env.RESULTS_FILENAME }} \
--database tfhe_rs \
--hardware ${{ inputs.instance_type }} \
--project-version "${COMMIT_HASH}" \
--branch ${{ github.ref_name }} \
--commit-date "${COMMIT_DATE}" \
--bench-date "${{ env.BENCH_DATE }}" \
--walk-subdirs \
--name-suffix avx512 \
--throughput
- name: Upload parsed results artifact
uses: actions/upload-artifact@5d5d22a31266ced268874388b861e4b58bb5c2f3
with:
name: ${{ github.sha }}_integer
path: ${{ env.RESULTS_FILENAME }}
- name: Checkout Slab repo
uses: actions/checkout@9bb56186c3b09b4f86b1c65136769dd318469633
with:
repository: zama-ai/slab
path: slab
token: ${{ secrets.FHE_ACTIONS_TOKEN }}
- name: Send data to Slab
shell: bash
run: |
echo "Computing HMac on results file"
SIGNATURE="$(slab/scripts/hmac_calculator.sh ${{ env.RESULTS_FILENAME }} '${{ secrets.JOB_SECRET }}')"
echo "Sending results to Slab..."
curl -v -k \
-H "Content-Type: application/json" \
-H "X-Slab-Repository: ${{ github.repository }}" \
-H "X-Slab-Command: store_data_v2" \
-H "X-Hub-Signature-256: sha256=${SIGNATURE}" \
-d @${{ env.RESULTS_FILENAME }} \
${{ secrets.SLAB_URL }}
- name: Slack Notification
if: ${{ failure() }}
continue-on-error: true
uses: rtCamp/action-slack-notify@4e5fb42d249be6a45a298f3c9543b111b02f7907
env:
SLACK_COLOR: ${{ job.status }}
SLACK_CHANNEL: ${{ secrets.SLACK_CHANNEL }}
SLACK_ICON: https://pbs.twimg.com/profile_images/1274014582265298945/OjBKP9kn_400x400.png
SLACK_MESSAGE: "Signed integer benchmarks finished with status: ${{ job.status }}. (${{ env.ACTION_RUN_URL }})"
SLACK_USERNAME: ${{ secrets.BOT_USERNAME }}
SLACK_WEBHOOK: ${{ secrets.SLACK_WEBHOOK }}

View File

@@ -1,136 +0,0 @@
# Run all signed integer benchmarks on an AWS instance and return parsed results to Slab CI bot.
name: Signed Integer full benchmarks
on:
workflow_dispatch:
inputs:
instance_id:
description: "Instance ID"
type: string
instance_image_id:
description: "Instance AMI ID"
type: string
instance_type:
description: "Instance product type"
type: string
runner_name:
description: "Action runner name"
type: string
request_id:
description: "Slab request ID"
type: string
user_inputs:
description: "Type of benchmarks to run"
type: string
default: "weekly_benchmarks"
env:
CARGO_TERM_COLOR: always
RESULTS_FILENAME: parsed_benchmark_results_${{ github.sha }}.json
ACTION_RUN_URL: ${{ github.server_url }}/${{ github.repository }}/actions/runs/${{ github.run_id }}
RUST_BACKTRACE: "full"
RUST_MIN_STACK: "8388608"
jobs:
integer-benchmarks:
name: Execute signed integer benchmarks for all operations flavor
runs-on: ${{ github.event.inputs.runner_name }}
if: ${{ !cancelled() }}
continue-on-error: true
timeout-minutes: 1440 # 24 hours
strategy:
max-parallel: 1
matrix:
command: [ integer, integer_multi_bit ]
op_flavor: [ default, unchecked ]
steps:
- name: Instance configuration used
run: |
echo "IDs: ${{ inputs.instance_id }}"
echo "AMI: ${{ inputs.instance_image_id }}"
echo "Type: ${{ inputs.instance_type }}"
echo "Request ID: ${{ inputs.request_id }}"
- name: Checkout tfhe-rs repo with tags
uses: actions/checkout@9bb56186c3b09b4f86b1c65136769dd318469633
with:
fetch-depth: 0
- name: Get benchmark details
run: |
{
echo "BENCH_DATE=$(date --iso-8601=seconds)";
echo "COMMIT_DATE=$(git --no-pager show -s --format=%cd --date=iso8601-strict ${{ github.sha }})";
echo "COMMIT_HASH=$(git describe --tags --dirty)";
} >> "${GITHUB_ENV}"
- name: Set up home
# "Install rust" step require root user to have a HOME directory which is not set.
run: |
echo "HOME=/home/ubuntu" >> "${GITHUB_ENV}"
- name: Install rust
uses: dtolnay/rust-toolchain@dc6353516c68da0f06325f42ad880f76a5e77ec9
with:
toolchain: nightly
- name: Checkout Slab repo
uses: actions/checkout@9bb56186c3b09b4f86b1c65136769dd318469633
with:
repository: zama-ai/slab
path: slab
token: ${{ secrets.FHE_ACTIONS_TOKEN }}
- name: Run benchmarks with AVX512
run: |
make BENCH_OP_FLAVOR=${{ matrix.op_flavor }} bench_signed_${{ matrix.command }}
- name: Parse results
run: |
python3 ./ci/benchmark_parser.py target/criterion ${{ env.RESULTS_FILENAME }} \
--database tfhe_rs \
--hardware ${{ inputs.instance_type }} \
--project-version "${{ env.COMMIT_HASH }}" \
--branch ${{ github.ref_name }} \
--commit-date "${{ env.COMMIT_DATE }}" \
--bench-date "${{ env.BENCH_DATE }}" \
--walk-subdirs \
--name-suffix avx512 \
--throughput
- name: Upload parsed results artifact
uses: actions/upload-artifact@5d5d22a31266ced268874388b861e4b58bb5c2f3
with:
name: ${{ github.sha }}_${{ matrix.command }}_${{ matrix.op_flavor }}
path: ${{ env.RESULTS_FILENAME }}
- name: Send data to Slab
shell: bash
run: |
echo "Computing HMac on results file"
SIGNATURE="$(slab/scripts/hmac_calculator.sh ${{ env.RESULTS_FILENAME }} '${{ secrets.JOB_SECRET }}')"
echo "Sending results to Slab..."
curl -v -k \
-H "Content-Type: application/json" \
-H "X-Slab-Repository: ${{ github.repository }}" \
-H "X-Slab-Command: store_data_v2" \
-H "X-Hub-Signature-256: sha256=${SIGNATURE}" \
-d @${{ env.RESULTS_FILENAME }} \
${{ secrets.SLAB_URL }}
slack-notification:
name: Slack Notification
runs-on: ${{ github.event.inputs.runner_name }}
if: ${{ failure() }}
needs: integer-benchmarks
steps:
- name: Notify
continue-on-error: true
uses: rtCamp/action-slack-notify@4e5fb42d249be6a45a298f3c9543b111b02f7907
env:
SLACK_COLOR: ${{ job.status }}
SLACK_CHANNEL: ${{ secrets.SLACK_CHANNEL }}
SLACK_ICON: https://pbs.twimg.com/profile_images/1274014582265298945/OjBKP9kn_400x400.png
SLACK_MESSAGE: "Signed integer full benchmarks finished with status: ${{ job.status }}. (${{ env.ACTION_RUN_URL }})"
SLACK_USERNAME: ${{ secrets.BOT_USERNAME }}
SLACK_WEBHOOK: ${{ secrets.SLACK_WEBHOOK }}

View File

@@ -1,130 +0,0 @@
# Run signed integer benchmarks with multi-bit cryptographic parameters on an AWS instance and return parsed results to Slab CI bot.
name: Signed Integer Multi-bit benchmarks
on:
workflow_dispatch:
inputs:
instance_id:
description: "Instance ID"
type: string
instance_image_id:
description: "Instance AMI ID"
type: string
instance_type:
description: "Instance product type"
type: string
runner_name:
description: "Action runner name"
type: string
request_id:
description: "Slab request ID"
type: string
env:
CARGO_TERM_COLOR: always
RESULTS_FILENAME: parsed_benchmark_results_${{ github.sha }}.json
PARSE_INTEGER_BENCH_CSV_FILE: tfhe_rs_integer_benches_${{ github.sha }}.csv
ACTION_RUN_URL: ${{ github.server_url }}/${{ github.repository }}/actions/runs/${{ github.run_id }}
RUST_BACKTRACE: "full"
RUST_MIN_STACK: "8388608"
jobs:
run-integer-benchmarks:
name: Execute signed integer multi-bit benchmarks in EC2
runs-on: ${{ github.event.inputs.runner_name }}
if: ${{ !cancelled() }}
steps:
- name: Instance configuration used
run: |
echo "IDs: ${{ inputs.instance_id }}"
echo "AMI: ${{ inputs.instance_image_id }}"
echo "Type: ${{ inputs.instance_type }}"
echo "Request ID: ${{ inputs.request_id }}"
- name: Get benchmark date
run: |
echo "BENCH_DATE=$(date --iso-8601=seconds)" >> "${GITHUB_ENV}"
- name: Checkout tfhe-rs repo with tags
uses: actions/checkout@9bb56186c3b09b4f86b1c65136769dd318469633
with:
fetch-depth: 0
- name: Set up home
# "Install rust" step require root user to have a HOME directory which is not set.
run: |
echo "HOME=/home/ubuntu" >> "${GITHUB_ENV}"
- name: Install rust
uses: dtolnay/rust-toolchain@dc6353516c68da0f06325f42ad880f76a5e77ec9
with:
toolchain: nightly
- name: Run multi-bit benchmarks with AVX512
run: |
make FAST_BENCH=TRUE bench_signed_integer_multi_bit
- name: Parse benchmarks to csv
run: |
make PARSE_INTEGER_BENCH_CSV_FILE=${{ env.PARSE_INTEGER_BENCH_CSV_FILE }} \
parse_integer_benches
- name: Upload csv results artifact
uses: actions/upload-artifact@5d5d22a31266ced268874388b861e4b58bb5c2f3
with:
name: ${{ github.sha }}_csv_integer
path: ${{ env.PARSE_INTEGER_BENCH_CSV_FILE }}
- name: Parse results
run: |
COMMIT_DATE="$(git --no-pager show -s --format=%cd --date=iso8601-strict ${{ github.sha }})"
COMMIT_HASH="$(git describe --tags --dirty)"
python3 ./ci/benchmark_parser.py target/criterion ${{ env.RESULTS_FILENAME }} \
--database tfhe_rs \
--hardware ${{ inputs.instance_type }} \
--project-version "${COMMIT_HASH}" \
--branch ${{ github.ref_name }} \
--commit-date "${COMMIT_DATE}" \
--bench-date "${{ env.BENCH_DATE }}" \
--walk-subdirs \
--name-suffix avx512 \
--throughput
- name: Upload parsed results artifact
uses: actions/upload-artifact@5d5d22a31266ced268874388b861e4b58bb5c2f3
with:
name: ${{ github.sha }}_integer
path: ${{ env.RESULTS_FILENAME }}
- name: Checkout Slab repo
uses: actions/checkout@9bb56186c3b09b4f86b1c65136769dd318469633
with:
repository: zama-ai/slab
path: slab
token: ${{ secrets.FHE_ACTIONS_TOKEN }}
- name: Send data to Slab
shell: bash
run: |
echo "Computing HMac on results file"
SIGNATURE="$(slab/scripts/hmac_calculator.sh ${{ env.RESULTS_FILENAME }} '${{ secrets.JOB_SECRET }}')"
echo "Sending results to Slab..."
curl -v -k \
-H "Content-Type: application/json" \
-H "X-Slab-Repository: ${{ github.repository }}" \
-H "X-Slab-Command: store_data_v2" \
-H "X-Hub-Signature-256: sha256=${SIGNATURE}" \
-d @${{ env.RESULTS_FILENAME }} \
${{ secrets.SLAB_URL }}
- name: Slack Notification
if: ${{ failure() }}
continue-on-error: true
uses: rtCamp/action-slack-notify@4e5fb42d249be6a45a298f3c9543b111b02f7907
env:
SLACK_COLOR: ${{ job.status }}
SLACK_CHANNEL: ${{ secrets.SLACK_CHANNEL }}
SLACK_ICON: https://pbs.twimg.com/profile_images/1274014582265298945/OjBKP9kn_400x400.png
SLACK_MESSAGE: "Signed integer benchmarks finished with status: ${{ job.status }}. (${{ env.ACTION_RUN_URL }})"
SLACK_USERNAME: ${{ secrets.BOT_USERNAME }}
SLACK_WEBHOOK: ${{ secrets.SLACK_WEBHOOK }}

View File

@@ -20,24 +20,12 @@ on:
description: "Run integer benches"
type: boolean
default: true
signed_integer_bench:
description: "Run signed integer benches"
type: boolean
default: true
integer_multi_bit_bench:
description: "Run integer multi bit benches"
type: boolean
default: true
signed_integer_multi_bit_bench:
description: "Run signed integer multi bit benches"
type: boolean
default: true
core_crypto_bench:
description: "Run core crypto benches"
type: boolean
default: true
core_crypto_gpu_bench:
description: "Run core crypto benches on GPU"
pbs_bench:
description: "Run PBS benches"
type: boolean
default: true
wasm_client_bench:
@@ -50,21 +38,17 @@ jobs:
if: ${{ (github.event_name == 'push' && github.repository == 'zama-ai/tfhe-rs') || github.event_name == 'workflow_dispatch' }}
strategy:
matrix:
command: [ boolean_bench, shortint_bench,
integer_bench, integer_multi_bit_bench,
signed_integer_bench, signed_integer_multi_bit_bench,
integer_gpu_bench, integer_multi_bit_gpu_bench,
core_crypto_bench, core_crypto_gpu_bench, wasm_client_bench ]
command: [boolean_bench, shortint_bench, integer_bench, integer_multi_bit_bench, pbs_bench, wasm_client_bench]
runs-on: ubuntu-latest
steps:
- name: Checkout tfhe-rs
uses: actions/checkout@9bb56186c3b09b4f86b1c65136769dd318469633
uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608
with:
fetch-depth: 0
- name: Check for file changes
id: changed-files
uses: tj-actions/changed-files@2d756ea4c53f7f6b397767d8723b3a10a9f35bf2
uses: tj-actions/changed-files@408093d9ff9c134c33b974e0722ce06b9d6e8263
with:
files_yaml: |
common_benches:
@@ -85,37 +69,27 @@ jobs:
integer_bench:
- tfhe/src/shortint/**
- tfhe/src/integer/**
- tfhe/benches/integer/bench.rs
- tfhe/benches/integer/**
- .github/workflows/integer_benchmark.yml
integer_multi_bit_bench:
- tfhe/src/shortint/**
- tfhe/src/integer/**
- tfhe/benches/integer/bench.rs
- .github/workflows/integer_multi_bit_benchmark.yml
signed_integer_bench:
- tfhe/src/shortint/**
- tfhe/src/integer/**
- tfhe/benches/integer/signed_bench.rs
- .github/workflows/signed_integer_benchmark.yml
signed_integer_multi_bit_bench:
- tfhe/src/shortint/**
- tfhe/src/integer/**
- tfhe/benches/integer/signed_bench.rs
- .github/workflows/signed_integer_multi_bit_benchmark.yml
core_crypto_bench:
- tfhe/benches/integer/**
- .github/workflows/integer_benchmark.yml
pbs_bench:
- tfhe/src/core_crypto/**
- tfhe/benches/core_crypto/**
- .github/workflows/core_crypto_benchmark.yml
- .github/workflows/pbs_benchmark.yml
wasm_client_bench:
- tfhe/web_wasm_parallel_tests/**
- .github/workflows/wasm_client_benchmark.yml
- name: Checkout Slab repo
uses: actions/checkout@9bb56186c3b09b4f86b1c65136769dd318469633
uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608
with:
repository: zama-ai/slab
path: slab
token: ${{ secrets.FHE_ACTIONS_TOKEN }}
token: ${{ secrets.CONCRETE_ACTIONS_TOKEN }}
- name: Start AWS job in Slab
# If manually triggered check that the current bench has been requested

View File

@@ -24,22 +24,20 @@ jobs:
if: ${{ (github.event_name == 'schedule' && github.repository == 'zama-ai/tfhe-rs') || github.event_name == 'workflow_dispatch' }}
strategy:
matrix:
command: [ boolean_bench, shortint_full_bench,
integer_full_bench, signed_integer_full_bench, integer_gpu_full_bench,
core_crypto_bench, core_crypto_gpu_bench, wasm_client_bench ]
command: [ boolean_bench, shortint_full_bench, integer_full_bench, pbs_bench, wasm_client_bench ]
runs-on: ubuntu-latest
steps:
- name: Checkout tfhe-rs
uses: actions/checkout@9bb56186c3b09b4f86b1c65136769dd318469633
uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608
with:
fetch-depth: 0
- name: Checkout Slab repo
uses: actions/checkout@9bb56186c3b09b4f86b1c65136769dd318469633
uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608
with:
repository: zama-ai/slab
path: slab
token: ${{ secrets.FHE_ACTIONS_TOKEN }}
token: ${{ secrets.CONCRETE_ACTIONS_TOKEN }}
- name: Set benchmarks type as weekly
if: (github.event_name == 'workflow_dispatch' && inputs.benchmark_type == 'weekly') || github.event.schedule == '0 1 * * 6'

View File

@@ -13,11 +13,11 @@ jobs:
runs-on: ubuntu-latest
steps:
- name: Checkout repo
uses: actions/checkout@9bb56186c3b09b4f86b1c65136769dd318469633
uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608
with:
fetch-depth: 0
- name: Save repo
uses: actions/upload-artifact@5d5d22a31266ced268874388b861e4b58bb5c2f3
uses: actions/upload-artifact@a8a3f3ad30e3422c9c7b888a15615d19a852ae32
with:
name: repo-archive
path: '.'
@@ -26,12 +26,12 @@ jobs:
with:
source_repo: "zama-ai/tfhe-rs"
source_branch: "main"
destination_repo: "https://${{ secrets.BOT_USERNAME }}:${{ secrets.FHE_ACTIONS_TOKEN }}@github.com/${{ secrets.SYNC_DEST_REPO }}"
destination_repo: "https://${{ secrets.BOT_USERNAME }}:${{ secrets.CONCRETE_ACTIONS_TOKEN }}@github.com/${{ secrets.SYNC_DEST_REPO }}"
destination_branch: "main"
- name: git-sync tags
uses: wei/git-sync@55c6b63b4f21607da0e9877ca9b4d11a29fc6d83
with:
source_repo: "zama-ai/tfhe-rs"
source_branch: "refs/tags/*"
destination_repo: "https://${{ secrets.BOT_USERNAME }}:${{ secrets.FHE_ACTIONS_TOKEN }}@github.com/${{ secrets.SYNC_DEST_REPO }}"
destination_repo: "https://${{ secrets.BOT_USERNAME }}:${{ secrets.CONCRETE_ACTIONS_TOKEN }}@github.com/${{ secrets.SYNC_DEST_REPO }}"
destination_branch: "refs/tags/*"

View File

@@ -0,0 +1,54 @@
# Trigger an AWS build each time commits are pushed to a pull request.
name: PR AWS build trigger
on:
pull_request:
pull_request_review:
types: [submitted]
jobs:
trigger-tests:
runs-on: ubuntu-latest
permissions:
pull-requests: write
steps:
- name: Get current labels
uses: snnaplab/get-labels-action@f426df40304808ace3b5282d4f036515f7609576
- name: Remove approved label
if: ${{ github.event_name == 'pull_request' && contains(fromJSON(env.LABELS), 'approved') }}
uses: actions-ecosystem/action-remove-labels@2ce5d41b4b6aa8503e285553f75ed56e0a40bae0
with:
github_token: ${{ secrets.GITHUB_TOKEN }}
labels: approved
- name: Launch fast tests
if: ${{ github.event_name == 'pull_request' }}
uses: mshick/add-pr-comment@a65df5f64fc741e91c59b8359a4bc56e57aaf5b1
with:
allow-repeats: true
message: |
@slab-ci cpu_fast_test
- name: Add approved label
uses: actions-ecosystem/action-add-labels@18f1af5e3544586314bbe15c0273249c770b2daf
if: ${{ github.event_name == 'pull_request_review' && github.event.review.state == 'approved' && !contains(fromJSON(env.LABELS), 'approved') }}
with:
github_token: ${{ secrets.GITHUB_TOKEN }}
labels: approved
# PR label 'approved' presence is checked to avoid running the full test suite several times
# in case of multiple approvals without new commits in between.
- name: Launch full tests suite
if: ${{ github.event_name == 'pull_request_review' && github.event.review.state == 'approved' && !contains(fromJSON(env.LABELS), 'approved') }}
uses: mshick/add-pr-comment@a65df5f64fc741e91c59b8359a4bc56e57aaf5b1
with:
allow-repeats: true
message: |
Pull Request has been approved :tada:
Launching full test suite...
@slab-ci cpu_test
@slab-ci cpu_integer_test
@slab-ci cpu_multi_bit_test
@slab-ci cpu_wasm_test
@slab-ci csprng_randomness_testing

View File

@@ -32,8 +32,6 @@ env:
CARGO_TERM_COLOR: always
RESULTS_FILENAME: parsed_benchmark_results_${{ github.sha }}.json
ACTION_RUN_URL: ${{ github.server_url }}/${{ github.repository }}/actions/runs/${{ github.run_id }}
RUST_BACKTRACE: "full"
RUST_MIN_STACK: "8388608"
jobs:
run-wasm-client-benchmarks:
@@ -53,7 +51,7 @@ jobs:
echo "BENCH_DATE=$(date --iso-8601=seconds)" >> "${GITHUB_ENV}"
- name: Checkout tfhe-rs repo with tags
uses: actions/checkout@9bb56186c3b09b4f86b1c65136769dd318469633
uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608
with:
fetch-depth: 0
@@ -63,9 +61,10 @@ jobs:
echo "HOME=/home/ubuntu" >> "${GITHUB_ENV}"
- name: Install rust
uses: dtolnay/rust-toolchain@dc6353516c68da0f06325f42ad880f76a5e77ec9
uses: actions-rs/toolchain@16499b5e05bf2e26879000db0c1d13f7e13fa3af
with:
toolchain: nightly
override: true
- name: Run benchmarks
run: |
@@ -98,17 +97,17 @@ jobs:
--append-results
- name: Upload parsed results artifact
uses: actions/upload-artifact@5d5d22a31266ced268874388b861e4b58bb5c2f3
uses: actions/upload-artifact@a8a3f3ad30e3422c9c7b888a15615d19a852ae32
with:
name: ${{ github.sha }}_wasm
path: ${{ env.RESULTS_FILENAME }}
- name: Checkout Slab repo
uses: actions/checkout@9bb56186c3b09b4f86b1c65136769dd318469633
uses: actions/checkout@8ade135a41bc03ea155e62e844d188df1ea18608
with:
repository: zama-ai/slab
path: slab
token: ${{ secrets.FHE_ACTIONS_TOKEN }}
token: ${{ secrets.CONCRETE_ACTIONS_TOKEN }}
- name: Send data to Slab
shell: bash
@@ -127,11 +126,11 @@ jobs:
- name: Slack Notification
if: ${{ failure() }}
continue-on-error: true
uses: rtCamp/action-slack-notify@4e5fb42d249be6a45a298f3c9543b111b02f7907
uses: rtCamp/action-slack-notify@b24d75fe0e728a4bf9fc42ee217caa686d141ee8
env:
SLACK_COLOR: ${{ job.status }}
SLACK_CHANNEL: ${{ secrets.SLACK_CHANNEL }}
SLACK_ICON: https://pbs.twimg.com/profile_images/1274014582265298945/OjBKP9kn_400x400.png
SLACK_MESSAGE: "WASM benchmarks finished with status: ${{ job.status }}. (${{ env.ACTION_RUN_URL }})"
SLACK_MESSAGE: "WASM benchmarks failed. (${{ env.ACTION_RUN_URL }})"
SLACK_USERNAME: ${{ secrets.BOT_USERNAME }}
SLACK_WEBHOOK: ${{ secrets.SLACK_WEBHOOK }}

9
.gitignore vendored
View File

@@ -3,9 +3,9 @@ target/
.vscode/
# Path we use for internal-keycache during tests
/keys/
./keys/
# In case of symlinked keys
/keys
./keys
**/Cargo.lock
**/*.bin
@@ -18,7 +18,4 @@ target/
dieharder_run.log
# Coverage reports
/coverage/
# Cuda local build
backends/tfhe-cuda-backend/cuda/cmake-build-debug/
./coverage/

View File

@@ -1,13 +1,6 @@
[workspace]
resolver = "2"
members = [
"tfhe",
"tfhe-zk-pok",
"tasks",
"apps/trivium",
"concrete-csprng",
"backends/tfhe-cuda-backend",
]
members = ["tfhe", "tasks", "apps/trivium", "concrete-csprng"]
[profile.bench]
lto = "fat"
@@ -24,4 +17,3 @@ lto = "off"
inherits = "dev"
opt-level = 3
lto = "off"
debug-assertions = false

View File

@@ -1,6 +1,6 @@
BSD 3-Clause Clear License
Copyright © 2024 ZAMA.
Copyright © 2023 ZAMA.
All rights reserved.
Redistribution and use in source and binary forms, with or without modification,

433
Makefile
View File

@@ -3,7 +3,6 @@ OS:=$(shell uname)
RS_CHECK_TOOLCHAIN:=$(shell cat toolchain.txt | tr -d '\n')
CARGO_RS_CHECK_TOOLCHAIN:=+$(RS_CHECK_TOOLCHAIN)
TARGET_ARCH_FEATURE:=$(shell ./scripts/get_arch_feature.sh)
CPU_COUNT=$(shell ./scripts/cpu_count.sh)
RS_BUILD_TOOLCHAIN:=stable
CARGO_RS_BUILD_TOOLCHAIN:=+$(RS_BUILD_TOOLCHAIN)
CARGO_PROFILE?=release
@@ -19,13 +18,7 @@ FAST_BENCH?=FALSE
BENCH_OP_FLAVOR?=DEFAULT
NODE_VERSION=20
FORWARD_COMPAT?=OFF
# sed: -n, do not print input stream, -e means a script/expression
# 1,/version/ indicates from the first line, to the line matching version at the start of the line
# p indicates to print, so we keep only the start of the Cargo.toml until we hit the first version
# entry which should be the version of tfhe
TFHE_CURRENT_VERSION:=\
$(shell sed -n -e '1,/^version/p' tfhe/Cargo.toml | \
grep '^version[[:space:]]*=' | cut -d '=' -f 2 | xargs)
TFHE_CURRENT_VERSION:=$(shell grep '^version[[:space:]]*=' tfhe/Cargo.toml | cut -d '=' -f 2 | xargs)
# Cargo has a hard time distinguishing between our package from the workspace and a package that
# could be a dependency, so we build an unambiguous spec here
TFHE_SPEC:=tfhe@$(TFHE_CURRENT_VERSION)
@@ -61,10 +54,6 @@ endif
REGEX_STRING?=''
REGEX_PATTERN?=''
# tfhe-cuda-backend
TFHECUDA_SRC=backends/tfhe-cuda-backend/cuda
TFHECUDA_BUILD=$(TFHECUDA_SRC)/build
# Exclude these files from coverage reports
define COVERAGE_EXCLUDED_FILES
--exclude-files apps/trivium/src/trivium/* \
@@ -120,12 +109,7 @@ install_wasm_pack: install_rs_build_toolchain
.PHONY: install_node # Install last version of NodeJS via nvm
install_node:
curl -o nvm_install.sh https://raw.githubusercontent.com/nvm-sh/nvm/v0.39.3/install.sh
@echo "2ed5e94ba12434370f0358800deb69f514e8bce90f13beb0e1b241d42c6abafd nvm_install.sh" > nvm_checksum
@sha256sum -c nvm_checksum
@rm nvm_checksum
$(SHELL) nvm_install.sh
@rm nvm_install.sh
curl -o- https://raw.githubusercontent.com/nvm-sh/nvm/v0.39.3/install.sh | $(SHELL)
source ~/.bashrc
$(SHELL) -i -c 'nvm install $(NODE_VERSION)' || \
( echo "Unable to install node, unknown error." && exit 1 )
@@ -148,65 +132,16 @@ install_tarpaulin: install_rs_build_toolchain
.PHONY: check_linelint_installed # Check if linelint newline linter is installed
check_linelint_installed:
@printf "\n" | linelint - > /dev/null 2>&1 || \
( echo "Unable to locate linelint. Try installing it: https://github.com/fernandrone/linelint/releases" && exit 1 )
.PHONY: check_actionlint_installed # Check if actionlint workflow linter is installed
check_actionlint_installed:
@actionlint --version > /dev/null 2>&1 || \
( echo "Unable to locate actionlint. Try installing it: https://github.com/rhysd/actionlint/releases" && exit 1 )
.PHONY: check_nvm_installed # Check if Node Version Manager is installed
check_nvm_installed:
@source ~/.nvm/nvm.sh && nvm --version > /dev/null 2>&1 || \
( echo "Unable to locate Node. Run 'make install_node'" && exit 1 )
( echo "Unable to locate linelint. Try installing it: https://github.com/fernandrone/linelint/releases" && exit 1 )
.PHONY: fmt # Format rust code
fmt: install_rs_check_toolchain
cargo "$(CARGO_RS_CHECK_TOOLCHAIN)" fmt
.PHONY: fmt_js # Format javascript code
fmt_js: check_nvm_installed
source ~/.nvm/nvm.sh && \
nvm install $(NODE_VERSION) && \
nvm use $(NODE_VERSION) && \
$(MAKE) -C tfhe/web_wasm_parallel_tests fmt
.PHONY: fmt_gpu # Format rust and cuda code
fmt_gpu: install_rs_check_toolchain
cargo "$(CARGO_RS_CHECK_TOOLCHAIN)" fmt
cd "$(TFHECUDA_SRC)" && ./format_tfhe_cuda_backend.sh
.PHONY: fmt_c_tests # Format c tests
fmt_c_tests:
find tfhe/c_api_tests/ -regex '.*\.\(cpp\|hpp\|cu\|c\|h\)' -exec clang-format -style=file -i {} \;
.PHONY: check_fmt # Check rust code format
check_fmt: install_rs_check_toolchain
cargo "$(CARGO_RS_CHECK_TOOLCHAIN)" fmt --check
.PHONY: check_fmt_c_tests # Check C tests format
check_fmt_c_tests:
find tfhe/c_api_tests/ -regex '.*\.\(cpp\|hpp\|cu\|c\|h\)' -exec clang-format --dry-run --Werror -style=file {} \;
.PHONY: check_fmt_gpu # Check rust and cuda code format
check_fmt_gpu: install_rs_check_toolchain
cargo "$(CARGO_RS_CHECK_TOOLCHAIN)" fmt --check
cd "$(TFHECUDA_SRC)" && ./format_tfhe_cuda_backend.sh -c
.PHONY: check_fmt_js # Check javascript code format
check_fmt_js: check_nvm_installed
source ~/.nvm/nvm.sh && \
nvm install $(NODE_VERSION) && \
nvm use $(NODE_VERSION) && \
$(MAKE) -C tfhe/web_wasm_parallel_tests check_fmt
.PHONY: clippy_gpu # Run clippy lints on tfhe with "gpu" enabled
clippy_gpu: install_rs_check_toolchain
RUSTFLAGS="$(RUSTFLAGS)" cargo "$(CARGO_RS_CHECK_TOOLCHAIN)" clippy \
--features=$(TARGET_ARCH_FEATURE),boolean,shortint,integer,internal-keycache,gpu \
--all-targets \
-p $(TFHE_SPEC) -- --no-deps -D warnings
.PHONY: fix_newline # Fix newline at end of file issues to be UNIX compliant
fix_newline: check_linelint_installed
linelint -a .
@@ -215,10 +150,6 @@ fix_newline: check_linelint_installed
check_newline: check_linelint_installed
linelint .
.PHONY: lint_workflow # Run static linter on GitHub workflows
lint_workflow: check_actionlint_installed
actionlint
.PHONY: clippy_core # Run clippy lints on core_crypto with and without experimental features
clippy_core: install_rs_check_toolchain
RUSTFLAGS="$(RUSTFLAGS)" cargo "$(CARGO_RS_CHECK_TOOLCHAIN)" clippy \
@@ -261,7 +192,7 @@ clippy: install_rs_check_toolchain
.PHONY: clippy_c_api # Run clippy lints enabling the boolean, shortint and the C API
clippy_c_api: install_rs_check_toolchain
RUSTFLAGS="$(RUSTFLAGS)" cargo "$(CARGO_RS_CHECK_TOOLCHAIN)" clippy \
--features=$(TARGET_ARCH_FEATURE),boolean-c-api,shortint-c-api,high-level-c-api \
--features=$(TARGET_ARCH_FEATURE),boolean-c-api,shortint-c-api \
-p $(TFHE_SPEC) -- --no-deps -D warnings
.PHONY: clippy_js_wasm_api # Run clippy lints enabling the boolean, shortint, integer and the js wasm API
@@ -277,13 +208,19 @@ clippy_tasks:
.PHONY: clippy_trivium # Run clippy lints on Trivium app
clippy_trivium: install_rs_check_toolchain
RUSTFLAGS="$(RUSTFLAGS)" cargo "$(CARGO_RS_CHECK_TOOLCHAIN)" clippy --all-targets \
RUSTFLAGS="$(RUSTFLAGS)" cargo "$(CARGO_RS_CHECK_TOOLCHAIN)" clippy \
-p tfhe-trivium -- --no-deps -D warnings
.PHONY: clippy_all_targets # Run clippy lints on all targets (benches, examples, etc.)
clippy_all_targets:
clippy_all_targets: install_rs_check_toolchain
RUSTFLAGS="$(RUSTFLAGS)" cargo "$(CARGO_RS_CHECK_TOOLCHAIN)" clippy --all-targets \
--features=$(TARGET_ARCH_FEATURE),boolean,shortint,integer,internal-keycache,zk-pok-experimental \
--features=$(TARGET_ARCH_FEATURE),boolean,shortint,integer,internal-keycache,safe-deserialization \
-p $(TFHE_SPEC) -- --no-deps -D warnings
.PHONY: clippy_all_targets_forward_compatibility # Run clippy lints on all targets (benches, examples, etc.)
clippy_all_targets_forward_compatibility: install_rs_check_toolchain
RUSTFLAGS="$(RUSTFLAGS)" cargo "$(CARGO_RS_CHECK_TOOLCHAIN)" clippy --all-targets \
--features=$(TARGET_ARCH_FEATURE),boolean,shortint,integer,internal-keycache,safe-deserialization,forward_compatibility \
-p $(TFHE_SPEC) -- --no-deps -D warnings
.PHONY: clippy_concrete_csprng # Run clippy lints on concrete-csprng
@@ -292,23 +229,21 @@ clippy_concrete_csprng:
--features=$(TARGET_ARCH_FEATURE) \
-p concrete-csprng -- --no-deps -D warnings
.PHONY: clippy_zk_pok # Run clippy lints on tfhe-zk-pok
clippy_zk_pok:
RUSTFLAGS="$(RUSTFLAGS)" cargo "$(CARGO_RS_CHECK_TOOLCHAIN)" clippy --all-targets \
-p tfhe-zk-pok -- --no-deps -D warnings
.PHONY: clippy_all # Run all clippy targets
clippy_all: clippy clippy_boolean clippy_shortint clippy_integer clippy_all_targets clippy_c_api \
clippy_js_wasm_api clippy_tasks clippy_core clippy_concrete_csprng clippy_zk_pok clippy_trivium
clippy_js_wasm_api clippy_tasks clippy_core clippy_concrete_csprng clippy_trivium \
clippy_all_targets_forward_compatibility
.PHONY: clippy_fast # Run main clippy targets
clippy_fast: clippy clippy_all_targets clippy_c_api clippy_js_wasm_api clippy_tasks clippy_core \
clippy_concrete_csprng
.PHONY: clippy_cuda_backend # Run clippy lints on the tfhe-cuda-backend
clippy_cuda_backend: install_rs_check_toolchain
RUSTFLAGS="$(RUSTFLAGS)" cargo "$(CARGO_RS_CHECK_TOOLCHAIN)" clippy --all-targets \
-p tfhe-cuda-backend -- --no-deps -D warnings
.PHONY: gen_key_cache # Run the script to generate keys and cache them for shortint tests
gen_key_cache: install_rs_build_toolchain
RUSTFLAGS="$(RUSTFLAGS)" cargo $(CARGO_RS_BUILD_TOOLCHAIN) run --profile $(CARGO_PROFILE) \
--example generates_test_keys \
--features=$(TARGET_ARCH_FEATURE),boolean,shortint,internal-keycache -- \
$(MULTI_BIT_ONLY) $(COVERAGE_ONLY)
.PHONY: build_core # Build core_crypto without experimental features
build_core: install_rs_build_toolchain install_rs_check_toolchain
@@ -348,11 +283,6 @@ build_tfhe_full: install_rs_build_toolchain
RUSTFLAGS="$(RUSTFLAGS)" cargo $(CARGO_RS_BUILD_TOOLCHAIN) build --profile $(CARGO_PROFILE) \
--features=$(TARGET_ARCH_FEATURE),boolean,shortint,integer -p $(TFHE_SPEC) --all-targets
.PHONY: build_tfhe_coverage # Build with test coverage enabled
build_tfhe_coverage: install_rs_build_toolchain
RUSTFLAGS="$(RUSTFLAGS) --cfg tarpaulin" cargo $(CARGO_RS_BUILD_TOOLCHAIN) build --profile $(CARGO_PROFILE) \
--features=$(TARGET_ARCH_FEATURE),boolean,shortint,integer,internal-keycache -p $(TFHE_SPEC) --tests
.PHONY: symlink_c_libs_without_fingerprint # Link the .a and .so files without the changing hash part in target
symlink_c_libs_without_fingerprint:
@./scripts/symlink_c_libs_without_fingerprint.sh \
@@ -362,21 +292,14 @@ symlink_c_libs_without_fingerprint:
.PHONY: build_c_api # Build the C API for boolean, shortint and integer
build_c_api: install_rs_check_toolchain
RUSTFLAGS="$(RUSTFLAGS)" cargo $(CARGO_RS_CHECK_TOOLCHAIN) build --profile $(CARGO_PROFILE) \
--features=$(TARGET_ARCH_FEATURE),boolean-c-api,shortint-c-api,high-level-c-api,zk-pok-experimental,$(FORWARD_COMPAT_FEATURE) \
-p $(TFHE_SPEC)
@"$(MAKE)" symlink_c_libs_without_fingerprint
.PHONY: build_c_api_gpu # Build the C API for boolean, shortint and integer
build_c_api_gpu: install_rs_check_toolchain
RUSTFLAGS="$(RUSTFLAGS)" cargo $(CARGO_RS_CHECK_TOOLCHAIN) build --profile $(CARGO_PROFILE) \
--features=$(TARGET_ARCH_FEATURE),boolean-c-api,shortint-c-api,high-level-c-api,zk-pok-experimental,gpu \
--features=$(TARGET_ARCH_FEATURE),boolean-c-api,shortint-c-api,high-level-c-api,safe-deserialization,$(FORWARD_COMPAT_FEATURE) \
-p $(TFHE_SPEC)
@"$(MAKE)" symlink_c_libs_without_fingerprint
.PHONY: build_c_api_experimental_deterministic_fft # Build the C API for boolean, shortint and integer with experimental deterministic FFT
build_c_api_experimental_deterministic_fft: install_rs_check_toolchain
RUSTFLAGS="$(RUSTFLAGS)" cargo $(CARGO_RS_CHECK_TOOLCHAIN) build --profile $(CARGO_PROFILE) \
--features=$(TARGET_ARCH_FEATURE),boolean-c-api,shortint-c-api,high-level-c-api,experimental-force_fft_algo_dif4,$(FORWARD_COMPAT_FEATURE) \
--features=$(TARGET_ARCH_FEATURE),boolean-c-api,shortint-c-api,high-level-c-api,safe-deserialization,experimental-force_fft_algo_dif4,$(FORWARD_COMPAT_FEATURE) \
-p $(TFHE_SPEC)
@"$(MAKE)" symlink_c_libs_without_fingerprint
@@ -385,7 +308,7 @@ build_web_js_api: install_rs_build_toolchain install_wasm_pack
cd tfhe && \
RUSTFLAGS="$(WASM_RUSTFLAGS)" rustup run "$(RS_BUILD_TOOLCHAIN)" \
wasm-pack build --release --target=web \
-- --features=boolean-client-js-wasm-api,shortint-client-js-wasm-api,integer-client-js-wasm-api,zk-pok-experimental
-- --features=boolean-client-js-wasm-api,shortint-client-js-wasm-api,integer-client-js-wasm-api
.PHONY: build_web_js_api_parallel # Build the js API targeting the web browser with parallelism support
build_web_js_api_parallel: install_rs_check_toolchain install_wasm_pack
@@ -393,7 +316,7 @@ build_web_js_api_parallel: install_rs_check_toolchain install_wasm_pack
rustup component add rust-src --toolchain $(RS_CHECK_TOOLCHAIN) && \
RUSTFLAGS="$(WASM_RUSTFLAGS) -C target-feature=+atomics,+bulk-memory,+mutable-globals" rustup run $(RS_CHECK_TOOLCHAIN) \
wasm-pack build --release --target=web \
-- --features=boolean-client-js-wasm-api,shortint-client-js-wasm-api,integer-client-js-wasm-api,parallel-wasm-api,zk-pok-experimental \
-- --features=boolean-client-js-wasm-api,shortint-client-js-wasm-api,integer-client-js-wasm-api,parallel-wasm-api \
-Z build-std=panic_abort,std
.PHONY: build_node_js_api # Build the js API targeting nodejs
@@ -401,7 +324,7 @@ build_node_js_api: install_rs_build_toolchain install_wasm_pack
cd tfhe && \
RUSTFLAGS="$(WASM_RUSTFLAGS)" rustup run "$(RS_BUILD_TOOLCHAIN)" \
wasm-pack build --release --target=nodejs \
-- --features=boolean-client-js-wasm-api,shortint-client-js-wasm-api,integer-client-js-wasm-api,zk-pok-experimental
-- --features=boolean-client-js-wasm-api,shortint-client-js-wasm-api,integer-client-js-wasm-api
.PHONY: build_concrete_csprng # Build concrete_csprng
build_concrete_csprng: install_rs_build_toolchain
@@ -411,51 +334,29 @@ build_concrete_csprng: install_rs_build_toolchain
.PHONY: test_core_crypto # Run the tests of the core_crypto module including experimental ones
test_core_crypto: install_rs_build_toolchain install_rs_check_toolchain
RUSTFLAGS="$(RUSTFLAGS)" cargo $(CARGO_RS_BUILD_TOOLCHAIN) test --profile $(CARGO_PROFILE) \
--features=$(TARGET_ARCH_FEATURE),experimental,zk-pok-experimental -p $(TFHE_SPEC) -- core_crypto::
--features=$(TARGET_ARCH_FEATURE),experimental -p $(TFHE_SPEC) -- core_crypto::
@if [[ "$(AVX512_SUPPORT)" == "ON" ]]; then \
RUSTFLAGS="$(RUSTFLAGS)" cargo $(CARGO_RS_CHECK_TOOLCHAIN) test --profile $(CARGO_PROFILE) \
--features=$(TARGET_ARCH_FEATURE),experimental,zk-pok-experimental,$(AVX512_FEATURE) -p $(TFHE_SPEC) -- core_crypto::; \
--features=$(TARGET_ARCH_FEATURE),experimental,$(AVX512_FEATURE) -p $(TFHE_SPEC) -- core_crypto::; \
fi
.PHONY: test_core_crypto_cov # Run the tests of the core_crypto module with code coverage
test_core_crypto_cov: install_rs_build_toolchain install_rs_check_toolchain install_tarpaulin
RUSTFLAGS="$(RUSTFLAGS)" cargo $(CARGO_RS_BUILD_TOOLCHAIN) tarpaulin --profile $(CARGO_PROFILE) \
--out xml --output-dir coverage/core_crypto --line --engine llvm --timeout 500 \
--implicit-test-threads $(COVERAGE_EXCLUDED_FILES) \
--features=$(TARGET_ARCH_FEATURE),experimental,internal-keycache \
-p $(TFHE_SPEC) -- core_crypto::
.PHONY: test_ccs_2024_stair_ks # Run the tests of the core_crypto module including experimental ones
test_ccs_2024_stair_ks: install_rs_build_toolchain install_rs_check_toolchain
RUSTFLAGS="$(RUSTFLAGS)" cargo $(CARGO_RS_BUILD_TOOLCHAIN) test --profile $(CARGO_PROFILE) \
--features=$(TARGET_ARCH_FEATURE),experimental -p $(TFHE_SPEC) -- core_crypto::algorithms::test::lwe_stair_keyswitch
@if [[ "$(AVX512_SUPPORT)" == "ON" ]]; then \
RUSTFLAGS="$(RUSTFLAGS)" cargo $(CARGO_RS_CHECK_TOOLCHAIN) tarpaulin --profile $(CARGO_PROFILE) \
--out xml --output-dir coverage/core_crypto_avx512 --line --engine llvm --timeout 500 \
--implicit-test-threads $(COVERAGE_EXCLUDED_FILES) \
--features=$(TARGET_ARCH_FEATURE),experimental,internal-keycache,$(AVX512_FEATURE) \
-p $(TFHE_SPEC) -- -Z unstable-options --report-time core_crypto::; \
RUSTFLAGS="$(RUSTFLAGS)" cargo $(CARGO_RS_CHECK_TOOLCHAIN) test --profile $(CARGO_PROFILE) \
--features=$(TARGET_ARCH_FEATURE),experimental,$(AVX512_FEATURE) -p $(TFHE_SPEC) -- core_crypto::algorithms::test::lwe_stair_keyswitch; \
fi
.PHONY: test_cuda_backend # Run the internal tests of the CUDA backend
test_cuda_backend:
mkdir -p "$(TFHECUDA_BUILD)" && \
cd "$(TFHECUDA_BUILD)" && \
cmake .. -DCMAKE_BUILD_TYPE=Release -DTFHE_CUDA_BACKEND_BUILD_TESTS=ON && \
make -j "$(CPU_COUNT)" && \
make test
.PHONY: test_gpu # Run the tests of the core_crypto module including experimental on the gpu backend
test_gpu: test_core_crypto_gpu test_integer_gpu test_cuda_backend
.PHONY: test_core_crypto_gpu # Run the tests of the core_crypto module including experimental on the gpu backend
test_core_crypto_gpu: install_rs_build_toolchain install_rs_check_toolchain
.PHONY: test_ccs_2024_fft_shrinking_ks # Run the tests of the core_crypto module including experimental ones
test_ccs_2024_fft_shrinking_ks: install_rs_build_toolchain install_rs_check_toolchain
RUSTFLAGS="$(RUSTFLAGS)" cargo $(CARGO_RS_BUILD_TOOLCHAIN) test --profile $(CARGO_PROFILE) \
--features=$(TARGET_ARCH_FEATURE),gpu -p $(TFHE_SPEC) -- core_crypto::gpu::
RUSTFLAGS="$(RUSTFLAGS)" cargo $(CARGO_RS_BUILD_TOOLCHAIN) test --doc --profile $(CARGO_PROFILE) \
--features=$(TARGET_ARCH_FEATURE),gpu -p $(TFHE_SPEC) -- core_crypto::gpu::
.PHONY: test_integer_gpu # Run the tests of the integer module including experimental on the gpu backend
test_integer_gpu: install_rs_build_toolchain install_rs_check_toolchain
RUSTFLAGS="$(RUSTFLAGS)" cargo $(CARGO_RS_BUILD_TOOLCHAIN) test --profile $(CARGO_PROFILE) \
--features=$(TARGET_ARCH_FEATURE),integer,gpu -p $(TFHE_SPEC) -- integer::gpu::server_key::
RUSTFLAGS="$(RUSTFLAGS)" cargo $(CARGO_RS_BUILD_TOOLCHAIN) test --doc --profile $(CARGO_PROFILE) \
--features=$(TARGET_ARCH_FEATURE),integer,gpu -p $(TFHE_SPEC) -- integer::gpu::server_key::
--features=$(TARGET_ARCH_FEATURE),experimental -p $(TFHE_SPEC) -- core_crypto::algorithms::test::lwe_fast_keyswitch
@if [[ "$(AVX512_SUPPORT)" == "ON" ]]; then \
RUSTFLAGS="$(RUSTFLAGS)" cargo $(CARGO_RS_CHECK_TOOLCHAIN) test --profile $(CARGO_PROFILE) \
--features=$(TARGET_ARCH_FEATURE),experimental,$(AVX512_FEATURE) -p $(TFHE_SPEC) -- core_crypto::algorithms::test::lwe_fast_keyswitch; \
fi
.PHONY: test_boolean # Run the tests of the boolean module
test_boolean: install_rs_build_toolchain
@@ -467,27 +368,23 @@ test_boolean_cov: install_rs_check_toolchain install_tarpaulin
RUSTFLAGS="$(RUSTFLAGS)" cargo $(CARGO_RS_CHECK_TOOLCHAIN) tarpaulin --profile $(CARGO_PROFILE) \
--out xml --output-dir coverage/boolean --line --engine llvm --timeout 500 \
$(COVERAGE_EXCLUDED_FILES) \
--features=$(TARGET_ARCH_FEATURE),boolean,internal-keycache \
-p $(TFHE_SPEC) -- -Z unstable-options --report-time boolean::
--features=$(TARGET_ARCH_FEATURE),boolean,internal-keycache,__coverage \
-p $(TFHE_SPEC) -- boolean::
.PHONY: test_c_api_rs # Run the rust tests for the C API
test_c_api_rs: install_rs_check_toolchain
RUSTFLAGS="$(RUSTFLAGS)" cargo $(CARGO_RS_CHECK_TOOLCHAIN) test --profile $(CARGO_PROFILE) \
--features=$(TARGET_ARCH_FEATURE),boolean-c-api,shortint-c-api,high-level-c-api \
--features=$(TARGET_ARCH_FEATURE),boolean-c-api,shortint-c-api,high-level-c-api,safe-deserialization \
-p $(TFHE_SPEC) \
c_api
.PHONY: test_c_api_c # Run the C tests for the C API
test_c_api_c: build_c_api
./scripts/c_api_tests.sh
./scripts/c_api_tests.sh --forward-compat "$(FORWARD_COMPAT)"
.PHONY: test_c_api # Run all the tests for the C API
test_c_api: test_c_api_rs test_c_api_c
.PHONY: test_c_api_gpu # Run the C tests for the C API
test_c_api_gpu: build_c_api_gpu
./scripts/c_api_tests.sh --gpu
.PHONY: test_shortint_ci # Run the tests for shortint ci
test_shortint_ci: install_rs_build_toolchain install_cargo_nextest
BIG_TESTS_INSTANCE="$(BIG_TESTS_INSTANCE)" \
@@ -512,106 +409,51 @@ test_shortint_cov: install_rs_check_toolchain install_tarpaulin
RUSTFLAGS="$(RUSTFLAGS)" cargo $(CARGO_RS_CHECK_TOOLCHAIN) tarpaulin --profile $(CARGO_PROFILE) \
--out xml --output-dir coverage/shortint --line --engine llvm --timeout 500 \
$(COVERAGE_EXCLUDED_FILES) \
--features=$(TARGET_ARCH_FEATURE),shortint,internal-keycache \
-p $(TFHE_SPEC) -- -Z unstable-options --report-time shortint::
--features=$(TARGET_ARCH_FEATURE),shortint,internal-keycache,__coverage \
-p $(TFHE_SPEC) -- shortint::
.PHONY: test_integer_ci # Run the tests for integer ci
test_integer_ci: install_rs_check_toolchain install_cargo_nextest
test_integer_ci: install_rs_build_toolchain install_cargo_nextest
BIG_TESTS_INSTANCE="$(BIG_TESTS_INSTANCE)" \
FAST_TESTS="$(FAST_TESTS)" \
./scripts/integer-tests.sh --rust-toolchain $(CARGO_RS_CHECK_TOOLCHAIN) \
--cargo-profile "$(CARGO_PROFILE)" --avx512-support "$(AVX512_SUPPORT)" \
--tfhe-package "$(TFHE_SPEC)"
.PHONY: test_unsigned_integer_ci # Run the tests for unsigned integer ci
test_unsigned_integer_ci: install_rs_check_toolchain install_cargo_nextest
BIG_TESTS_INSTANCE="$(BIG_TESTS_INSTANCE)" \
FAST_TESTS="$(FAST_TESTS)" \
./scripts/integer-tests.sh --rust-toolchain $(CARGO_RS_CHECK_TOOLCHAIN) \
--cargo-profile "$(CARGO_PROFILE)" --avx512-support "$(AVX512_SUPPORT)" \
--unsigned-only --tfhe-package "$(TFHE_SPEC)"
.PHONY: test_signed_integer_ci # Run the tests for signed integer ci
test_signed_integer_ci: install_rs_check_toolchain install_cargo_nextest
BIG_TESTS_INSTANCE="$(BIG_TESTS_INSTANCE)" \
FAST_TESTS="$(FAST_TESTS)" \
./scripts/integer-tests.sh --rust-toolchain $(CARGO_RS_CHECK_TOOLCHAIN) \
--cargo-profile "$(CARGO_PROFILE)" --avx512-support "$(AVX512_SUPPORT)" \
--signed-only --tfhe-package "$(TFHE_SPEC)"
./scripts/integer-tests.sh --rust-toolchain $(CARGO_RS_BUILD_TOOLCHAIN) \
--cargo-profile "$(CARGO_PROFILE)" --tfhe-package "$(TFHE_SPEC)"
.PHONY: test_integer_multi_bit_ci # Run the tests for integer ci running only multibit tests
test_integer_multi_bit_ci: install_rs_check_toolchain install_cargo_nextest
test_integer_multi_bit_ci: install_rs_build_toolchain install_cargo_nextest
BIG_TESTS_INSTANCE="$(BIG_TESTS_INSTANCE)" \
FAST_TESTS="$(FAST_TESTS)" \
./scripts/integer-tests.sh --rust-toolchain $(CARGO_RS_CHECK_TOOLCHAIN) \
--cargo-profile "$(CARGO_PROFILE)" --multi-bit --avx512-support "$(AVX512_SUPPORT)" \
--tfhe-package "$(TFHE_SPEC)"
.PHONY: test_unsigned_integer_multi_bit_ci # Run the tests for nsigned integer ci running only multibit tests
test_unsigned_integer_multi_bit_ci: install_rs_check_toolchain install_cargo_nextest
BIG_TESTS_INSTANCE="$(BIG_TESTS_INSTANCE)" \
FAST_TESTS="$(FAST_TESTS)" \
./scripts/integer-tests.sh --rust-toolchain $(CARGO_RS_CHECK_TOOLCHAIN) \
--cargo-profile "$(CARGO_PROFILE)" --multi-bit --avx512-support "$(AVX512_SUPPORT)" \
--unsigned-only --tfhe-package "$(TFHE_SPEC)"
.PHONY: test_signed_integer_multi_bit_ci # Run the tests for nsigned integer ci running only multibit tests
test_signed_integer_multi_bit_ci: install_rs_check_toolchain install_cargo_nextest
BIG_TESTS_INSTANCE="$(BIG_TESTS_INSTANCE)" \
FAST_TESTS="$(FAST_TESTS)" \
./scripts/integer-tests.sh --rust-toolchain $(CARGO_RS_CHECK_TOOLCHAIN) \
--cargo-profile "$(CARGO_PROFILE)" --multi-bit --avx512-support "$(AVX512_SUPPORT)" \
--signed-only --tfhe-package "$(TFHE_SPEC)"
./scripts/integer-tests.sh --rust-toolchain $(CARGO_RS_BUILD_TOOLCHAIN) \
--cargo-profile "$(CARGO_PROFILE)" --multi-bit --tfhe-package "$(TFHE_SPEC)"
.PHONY: test_safe_deserialization # Run the tests for safe deserialization
test_safe_deserialization: install_rs_build_toolchain install_cargo_nextest
RUSTFLAGS="$(RUSTFLAGS)" cargo $(CARGO_RS_BUILD_TOOLCHAIN) test --profile $(CARGO_PROFILE) \
--features=$(TARGET_ARCH_FEATURE),boolean,shortint,integer,internal-keycache -p $(TFHE_SPEC) -- safe_deserialization::
--features=$(TARGET_ARCH_FEATURE),boolean,shortint,integer,internal-keycache,safe-deserialization -p $(TFHE_SPEC) -- safe_deserialization::
.PHONY: test_integer # Run all the tests for integer
test_integer: install_rs_build_toolchain
RUSTFLAGS="$(RUSTFLAGS)" cargo $(CARGO_RS_BUILD_TOOLCHAIN) test --profile $(CARGO_PROFILE) \
--features=$(TARGET_ARCH_FEATURE),integer,internal-keycache -p $(TFHE_SPEC) -- integer::
.PHONY: test_integer_cov # Run the tests of the integer module with code coverage
test_integer_cov: install_rs_check_toolchain install_tarpaulin
RUSTFLAGS="$(RUSTFLAGS)" cargo $(CARGO_RS_CHECK_TOOLCHAIN) tarpaulin --profile $(CARGO_PROFILE) \
--out xml --output-dir coverage/integer --line --engine llvm --timeout 500 \
--implicit-test-threads \
--exclude-files $(COVERAGE_EXCLUDED_FILES) \
--features=$(TARGET_ARCH_FEATURE),integer,internal-keycache \
-p $(TFHE_SPEC) -- -Z unstable-options --report-time integer::
.PHONY: test_high_level_api # Run all the tests for high_level_api
test_high_level_api: install_rs_build_toolchain
RUSTFLAGS="$(RUSTFLAGS)" cargo $(CARGO_RS_BUILD_TOOLCHAIN) test --profile $(CARGO_PROFILE) \
--features=$(TARGET_ARCH_FEATURE),boolean,shortint,integer,internal-keycache,zk-pok-experimental -p $(TFHE_SPEC) \
--features=$(TARGET_ARCH_FEATURE),boolean,shortint,integer,internal-keycache -p $(TFHE_SPEC) \
-- high_level_api::
test_high_level_api_gpu: install_rs_build_toolchain install_cargo_nextest
RUSTFLAGS="$(RUSTFLAGS)" cargo $(CARGO_RS_BUILD_TOOLCHAIN) nextest run --cargo-profile $(CARGO_PROFILE) \
--features=$(TARGET_ARCH_FEATURE),integer,internal-keycache,gpu -p $(TFHE_SPEC) \
-E "test(/high_level_api::.*gpu.*/)"
.PHONY: test_forward_compatibility # Run forward compatibility tests
test_forward_compatibility: install_rs_build_toolchain
RUSTFLAGS="$(RUSTFLAGS)" cargo $(CARGO_RS_BUILD_TOOLCHAIN) test --tests --profile $(CARGO_PROFILE) \
--features=$(TARGET_ARCH_FEATURE),boolean,shortint,integer,forward_compatibility,internal-keycache -p $(TFHE_SPEC) \
-- forward_compatibility::
.PHONY: test_user_doc # Run tests from the .md documentation
test_user_doc: install_rs_build_toolchain
RUSTFLAGS="$(RUSTFLAGS)" cargo $(CARGO_RS_BUILD_TOOLCHAIN) test --profile $(CARGO_PROFILE) --doc \
--features=$(TARGET_ARCH_FEATURE),boolean,shortint,integer,internal-keycache,pbs-stats,zk-pok-experimental \
-p $(TFHE_SPEC) \
--features=$(TARGET_ARCH_FEATURE),boolean,shortint,integer,internal-keycache -p $(TFHE_SPEC) \
-- test_user_docs::
.PHONY: test_user_doc_gpu # Run tests for GPU from the .md documentation
test_user_doc_gpu: install_rs_build_toolchain
RUSTFLAGS="$(RUSTFLAGS)" cargo $(CARGO_RS_BUILD_TOOLCHAIN) test --profile $(CARGO_PROFILE) --doc \
--features=$(TARGET_ARCH_FEATURE),boolean,shortint,integer,internal-keycache,gpu,zk-pok-experimental -p $(TFHE_SPEC) \
-- test_user_docs::
.PHONY: test_fhe_strings # Run tests for fhe_strings example
test_fhe_strings: install_rs_build_toolchain
RUSTFLAGS="$(RUSTFLAGS)" cargo $(CARGO_RS_BUILD_TOOLCHAIN) test --profile $(CARGO_PROFILE) \
--example fhe_strings \
--features=$(TARGET_ARCH_FEATURE),integer
.PHONY: test_regex_engine # Run tests for regex_engine example
test_regex_engine: install_rs_build_toolchain
RUSTFLAGS="$(RUSTFLAGS)" cargo $(CARGO_RS_BUILD_TOOLCHAIN) test --profile $(CARGO_PROFILE) \
@@ -642,67 +484,46 @@ test_concrete_csprng:
RUSTFLAGS="$(RUSTFLAGS)" cargo $(CARGO_RS_BUILD_TOOLCHAIN) test --profile $(CARGO_PROFILE) \
--features=$(TARGET_ARCH_FEATURE) -p concrete-csprng
.PHONY: test_zk_pok # Run tfhe-zk-pok-experimental tests
test_zk_pok:
RUSTFLAGS="$(RUSTFLAGS)" cargo $(CARGO_RS_BUILD_TOOLCHAIN) test --profile $(CARGO_PROFILE) \
-p tfhe-zk-pok
.PHONY: doc # Build rust doc
doc: install_rs_check_toolchain
@# Even though we are not in docs.rs, this allows to "just" build the doc
DOCS_RS=1 \
RUSTDOCFLAGS="--html-in-header katex-header.html" \
cargo "$(CARGO_RS_CHECK_TOOLCHAIN)" doc \
--features=$(TARGET_ARCH_FEATURE),boolean,shortint,integer,gpu,internal-keycache,experimental --no-deps -p $(TFHE_SPEC)
--features=$(TARGET_ARCH_FEATURE),boolean,shortint,integer --no-deps
.PHONY: docs # Build rust doc alias for doc
docs: doc
.PHONY: lint_doc # Build rust doc with linting enabled
lint_doc: install_rs_check_toolchain
@# Even though we are not in docs.rs, this allows to "just" build the doc
DOCS_RS=1 \
RUSTDOCFLAGS="--html-in-header katex-header.html -Dwarnings" \
cargo "$(CARGO_RS_CHECK_TOOLCHAIN)" doc \
--features=$(TARGET_ARCH_FEATURE),boolean,shortint,integer,gpu,internal-keycache,experimental -p $(TFHE_SPEC) --no-deps
--features=$(TARGET_ARCH_FEATURE),boolean,shortint,integer --no-deps
.PHONY: lint_docs # Build rust doc with linting enabled alias for lint_doc
lint_docs: lint_doc
.PHONY: format_doc_latex # Format the documentation latex equations to avoid broken rendering.
format_doc_latex:
RUSTFLAGS="" cargo xtask format_latex_doc
cargo xtask format_latex_doc
@"$(MAKE)" --no-print-directory fmt
@printf "\n===============================\n\n"
@printf "Please manually inspect changes made by format_latex_doc, rustfmt can break equations \
if the line length is exceeded\n"
@printf "\n===============================\n"
.PHONY: check_md_docs_are_tested # Checks that the rust codeblocks in our .md files are tested
check_md_docs_are_tested:
RUSTFLAGS="" cargo xtask check_tfhe_docs_are_tested
.PHONY: check_compile_tests # Build tests in debug without running them
check_compile_tests:
RUSTFLAGS="$(RUSTFLAGS)" cargo $(CARGO_RS_BUILD_TOOLCHAIN) test --no-run \
--features=$(TARGET_ARCH_FEATURE),experimental,boolean,shortint,integer,internal-keycache \
--features=$(TARGET_ARCH_FEATURE),experimental,boolean,shortint,integer,internal-keycache,safe-deserialization \
-p $(TFHE_SPEC)
@if [[ "$(OS)" == "Linux" || "$(OS)" == "Darwin" ]]; then \
"$(MAKE)" build_c_api && \
./scripts/c_api_tests.sh --build-only; \
./scripts/c_api_tests.sh --build-only --forward-compat "$(FORWARD_COMPAT)" && \
FORWARD_COMPAT=ON "$(MAKE)" build_c_api && \
./scripts/c_api_tests.sh --build-only --forward-compat "$(FORWARD_COMPAT)"; \
fi
.PHONY: check_compile_tests_benches_gpu # Build tests in debug without running them
check_compile_tests_benches_gpu: install_rs_build_toolchain
RUSTFLAGS="$(RUSTFLAGS)" cargo $(CARGO_RS_BUILD_TOOLCHAIN) test --no-run \
--features=$(TARGET_ARCH_FEATURE),experimental,boolean,shortint,integer,internal-keycache,gpu \
-p $(TFHE_SPEC)
mkdir -p "$(TFHECUDA_BUILD)" && \
cd "$(TFHECUDA_BUILD)" && \
cmake .. -DCMAKE_BUILD_TYPE=Debug -DTFHE_CUDA_BACKEND_BUILD_TESTS=ON -DTFHE_CUDA_BACKEND_BUILD_BENCHMARKS=ON && \
make -j "$(CPU_COUNT)"
.PHONY: build_nodejs_test_docker # Build a docker image with tools to run nodejs tests for wasm API
build_nodejs_test_docker:
DOCKER_BUILDKIT=1 docker build --build-arg RUST_TOOLCHAIN="$(RS_BUILD_TOOLCHAIN)" \
@@ -750,70 +571,27 @@ dieharder_csprng: install_dieharder build_concrete_csprng
# Benchmarks
#
.PHONY: bench_integer # Run benchmarks for unsigned integer
.PHONY: bench_integer # Run benchmarks for integer
bench_integer: install_rs_check_toolchain
RUSTFLAGS="$(RUSTFLAGS)" __TFHE_RS_BENCH_OP_FLAVOR=$(BENCH_OP_FLAVOR) __TFHE_RS_FAST_BENCH=$(FAST_BENCH) \
cargo $(CARGO_RS_CHECK_TOOLCHAIN) bench \
--bench integer-bench \
--features=$(TARGET_ARCH_FEATURE),integer,internal-keycache,nightly-avx512 -p $(TFHE_SPEC) --
--features=$(TARGET_ARCH_FEATURE),integer,internal-keycache,$(AVX512_FEATURE) -p $(TFHE_SPEC) --
.PHONY: bench_signed_integer # Run benchmarks for signed integer
bench_signed_integer: install_rs_check_toolchain
RUSTFLAGS="$(RUSTFLAGS)" __TFHE_RS_BENCH_OP_FLAVOR=$(BENCH_OP_FLAVOR) __TFHE_RS_FAST_BENCH=$(FAST_BENCH) \
cargo $(CARGO_RS_CHECK_TOOLCHAIN) bench \
--bench integer-signed-bench \
--features=$(TARGET_ARCH_FEATURE),integer,internal-keycache,nightly-avx512 -p $(TFHE_SPEC) --
.PHONY: bench_integer_gpu # Run benchmarks for integer on GPU backend
bench_integer_gpu: install_rs_check_toolchain
RUSTFLAGS="$(RUSTFLAGS)" __TFHE_RS_BENCH_OP_FLAVOR=$(BENCH_OP_FLAVOR) __TFHE_RS_FAST_BENCH=$(FAST_BENCH) \
cargo $(CARGO_RS_CHECK_TOOLCHAIN) bench \
--bench integer-bench \
--features=$(TARGET_ARCH_FEATURE),integer,gpu,internal-keycache,nightly-avx512 -p $(TFHE_SPEC) --
.PHONY: bench_integer_multi_bit # Run benchmarks for unsigned integer using multi-bit parameters
.PHONY: bench_integer_multi_bit # Run benchmarks for integer using multi-bit parameters
bench_integer_multi_bit: install_rs_check_toolchain
RUSTFLAGS="$(RUSTFLAGS)" __TFHE_RS_BENCH_TYPE=MULTI_BIT \
__TFHE_RS_BENCH_OP_FLAVOR=$(BENCH_OP_FLAVOR) __TFHE_RS_FAST_BENCH=$(FAST_BENCH) \
cargo $(CARGO_RS_CHECK_TOOLCHAIN) bench \
--bench integer-bench \
--features=$(TARGET_ARCH_FEATURE),integer,internal-keycache,nightly-avx512 -p $(TFHE_SPEC) --
.PHONY: bench_signed_integer_multi_bit # Run benchmarks for signed integer using multi-bit parameters
bench_signed_integer_multi_bit: install_rs_check_toolchain
RUSTFLAGS="$(RUSTFLAGS)" __TFHE_RS_BENCH_TYPE=MULTI_BIT \
__TFHE_RS_BENCH_OP_FLAVOR=$(BENCH_OP_FLAVOR) __TFHE_RS_FAST_BENCH=$(FAST_BENCH) \
cargo $(CARGO_RS_CHECK_TOOLCHAIN) bench \
--bench integer-signed-bench \
--features=$(TARGET_ARCH_FEATURE),integer,internal-keycache,nightly-avx512 -p $(TFHE_SPEC) --
.PHONY: bench_integer_multi_bit_gpu # Run benchmarks for integer on GPU backend using multi-bit parameters
bench_integer_multi_bit_gpu: install_rs_check_toolchain
RUSTFLAGS="$(RUSTFLAGS)" __TFHE_RS_BENCH_TYPE=MULTI_BIT \
__TFHE_RS_BENCH_OP_FLAVOR=$(BENCH_OP_FLAVOR) __TFHE_RS_FAST_BENCH=$(FAST_BENCH) \
cargo $(CARGO_RS_CHECK_TOOLCHAIN) bench \
--bench integer-bench \
--features=$(TARGET_ARCH_FEATURE),integer,gpu,internal-keycache,nightly-avx512 -p $(TFHE_SPEC) --
--features=$(TARGET_ARCH_FEATURE),integer,internal-keycache,$(AVX512_FEATURE) -p $(TFHE_SPEC) --
.PHONY: bench_shortint # Run benchmarks for shortint
bench_shortint: install_rs_check_toolchain
RUSTFLAGS="$(RUSTFLAGS)" __TFHE_RS_BENCH_OP_FLAVOR=$(BENCH_OP_FLAVOR) \
cargo $(CARGO_RS_CHECK_TOOLCHAIN) bench \
--bench shortint-bench \
--features=$(TARGET_ARCH_FEATURE),shortint,internal-keycache,nightly-avx512 -p $(TFHE_SPEC)
.PHONY: bench_oprf # Run benchmarks for shortint
bench_oprf: install_rs_check_toolchain
RUSTFLAGS="$(RUSTFLAGS)" \
cargo $(CARGO_RS_CHECK_TOOLCHAIN) bench \
--bench oprf-shortint-bench \
--features=$(TARGET_ARCH_FEATURE),shortint,internal-keycache,nightly-avx512 -p $(TFHE_SPEC)
RUSTFLAGS="$(RUSTFLAGS)" \
cargo $(CARGO_RS_CHECK_TOOLCHAIN) bench \
--bench oprf-integer-bench \
--features=$(TARGET_ARCH_FEATURE),integer,internal-keycache,nightly-avx512 -p $(TFHE_SPEC)
--features=$(TARGET_ARCH_FEATURE),shortint,internal-keycache,$(AVX512_FEATURE) -p $(TFHE_SPEC)
.PHONY: bench_shortint_multi_bit # Run benchmarks for shortint using multi-bit parameters
bench_shortint_multi_bit: install_rs_check_toolchain
@@ -821,38 +599,20 @@ bench_shortint_multi_bit: install_rs_check_toolchain
__TFHE_RS_BENCH_OP_FLAVOR=$(BENCH_OP_FLAVOR) \
cargo $(CARGO_RS_CHECK_TOOLCHAIN) bench \
--bench shortint-bench \
--features=$(TARGET_ARCH_FEATURE),shortint,internal-keycache,nightly-avx512 -p $(TFHE_SPEC) --
--features=$(TARGET_ARCH_FEATURE),shortint,internal-keycache,$(AVX512_FEATURE) -p $(TFHE_SPEC) --
.PHONY: bench_boolean # Run benchmarks for boolean
bench_boolean: install_rs_check_toolchain
RUSTFLAGS="$(RUSTFLAGS)" cargo $(CARGO_RS_CHECK_TOOLCHAIN) bench \
--bench boolean-bench \
--features=$(TARGET_ARCH_FEATURE),boolean,internal-keycache,nightly-avx512 -p $(TFHE_SPEC)
--features=$(TARGET_ARCH_FEATURE),boolean,internal-keycache,$(AVX512_FEATURE) -p $(TFHE_SPEC)
.PHONY: bench_pbs # Run benchmarks for PBS
bench_pbs: install_rs_check_toolchain
RUSTFLAGS="$(RUSTFLAGS)" cargo $(CARGO_RS_CHECK_TOOLCHAIN) bench \
--bench pbs-bench \
--features=$(TARGET_ARCH_FEATURE),boolean,shortint,internal-keycache,nightly-avx512 -p $(TFHE_SPEC)
.PHONY: bench_pbs_gpu # Run benchmarks for PBS on GPU backend
bench_pbs_gpu: install_rs_check_toolchain
RUSTFLAGS="$(RUSTFLAGS)" cargo $(CARGO_RS_CHECK_TOOLCHAIN) bench \
--bench pbs-bench \
--features=$(TARGET_ARCH_FEATURE),boolean,shortint,gpu,internal-keycache,nightly-avx512 -p $(TFHE_SPEC)
.PHONY: bench_ks # Run benchmarks for keyswitch
bench_ks: install_rs_check_toolchain
RUSTFLAGS="$(RUSTFLAGS)" cargo $(CARGO_RS_CHECK_TOOLCHAIN) bench \
--bench ks-bench \
--features=$(TARGET_ARCH_FEATURE),boolean,shortint,internal-keycache,nightly-avx512 -p $(TFHE_SPEC)
.PHONY: bench_ks_gpu # Run benchmarks for PBS on GPU backend
bench_ks_gpu: install_rs_check_toolchain
RUSTFLAGS="$(RUSTFLAGS)" cargo $(CARGO_RS_CHECK_TOOLCHAIN) bench \
--bench ks-bench \
--features=$(TARGET_ARCH_FEATURE),boolean,shortint,gpu,internal-keycache,nightly-avx512 -p $(TFHE_SPEC)
--features=$(TARGET_ARCH_FEATURE),boolean,shortint,internal-keycache,$(AVX512_FEATURE) -p $(TFHE_SPEC)
.PHONY: bench_web_js_api_parallel # Run benchmarks for the web wasm api
bench_web_js_api_parallel: build_web_js_api_parallel
@@ -864,21 +624,27 @@ ci_bench_web_js_api_parallel: build_web_js_api_parallel
nvm use node && \
$(MAKE) -C tfhe/web_wasm_parallel_tests bench-ci
.PHONY: bench_ccs_2024_cjp # Run benchmarks for PBS
bench_ccs_2024_cjp: install_rs_check_toolchain
RUSTFLAGS="$(RUSTFLAGS)" cargo $(CARGO_RS_CHECK_TOOLCHAIN) bench \
--bench ccs-2024-cjp \
--features=$(TARGET_ARCH_FEATURE),boolean,shortint,internal-keycache,$(AVX512_FEATURE) -p $(TFHE_SPEC)
.PHONY: bench_ccs_2024_fft_shrinking_ks # Run benchmarks for PBS
bench_ccs_2024_fft_shrinking_ks: install_rs_check_toolchain
RUSTFLAGS="$(RUSTFLAGS)" cargo $(CARGO_RS_CHECK_TOOLCHAIN) bench \
--bench ccs-2024-fft-shrinking-ks \
--features=$(TARGET_ARCH_FEATURE),internal-keycache,$(AVX512_FEATURE) -p $(TFHE_SPEC)
.PHONY: bench_ccs_2024_stair_ks # Run benchmarks for PBS
bench_ccs_2024_stair_ks: install_rs_check_toolchain
RUSTFLAGS="$(RUSTFLAGS)" cargo $(CARGO_RS_CHECK_TOOLCHAIN) bench \
--bench ccs-2024-stair-ks \
--features=$(TARGET_ARCH_FEATURE),internal-keycache,$(AVX512_FEATURE) -p $(TFHE_SPEC)
#
# Utility tools
#
.PHONY: gen_key_cache # Run the script to generate keys and cache them for shortint tests
gen_key_cache: install_rs_build_toolchain
RUSTFLAGS="$(RUSTFLAGS) --cfg tarpaulin" cargo $(CARGO_RS_BUILD_TOOLCHAIN) run --profile $(CARGO_PROFILE) \
--example generates_test_keys \
--features=$(TARGET_ARCH_FEATURE),boolean,shortint,internal-keycache -- \
$(MULTI_BIT_ONLY) $(COVERAGE_ONLY)
.PHONY: gen_key_cache_core_crypto # Run function to generate keys and cache them for core_crypto tests
gen_key_cache_core_crypto: install_rs_build_toolchain
RUSTFLAGS="$(RUSTFLAGS)" cargo $(CARGO_RS_BUILD_TOOLCHAIN) test --tests --profile $(CARGO_PROFILE) \
--features=$(TARGET_ARCH_FEATURE),experimental,internal-keycache -p $(TFHE_SPEC) -- --nocapture \
core_crypto::keycache::generate_keys
.PHONY: measure_hlapi_compact_pk_ct_sizes # Measure sizes of public keys and ciphertext for high-level API
measure_hlapi_compact_pk_ct_sizes: install_rs_check_toolchain
@@ -941,16 +707,11 @@ sha256_bool: install_rs_check_toolchain
--example sha256_bool \
--features=$(TARGET_ARCH_FEATURE),boolean
.PHONY: pcc # pcc stands for pre commit checks (except GPU)
pcc: no_tfhe_typo no_dbg_log check_fmt lint_doc check_md_docs_are_tested clippy_all \
check_compile_tests
.PHONY: pcc_gpu # pcc stands for pre commit checks for GPU compilation
pcc_gpu: clippy_gpu clippy_cuda_backend check_compile_tests_benches_gpu
.PHONY: pcc # pcc stands for pre commit checks
pcc: no_tfhe_typo no_dbg_log check_fmt lint_doc clippy_all check_compile_tests
.PHONY: fpcc # pcc stands for pre commit checks, the f stands for fast
fpcc: no_tfhe_typo no_dbg_log check_fmt lint_doc check_md_docs_are_tested clippy_fast \
check_compile_tests
fpcc: no_tfhe_typo no_dbg_log check_fmt lint_doc clippy_fast check_compile_tests
.PHONY: conformance # Automatically fix problems that can be fixed
conformance: fix_newline fmt

211
README.md
View File

@@ -1,71 +1,37 @@
<p align="center">
<!-- product name logo -->
<picture>
<source media="(prefers-color-scheme: dark)" srcset="https://github.com/zama-ai/tfhe-rs/assets/157474013/5283e0ba-da1e-43af-9f2a-c5221367a12b">
<source media="(prefers-color-scheme: light)" srcset="https://github.com/zama-ai/tfhe-rs/assets/157474013/b94a8c96-7595-400b-9311-70765c706955">
<img width=600 alt="Zama TFHE-rs">
</picture>
<img width=600 src="https://user-images.githubusercontent.com/5758427/231206749-8f146b97-3c5a-4201-8388-3ffa88580415.png">
</p>
<hr/>
<p align="center">
<a href="https://docs.zama.ai/tfhe-rs"> 📒 Read documentation</a> | <a href="https://zama.ai/community"> 💛 Community support</a>
</p>
<p align="center">
<!-- Version badge using shields.io -->
<a href="https://github.com/zama-ai/tfhe-rs/releases">
<img src="https://img.shields.io/github/v/release/zama-ai/tfhe-rs?style=flat-square">
</a>
<!-- Zama Bounty Program -->
<a href="https://github.com/zama-ai/bounty-program">
<img src="https://img.shields.io/badge/Contribute-Zama%20Bounty%20Program-yellow?style=flat-square">
</a>
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<hr/>
<p align="center">
<a href="https://docs.zama.ai/tfhe-rs"> 📒 Documentation</a> | <a href="https://zama.ai/community"> 💛 Community support</a> | <a href="https://github.com/zama-ai/awesome-zama"> 📚 FHE resources by Zama</a>
</p>
**TFHE-rs** is a pure Rust implementation of TFHE for boolean and integer
arithmetics over encrypted data. It includes:
- a **Rust** API
- a **C** API
- and a **client-side WASM** API
<p align="center">
<a href="https://github.com/zama-ai/tfhe-rs/releases"><img src="https://img.shields.io/github/v/release/zama-ai/tfhe-rs?style=flat-square"></a>
<a href="LICENSE"><img src="https://img.shields.io/badge/License-BSD--3--Clause--Clear-%23ffb243?style=flat-square"></a>
<a href="https://github.com/zama-ai/bounty-program"><img src="https://img.shields.io/badge/Contribute-Zama%20Bounty%20Program-%23ffd208?style=flat-square"></a>
</p>
## About
### What is TFHE-rs
**TFHE-rs** is a pure Rust implementation of TFHE for boolean and integer arithmetics over encrypted data.
It includes:
- a **Rust** API
- a **C** API
- and a **client-side WASM** API
TFHE-rs is designed for developers and researchers who want full control over
what they can do with TFHE, while not having to worry about the low-level
**TFHE-rs** is meant for developers and researchers who want full control over
what they can do with TFHE, while not having to worry about the low level
implementation. The goal is to have a stable, simple, high-performance, and
production-ready library for all the advanced features of TFHE.
<br></br>
### Main features
- **Low-level cryptographic library** that implements Zamas variant of TFHE, including programmable bootstrapping
- **Implementation of the original TFHE boolean API** that can be used as a drop-in replacement for other TFHE libraries
- **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**.
*Learn more about TFHE-rs features in the [documentation](https://docs.zama.ai/tfhe-rs/readme).*
<br></br>
## Table of Contents
- **[Getting Started](#getting-started)**
- [Cargo.toml configuration](#cargotoml-configuration)
- [A simple example](#a-simple-example)
- **[Resources](#resources)**
- [TFHE deep dive](#tfhe-deep-dive)
- [Tutorials](#tutorials)
- [Documentation](#documentation)
- **[Working with TFHE-rs](#working-with-tfhe-rs)**
- [Disclaimers](#disclaimers)
- [Citations](#citations)
- [Contributing](#contributing)
- [License](#license)
- **[Support](#support)**
<br></br>
## Getting Started
The steps to run a first example are described below.
### Cargo.toml configuration
To use the latest version of `TFHE-rs` in your project, you first need to add it as a dependency in your `Cargo.toml`:
@@ -81,24 +47,20 @@ tfhe = { version = "*", features = ["boolean", "shortint", "integer", "x86_64-un
```toml
tfhe = { version = "*", features = ["boolean", "shortint", "integer", "aarch64-unix"] }
```
Note: users with ARM devices must compile `TFHE-rs` using a stable toolchain with version >= 1.72.
+ For x86_64-based machines with the [`rdseed instruction`](https://en.wikipedia.org/wiki/RDRAND) running Windows:
+ For x86_64-based machines with the [`rdseed instruction`](https://en.wikipedia.org/wiki/RDRAND)
running Windows:
```toml
tfhe = { version = "*", features = ["boolean", "shortint", "integer", "x86_64"] }
```
> [!Note]
> Note: You need to use a Rust version >= 1.73 to compile TFHE-rs.
Note: aarch64-based machines are not yet 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
> [!Note]
> Note: aarch64-based machines are not yet 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.
<p align="right">
<a href="#about" > ↑ Back to top </a>
</p>
### A simple example
## A simple example
Here is a full example:
@@ -108,7 +70,9 @@ use tfhe::{generate_keys, set_server_key, ConfigBuilder, FheUint32, FheUint8};
fn main() -> Result<(), Box<dyn std::error::Error>> {
// Basic configuration to use homomorphic integers
let config = ConfigBuilder::default().build();
let config = ConfigBuilder::all_disabled()
.enable_default_integers()
.build();
// Key generation
let (client_key, server_keys) = generate_keys(config);
@@ -131,13 +95,13 @@ fn main() -> Result<(), Box<dyn std::error::Error>> {
// Clear equivalent computations: 1344 * 5 = 6720
let encrypted_res_mul = &encrypted_a * &encrypted_b;
// Clear equivalent computations: 6720 >> 5 = 210
// Clear equivalent computations: 1344 >> 5 = 42
encrypted_a = &encrypted_res_mul >> &encrypted_b;
// Clear equivalent computations: let casted_a = a as u8;
let casted_a: FheUint8 = encrypted_a.cast_into();
// Clear equivalent computations: min(210, 7) = 7
// Clear equivalent computations: min(42, 7) = 7
let encrypted_res_min = &casted_a.min(&encrypted_c);
// Operation between clear and encrypted data:
@@ -155,70 +119,32 @@ fn main() -> Result<(), Box<dyn std::error::Error>> {
To run this code, use the following command:
<p align="center"> <code> cargo run --release </code> </p>
> [!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 performances possible.
*Find an example with more explanations in [this part of the documentation](https://docs.zama.ai/tfhe-rs/getting-started/quick_start)*
<p align="right">
<a href="#about" > ↑ Back to top </a>
</p>
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 performances possible,
## Contributing
## Resources
There are two ways to contribute to TFHE-rs:
### TFHE deep dive
- [TFHE Deep Dive - Part I - Ciphertext types](https://www.zama.ai/post/tfhe-deep-dive-part-1)
- [TFHE Deep Dive - Part II - Encodings and linear leveled operations](https://www.zama.ai/post/tfhe-deep-dive-part-2)
- [TFHE Deep Dive - Part III - Key switching and leveled multiplications](https://www.zama.ai/post/tfhe-deep-dive-part-3)
- [TFHE Deep Dive - Part IV - Programmable Bootstrapping](https://www.zama.ai/post/tfhe-deep-dive-part-4)
<br></br>
- you can open issues to report bugs or typos, or to suggest new ideas
- you can ask to become an official contributor by emailing [hello@zama.ai](mailto:hello@zama.ai).
(becoming an approved contributor involves signing our Contributor License Agreement (CLA))
### Tutorials
- [[Video tutorial] Implement signed integers using TFHE-rs ](https://www.zama.ai/post/video-tutorial-implement-signed-integers-ssing-tfhe-rs)
- [Homomorphic parity bit](https://docs.zama.ai/tfhe-rs/tutorials/parity_bit)
- [Homomorphic case changing on Ascii string](https://docs.zama.ai/tfhe-rs/tutorials/ascii_fhe_string)
- [Boolean SHA256 with TFHE-rs](https://www.zama.ai/post/boolean-sha256-tfhe-rs)
- [Dark market with TFHE-rs](https://www.zama.ai/post/dark-market-tfhe-rs)
- [Regular expression engine with TFHE-rs](https://www.zama.ai/post/regex-engine-tfhe-rs)
Only approved contributors can send pull requests, so please make sure to get in touch before you do!
*Explore more useful resources in [TFHE-rs tutorials](https://docs.zama.ai/tfhe-rs/tutorials) and [Awesome Zama repo](https://github.com/zama-ai/awesome-zama)*
<br></br>
### Documentation
## Credits
Full, comprehensive documentation is available here: [https://docs.zama.ai/tfhe-rs](https://docs.zama.ai/tfhe-rs).
<p align="right">
<a href="#about" > ↑ Back to top </a>
</p>
This library uses several dependencies and we would like to thank the contributors of those
libraries.
## Need support?
<a target="_blank" href="https://community.zama.ai">
<img src="https://user-images.githubusercontent.com/5758427/231115030-21195b55-2629-4c01-9809-be5059243999.png">
</a>
## Working with TFHE-rs
## Citing TFHE-rs
### Disclaimers
#### Security Estimation
Security estimations are done using the
[Lattice Estimator](https://github.com/malb/lattice-estimator)
with `red_cost_model = reduction.RC.BDGL16`.
When a new update is published in the Lattice Estimator, we update parameters accordingly.
### Security Model
The default parameters for the TFHE-rs library are chosen considering the IND-CPA security model, and are selected with a bootstrapping failure probability fixed at p_error = $2^{-40}$. In particular, it is assumed that the results of decrypted computations are not shared by the secret key owner with any third parties, as such an action can lead to leakage of the secret encryption key. If you are designing an application where decryptions must be shared, you will need to craft custom encryption parameters which are chosen in consideration of the IND-CPA^D security model [1].
[1] Li, Baiyu, et al. "Securing approximate homomorphic encryption using differential privacy." Annual International Cryptology Conference. Cham: Springer Nature Switzerland, 2022. https://eprint.iacr.org/2022/816.pdf
#### Side-Channel Attacks
Mitigation for side-channel attacks has not yet been implemented in TFHE-rs,
and will be released in upcoming versions.
<br></br>
### Citations
To cite TFHE-rs in academic papers, please use the following entry:
```text
@@ -230,35 +156,22 @@ To cite TFHE-rs in academic papers, please use the following entry:
}
```
### Contributing
## License
There are two ways to contribute to TFHE-rs:
This software is distributed under the BSD-3-Clause-Clear license. If you have any questions,
please contact us at `hello@zama.ai`.
- [Open issues](https://github.com/zama-ai/tfhe-rs/issues/new/choose) to report bugs and typos, or to suggest new ideas
- Request to become an official contributor by emailing [hello@zama.ai](mailto:hello@zama.ai).
## Disclaimers
Becoming an approved contributor involves signing our Contributor License Agreement (CLA). Only approved contributors can send pull requests, so please make sure to get in touch before you do!
<br></br>
### Security Estimation
### License
This software is distributed under the **BSD-3-Clause-Clear** license. If you have any questions, please contact us at hello@zama.ai.
<p align="right">
<a href="#about" > ↑ Back to top </a>
</p>
Security estimations are done using the
[Lattice Estimator](https://github.com/malb/lattice-estimator)
with `red_cost_model = reduction.RC.BDGL16`.
When a new update is published in the Lattice Estimator, we update parameters accordingly.
## Support
### Side-Channel Attacks
<a target="_blank" href="https://community.zama.ai">
<picture>
<source media="(prefers-color-scheme: dark)" srcset="https://github.com/zama-ai/tfhe-rs/assets/157474013/08656d0a-3f44-4126-b8b6-8c601dff5380">
<source media="(prefers-color-scheme: light)" srcset="https://github.com/zama-ai/tfhe-rs/assets/157474013/1c9c9308-50ac-4aab-a4b9-469bb8c536a4">
<img alt="Support">
</picture>
</a>
🌟 If you find this project helpful or interesting, please consider giving it a star on GitHub! Your support helps to grow the community and motivates further development.
<p align="right">
<a href="#about" > ↑ Back to top </a>
</p>
Mitigation for side channel attacks have not yet been implemented in TFHE-rs,
and will be released in upcoming versions.

84
README_CCS.md Normal file
View File

@@ -0,0 +1,84 @@
# Description
In what follows, we provide instructions on how to run benchmarks from the paper entitled "New Secret Keys for Enhanced Performance in (T)FHE". In particular, Table 2 and Figure 4 (in the Appendix) can be easily reproduced using this code.
The implementation of the techniques from the aforementioned paper has been integrated into the TFHE-rs library, version 0.4.
Modified or added source files are located in `tfhe/src/core_crypto/`:
- `algorithms/pseudo_ggsw_encryption.rs`
- `algorithms/pseudo_ggsw_conversion.rs`
- `algorithms/lwe_shrinking_keyswitch_key_generation.rs`
- `algorithms/lwe_shrinking_keyswitch.rs`
- `algorithms/lwe_secret_key_generation.rs`
- `algorithms/lwe_partial_secret_key_generation.rs`
- `algorithms/lwe_fast_keyswitch_key_generation.rs`
- `algorithms/lwe_fast_keyswitch.rs`
- `algorithms/glwe_secret_key_generation.rs`
- `algorithms/glwe_partial_secret_key_generation.rs`
- `algorithms/glwe_partial_sample_extraction.rs`
Test files are located in `tfhe/src/core_crypto/algorithms/test`:
- `lwe_stair_keyswitch.rs`
- `lwe_fast_keyswitch.rs`
Benchmarks are located in `tfhe/benches/core_crypto`:
- `ccs_2024_cjp.rs`
- `ccs_2024_fft_shrinking_ks.rs`
- `ccs_2024_stair_ks.rs`
# Dependencies
Tested on Linux and Mac OS with Rust >= 1.75 (see [here](https://www.rust-lang.org/tools/install) a guide to install Rust).
# How to run benchmarks
At the root of the project (i.e., in the TFHE-rs folder), enter the following commands to run the benchmarks:
- `make bench_ccs_2024_cjp`: Returns the timings associated with the CJP-based bootstrapping (Table 2, Line 1 + Figure 4, blue line);
- `make bench_ccs_2024_stair_ks`: Returns the timings associated with the "All+Stair-KS"-based bootstrapping (Table 2, Line 2 + Figure 4, red line);
- `make bench_ccs_2024_fft_shrinking_ks`: Returns the timings associated with the "All+FFT Shrinking-KS"-based bootstrapping (Table 2, Line 3 + Figure 4, green line);
This outputs the timings depending on the input precision.
Since large precision (>= 6 bits) might be long to execute, particularly on a laptop, these are disable by default. To choose which precision to launch, please uncomment lines associated to the parameter names into the `param_vec` variable, inside the `criterion_bench` function inside one of the benchmark files.
For instance, to launch only the precision 7 of the stair-KS benchmark, the correct `param_vec` variable (line 353 of `ccs_2024_stair_ks.rs`) looks like:
```rust
let param_vec = [
// PRECISION_1_STAIR,
// PRECISION_2_STAIR,
// PRECISION_3_STAIR,
// PRECISION_4_STAIR,
// PRECISION_5_STAIR,
// PRECISION_6_STAIR,
PRECISION_7_STAIR
// PRECISION_8_STAIR,
// PRECISION_9_STAIR,
// PRECISION_10_STAIR,
// PRECISION_11_STAIR,
];
```
Running the command `make bench_ccs_2024_stair_ks`will give the correct benchmark.
# How to run the tests
At the root of the project (i.e., in the TFHE-rs folder), enter the following commands to run the tests:
- `make test_ccs_2024_stair_ks`: Returns the timings associated with the "All+Stair-KS"-based bootstrapping (Table 2, Line 2 + Figure 4, red line);
- `make test_ccs_2024_fft_shrinking_ks`: Returns the timings associated with the "All+FFT Shrinking-KS"-based bootstrapping (Table 2, Line 3 + Figure 4, green line);
As for the benchmarks, all precision are not enabled by default. To add precision in the test, associated parameters must be uncommented in the macro `create_parametrized_test!` (located at the end of each test file)
For instance, in the file `lwe_fast_keyswitch.rs`, testing only the precision will look like this:
```rust
create_parametrized_test!(lwe_encrypt_fast_ks_decrypt_custom_mod {
PRECISION_1_FAST_KS,
PRECISION_2_FAST_KS,
PRECISION_3_FAST_KS,
PRECISION_4_FAST_KS,
PRECISION_5_FAST_KS,
PRECISION_6_FAST_KS,
PRECISION_7_FAST_KS,
PRECISION_8_FAST_KS,
// PRECISION_9_FAST_KS,
PRECISION_10_FAST_KS
// PRECISION_11_FAST_KS
});
```
Please note that the last parameter MUST NOT be followed by a comma `,` to correctly compile.

View File

@@ -15,6 +15,7 @@ Example of a Rust main below:
```rust
use tfhe::{ConfigBuilder, generate_keys, FheBool};
use tfhe::prelude::*;
use tfhe_trivium::TriviumStream;
fn get_hexadecimal_string_from_lsb_first_stream(a: Vec<bool>) -> String {
@@ -138,8 +139,10 @@ Example code:
```rust
use tfhe::shortint::prelude::*;
use tfhe::shortint::CastingKey;
use tfhe::{ConfigBuilder, generate_keys, FheUint64};
use tfhe::prelude::*;
use tfhe_trivium::TriviumStreamShortint;
fn test_shortint() {

View File

@@ -1,10 +1,12 @@
use criterion::Criterion;
use tfhe::prelude::*;
use tfhe::{generate_keys, ConfigBuilder, FheBool};
use tfhe_trivium::KreyviumStream;
use criterion::Criterion;
pub fn kreyvium_bool_gen(c: &mut Criterion) {
let config = ConfigBuilder::default().build();
let config = ConfigBuilder::all_disabled().enable_default_bool().build();
let (client_key, server_key) = generate_keys(config);
let key_string = "0053A6F94C9FF24598EB000000000000".to_string();
@@ -39,7 +41,7 @@ pub fn kreyvium_bool_gen(c: &mut Criterion) {
}
pub fn kreyvium_bool_warmup(c: &mut Criterion) {
let config = ConfigBuilder::default().build();
let config = ConfigBuilder::all_disabled().enable_default_bool().build();
let (client_key, server_key) = generate_keys(config);
let key_string = "0053A6F94C9FF24598EB000000000000".to_string();

View File

@@ -1,11 +1,14 @@
use criterion::Criterion;
use tfhe::prelude::*;
use tfhe::{generate_keys, ConfigBuilder, FheUint64, FheUint8};
use tfhe_trivium::{KreyviumStreamByte, TransCiphering};
use criterion::Criterion;
pub fn kreyvium_byte_gen(c: &mut Criterion) {
let config = ConfigBuilder::default()
.enable_function_evaluation()
let config = ConfigBuilder::all_disabled()
.enable_default_integers()
.enable_function_evaluation_integers()
.build();
let (client_key, server_key) = generate_keys(config);
@@ -33,8 +36,9 @@ pub fn kreyvium_byte_gen(c: &mut Criterion) {
}
pub fn kreyvium_byte_trans(c: &mut Criterion) {
let config = ConfigBuilder::default()
.enable_function_evaluation()
let config = ConfigBuilder::all_disabled()
.enable_default_integers()
.enable_function_evaluation_integers()
.build();
let (client_key, server_key) = generate_keys(config);
@@ -63,8 +67,9 @@ pub fn kreyvium_byte_trans(c: &mut Criterion) {
}
pub fn kreyvium_byte_warmup(c: &mut Criterion) {
let config = ConfigBuilder::default()
.enable_function_evaluation()
let config = ConfigBuilder::all_disabled()
.enable_default_integers()
.enable_function_evaluation_integers()
.build();
let (client_key, server_key) = generate_keys(config);

View File

@@ -1,11 +1,16 @@
use criterion::Criterion;
use tfhe::prelude::*;
use tfhe::shortint::prelude::*;
use tfhe::shortint::KeySwitchingKey;
use tfhe::{generate_keys, ConfigBuilder, FheUint64};
use tfhe_trivium::{KreyviumStreamShortint, TransCiphering};
use criterion::Criterion;
pub fn kreyvium_shortint_warmup(c: &mut Criterion) {
let config = ConfigBuilder::default().build();
let config = ConfigBuilder::all_disabled()
.enable_default_integers()
.build();
let (hl_client_key, hl_server_key) = generate_keys(config);
let underlying_ck: tfhe::shortint::ClientKey = (*hl_client_key.as_ref()).clone().into();
let underlying_sk: tfhe::shortint::ServerKey = (*hl_server_key.as_ref()).clone().into();
@@ -55,7 +60,9 @@ pub fn kreyvium_shortint_warmup(c: &mut Criterion) {
}
pub fn kreyvium_shortint_gen(c: &mut Criterion) {
let config = ConfigBuilder::default().build();
let config = ConfigBuilder::all_disabled()
.enable_default_integers()
.build();
let (hl_client_key, hl_server_key) = generate_keys(config);
let underlying_ck: tfhe::shortint::ClientKey = (*hl_client_key.as_ref()).clone().into();
let underlying_sk: tfhe::shortint::ServerKey = (*hl_server_key.as_ref()).clone().into();
@@ -100,7 +107,9 @@ pub fn kreyvium_shortint_gen(c: &mut Criterion) {
}
pub fn kreyvium_shortint_trans(c: &mut Criterion) {
let config = ConfigBuilder::default().build();
let config = ConfigBuilder::all_disabled()
.enable_default_integers()
.build();
let (hl_client_key, hl_server_key) = generate_keys(config);
let underlying_ck: tfhe::shortint::ClientKey = (*hl_client_key.as_ref()).clone().into();
let underlying_sk: tfhe::shortint::ServerKey = (*hl_server_key.as_ref()).clone().into();

View File

@@ -1,10 +1,12 @@
use criterion::Criterion;
use tfhe::prelude::*;
use tfhe::{generate_keys, ConfigBuilder, FheBool};
use tfhe_trivium::TriviumStream;
use criterion::Criterion;
pub fn trivium_bool_gen(c: &mut Criterion) {
let config = ConfigBuilder::default().build();
let config = ConfigBuilder::all_disabled().enable_default_bool().build();
let (client_key, server_key) = generate_keys(config);
let key_string = "0053A6F94C9FF24598EB".to_string();
@@ -39,7 +41,7 @@ pub fn trivium_bool_gen(c: &mut Criterion) {
}
pub fn trivium_bool_warmup(c: &mut Criterion) {
let config = ConfigBuilder::default().build();
let config = ConfigBuilder::all_disabled().enable_default_bool().build();
let (client_key, server_key) = generate_keys(config);
let key_string = "0053A6F94C9FF24598EB".to_string();

View File

@@ -1,10 +1,14 @@
use criterion::Criterion;
use tfhe::prelude::*;
use tfhe::{generate_keys, ConfigBuilder, FheUint64, FheUint8};
use tfhe_trivium::{TransCiphering, TriviumStreamByte};
use criterion::Criterion;
pub fn trivium_byte_gen(c: &mut Criterion) {
let config = ConfigBuilder::default().build();
let config = ConfigBuilder::all_disabled()
.enable_default_integers()
.build();
let (client_key, server_key) = generate_keys(config);
let key_string = "0053A6F94C9FF24598EB".to_string();
@@ -31,7 +35,9 @@ pub fn trivium_byte_gen(c: &mut Criterion) {
}
pub fn trivium_byte_trans(c: &mut Criterion) {
let config = ConfigBuilder::default().build();
let config = ConfigBuilder::all_disabled()
.enable_default_integers()
.build();
let (client_key, server_key) = generate_keys(config);
let key_string = "0053A6F94C9FF24598EB".to_string();
@@ -59,7 +65,9 @@ pub fn trivium_byte_trans(c: &mut Criterion) {
}
pub fn trivium_byte_warmup(c: &mut Criterion) {
let config = ConfigBuilder::default().build();
let config = ConfigBuilder::all_disabled()
.enable_default_integers()
.build();
let (client_key, server_key) = generate_keys(config);
let key_string = "0053A6F94C9FF24598EB".to_string();

View File

@@ -1,11 +1,16 @@
use criterion::Criterion;
use tfhe::prelude::*;
use tfhe::shortint::prelude::*;
use tfhe::shortint::KeySwitchingKey;
use tfhe::{generate_keys, ConfigBuilder, FheUint64};
use tfhe_trivium::{TransCiphering, TriviumStreamShortint};
use criterion::Criterion;
pub fn trivium_shortint_warmup(c: &mut Criterion) {
let config = ConfigBuilder::default().build();
let config = ConfigBuilder::all_disabled()
.enable_default_integers()
.build();
let (hl_client_key, hl_server_key) = generate_keys(config);
let underlying_ck: tfhe::shortint::ClientKey = (*hl_client_key.as_ref()).clone().into();
let underlying_sk: tfhe::shortint::ServerKey = (*hl_server_key.as_ref()).clone().into();
@@ -55,7 +60,9 @@ pub fn trivium_shortint_warmup(c: &mut Criterion) {
}
pub fn trivium_shortint_gen(c: &mut Criterion) {
let config = ConfigBuilder::default().build();
let config = ConfigBuilder::all_disabled()
.enable_default_integers()
.build();
let (hl_client_key, hl_server_key) = generate_keys(config);
let underlying_ck: tfhe::shortint::ClientKey = (*hl_client_key.as_ref()).clone().into();
let underlying_sk: tfhe::shortint::ServerKey = (*hl_server_key.as_ref()).clone().into();
@@ -100,7 +107,9 @@ pub fn trivium_shortint_gen(c: &mut Criterion) {
}
pub fn trivium_shortint_trans(c: &mut Criterion) {
let config = ConfigBuilder::default().build();
let config = ConfigBuilder::all_disabled()
.enable_default_integers()
.build();
let (hl_client_key, hl_server_key) = generate_keys(config);
let underlying_ck: tfhe::shortint::ClientKey = (*hl_client_key.as_ref()).clone().into();
let underlying_sk: tfhe::shortint::ServerKey = (*hl_server_key.as_ref()).clone().into();

View File

@@ -2,10 +2,12 @@
//! for the representation of the inner bits.
use crate::static_deque::StaticDeque;
use rayon::prelude::*;
use tfhe::prelude::*;
use tfhe::{set_server_key, unset_server_key, FheBool, ServerKey};
use rayon::prelude::*;
/// Internal trait specifying which operations are necessary for KreyviumStream generic type
pub trait KreyviumBoolInput<OpOutput>:
Sized

View File

@@ -2,10 +2,12 @@
//! for the representation of the inner bits.
use crate::static_deque::{StaticByteDeque, StaticByteDequeInput};
use rayon::prelude::*;
use tfhe::prelude::*;
use tfhe::{set_server_key, unset_server_key, FheUint8, ServerKey};
use rayon::prelude::*;
/// Internal trait specifying which operations are necessary for KreyviumStreamByte generic type
pub trait KreyviumByteInput<OpOutput>:
Sized

View File

@@ -1,7 +1,9 @@
use crate::static_deque::StaticDeque;
use rayon::prelude::*;
use tfhe::shortint::prelude::*;
use rayon::prelude::*;
/// KreyviumStreamShortint: a struct implementing the Kreyvium stream cipher, using a generic
/// Ciphertext for the internal representation of bits (intended to represent a single bit). To be
/// able to compute FHE operations, it also owns a ServerKey.
@@ -34,7 +36,7 @@ impl KreyviumStreamShortint {
let mut c_register: [Ciphertext; 111] = [0; 111].map(|x| sk.create_trivial(x));
for i in 0..93 {
a_register[i].clone_from(&key[128 - 93 + i]);
a_register[i] = key[128 - 93 + i].clone();
}
for i in 0..84 {
b_register[i] = sk.create_trivial(iv[128 - 84 + i]);

View File

@@ -1,7 +1,8 @@
use crate::{KreyviumStream, KreyviumStreamByte, KreyviumStreamShortint, TransCiphering};
use tfhe::prelude::*;
use tfhe::{generate_keys, ConfigBuilder, FheBool, FheUint64, FheUint8};
use crate::{KreyviumStream, KreyviumStreamByte, KreyviumStreamShortint, TransCiphering};
// Values for these tests come from the github repo renaud1239/Kreyvium,
// commit fd6828f68711276c25f55e605935028f5e843f43
@@ -169,7 +170,7 @@ fn kreyvium_test_4() {
#[test]
fn kreyvium_test_fhe_long() {
let config = ConfigBuilder::default().build();
let config = ConfigBuilder::all_disabled().enable_default_bool().build();
let (client_key, server_key) = generate_keys(config);
let key_string = "0053A6F94C9FF24598EB000000000000".to_string();
@@ -216,7 +217,9 @@ use tfhe::shortint::prelude::*;
#[test]
fn kreyvium_test_shortint_long() {
let config = ConfigBuilder::default().build();
let config = ConfigBuilder::all_disabled()
.enable_default_integers()
.build();
let (hl_client_key, hl_server_key) = generate_keys(config);
let underlying_ck: tfhe::shortint::ClientKey = (*hl_client_key.as_ref()).clone().into();
let underlying_sk: tfhe::shortint::ServerKey = (*hl_server_key.as_ref()).clone().into();
@@ -299,8 +302,9 @@ fn kreyvium_test_clear_byte() {
#[test]
fn kreyvium_test_byte_long() {
let config = ConfigBuilder::default()
.enable_function_evaluation()
let config = ConfigBuilder::all_disabled()
.enable_default_integers()
.enable_function_evaluation_integers()
.build();
let (client_key, server_key) = generate_keys(config);
@@ -338,8 +342,9 @@ fn kreyvium_test_byte_long() {
#[test]
fn kreyvium_test_fhe_byte_transciphering_long() {
let config = ConfigBuilder::default()
.enable_function_evaluation()
let config = ConfigBuilder::all_disabled()
.enable_default_integers()
.enable_function_evaluation_integers()
.build();
let (client_key, server_key) = generate_keys(config);

View File

@@ -1,6 +1,5 @@
#[allow(clippy::module_inception)]
mod static_deque;
pub use static_deque::StaticDeque;
mod static_byte_deque;
pub use static_byte_deque::{StaticByteDeque, StaticByteDequeInput};

View File

@@ -4,6 +4,7 @@
//! This is pretending to store bits, and allows accessing bits in chunks of 8 consecutive.
use crate::static_deque::StaticDeque;
use tfhe::FheUint8;
/// Internal trait specifying which operations are needed by StaticByteDeque

View File

@@ -2,11 +2,12 @@
//! when trans ciphering is available to them.
use crate::{KreyviumStreamByte, KreyviumStreamShortint, TriviumStreamByte, TriviumStreamShortint};
use rayon::prelude::*;
use tfhe::prelude::*;
use tfhe::shortint::Ciphertext;
use tfhe::{set_server_key, unset_server_key, FheUint64, FheUint8, ServerKey};
use rayon::prelude::*;
/// Triat specifying the interface for trans ciphering a FheUint64 object. Since it is meant
/// to be used with stream ciphers, encryption and decryption are by default the same.
pub trait TransCiphering {

View File

@@ -1,7 +1,8 @@
use crate::{TransCiphering, TriviumStream, TriviumStreamByte, TriviumStreamShortint};
use tfhe::prelude::*;
use tfhe::{generate_keys, ConfigBuilder, FheBool, FheUint64, FheUint8};
use crate::{TransCiphering, TriviumStream, TriviumStreamByte, TriviumStreamShortint};
// Values for these tests come from the github repo cantora/avr-crypto-lib, commit 2a5b018,
// file testvectors/trivium-80.80.test-vectors
@@ -231,7 +232,7 @@ fn trivium_test_clear_byte() {
#[test]
fn trivium_test_fhe_long() {
let config = ConfigBuilder::default().build();
let config = ConfigBuilder::all_disabled().enable_default_bool().build();
let (client_key, server_key) = generate_keys(config);
let key_string = "0053A6F94C9FF24598EB".to_string();
@@ -276,7 +277,9 @@ fn trivium_test_fhe_long() {
#[test]
fn trivium_test_fhe_byte_long() {
let config = ConfigBuilder::default().build();
let config = ConfigBuilder::all_disabled()
.enable_default_integers()
.build();
let (client_key, server_key) = generate_keys(config);
let key_string = "0053A6F94C9FF24598EB".to_string();
@@ -313,7 +316,9 @@ fn trivium_test_fhe_byte_long() {
#[test]
fn trivium_test_fhe_byte_transciphering_long() {
let config = ConfigBuilder::default().build();
let config = ConfigBuilder::all_disabled()
.enable_default_integers()
.build();
let (client_key, server_key) = generate_keys(config);
let key_string = "0053A6F94C9FF24598EB".to_string();
@@ -352,7 +357,9 @@ use tfhe::shortint::prelude::*;
#[test]
fn trivium_test_shortint_long() {
let config = ConfigBuilder::default().build();
let config = ConfigBuilder::all_disabled()
.enable_default_integers()
.build();
let (hl_client_key, hl_server_key) = generate_keys(config);
let underlying_ck: tfhe::shortint::ClientKey = (*hl_client_key.as_ref()).clone().into();
let underlying_sk: tfhe::shortint::ServerKey = (*hl_server_key.as_ref()).clone().into();

View File

@@ -2,10 +2,12 @@
//! for the representation of the inner bits.
use crate::static_deque::StaticDeque;
use rayon::prelude::*;
use tfhe::prelude::*;
use tfhe::{set_server_key, unset_server_key, FheBool, ServerKey};
use rayon::prelude::*;
/// Internal trait specifying which operations are necessary for TriviumStream generic type
pub trait TriviumBoolInput<OpOutput>:
Sized

View File

@@ -2,10 +2,12 @@
//! for the representation of the inner bits.
use crate::static_deque::{StaticByteDeque, StaticByteDequeInput};
use rayon::prelude::*;
use tfhe::prelude::*;
use tfhe::{set_server_key, unset_server_key, FheUint8, ServerKey};
use rayon::prelude::*;
/// Internal trait specifying which operations are necessary for TriviumStreamByte generic type
pub trait TriviumByteInput<OpOutput>:
Sized

View File

@@ -1,7 +1,9 @@
use crate::static_deque::StaticDeque;
use rayon::prelude::*;
use tfhe::shortint::prelude::*;
use rayon::prelude::*;
/// TriviumStreamShortint: a struct implementing the Trivium stream cipher, using a generic
/// Ciphertext for the internal representation of bits (intended to represent a single bit). To be
/// able to compute FHE operations, it also owns a ServerKey.
@@ -32,7 +34,7 @@ impl TriviumStreamShortint {
let mut c_register: [Ciphertext; 111] = [0; 111].map(|x| sk.create_trivial(x));
for i in 0..80 {
a_register[93 - 80 + i].clone_from(&key[i]);
a_register[93 - 80 + i] = key[i].clone();
b_register[84 - 80 + i] = sk.create_trivial(iv[i]);
}

View File

@@ -1,18 +0,0 @@
[package]
name = "tfhe-cuda-backend"
version = "0.2.0"
edition = "2021"
authors = ["Zama team"]
license = "BSD-3-Clause-Clear"
description = "Cuda implementation of TFHE-rs primitives."
homepage = "https://www.zama.ai/"
documentation = "https://docs.zama.ai/tfhe-rs"
repository = "https://github.com/zama-ai/tfhe-rs"
readme = "README.md"
keywords = ["fully", "homomorphic", "encryption", "fhe", "cryptography"]
[build-dependencies]
cmake = { version = "0.1" }
[dependencies]
thiserror = "1.0"

View File

@@ -1,28 +0,0 @@
BSD 3-Clause Clear License
Copyright © 2024 ZAMA.
All rights reserved.
Redistribution and use in source and binary forms, with or without modification,
are permitted provided that the following conditions are met:
1. Redistributions of source code must retain the above copyright notice, this
list of conditions and the following disclaimer.
2. Redistributions in binary form must reproduce the above copyright notice, this
list of conditions and the following disclaimer in the documentation and/or other
materials provided with the distribution.
3. Neither the name of ZAMA nor the names of its contributors may be used to endorse
or promote products derived from this software without specific prior written permission.
NO EXPRESS OR IMPLIED LICENSES TO ANY PARTY'S PATENT RIGHTS ARE GRANTED BY THIS LICENSE.
THIS SOFTWARE IS PROVIDED BY THE ZAMA AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR
IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF
MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL
ZAMA OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY,
OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS
OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND
ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING
NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF
ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.

View File

@@ -1,52 +0,0 @@
# TFHE Cuda backend
## Introduction
The `tfhe-cuda-backend` holds the code for GPU acceleration of Zama's variant of TFHE.
It implements CUDA/C++ functions to perform homomorphic operations on LWE ciphertexts.
It provides functions to allocate memory on the GPU, to copy data back
and forth between the CPU and the GPU, to create and destroy Cuda streams, etc.:
- `cuda_create_stream`, `cuda_destroy_stream`
- `cuda_malloc`, `cuda_check_valid_malloc`
- `cuda_memcpy_async_to_cpu`, `cuda_memcpy_async_to_gpu`
- `cuda_get_number_of_gpus`
- `cuda_synchronize_device`
The cryptographic operations it provides are:
- an amortized implementation of the TFHE programmable bootstrap: `cuda_bootstrap_amortized_lwe_ciphertext_vector_32` and `cuda_bootstrap_amortized_lwe_ciphertext_vector_64`
- a low latency implementation of the TFHE programmable bootstrap: `cuda_bootstrap_low latency_lwe_ciphertext_vector_32` and `cuda_bootstrap_low_latency_lwe_ciphertext_vector_64`
- the keyswitch: `cuda_keyswitch_lwe_ciphertext_vector_32` and `cuda_keyswitch_lwe_ciphertext_vector_64`
- the larger precision programmable bootstrap (wop PBS, which supports up to 16 bits of message while the classical PBS only supports up to 8 bits of message) and its sub-components: `cuda_wop_pbs_64`, `cuda_extract_bits_64`, `cuda_circuit_bootstrap_64`, `cuda_cmux_tree_64`, `cuda_blind_rotation_sample_extraction_64`
- acceleration for leveled operations: `cuda_negate_lwe_ciphertext_vector_64`, `cuda_add_lwe_ciphertext_vector_64`, `cuda_add_lwe_ciphertext_vector_plaintext_vector_64`, `cuda_mult_lwe_ciphertext_vector_cleartext_vector`.
## Dependencies
**Disclaimer**: Compilation on Windows/Mac is not supported yet. Only Nvidia GPUs are supported.
- nvidia driver - for example, if you're running Ubuntu 20.04 check this [page](https://linuxconfig.org/how-to-install-the-nvidia-drivers-on-ubuntu-20-04-focal-fossa-linux) for installation
- [nvcc](https://docs.nvidia.com/cuda/cuda-installation-guide-linux/index.html) >= 10.0
- [gcc](https://gcc.gnu.org/) >= 8.0 - check this [page](https://gist.github.com/ax3l/9489132) for more details about nvcc/gcc compatible versions
- [cmake](https://cmake.org/) >= 3.24
## Build
The Cuda project held in `tfhe-cuda-backend` can be compiled independently from TFHE-rs in the following way:
```
git clone git@github.com:zama-ai/tfhe-rs
cd backends/tfhe-cuda-backend/cuda
mkdir build
cd build
cmake ..
make
```
The compute capability is detected automatically (with the first GPU information) and set accordingly.
If your machine does not have an available Nvidia GPU, the compilation will work if you have the nvcc compiler installed. The generated executable will target a 7.0 compute capability (sm_70).
## Links
- [TFHE](https://eprint.iacr.org/2018/421.pdf)
## License
This software is distributed under the BSD-3-Clause-Clear license. If you have any questions,
please contact us at `hello@zama.ai`.

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@@ -1,34 +0,0 @@
use std::env;
use std::process::Command;
fn main() {
if let Ok(val) = env::var("DOCS_RS") {
if val.parse::<u32>() == Ok(1) {
return;
}
}
println!("Build tfhe-cuda-backend");
if env::consts::OS == "linux" {
let output = Command::new("./get_os_name.sh").output().unwrap();
let distribution = String::from_utf8(output.stdout).unwrap();
if distribution != "Ubuntu\n" {
println!(
"cargo:warning=This Linux distribution is not officially supported. \
Only Ubuntu is supported by tfhe-cuda-backend at this time. Build may fail\n"
);
}
let dest = cmake::build("cuda");
println!("cargo:rustc-link-search=native={}", dest.display());
println!("cargo:rustc-link-lib=static=tfhe_cuda_backend");
println!("cargo:rustc-link-search=native=/usr/local/cuda/lib64");
println!("cargo:rustc-link-lib=gomp");
println!("cargo:rustc-link-lib=cudart");
println!("cargo:rustc-link-search=native=/usr/lib/x86_64-linux-gnu/");
println!("cargo:rustc-link-lib=stdc++");
} else {
panic!(
"Error: platform not supported, tfhe-cuda-backend not built (only Linux is supported)"
);
}
}

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@@ -1,10 +0,0 @@
# -----------------------------
# Options effecting formatting.
# -----------------------------
with section("format"):
# How wide to allow formatted cmake files
line_width = 120
# How many spaces to tab for indent
tab_size = 2

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@@ -1,2 +0,0 @@
/build/
include/cuda_config.h

View File

@@ -1,96 +0,0 @@
cmake_minimum_required(VERSION 3.24 FATAL_ERROR)
project(tfhe_cuda_backend LANGUAGES CXX)
# See if the minimum CUDA version is available. If not, only enable documentation building.
set(MINIMUM_SUPPORTED_CUDA_VERSION 10.0)
include(CheckLanguage)
# See if CUDA is available
check_language(CUDA)
# If so, enable CUDA to check the version.
if(CMAKE_CUDA_COMPILER)
enable_language(CUDA)
endif()
# If CUDA is not available, or the minimum version is too low do not build
if(NOT CMAKE_CUDA_COMPILER)
message(FATAL_ERROR "Cuda compiler not found.")
endif()
if(CMAKE_CUDA_COMPILER_VERSION VERSION_LESS ${MINIMUM_SUPPORTED_CUDA_VERSION})
message(FATAL_ERROR "CUDA ${MINIMUM_SUPPORTED_CUDA_VERSION} or greater is required for compilation.")
endif()
# Get CUDA compute capability
set(OUTPUTFILE ${CMAKE_CURRENT_SOURCE_DIR}/cuda_script) # No suffix required
set(CUDAFILE ${CMAKE_CURRENT_SOURCE_DIR}/check_cuda.cu)
execute_process(COMMAND nvcc -lcuda ${CUDAFILE} -o ${OUTPUTFILE})
execute_process(
COMMAND ${OUTPUTFILE}
RESULT_VARIABLE CUDA_RETURN_CODE
OUTPUT_VARIABLE ARCH)
file(REMOVE ${OUTPUTFILE})
if(${CUDA_RETURN_CODE} EQUAL 0)
set(CUDA_SUCCESS "TRUE")
else()
set(CUDA_SUCCESS "FALSE")
endif()
if(${CUDA_SUCCESS})
message(STATUS "CUDA Architecture: ${ARCH}")
message(STATUS "CUDA Version: ${CUDA_VERSION_STRING}")
message(STATUS "CUDA Path: ${CUDA_TOOLKIT_ROOT_DIR}")
message(STATUS "CUDA Libraries: ${CUDA_LIBRARIES}")
message(STATUS "CUDA Performance Primitives: ${CUDA_npp_LIBRARY}")
else()
message(WARNING ${ARCH})
endif()
if(NOT CMAKE_BUILD_TYPE)
set(CMAKE_BUILD_TYPE Release)
endif()
# Add OpenMP support
find_package(OpenMP REQUIRED)
set(CMAKE_CXX_STANDARD 17)
set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -Wall -Wextra")
set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -g")
set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} ${OpenMP_CXX_FLAGS}")
set(CMAKE_CUDA_FLAGS "${CMAKE_CUDA_FLAGS} -Xcompiler ${OpenMP_CXX_FLAGS}")
if(${CUDA_SUCCESS})
set(CMAKE_CUDA_ARCHITECTURES native)
string(REPLACE "-arch=sm_" "" CUDA_ARCH "${ARCH}")
set(CUDA_ARCH "${CUDA_ARCH}0")
else()
set(CMAKE_CUDA_ARCHITECTURES 70)
set(CUDA_ARCH "700")
endif()
add_compile_definitions(CUDA_ARCH=${CUDA_ARCH})
# in production, should use -arch=sm_70 --ptxas-options=-v to see register spills -lineinfo for better debugging
set(CMAKE_CUDA_FLAGS
"${CMAKE_CUDA_FLAGS} -ccbin ${CMAKE_CXX_COMPILER} -O3 \
-std=c++17 --no-exceptions --expt-relaxed-constexpr -rdc=true \
--use_fast_math -Xcompiler -fPIC")
set(INCLUDE_DIR include)
add_subdirectory(src)
enable_testing()
add_subdirectory(tests_and_benchmarks)
target_include_directories(tfhe_cuda_backend PRIVATE ${INCLUDE_DIR})
# This is required for rust cargo build
install(TARGETS tfhe_cuda_backend DESTINATION .)
install(TARGETS tfhe_cuda_backend DESTINATION lib)
# Define a function to add a lint target.
find_file(CPPLINT NAMES cpplint cpplint.exe)
if(CPPLINT)
# Add a custom target to lint all child projects. Dependencies are specified in child projects.
add_custom_target(all_lint)
# Don't trigger this target on ALL_BUILD or Visual Studio 'Rebuild Solution'
set_target_properties(all_lint PROPERTIES EXCLUDE_FROM_ALL TRUE)
# set_target_properties(all_lint PROPERTIES EXCLUDE_FROM_DEFAULT_BUILD TRUE)
endif()

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@@ -1,3 +0,0 @@
set noparent
linelength=240
filter=-legal/copyright,-readability/todo,-runtime/references,-build/c++17

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@@ -1,22 +0,0 @@
#include <stdio.h>
int main(int argc, char **argv) {
cudaDeviceProp dP;
float min_cc = 3.0;
int rc = cudaGetDeviceProperties(&dP, 0);
if (rc != cudaSuccess) {
cudaError_t error = cudaGetLastError();
printf("CUDA error: %s", cudaGetErrorString(error));
return rc; /* Failure */
}
if ((dP.major + (dP.minor / 10)) < min_cc) {
printf("Min Compute Capability of %2.1f required: %d.%d found\n Not "
"Building CUDA Code",
min_cc, dP.major, dP.minor);
return 1; /* Failure */
} else {
printf("-arch=sm_%d%d", dP.major, dP.minor);
return 0; /* Success */
}
}

View File

@@ -1,19 +0,0 @@
#!/bin/bash
set -e
while getopts ":c" option; do
case $option in
c)
# code to execute when flag1 is provided
find ./{include,src,tests_and_benchmarks/include,tests_and_benchmarks/tests,tests_and_benchmarks/benchmarks} -iregex '^.*\.\(cpp\|cu\|h\|cuh\)$' -print | xargs clang-format-15 -i -style='file' --dry-run --Werror
cmake-format -i CMakeLists.txt -c .cmake-format-config.py
find ./{include,src,tests_and_benchmarks/include,tests_and_benchmarks/tests,tests_and_benchmarks/benchmarks} -type f -name "CMakeLists.txt" | xargs -I % sh -c 'cmake-format -i % -c .cmake-format-config.py'
git diff --exit-code
exit
;;
esac
done
find ./{include,src,tests_and_benchmarks/include,tests_and_benchmarks/tests,tests_and_benchmarks/benchmarks} -iregex '^.*\.\(cpp\|cu\|h\|cuh\)$' -print | xargs clang-format-15 -i -style='file'
cmake-format -i CMakeLists.txt -c .cmake-format-config.py
find ./{include,src,tests_and_benchmarks/include,tests_and_benchmarks/tests,tests_and_benchmarks/benchmarks} -type f -name "CMakeLists.txt" | xargs -I % sh -c 'cmake-format -i % -c .cmake-format-config.py'

View File

@@ -1,18 +0,0 @@
#ifndef CUDA_CIPHERTEXT_H
#define CUDA_CIPHERTEXT_H
#include <cstdint>
extern "C" {
void cuda_convert_lwe_ciphertext_vector_to_gpu_64(void *dest, void *src,
void *v_stream,
uint32_t gpu_index,
uint32_t number_of_cts,
uint32_t lwe_dimension);
void cuda_convert_lwe_ciphertext_vector_to_cpu_64(void *dest, void *src,
void *v_stream,
uint32_t gpu_index,
uint32_t number_of_cts,
uint32_t lwe_dimension);
};
#endif

View File

@@ -1,94 +0,0 @@
#ifndef DEVICE_H
#define DEVICE_H
#include <cstdint>
#include <cstdio>
#include <cstdlib>
#include <cstring>
#include <cuda_runtime.h>
#define synchronize_threads_in_block() __syncthreads()
extern "C" {
#define check_cuda_error(ans) \
{ cuda_error((ans), __FILE__, __LINE__); }
inline void cuda_error(cudaError_t code, const char *file, int line) {
if (code != cudaSuccess) {
std::fprintf(stderr, "Cuda error: %s %s %d\n", cudaGetErrorString(code),
file, line);
std::abort();
}
}
#define PANIC(format, ...) \
{ \
std::fprintf(stderr, "%s::%d::%s: panic.\n" format "\n", __FILE__, \
__LINE__, __func__, ##__VA_ARGS__); \
std::abort(); \
}
struct cuda_stream_t {
cudaStream_t stream;
uint32_t gpu_index;
cuda_stream_t(uint32_t gpu_index) {
this->gpu_index = gpu_index;
check_cuda_error(cudaStreamCreate(&stream));
}
void release() {
check_cuda_error(cudaSetDevice(gpu_index));
check_cuda_error(cudaStreamDestroy(stream));
}
void synchronize() { check_cuda_error(cudaStreamSynchronize(stream)); }
};
cuda_stream_t *cuda_create_stream(uint32_t gpu_index);
void cuda_destroy_stream(cuda_stream_t *stream);
void *cuda_malloc(uint64_t size, uint32_t gpu_index);
void *cuda_malloc_async(uint64_t size, cuda_stream_t *stream);
void cuda_check_valid_malloc(uint64_t size, uint32_t gpu_index);
bool cuda_check_support_cooperative_groups();
void cuda_memcpy_async_to_gpu(void *dest, void *src, uint64_t size,
cuda_stream_t *stream);
void cuda_memcpy_async_gpu_to_gpu(void *dest, void *src, uint64_t size,
cuda_stream_t *stream);
void cuda_memcpy_async_to_cpu(void *dest, const void *src, uint64_t size,
cuda_stream_t *stream);
void cuda_memset_async(void *dest, uint64_t val, uint64_t size,
cuda_stream_t *stream);
int cuda_get_number_of_gpus();
void cuda_synchronize_device(uint32_t gpu_index);
void cuda_drop(void *ptr, uint32_t gpu_index);
void cuda_drop_async(void *ptr, cuda_stream_t *stream);
int cuda_get_max_shared_memory(uint32_t gpu_index);
void cuda_synchronize_stream(cuda_stream_t *stream);
void cuda_stream_add_callback(cuda_stream_t *stream,
cudaStreamCallback_t callback, void *user_data);
void host_free_on_stream_callback(cudaStream_t stream, cudaError_t status,
void *host_pointer);
}
template <typename Torus>
void cuda_set_value_async(cudaStream_t *stream, Torus *d_array, Torus value,
Torus n);
#endif

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@@ -1,100 +0,0 @@
#include "cuComplex.h"
#include "thrust/complex.h"
#include <iostream>
#include <string>
#include <type_traits>
#define PRINT_VARS
#ifdef PRINT_VARS
#define PRINT_DEBUG_5(var, begin, end, step, cond) \
_print_debug(var, #var, begin, end, step, cond, "", false)
#define PRINT_DEBUG_6(var, begin, end, step, cond, text) \
_print_debug(var, #var, begin, end, step, cond, text, true)
#define CAT(A, B) A##B
#define PRINT_SELECT(NAME, NUM) CAT(NAME##_, NUM)
#define GET_COUNT(_1, _2, _3, _4, _5, _6, COUNT, ...) COUNT
#define VA_SIZE(...) GET_COUNT(__VA_ARGS__, 6, 5, 4, 3, 2, 1)
#define PRINT_DEBUG(...) \
PRINT_SELECT(PRINT_DEBUG, VA_SIZE(__VA_ARGS__))(__VA_ARGS__)
#else
#define PRINT_DEBUG(...)
#endif
template <typename T>
__device__ typename std::enable_if<std::is_unsigned<T>::value, void>::type
_print_debug(T *var, const char *var_name, int start, int end, int step,
bool cond, const char *text, bool has_text) {
__syncthreads();
if (cond) {
if (has_text)
printf("%s\n", text);
for (int i = start; i < end; i += step) {
printf("%s[%u]: %u\n", var_name, i, var[i]);
}
}
__syncthreads();
}
template <typename T>
__device__ typename std::enable_if<std::is_signed<T>::value, void>::type
_print_debug(T *var, const char *var_name, int start, int end, int step,
bool cond, const char *text, bool has_text) {
__syncthreads();
if (cond) {
if (has_text)
printf("%s\n", text);
for (int i = start; i < end; i += step) {
printf("%s[%u]: %d\n", var_name, i, var[i]);
}
}
__syncthreads();
}
template <typename T>
__device__ typename std::enable_if<std::is_floating_point<T>::value, void>::type
_print_debug(T *var, const char *var_name, int start, int end, int step,
bool cond, const char *text, bool has_text) {
__syncthreads();
if (cond) {
if (has_text)
printf("%s\n", text);
for (int i = start; i < end; i += step) {
printf("%s[%u]: %.15f\n", var_name, i, var[i]);
}
}
__syncthreads();
}
template <typename T>
__device__
typename std::enable_if<std::is_same<T, thrust::complex<double>>::value,
void>::type
_print_debug(T *var, const char *var_name, int start, int end, int step,
bool cond, const char *text, bool has_text) {
__syncthreads();
if (cond) {
if (has_text)
printf("%s\n", text);
for (int i = start; i < end; i += step) {
printf("%s[%u]: %.15f , %.15f\n", var_name, i, var[i].real(),
var[i].imag());
}
}
__syncthreads();
}
template <typename T>
__device__
typename std::enable_if<std::is_same<T, cuDoubleComplex>::value, void>::type
_print_debug(T *var, const char *var_name, int start, int end, int step,
bool cond, const char *text, bool has_text) {
__syncthreads();
if (cond) {
if (has_text)
printf("%s\n", text);
for (int i = start; i < end; i += step) {
printf("%s[%u]: %.15f , %.15f\n", var_name, i, var[i].x, var[i].y);
}
}
__syncthreads();
}

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@@ -1,21 +0,0 @@
#ifndef CNCRT_KS_H_
#define CNCRT_KS_H_
#include <cstdint>
extern "C" {
void cuda_keyswitch_lwe_ciphertext_vector_32(
cuda_stream_t *stream, void *lwe_array_out, void *lwe_output_indexes,
void *lwe_array_in, void *lwe_input_indexes, void *ksk,
uint32_t lwe_dimension_in, uint32_t lwe_dimension_out, uint32_t base_log,
uint32_t level_count, uint32_t num_samples);
void cuda_keyswitch_lwe_ciphertext_vector_64(
cuda_stream_t *stream, void *lwe_array_out, void *lwe_output_indexes,
void *lwe_array_in, void *lwe_input_indexes, void *ksk,
uint32_t lwe_dimension_in, uint32_t lwe_dimension_out, uint32_t base_log,
uint32_t level_count, uint32_t num_samples);
}
#endif // CNCRT_KS_H_

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@@ -1,50 +0,0 @@
#ifndef CUDA_LINALG_H_
#define CUDA_LINALG_H_
#include "programmable_bootstrap.h"
#include <cstdint>
#include <device.h>
extern "C" {
void cuda_negate_lwe_ciphertext_vector_32(cuda_stream_t *stream,
void *lwe_array_out,
void *lwe_array_in,
uint32_t input_lwe_dimension,
uint32_t input_lwe_ciphertext_count);
void cuda_negate_lwe_ciphertext_vector_64(cuda_stream_t *stream,
void *lwe_array_out,
void *lwe_array_in,
uint32_t input_lwe_dimension,
uint32_t input_lwe_ciphertext_count);
void cuda_add_lwe_ciphertext_vector_32(cuda_stream_t *stream,
void *lwe_array_out,
void *lwe_array_in_1,
void *lwe_array_in_2,
uint32_t input_lwe_dimension,
uint32_t input_lwe_ciphertext_count);
void cuda_add_lwe_ciphertext_vector_64(cuda_stream_t *stream,
void *lwe_array_out,
void *lwe_array_in_1,
void *lwe_array_in_2,
uint32_t input_lwe_dimension,
uint32_t input_lwe_ciphertext_count);
void cuda_add_lwe_ciphertext_vector_plaintext_vector_32(
cuda_stream_t *stream, void *lwe_array_out, void *lwe_array_in,
void *plaintext_array_in, uint32_t input_lwe_dimension,
uint32_t input_lwe_ciphertext_count);
void cuda_add_lwe_ciphertext_vector_plaintext_vector_64(
cuda_stream_t *stream, void *lwe_array_out, void *lwe_array_in,
void *plaintext_array_in, uint32_t input_lwe_dimension,
uint32_t input_lwe_ciphertext_count);
void cuda_mult_lwe_ciphertext_vector_cleartext_vector_32(
cuda_stream_t *stream, void *lwe_array_out, void *lwe_array_in,
void *cleartext_array_in, uint32_t input_lwe_dimension,
uint32_t input_lwe_ciphertext_count);
void cuda_mult_lwe_ciphertext_vector_cleartext_vector_64(
cuda_stream_t *stream, void *lwe_array_out, void *lwe_array_in,
void *cleartext_array_in, uint32_t input_lwe_dimension,
uint32_t input_lwe_ciphertext_count);
}
#endif // CUDA_LINALG_H_

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@@ -1,320 +0,0 @@
#ifndef CUDA_BOOTSTRAP_H
#define CUDA_BOOTSTRAP_H
#include "device.h"
#include <cstdint>
enum PBS_TYPE { MULTI_BIT = 0, CLASSICAL = 1 };
enum PBS_VARIANT { DEFAULT = 0, CG = 1 };
extern "C" {
void cuda_fourier_polynomial_mul(void *input1, void *input2, void *output,
cuda_stream_t *stream,
uint32_t polynomial_size,
uint32_t total_polynomials);
void cuda_convert_lwe_programmable_bootstrap_key_32(
void *dest, void *src, cuda_stream_t *stream, uint32_t input_lwe_dim,
uint32_t glwe_dim, uint32_t level_count, uint32_t polynomial_size);
void cuda_convert_lwe_programmable_bootstrap_key_64(
void *dest, void *src, cuda_stream_t *stream, uint32_t input_lwe_dim,
uint32_t glwe_dim, uint32_t level_count, uint32_t polynomial_size);
void scratch_cuda_programmable_bootstrap_amortized_32(
cuda_stream_t *stream, int8_t **pbs_buffer, uint32_t glwe_dimension,
uint32_t polynomial_size, uint32_t input_lwe_ciphertext_count,
uint32_t max_shared_memory, bool allocate_gpu_memory);
void scratch_cuda_programmable_bootstrap_amortized_64(
cuda_stream_t *stream, int8_t **pbs_buffer, uint32_t glwe_dimension,
uint32_t polynomial_size, uint32_t input_lwe_ciphertext_count,
uint32_t max_shared_memory, bool allocate_gpu_memory);
void cuda_programmable_bootstrap_amortized_lwe_ciphertext_vector_32(
cuda_stream_t *stream, void *lwe_array_out, void *lwe_output_indexes,
void *lut_vector, void *lut_vector_indexes, void *lwe_array_in,
void *lwe_input_indexes, void *bootstrapping_key, int8_t *pbs_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_luts, uint32_t lwe_idx, uint32_t max_shared_memory);
void cuda_programmable_bootstrap_amortized_lwe_ciphertext_vector_64(
cuda_stream_t *stream, void *lwe_array_out, void *lwe_output_indexes,
void *lut_vector, void *lut_vector_indexes, void *lwe_array_in,
void *lwe_input_indexes, void *bootstrapping_key, int8_t *pbs_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_luts, uint32_t lwe_idx, uint32_t max_shared_memory);
void cleanup_cuda_programmable_bootstrap_amortized(cuda_stream_t *stream,
int8_t **pbs_buffer);
void scratch_cuda_programmable_bootstrap_32(
cuda_stream_t *stream, int8_t **buffer, uint32_t glwe_dimension,
uint32_t polynomial_size, uint32_t level_count,
uint32_t input_lwe_ciphertext_count, uint32_t max_shared_memory,
bool allocate_gpu_memory);
void scratch_cuda_programmable_bootstrap_64(
cuda_stream_t *stream, int8_t **buffer, uint32_t glwe_dimension,
uint32_t polynomial_size, uint32_t level_count,
uint32_t input_lwe_ciphertext_count, uint32_t max_shared_memory,
bool allocate_gpu_memory);
void cuda_programmable_bootstrap_lwe_ciphertext_vector_32(
cuda_stream_t *stream, void *lwe_array_out, void *lwe_output_indexes,
void *lut_vector, void *lut_vector_indexes, void *lwe_array_in,
void *lwe_input_indexes, void *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_luts, uint32_t lwe_idx, uint32_t max_shared_memory);
void cuda_programmable_bootstrap_lwe_ciphertext_vector_64(
cuda_stream_t *stream, void *lwe_array_out, void *lwe_output_indexes,
void *lut_vector, void *lut_vector_indexes, void *lwe_array_in,
void *lwe_input_indexes, void *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_luts, uint32_t lwe_idx, uint32_t max_shared_memory);
void cleanup_cuda_programmable_bootstrap(cuda_stream_t *stream,
int8_t **pbs_buffer);
uint64_t get_buffer_size_programmable_bootstrap_amortized_64(
uint32_t glwe_dimension, uint32_t polynomial_size,
uint32_t input_lwe_ciphertext_count, uint32_t max_shared_memory);
uint64_t get_buffer_size_programmable_bootstrap_64(
uint32_t glwe_dimension, uint32_t polynomial_size, uint32_t level_count,
uint32_t input_lwe_ciphertext_count, uint32_t max_shared_memory);
}
template <typename Torus>
__host__ __device__ uint64_t
get_buffer_size_full_sm_programmable_bootstrap_step_one(
uint32_t polynomial_size) {
return sizeof(Torus) * polynomial_size + // accumulator_rotated
sizeof(double2) * polynomial_size / 2; // accumulator fft
}
template <typename Torus>
__host__ __device__ uint64_t
get_buffer_size_full_sm_programmable_bootstrap_step_two(
uint32_t polynomial_size) {
return sizeof(Torus) * polynomial_size + // accumulator
sizeof(double2) * polynomial_size / 2; // accumulator fft
}
template <typename Torus>
__host__ __device__ uint64_t
get_buffer_size_partial_sm_programmable_bootstrap(uint32_t polynomial_size) {
return sizeof(double2) * polynomial_size / 2; // accumulator fft
}
template <typename Torus>
__host__ __device__ uint64_t
get_buffer_size_full_sm_programmable_bootstrap_cg(uint32_t polynomial_size) {
return sizeof(Torus) * polynomial_size + // accumulator_rotated
sizeof(Torus) * polynomial_size + // accumulator
sizeof(double2) * polynomial_size / 2; // accumulator fft
}
template <typename Torus>
__host__ __device__ uint64_t
get_buffer_size_partial_sm_programmable_bootstrap_cg(uint32_t polynomial_size) {
return sizeof(double2) * polynomial_size / 2; // accumulator fft mask & body
}
template <typename Torus, PBS_TYPE pbs_type> struct pbs_buffer;
template <typename Torus> struct pbs_buffer<Torus, PBS_TYPE::CLASSICAL> {
int8_t *d_mem;
Torus *global_accumulator;
double2 *global_accumulator_fft;
PBS_VARIANT pbs_variant;
pbs_buffer(cuda_stream_t *stream, uint32_t glwe_dimension,
uint32_t polynomial_size, uint32_t level_count,
uint32_t input_lwe_ciphertext_count, PBS_VARIANT pbs_variant,
bool allocate_gpu_memory) {
this->pbs_variant = pbs_variant;
auto max_shared_memory = cuda_get_max_shared_memory(stream->gpu_index);
if (allocate_gpu_memory) {
switch (pbs_variant) {
case PBS_VARIANT::DEFAULT: {
uint64_t full_sm_step_one =
get_buffer_size_full_sm_programmable_bootstrap_step_one<Torus>(
polynomial_size);
uint64_t full_sm_step_two =
get_buffer_size_full_sm_programmable_bootstrap_step_two<Torus>(
polynomial_size);
uint64_t partial_sm =
get_buffer_size_partial_sm_programmable_bootstrap<Torus>(
polynomial_size);
uint64_t partial_dm_step_one = full_sm_step_one - partial_sm;
uint64_t partial_dm_step_two = full_sm_step_two - partial_sm;
uint64_t full_dm = full_sm_step_one;
uint64_t device_mem = 0;
if (max_shared_memory < partial_sm) {
device_mem = full_dm * input_lwe_ciphertext_count * level_count *
(glwe_dimension + 1);
} else if (max_shared_memory < full_sm_step_two) {
device_mem =
(partial_dm_step_two + partial_dm_step_one * level_count) *
input_lwe_ciphertext_count * (glwe_dimension + 1);
} else if (max_shared_memory < full_sm_step_one) {
device_mem = partial_dm_step_one * input_lwe_ciphertext_count *
level_count * (glwe_dimension + 1);
}
// Otherwise, both kernels run all in shared memory
d_mem = (int8_t *)cuda_malloc_async(device_mem, stream);
global_accumulator_fft = (double2 *)cuda_malloc_async(
(glwe_dimension + 1) * level_count * input_lwe_ciphertext_count *
(polynomial_size / 2) * sizeof(double2),
stream);
global_accumulator = (Torus *)cuda_malloc_async(
(glwe_dimension + 1) * input_lwe_ciphertext_count *
polynomial_size * sizeof(Torus),
stream);
} break;
case PBS_VARIANT::CG: {
uint64_t full_sm =
get_buffer_size_full_sm_programmable_bootstrap_cg<Torus>(
polynomial_size);
uint64_t partial_sm =
get_buffer_size_partial_sm_programmable_bootstrap_cg<Torus>(
polynomial_size);
uint64_t partial_dm = full_sm - partial_sm;
uint64_t full_dm = full_sm;
uint64_t device_mem = 0;
if (max_shared_memory < partial_sm) {
device_mem = full_dm * input_lwe_ciphertext_count * level_count *
(glwe_dimension + 1);
} else if (max_shared_memory < full_sm) {
device_mem = partial_dm * input_lwe_ciphertext_count * level_count *
(glwe_dimension + 1);
}
// Otherwise, both kernels run all in shared memory
d_mem = (int8_t *)cuda_malloc_async(device_mem, stream);
global_accumulator_fft = (double2 *)cuda_malloc_async(
(glwe_dimension + 1) * level_count * input_lwe_ciphertext_count *
polynomial_size / 2 * sizeof(double2),
stream);
} break;
default:
PANIC("Cuda error (PBS): unsupported implementation variant.")
}
}
}
void release(cuda_stream_t *stream) {
cuda_drop_async(d_mem, stream);
cuda_drop_async(global_accumulator_fft, stream);
if (pbs_variant == DEFAULT)
cuda_drop_async(global_accumulator, stream);
}
};
template <typename Torus>
__host__ __device__ uint64_t get_buffer_size_programmable_bootstrap_cg(
uint32_t glwe_dimension, uint32_t polynomial_size, uint32_t level_count,
uint32_t input_lwe_ciphertext_count, uint32_t max_shared_memory) {
uint64_t full_sm =
get_buffer_size_full_sm_programmable_bootstrap_cg<Torus>(polynomial_size);
uint64_t partial_sm =
get_buffer_size_partial_sm_programmable_bootstrap_cg<Torus>(
polynomial_size);
uint64_t partial_dm = full_sm - partial_sm;
uint64_t full_dm = full_sm;
uint64_t device_mem = 0;
if (max_shared_memory < partial_sm) {
device_mem = full_dm * input_lwe_ciphertext_count * level_count *
(glwe_dimension + 1);
} else if (max_shared_memory < full_sm) {
device_mem = partial_dm * input_lwe_ciphertext_count * level_count *
(glwe_dimension + 1);
}
uint64_t buffer_size = device_mem + (glwe_dimension + 1) * level_count *
input_lwe_ciphertext_count *
polynomial_size / 2 * sizeof(double2);
return buffer_size + buffer_size % sizeof(double2);
}
template <typename Torus>
bool has_support_to_cuda_programmable_bootstrap_cg(uint32_t glwe_dimension,
uint32_t polynomial_size,
uint32_t level_count,
uint32_t num_samples,
uint32_t max_shared_memory);
template <typename Torus>
void cuda_programmable_bootstrap_cg_lwe_ciphertext_vector(
cuda_stream_t *stream, Torus *lwe_array_out, Torus *lwe_output_indexes,
Torus *lut_vector, Torus *lut_vector_indexes, Torus *lwe_array_in,
Torus *lwe_input_indexes, double2 *bootstrapping_key,
pbs_buffer<Torus, 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, uint32_t num_luts,
uint32_t lwe_idx, uint32_t max_shared_memory);
template <typename Torus>
void cuda_programmable_bootstrap_lwe_ciphertext_vector(
cuda_stream_t *stream, Torus *lwe_array_out, Torus *lwe_output_indexes,
Torus *lut_vector, Torus *lut_vector_indexes, Torus *lwe_array_in,
Torus *lwe_input_indexes, double2 *bootstrapping_key,
pbs_buffer<Torus, 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, uint32_t num_luts,
uint32_t lwe_idx, uint32_t max_shared_memory);
template <typename Torus, typename STorus>
void scratch_cuda_programmable_bootstrap_cg(
cuda_stream_t *stream, pbs_buffer<Torus, CLASSICAL> **pbs_buffer,
uint32_t glwe_dimension, uint32_t polynomial_size, uint32_t level_count,
uint32_t input_lwe_ciphertext_count, uint32_t max_shared_memory,
bool allocate_gpu_memory);
template <typename Torus, typename STorus>
void scratch_cuda_programmable_bootstrap(
cuda_stream_t *stream, pbs_buffer<Torus, CLASSICAL> **buffer,
uint32_t glwe_dimension, uint32_t polynomial_size, uint32_t level_count,
uint32_t input_lwe_ciphertext_count, uint32_t max_shared_memory,
bool allocate_gpu_memory);
#ifdef __CUDACC__
__device__ inline int get_start_ith_ggsw(int i, uint32_t polynomial_size,
int glwe_dimension,
uint32_t level_count);
template <typename T>
__device__ T *get_ith_mask_kth_block(T *ptr, int i, int k, int level,
uint32_t polynomial_size,
int glwe_dimension, uint32_t level_count);
template <typename T>
__device__ T *get_ith_body_kth_block(T *ptr, int i, int k, int level,
uint32_t polynomial_size,
int glwe_dimension, uint32_t level_count);
template <typename T>
__device__ T *get_multi_bit_ith_lwe_gth_group_kth_block(
T *ptr, int g, int i, int k, int level, uint32_t grouping_factor,
uint32_t polynomial_size, uint32_t glwe_dimension, uint32_t level_count);
#endif
#endif // CUDA_BOOTSTRAP_H

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@@ -1,241 +0,0 @@
#ifndef CUDA_MULTI_BIT_H
#define CUDA_MULTI_BIT_H
#include "programmable_bootstrap.h"
#include <cstdint>
extern "C" {
bool has_support_to_cuda_programmable_bootstrap_cg_multi_bit(
uint32_t glwe_dimension, uint32_t polynomial_size, uint32_t level_count,
uint32_t num_samples, uint32_t max_shared_memory);
void cuda_convert_lwe_multi_bit_programmable_bootstrap_key_64(
void *dest, void *src, cuda_stream_t *stream, uint32_t input_lwe_dim,
uint32_t glwe_dim, uint32_t level_count, uint32_t polynomial_size,
uint32_t grouping_factor);
void scratch_cuda_multi_bit_programmable_bootstrap_64(
cuda_stream_t *stream, int8_t **pbs_buffer, uint32_t lwe_dimension,
uint32_t glwe_dimension, uint32_t polynomial_size, uint32_t level_count,
uint32_t grouping_factor, uint32_t input_lwe_ciphertext_count,
uint32_t max_shared_memory, bool allocate_gpu_memory,
uint32_t chunk_size = 0);
void cuda_multi_bit_programmable_bootstrap_lwe_ciphertext_vector_64(
cuda_stream_t *stream, void *lwe_array_out, void *lwe_output_indexes,
void *lut_vector, void *lut_vector_indexes, void *lwe_array_in,
void *lwe_input_indexes, void *bootstrapping_key, int8_t *buffer,
uint32_t lwe_dimension, uint32_t glwe_dimension, uint32_t polynomial_size,
uint32_t grouping_factor, uint32_t base_log, uint32_t level_count,
uint32_t num_samples, uint32_t num_luts, uint32_t lwe_idx,
uint32_t max_shared_memory, uint32_t lwe_chunk_size = 0);
void scratch_cuda_generic_multi_bit_programmable_bootstrap_64(
cuda_stream_t *stream, int8_t **pbs_buffer, uint32_t lwe_dimension,
uint32_t glwe_dimension, uint32_t polynomial_size, uint32_t level_count,
uint32_t grouping_factor, uint32_t input_lwe_ciphertext_count,
uint32_t max_shared_memory, bool allocate_gpu_memory,
uint32_t lwe_chunk_size = 0);
void cuda_generic_multi_bit_programmable_bootstrap_lwe_ciphertext_vector_64(
cuda_stream_t *stream, void *lwe_array_out, void *lwe_output_indexes,
void *lut_vector, void *lut_vector_indexes, void *lwe_array_in,
void *lwe_input_indexes, void *bootstrapping_key, int8_t *pbs_buffer,
uint32_t lwe_dimension, uint32_t glwe_dimension, uint32_t polynomial_size,
uint32_t grouping_factor, uint32_t base_log, uint32_t level_count,
uint32_t num_samples, uint32_t num_luts, uint32_t lwe_idx,
uint32_t max_shared_memory, uint32_t lwe_chunk_size = 0);
void cleanup_cuda_multi_bit_programmable_bootstrap(cuda_stream_t *stream,
int8_t **pbs_buffer);
}
template <typename Torus, typename STorus>
void scratch_cuda_cg_multi_bit_programmable_bootstrap(
cuda_stream_t *stream, pbs_buffer<Torus, MULTI_BIT> **pbs_buffer,
uint32_t lwe_dimension, uint32_t glwe_dimension, uint32_t polynomial_size,
uint32_t level_count, uint32_t grouping_factor,
uint32_t input_lwe_ciphertext_count, uint32_t max_shared_memory,
bool allocate_gpu_memory, uint32_t lwe_chunk_size = 0);
template <typename Torus>
void cuda_cg_multi_bit_programmable_bootstrap_lwe_ciphertext_vector(
cuda_stream_t *stream, Torus *lwe_array_out, Torus *lwe_output_indexes,
Torus *lut_vector, Torus *lut_vector_indexes, Torus *lwe_array_in,
Torus *lwe_input_indexes, Torus *bootstrapping_key,
pbs_buffer<Torus, MULTI_BIT> *pbs_buffer, uint32_t lwe_dimension,
uint32_t glwe_dimension, uint32_t polynomial_size, uint32_t grouping_factor,
uint32_t base_log, uint32_t level_count, uint32_t num_samples,
uint32_t num_luts, uint32_t lwe_idx, uint32_t max_shared_memory,
uint32_t lwe_chunk_size = 0);
template <typename Torus, typename STorus>
void scratch_cuda_multi_bit_programmable_bootstrap(
cuda_stream_t *stream, pbs_buffer<Torus, MULTI_BIT> **pbs_buffer,
uint32_t lwe_dimension, uint32_t glwe_dimension, uint32_t polynomial_size,
uint32_t level_count, uint32_t grouping_factor,
uint32_t input_lwe_ciphertext_count, uint32_t max_shared_memory,
bool allocate_gpu_memory, uint32_t lwe_chunk_size = 0);
template <typename Torus>
void cuda_multi_bit_programmable_bootstrap_lwe_ciphertext_vector(
cuda_stream_t *stream, Torus *lwe_array_out, Torus *lwe_output_indexes,
Torus *lut_vector, Torus *lut_vector_indexes, Torus *lwe_array_in,
Torus *lwe_input_indexes, Torus *bootstrapping_key,
pbs_buffer<Torus, MULTI_BIT> *pbs_buffer, uint32_t lwe_dimension,
uint32_t glwe_dimension, uint32_t polynomial_size, uint32_t grouping_factor,
uint32_t base_log, uint32_t level_count, uint32_t num_samples,
uint32_t num_luts, uint32_t lwe_idx, uint32_t max_shared_memory,
uint32_t lwe_chunk_size = 0);
template <typename Torus>
__host__ __device__ uint64_t
get_buffer_size_full_sm_multibit_programmable_bootstrap_keybundle(
uint32_t polynomial_size);
template <typename Torus>
__host__ __device__ uint64_t
get_buffer_size_full_sm_multibit_programmable_bootstrap_step_one(
uint32_t polynomial_size);
template <typename Torus>
__host__ __device__ uint64_t
get_buffer_size_full_sm_multibit_programmable_bootstrap_step_two(
uint32_t polynomial_size);
template <typename Torus>
__host__ __device__ uint64_t
get_buffer_size_partial_sm_multibit_programmable_bootstrap_step_one(
uint32_t polynomial_size);
template <typename Torus>
__host__ __device__ uint64_t
get_buffer_size_full_sm_cg_multibit_programmable_bootstrap(
uint32_t polynomial_size);
template <typename Torus>
__host__ __device__ uint64_t
get_buffer_size_partial_sm_cg_multibit_programmable_bootstrap(
uint32_t polynomial_size);
template <typename Torus> struct pbs_buffer<Torus, PBS_TYPE::MULTI_BIT> {
int8_t *d_mem_keybundle = NULL;
int8_t *d_mem_acc_step_one = NULL;
int8_t *d_mem_acc_step_two = NULL;
int8_t *d_mem_acc_cg = NULL;
double2 *keybundle_fft;
Torus *global_accumulator;
double2 *global_accumulator_fft;
PBS_VARIANT pbs_variant;
pbs_buffer(cuda_stream_t *stream, uint32_t glwe_dimension,
uint32_t polynomial_size, uint32_t level_count,
uint32_t input_lwe_ciphertext_count, uint32_t lwe_chunk_size,
PBS_VARIANT pbs_variant, bool allocate_gpu_memory) {
this->pbs_variant = pbs_variant;
auto max_shared_memory = cuda_get_max_shared_memory(stream->gpu_index);
uint64_t full_sm_keybundle =
get_buffer_size_full_sm_multibit_programmable_bootstrap_keybundle<
Torus>(polynomial_size);
uint64_t full_sm_accumulate_step_one =
get_buffer_size_full_sm_multibit_programmable_bootstrap_step_one<Torus>(
polynomial_size);
uint64_t partial_sm_accumulate_step_one =
get_buffer_size_partial_sm_multibit_programmable_bootstrap_step_one<
Torus>(polynomial_size);
uint64_t full_sm_accumulate_step_two =
get_buffer_size_full_sm_multibit_programmable_bootstrap_step_two<Torus>(
polynomial_size);
uint64_t full_sm_cg_accumulate =
get_buffer_size_full_sm_cg_multibit_programmable_bootstrap<Torus>(
polynomial_size);
uint64_t partial_sm_cg_accumulate =
get_buffer_size_partial_sm_cg_multibit_programmable_bootstrap<Torus>(
polynomial_size);
auto num_blocks_keybundle = input_lwe_ciphertext_count * lwe_chunk_size *
(glwe_dimension + 1) * (glwe_dimension + 1) *
level_count;
auto num_blocks_acc_step_one =
level_count * (glwe_dimension + 1) * input_lwe_ciphertext_count;
auto num_blocks_acc_step_two =
input_lwe_ciphertext_count * (glwe_dimension + 1);
auto num_blocks_acc_cg =
level_count * (glwe_dimension + 1) * input_lwe_ciphertext_count;
if (allocate_gpu_memory) {
// Keybundle
if (max_shared_memory < full_sm_keybundle)
d_mem_keybundle = (int8_t *)cuda_malloc_async(
num_blocks_keybundle * full_sm_keybundle, stream);
switch (pbs_variant) {
case DEFAULT:
// Accumulator step one
if (max_shared_memory < partial_sm_accumulate_step_one)
d_mem_acc_step_one = (int8_t *)cuda_malloc_async(
num_blocks_acc_step_one * full_sm_accumulate_step_one, stream);
else if (max_shared_memory < full_sm_accumulate_step_one)
d_mem_acc_step_one = (int8_t *)cuda_malloc_async(
num_blocks_acc_step_one * partial_sm_accumulate_step_one, stream);
// Accumulator step two
if (max_shared_memory < full_sm_accumulate_step_two)
d_mem_acc_step_two = (int8_t *)cuda_malloc_async(
num_blocks_acc_step_two * full_sm_accumulate_step_two, stream);
break;
case CG:
// Accumulator CG
if (max_shared_memory < partial_sm_cg_accumulate)
d_mem_acc_cg = (int8_t *)cuda_malloc_async(
num_blocks_acc_cg * full_sm_cg_accumulate, stream);
else if (max_shared_memory < full_sm_cg_accumulate)
d_mem_acc_cg = (int8_t *)cuda_malloc_async(
num_blocks_acc_cg * partial_sm_cg_accumulate, stream);
break;
default:
PANIC("Cuda error (PBS): unsupported implementation variant.")
}
keybundle_fft = (double2 *)cuda_malloc_async(
num_blocks_keybundle * (polynomial_size / 2) * sizeof(double2),
stream);
global_accumulator = (Torus *)cuda_malloc_async(
num_blocks_acc_step_two * polynomial_size * sizeof(Torus), stream);
global_accumulator_fft = (double2 *)cuda_malloc_async(
num_blocks_acc_step_one * (polynomial_size / 2) * sizeof(double2),
stream);
}
}
void release(cuda_stream_t *stream) {
if (d_mem_keybundle)
cuda_drop_async(d_mem_keybundle, stream);
switch (pbs_variant) {
case DEFAULT:
if (d_mem_acc_step_one)
cuda_drop_async(d_mem_acc_step_one, stream);
if (d_mem_acc_step_two)
cuda_drop_async(d_mem_acc_step_two, stream);
break;
case CG:
if (d_mem_acc_cg)
cuda_drop_async(d_mem_acc_cg, stream);
break;
default:
PANIC("Cuda error (PBS): unsupported implementation variant.")
}
cuda_drop_async(keybundle_fft, stream);
cuda_drop_async(global_accumulator, stream);
cuda_drop_async(global_accumulator_fft, stream);
}
};
#ifdef __CUDACC__
__host__ uint32_t get_lwe_chunk_size(uint32_t ct_count);
#endif
#endif // CUDA_MULTI_BIT_H

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@@ -1,18 +0,0 @@
set(SOURCES
${CMAKE_SOURCE_DIR}/${INCLUDE_DIR}/bit_extraction.h
${CMAKE_SOURCE_DIR}/${INCLUDE_DIR}/bitwise_ops.h
${CMAKE_SOURCE_DIR}/${INCLUDE_DIR}/bootstrap.h
${CMAKE_SOURCE_DIR}/${INCLUDE_DIR}/bootstrap_multibit.h
${CMAKE_SOURCE_DIR}/${INCLUDE_DIR}/ciphertext.h
${CMAKE_SOURCE_DIR}/${INCLUDE_DIR}/circuit_bootstrap.h
${CMAKE_SOURCE_DIR}/${INCLUDE_DIR}/device.h
${CMAKE_SOURCE_DIR}/${INCLUDE_DIR}/integer.h
${CMAKE_SOURCE_DIR}/${INCLUDE_DIR}/keyswitch.h
${CMAKE_SOURCE_DIR}/${INCLUDE_DIR}/linear_algebra.h
${CMAKE_SOURCE_DIR}/${INCLUDE_DIR}/shifts.h
${CMAKE_SOURCE_DIR}/${INCLUDE_DIR}/vertical_packing.h)
file(GLOB_RECURSE SOURCES "*.cu")
add_library(tfhe_cuda_backend STATIC ${SOURCES})
set_target_properties(tfhe_cuda_backend PROPERTIES CUDA_SEPARABLE_COMPILATION ON CUDA_RESOLVE_DEVICE_SYMBOLS ON)
target_link_libraries(tfhe_cuda_backend PUBLIC cudart OpenMP::OpenMP_CXX)
target_include_directories(tfhe_cuda_backend PRIVATE .)

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@@ -1 +0,0 @@
#include "ciphertext.cuh"

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@@ -1,44 +0,0 @@
#ifndef CUDA_CIPHERTEXT_CUH
#define CUDA_CIPHERTEXT_CUH
#include "ciphertext.h"
#include "device.h"
#include <cstdint>
template <typename T>
void cuda_convert_lwe_ciphertext_vector_to_gpu(T *dest, T *src,
cuda_stream_t *stream,
uint32_t number_of_cts,
uint32_t lwe_dimension) {
cudaSetDevice(stream->gpu_index);
uint64_t size = number_of_cts * (lwe_dimension + 1) * sizeof(T);
cuda_memcpy_async_to_gpu(dest, src, size, stream);
}
void cuda_convert_lwe_ciphertext_vector_to_gpu_64(void *dest, void *src,
cuda_stream_t *stream,
uint32_t number_of_cts,
uint32_t lwe_dimension) {
cuda_convert_lwe_ciphertext_vector_to_gpu<uint64_t>(
(uint64_t *)dest, (uint64_t *)src, stream, number_of_cts, lwe_dimension);
}
template <typename T>
void cuda_convert_lwe_ciphertext_vector_to_cpu(T *dest, T *src,
cuda_stream_t *stream,
uint32_t number_of_cts,
uint32_t lwe_dimension) {
cudaSetDevice(stream->gpu_index);
uint64_t size = number_of_cts * (lwe_dimension + 1) * sizeof(T);
cuda_memcpy_async_to_cpu(dest, src, size, stream);
}
void cuda_convert_lwe_ciphertext_vector_to_cpu_64(void *dest, void *src,
cuda_stream_t *stream,
uint32_t number_of_cts,
uint32_t lwe_dimension) {
cuda_convert_lwe_ciphertext_vector_to_cpu<uint64_t>(
(uint64_t *)dest, (uint64_t *)src, stream, number_of_cts, lwe_dimension);
}
#endif

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@@ -1,162 +0,0 @@
#ifndef CNCRT_CRYPTO_CUH
#define CNCRT_CRPYTO_CUH
#include "device.h"
#include <cstdint>
/**
* GadgetMatrix implements the iterator design pattern to decompose a set of
* num_poly consecutive polynomials with degree params::degree. A total of
* level_count levels is expected and each call to decompose_and_compress_next()
* writes to the result the next level. It is also possible to advance an
* arbitrary amount of levels by using decompose_and_compress_level().
*
* This class always decomposes the entire set of num_poly polynomials.
* By default, it works on a single polynomial.
*/
#pragma once
template <typename T, class params> class GadgetMatrix {
private:
uint32_t level_count;
uint32_t base_log;
uint32_t mask;
uint32_t halfbg;
uint32_t num_poly;
T offset;
int current_level;
T mask_mod_b;
T *state;
public:
__device__ GadgetMatrix(uint32_t base_log, uint32_t level_count, T *state,
uint32_t num_poly = 1)
: base_log(base_log), level_count(level_count), num_poly(num_poly),
state(state) {
mask_mod_b = (1ll << base_log) - 1ll;
current_level = level_count;
int tid = threadIdx.x;
for (int i = 0; i < num_poly * params::opt; i++) {
state[tid] >>= (sizeof(T) * 8 - base_log * level_count);
tid += params::degree / params::opt;
}
synchronize_threads_in_block();
}
// Decomposes all polynomials at once
__device__ void decompose_and_compress_next(double2 *result) {
for (int j = 0; j < num_poly; j++) {
auto result_slice = result + j * params::degree / 2;
decompose_and_compress_next_polynomial(result_slice, j);
}
}
// Decomposes a single polynomial
__device__ void decompose_and_compress_next_polynomial(double2 *result,
int j) {
if (j == 0)
current_level -= 1;
int tid = threadIdx.x;
auto state_slice = state + j * params::degree;
for (int i = 0; i < params::opt / 2; i++) {
T res_re = state_slice[tid] & mask_mod_b;
T res_im = state_slice[tid + params::degree / 2] & mask_mod_b;
state_slice[tid] >>= base_log;
state_slice[tid + params::degree / 2] >>= base_log;
T carry_re = ((res_re - 1ll) | state_slice[tid]) & res_re;
T carry_im =
((res_im - 1ll) | state_slice[tid + params::degree / 2]) & res_im;
carry_re >>= (base_log - 1);
carry_im >>= (base_log - 1);
state_slice[tid] += carry_re;
state_slice[tid + params::degree / 2] += carry_im;
res_re -= carry_re << base_log;
res_im -= carry_im << base_log;
result[tid].x = (int32_t)res_re;
result[tid].y = (int32_t)res_im;
tid += params::degree / params::opt;
}
synchronize_threads_in_block();
}
// Decomposes a single polynomial
__device__ void
decompose_and_compress_next_polynomial_elements(double2 *result, int j) {
if (j == 0)
current_level -= 1;
int tid = threadIdx.x;
auto state_slice = state + j * params::degree;
for (int i = 0; i < params::opt / 2; i++) {
T res_re = state_slice[tid] & mask_mod_b;
T res_im = state_slice[tid + params::degree / 2] & mask_mod_b;
state_slice[tid] >>= base_log;
state_slice[tid + params::degree / 2] >>= base_log;
T carry_re = ((res_re - 1ll) | state_slice[tid]) & res_re;
T carry_im =
((res_im - 1ll) | state_slice[tid + params::degree / 2]) & res_im;
carry_re >>= (base_log - 1);
carry_im >>= (base_log - 1);
state_slice[tid] += carry_re;
state_slice[tid + params::degree / 2] += carry_im;
res_re -= carry_re << base_log;
res_im -= carry_im << base_log;
result[i].x = (int32_t)res_re;
result[i].y = (int32_t)res_im;
tid += params::degree / params::opt;
}
synchronize_threads_in_block();
}
__device__ void decompose_and_compress_level(double2 *result, int level) {
for (int i = 0; i < level_count - level; i++)
decompose_and_compress_next(result);
}
};
template <typename T> class GadgetMatrixSingle {
private:
uint32_t level_count;
uint32_t base_log;
uint32_t mask;
uint32_t halfbg;
T offset;
public:
__device__ GadgetMatrixSingle(uint32_t base_log, uint32_t level_count)
: base_log(base_log), level_count(level_count) {
uint32_t bg = 1 << base_log;
this->halfbg = bg / 2;
this->mask = bg - 1;
T temp = 0;
for (int i = 0; i < this->level_count; i++) {
temp += 1ULL << (sizeof(T) * 8 - (i + 1) * this->base_log);
}
this->offset = temp * this->halfbg;
}
__device__ T decompose_one_level_single(T element, uint32_t level) {
T s = element + this->offset;
uint32_t decal = (sizeof(T) * 8 - (level + 1) * this->base_log);
T temp1 = (s >> decal) & this->mask;
return (T)(temp1 - this->halfbg);
}
};
template <typename Torus>
__device__ Torus decompose_one(Torus &state, Torus mask_mod_b, int base_log) {
Torus res = state & mask_mod_b;
state >>= base_log;
Torus carry = ((res - 1ll) | state) & res;
carry >>= base_log - 1;
state += carry;
res -= carry << base_log;
return res;
}
#endif // CNCRT_CRPYTO_H

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@@ -1,74 +0,0 @@
#ifndef CNCRT_GGSW_CUH
#define CNCRT_GGSW_CUH
#include "device.h"
#include "fft/bnsmfft.cuh"
#include "polynomial/parameters.cuh"
template <typename T, typename ST, class params, sharedMemDegree SMD>
__global__ void device_batch_fft_ggsw_vector(double2 *dest, T *src,
int8_t *device_mem) {
extern __shared__ int8_t sharedmem[];
double2 *selected_memory;
if constexpr (SMD == FULLSM)
selected_memory = (double2 *)sharedmem;
else
selected_memory = (double2 *)device_mem[blockIdx.x * params::degree];
// Compression
int offset = blockIdx.x * blockDim.x;
int tid = threadIdx.x;
#pragma unroll
for (int i = 0; i < params::opt / 2; i++) {
ST x = src[(tid) + params::opt * offset];
ST y = src[(tid + params::degree / 2) + params::opt * offset];
selected_memory[tid].x = x / (double)std::numeric_limits<T>::max();
selected_memory[tid].y = y / (double)std::numeric_limits<T>::max();
tid += params::degree / params::opt;
}
synchronize_threads_in_block();
// Switch to the FFT space
NSMFFT_direct<HalfDegree<params>>(selected_memory);
synchronize_threads_in_block();
// Write the output to global memory
tid = threadIdx.x;
#pragma unroll
for (int j = 0; j < params::opt / 2; j++) {
dest[tid + (params::opt >> 1) * offset] = selected_memory[tid];
tid += params::degree / params::opt;
}
}
/**
* Applies the FFT transform on sequence of GGSW ciphertexts already in the
* global memory
*/
template <typename T, typename ST, class params>
void batch_fft_ggsw_vector(cuda_stream_t *stream, double2 *dest, T *src,
int8_t *d_mem, uint32_t r, uint32_t glwe_dim,
uint32_t polynomial_size, uint32_t level_count,
uint32_t gpu_index, uint32_t max_shared_memory) {
cudaSetDevice(stream->gpu_index);
int shared_memory_size = sizeof(double) * polynomial_size;
int gridSize = r * (glwe_dim + 1) * (glwe_dim + 1) * level_count;
int blockSize = polynomial_size / params::opt;
if (max_shared_memory < shared_memory_size) {
device_batch_fft_ggsw_vector<T, ST, params, NOSM>
<<<gridSize, blockSize, 0, stream->stream>>>(dest, src, d_mem);
} else {
device_batch_fft_ggsw_vector<T, ST, params, FULLSM>
<<<gridSize, blockSize, shared_memory_size, stream->stream>>>(dest, src,
d_mem);
}
check_cuda_error(cudaGetLastError());
}
#endif // CNCRT_GGSW_CUH

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@@ -1,48 +0,0 @@
#include "keyswitch.cuh"
#include "keyswitch.h"
#include <cstdint>
/* Perform keyswitch on a batch of 32 bits input LWE ciphertexts.
* Head out to the equivalent operation on 64 bits for more details.
*/
void cuda_keyswitch_lwe_ciphertext_vector_32(
cuda_stream_t *stream, void *lwe_array_out, void *lwe_output_indexes,
void *lwe_array_in, void *lwe_input_indexes, void *ksk,
uint32_t lwe_dimension_in, uint32_t lwe_dimension_out, uint32_t base_log,
uint32_t level_count, uint32_t num_samples) {
cuda_keyswitch_lwe_ciphertext_vector(
stream, static_cast<uint32_t *>(lwe_array_out),
static_cast<uint32_t *>(lwe_output_indexes),
static_cast<uint32_t *>(lwe_array_in),
static_cast<uint32_t *>(lwe_input_indexes), static_cast<uint32_t *>(ksk),
lwe_dimension_in, lwe_dimension_out, base_log, level_count, num_samples);
}
/* Perform keyswitch on a batch of 64 bits input LWE ciphertexts.
*
* - `v_stream` is a void pointer to the Cuda stream to be used in the kernel
* launch
* - `gpu_index` is the index of the GPU to be used in the kernel launch
* - lwe_array_out: output batch of num_samples keyswitched ciphertexts c =
* (a0,..an-1,b) where n is the output LWE dimension (lwe_dimension_out)
* - lwe_array_in: input batch of num_samples LWE ciphertexts, containing
* lwe_dimension_in mask values + 1 body value
* - ksk: the keyswitch key to be used in the operation
* - base log: the log of the base used in the decomposition (should be the one
* used to create the ksk)
*
* This function calls a wrapper to a device kernel that performs the keyswitch
* - num_samples blocks of threads are launched
*/
void cuda_keyswitch_lwe_ciphertext_vector_64(
cuda_stream_t *stream, void *lwe_array_out, void *lwe_output_indexes,
void *lwe_array_in, void *lwe_input_indexes, void *ksk,
uint32_t lwe_dimension_in, uint32_t lwe_dimension_out, uint32_t base_log,
uint32_t level_count, uint32_t num_samples) {
cuda_keyswitch_lwe_ciphertext_vector(
stream, static_cast<uint64_t *>(lwe_array_out),
static_cast<uint64_t *>(lwe_output_indexes),
static_cast<uint64_t *>(lwe_array_in),
static_cast<uint64_t *>(lwe_input_indexes), static_cast<uint64_t *>(ksk),
lwe_dimension_in, lwe_dimension_out, base_log, level_count, num_samples);
}

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@@ -1,140 +0,0 @@
#ifndef CNCRT_KS_CUH
#define CNCRT_KS_CUH
#include "device.h"
#include "gadget.cuh"
#include "polynomial/polynomial_math.cuh"
#include "torus.cuh"
#include <thread>
#include <vector>
template <typename Torus>
__device__ Torus *get_ith_block(Torus *ksk, int i, int level,
uint32_t lwe_dimension_out,
uint32_t level_count) {
int pos = i * level_count * (lwe_dimension_out + 1) +
level * (lwe_dimension_out + 1);
Torus *ptr = &ksk[pos];
return ptr;
}
/*
* keyswitch kernel
* Each thread handles a piece of the following equation:
* $$GLWE_s2(\Delta.m+e) = (0,0,..,0,b) - \sum_{i=0,k-1} <Dec(a_i),
* (GLWE_s2(s1_i q/beta),..,GLWE(s1_i q/beta^l)>$$ where k is the dimension of
* the GLWE ciphertext. If the polynomial dimension in GLWE is > 1, this
* equation is solved for each polynomial coefficient. where Dec denotes the
* decomposition with base beta and l levels and the inner product is done
* between the decomposition of a_i and l GLWE encryptions of s1_i q/\beta^j,
* with j in [1,l] We obtain a GLWE encryption of Delta.m (with Delta the
* scaling factor) under key s2 instead of s1, with an increased noise
*
*/
template <typename Torus>
__global__ void
keyswitch(Torus *lwe_array_out, Torus *lwe_output_indexes, Torus *lwe_array_in,
Torus *lwe_input_indexes, Torus *ksk, uint32_t lwe_dimension_in,
uint32_t lwe_dimension_out, uint32_t base_log, uint32_t level_count,
int lwe_lower, int lwe_upper, int cutoff) {
int tid = threadIdx.x;
extern __shared__ int8_t sharedmem[];
Torus *local_lwe_array_out = (Torus *)sharedmem;
auto block_lwe_array_in = get_chunk(
lwe_array_in, lwe_input_indexes[blockIdx.x], lwe_dimension_in + 1);
auto block_lwe_array_out = get_chunk(
lwe_array_out, lwe_output_indexes[blockIdx.x], lwe_dimension_out + 1);
auto gadget = GadgetMatrixSingle<Torus>(base_log, level_count);
int lwe_part_per_thd;
if (tid < cutoff) {
lwe_part_per_thd = lwe_upper;
} else {
lwe_part_per_thd = lwe_lower;
}
__syncthreads();
for (int k = 0; k < lwe_part_per_thd; k++) {
int idx = tid + k * blockDim.x;
local_lwe_array_out[idx] = 0;
}
__syncthreads();
if (tid == 0) {
local_lwe_array_out[lwe_dimension_out] =
block_lwe_array_in[lwe_dimension_in];
}
for (int i = 0; i < lwe_dimension_in; i++) {
__syncthreads();
Torus a_i =
round_to_closest_multiple(block_lwe_array_in[i], base_log, level_count);
Torus state = a_i >> (sizeof(Torus) * 8 - base_log * level_count);
Torus mask_mod_b = (1ll << base_log) - 1ll;
for (int j = 0; j < level_count; j++) {
auto ksk_block = get_ith_block(ksk, i, j, lwe_dimension_out, level_count);
Torus decomposed = decompose_one<Torus>(state, mask_mod_b, base_log);
for (int k = 0; k < lwe_part_per_thd; k++) {
int idx = tid + k * blockDim.x;
local_lwe_array_out[idx] -= (Torus)ksk_block[idx] * decomposed;
}
}
}
for (int k = 0; k < lwe_part_per_thd; k++) {
int idx = tid + k * blockDim.x;
block_lwe_array_out[idx] = local_lwe_array_out[idx];
}
}
/// assume lwe_array_in in the gpu
template <typename Torus>
__host__ void cuda_keyswitch_lwe_ciphertext_vector(
cuda_stream_t *stream, Torus *lwe_array_out, Torus *lwe_output_indexes,
Torus *lwe_array_in, Torus *lwe_input_indexes, Torus *ksk,
uint32_t lwe_dimension_in, uint32_t lwe_dimension_out, uint32_t base_log,
uint32_t level_count, uint32_t num_samples) {
cudaSetDevice(stream->gpu_index);
constexpr int ideal_threads = 128;
int lwe_size = lwe_dimension_out + 1;
int lwe_lower, lwe_upper, cutoff;
if (lwe_size % ideal_threads == 0) {
lwe_lower = lwe_size / ideal_threads;
lwe_upper = lwe_size / ideal_threads;
cutoff = 0;
} else {
int y = ceil((double)lwe_size / (double)ideal_threads) * ideal_threads -
lwe_size;
cutoff = ideal_threads - y;
lwe_lower = lwe_size / ideal_threads;
lwe_upper = (int)ceil((double)lwe_size / (double)ideal_threads);
}
int lwe_size_after = lwe_size * num_samples;
int shared_mem = sizeof(Torus) * lwe_size;
cuda_memset_async(lwe_array_out, 0, sizeof(Torus) * lwe_size_after, stream);
check_cuda_error(cudaGetLastError());
dim3 grid(num_samples, 1, 1);
dim3 threads(ideal_threads, 1, 1);
keyswitch<Torus><<<grid, threads, shared_mem, stream->stream>>>(
lwe_array_out, lwe_output_indexes, lwe_array_in, lwe_input_indexes, ksk,
lwe_dimension_in, lwe_dimension_out, base_log, level_count, lwe_lower,
lwe_upper, cutoff);
check_cuda_error(cudaGetLastError());
}
#endif

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@@ -1,74 +0,0 @@
#ifndef CNCRT_TORUS_CUH
#define CNCRT_TORUS_CUH
#include "types/int128.cuh"
#include <limits>
template <typename T>
__device__ inline void typecast_double_to_torus(double x, T &r) {
r = T(x);
}
template <>
__device__ inline void typecast_double_to_torus<uint32_t>(double x,
uint32_t &r) {
r = __double2uint_rn(x);
}
template <>
__device__ inline void typecast_double_to_torus<uint64_t>(double x,
uint64_t &r) {
// The ull intrinsic does not behave in the same way on all architectures and
// on some platforms this causes the cmux tree test to fail
// Hence the intrinsic is not used here
uint128 nnnn = make_uint128_from_float(x);
uint64_t lll = nnnn.lo_;
r = lll;
}
template <typename T>
__device__ inline T round_to_closest_multiple(T x, uint32_t base_log,
uint32_t level_count) {
T shift = sizeof(T) * 8 - level_count * base_log;
T mask = 1ll << (shift - 1);
T b = (x & mask) >> (shift - 1);
T res = x >> shift;
res += b;
res <<= shift;
return res;
}
template <typename T>
__device__ __forceinline__ void rescale_torus_element(T element, T &output,
uint32_t log_shift) {
output =
round((double)element / (double(std::numeric_limits<T>::max()) + 1.0) *
(double)log_shift);
}
template <typename T>
__device__ __forceinline__ T rescale_torus_element(T element,
uint32_t log_shift) {
return round((double)element / (double(std::numeric_limits<T>::max()) + 1.0) *
(double)log_shift);
}
template <>
__device__ __forceinline__ void
rescale_torus_element<uint32_t>(uint32_t element, uint32_t &output,
uint32_t log_shift) {
output =
round(__uint2double_rn(element) /
(__uint2double_rn(std::numeric_limits<uint32_t>::max()) + 1.0) *
__uint2double_rn(log_shift));
}
template <>
__device__ __forceinline__ void
rescale_torus_element<uint64_t>(uint64_t element, uint64_t &output,
uint32_t log_shift) {
output = round(__ull2double_rn(element) /
(__ull2double_rn(std::numeric_limits<uint64_t>::max()) + 1.0) *
__uint2double_rn(log_shift));
}
#endif // CNCRT_TORUS_H

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@@ -1,238 +0,0 @@
#include "device.h"
#include <cstdint>
#include <cuda_runtime.h>
/// Unsafe function to create a CUDA stream, must check first that GPU exists
cuda_stream_t *cuda_create_stream(uint32_t gpu_index) {
check_cuda_error(cudaSetDevice(gpu_index));
cuda_stream_t *stream = new cuda_stream_t(gpu_index);
return stream;
}
/// Unsafe function to destroy CUDA stream, must check first the GPU exists
void cuda_destroy_stream(cuda_stream_t *stream) { stream->release(); }
/// Unsafe function that will try to allocate even if gpu_index is invalid
/// or if there's not enough memory. A safe wrapper around it must call
/// cuda_check_valid_malloc() first
void *cuda_malloc(uint64_t size, uint32_t gpu_index) {
check_cuda_error(cudaSetDevice(gpu_index));
void *ptr;
check_cuda_error(cudaMalloc((void **)&ptr, size));
return ptr;
}
/// Allocates a size-byte array at the device memory. Tries to do it
/// asynchronously.
void *cuda_malloc_async(uint64_t size, cuda_stream_t *stream) {
check_cuda_error(cudaSetDevice(stream->gpu_index));
void *ptr;
#ifndef CUDART_VERSION
#error CUDART_VERSION Undefined!
#elif (CUDART_VERSION >= 11020)
int support_async_alloc;
check_cuda_error(cudaDeviceGetAttribute(&support_async_alloc,
cudaDevAttrMemoryPoolsSupported,
stream->gpu_index));
if (support_async_alloc) {
check_cuda_error(cudaMallocAsync((void **)&ptr, size, stream->stream));
} else {
check_cuda_error(cudaMalloc((void **)&ptr, size));
}
#else
check_cuda_error(cudaMalloc((void **)&ptr, size));
#endif
return ptr;
}
/// Check that allocation is valid
void cuda_check_valid_malloc(uint64_t size, uint32_t gpu_index) {
check_cuda_error(cudaSetDevice(gpu_index));
size_t total_mem, free_mem;
check_cuda_error(cudaMemGetInfo(&free_mem, &total_mem));
if (size > free_mem) {
PANIC("Cuda error: not enough memory on device. "
"Available: %zu vs Requested: %lu",
free_mem, size)
}
}
/// Returns
/// false if Cooperative Groups is not supported.
/// true otherwise
bool cuda_check_support_cooperative_groups() {
int cooperative_groups_supported = 0;
check_cuda_error(cudaDeviceGetAttribute(&cooperative_groups_supported,
cudaDevAttrCooperativeLaunch, 0));
return cooperative_groups_supported > 0;
}
/// Copy memory to the GPU asynchronously
void cuda_memcpy_async_to_gpu(void *dest, void *src, uint64_t size,
cuda_stream_t *stream) {
if (size == 0)
return;
cudaPointerAttributes attr;
check_cuda_error(cudaPointerGetAttributes(&attr, dest));
if (attr.device != stream->gpu_index && attr.type != cudaMemoryTypeDevice) {
PANIC("Cuda error: invalid device pointer in async copy to GPU.")
}
check_cuda_error(cudaSetDevice(stream->gpu_index));
check_cuda_error(
cudaMemcpyAsync(dest, src, size, cudaMemcpyHostToDevice, stream->stream));
}
/// Copy memory within a GPU asynchronously
void cuda_memcpy_async_gpu_to_gpu(void *dest, void *src, uint64_t size,
cuda_stream_t *stream) {
if (size == 0)
return;
cudaPointerAttributes attr_dest;
check_cuda_error(cudaPointerGetAttributes(&attr_dest, dest));
if (attr_dest.device != stream->gpu_index &&
attr_dest.type != cudaMemoryTypeDevice) {
PANIC("Cuda error: invalid dest device pointer in copy from GPU to GPU.")
}
cudaPointerAttributes attr_src;
check_cuda_error(cudaPointerGetAttributes(&attr_src, src));
if (attr_src.device != stream->gpu_index &&
attr_src.type != cudaMemoryTypeDevice) {
PANIC("Cuda error: invalid src device pointer in copy from GPU to GPU.")
}
if (attr_src.device != attr_dest.device) {
PANIC("Cuda error: different devices specified in copy from GPU to GPU.")
}
check_cuda_error(cudaSetDevice(stream->gpu_index));
check_cuda_error(cudaMemcpyAsync(dest, src, size, cudaMemcpyDeviceToDevice,
stream->stream));
}
/// Synchronizes device
void cuda_synchronize_device(uint32_t gpu_index) {
check_cuda_error(cudaSetDevice(gpu_index));
check_cuda_error(cudaDeviceSynchronize());
}
void cuda_memset_async(void *dest, uint64_t val, uint64_t size,
cuda_stream_t *stream) {
if (size == 0)
return;
cudaPointerAttributes attr;
check_cuda_error(cudaPointerGetAttributes(&attr, dest));
if (attr.device != stream->gpu_index && attr.type != cudaMemoryTypeDevice) {
PANIC("Cuda error: invalid dest device pointer in cuda memset.")
}
check_cuda_error(cudaSetDevice(stream->gpu_index));
check_cuda_error(cudaMemsetAsync(dest, val, size, stream->stream));
}
template <typename Torus>
__global__ void cuda_set_value_kernel(Torus *array, Torus value, Torus n) {
int index = threadIdx.x + blockIdx.x * blockDim.x;
if (index < n)
array[index] = value;
}
template <typename Torus>
void cuda_set_value_async(cudaStream_t *stream, Torus *d_array, Torus value,
Torus n) {
cudaPointerAttributes attr;
check_cuda_error(cudaPointerGetAttributes(&attr, d_array));
if (attr.type != cudaMemoryTypeDevice) {
PANIC("Cuda error: invalid dest device pointer in cuda set value.")
}
int block_size = 256;
int num_blocks = (n + block_size - 1) / block_size;
// Launch the kernel
cuda_set_value_kernel<<<num_blocks, block_size, 0, *stream>>>(d_array, value,
n);
check_cuda_error(cudaGetLastError());
}
/// Explicitly instantiate cuda_set_value_async for 32 and 64 bits
template void cuda_set_value_async(cudaStream_t *stream, uint64_t *d_array,
uint64_t value, uint64_t n);
template void cuda_set_value_async(cudaStream_t *stream, uint32_t *d_array,
uint32_t value, uint32_t n);
/// Copy memory to the CPU asynchronously
void cuda_memcpy_async_to_cpu(void *dest, const void *src, uint64_t size,
cuda_stream_t *stream) {
if (size == 0)
return;
cudaPointerAttributes attr;
check_cuda_error(cudaPointerGetAttributes(&attr, src));
if (attr.device != stream->gpu_index && attr.type != cudaMemoryTypeDevice) {
PANIC("Cuda error: invalid src device pointer in copy to CPU async.")
}
check_cuda_error(cudaSetDevice(stream->gpu_index));
check_cuda_error(
cudaMemcpyAsync(dest, src, size, cudaMemcpyDeviceToHost, stream->stream));
}
/// Return number of GPUs available
int cuda_get_number_of_gpus() {
int num_gpus;
check_cuda_error(cudaGetDeviceCount(&num_gpus));
return num_gpus;
}
/// Drop a cuda array
void cuda_drop(void *ptr, uint32_t gpu_index) {
check_cuda_error(cudaSetDevice(gpu_index));
check_cuda_error(cudaFree(ptr));
}
/// Drop a cuda array asynchronously, if supported on the device
void cuda_drop_async(void *ptr, cuda_stream_t *stream) {
check_cuda_error(cudaSetDevice(stream->gpu_index));
#ifndef CUDART_VERSION
#error CUDART_VERSION Undefined!
#elif (CUDART_VERSION >= 11020)
int support_async_alloc;
check_cuda_error(cudaDeviceGetAttribute(&support_async_alloc,
cudaDevAttrMemoryPoolsSupported,
stream->gpu_index));
if (support_async_alloc) {
check_cuda_error(cudaFreeAsync(ptr, stream->stream));
} else {
check_cuda_error(cudaFree(ptr));
}
#else
check_cuda_error(cudaFree(ptr));
#endif
}
/// Get the maximum size for the shared memory
int cuda_get_max_shared_memory(uint32_t gpu_index) {
check_cuda_error(cudaSetDevice(gpu_index));
int max_shared_memory = 0;
cudaDeviceGetAttribute(&max_shared_memory, cudaDevAttrMaxSharedMemoryPerBlock,
gpu_index);
check_cuda_error(cudaGetLastError());
return max_shared_memory;
}
void cuda_synchronize_stream(cuda_stream_t *stream) { stream->synchronize(); }
void cuda_stream_add_callback(cuda_stream_t *stream,
cudaStreamCallback_t callback, void *user_data) {
check_cuda_error(
cudaStreamAddCallback(stream->stream, callback, user_data, 0));
}
void host_free_on_stream_callback(cudaStream_t stream, cudaError_t status,
void *host_pointer) {
free(host_pointer);
}

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@@ -1,725 +0,0 @@
#ifndef GPU_BOOTSTRAP_FFT_CUH
#define GPU_BOOTSTRAP_FFT_CUH
#include "polynomial/functions.cuh"
#include "polynomial/parameters.cuh"
#include "twiddles.cuh"
#include "types/complex/operations.cuh"
/*
* Direct negacyclic FFT:
* - before the FFT the N real coefficients are stored into a
* N/2 sized complex with the even coefficients in the real part
* and the odd coefficients in the imaginary part. This is referred to
* as the half-size FFT
* - when calling BNSMFFT_direct for the forward negacyclic FFT of PBS,
* opt is divided by 2 because the butterfly pattern is always applied
* between pairs of coefficients
* - instead of twisting each coefficient A_j before the FFT by
* multiplying by the w^j roots of unity (aka twiddles, w=exp(-i pi /N)),
* the FFT is modified, and for each level k of the FFT the twiddle:
* w_j,k = exp(-i pi j/2^k)
* is replaced with:
* \zeta_j,k = exp(-i pi (2j-1)/2^k)
*/
template <class params> __device__ void NSMFFT_direct(double2 *A) {
/* We don't make bit reverse here, since twiddles are already reversed
* Each thread is always in charge of "opt/2" pairs of coefficients,
* which is why we always loop through N/2 by N/opt strides
* The pragma unroll instruction tells the compiler to unroll the
* full loop, which should increase performance
*/
size_t tid = threadIdx.x;
size_t twid_id;
size_t i1, i2;
double2 u, v, w;
// level 1
// we don't make actual complex multiplication on level1 since we have only
// one twiddle, it's real and image parts are equal, so we can multiply
// it with simpler operations
#pragma unroll
for (size_t i = 0; i < params::opt / 2; ++i) {
i1 = tid;
i2 = tid + params::degree / 2;
u = A[i1];
v = A[i2] * (double2){0.707106781186547461715008466854,
0.707106781186547461715008466854};
A[i1] += v;
A[i2] = u - v;
tid += params::degree / params::opt;
}
__syncthreads();
// level 2
// from this level there are more than one twiddles and none of them has equal
// real and imag parts, so complete complex multiplication is needed
// for each level params::degree / 2^level represents number of coefficients
// inside divided chunk of specific level
//
tid = threadIdx.x;
#pragma unroll
for (size_t i = 0; i < params::opt / 2; ++i) {
twid_id = tid / (params::degree / 4);
i1 = 2 * (params::degree / 4) * twid_id + (tid & (params::degree / 4 - 1));
i2 = i1 + params::degree / 4;
w = negtwiddles[twid_id + 2];
u = A[i1];
v = A[i2] * w;
A[i1] += v;
A[i2] = u - v;
tid += params::degree / params::opt;
}
__syncthreads();
// level 3
tid = threadIdx.x;
#pragma unroll
for (size_t i = 0; i < params::opt / 2; ++i) {
twid_id = tid / (params::degree / 8);
i1 = 2 * (params::degree / 8) * twid_id + (tid & (params::degree / 8 - 1));
i2 = i1 + params::degree / 8;
w = negtwiddles[twid_id + 4];
u = A[i1];
v = A[i2] * w;
A[i1] += v;
A[i2] = u - v;
tid += params::degree / params::opt;
}
__syncthreads();
// level 4
tid = threadIdx.x;
#pragma unroll
for (size_t i = 0; i < params::opt / 2; ++i) {
twid_id = tid / (params::degree / 16);
i1 =
2 * (params::degree / 16) * twid_id + (tid & (params::degree / 16 - 1));
i2 = i1 + params::degree / 16;
w = negtwiddles[twid_id + 8];
u = A[i1];
v = A[i2] * w;
A[i1] += v;
A[i2] = u - v;
tid += params::degree / params::opt;
}
__syncthreads();
// level 5
tid = threadIdx.x;
#pragma unroll
for (size_t i = 0; i < params::opt / 2; ++i) {
twid_id = tid / (params::degree / 32);
i1 =
2 * (params::degree / 32) * twid_id + (tid & (params::degree / 32 - 1));
i2 = i1 + params::degree / 32;
w = negtwiddles[twid_id + 16];
u = A[i1];
v = A[i2] * w;
A[i1] += v;
A[i2] = u - v;
tid += params::degree / params::opt;
}
__syncthreads();
// level 6
tid = threadIdx.x;
#pragma unroll
for (size_t i = 0; i < params::opt / 2; ++i) {
twid_id = tid / (params::degree / 64);
i1 =
2 * (params::degree / 64) * twid_id + (tid & (params::degree / 64 - 1));
i2 = i1 + params::degree / 64;
w = negtwiddles[twid_id + 32];
u = A[i1];
v = A[i2] * w;
A[i1] += v;
A[i2] = u - v;
tid += params::degree / params::opt;
}
__syncthreads();
// level 7
tid = threadIdx.x;
#pragma unroll
for (size_t i = 0; i < params::opt / 2; ++i) {
twid_id = tid / (params::degree / 128);
i1 = 2 * (params::degree / 128) * twid_id +
(tid & (params::degree / 128 - 1));
i2 = i1 + params::degree / 128;
w = negtwiddles[twid_id + 64];
u = A[i1];
v = A[i2] * w;
A[i1] += v;
A[i2] = u - v;
tid += params::degree / params::opt;
}
__syncthreads();
// from level 8, we need to check size of params degree, because we support
// minimum actual polynomial size = 256, when compressed size is halfed and
// minimum supported compressed size is 128, so we always need first 7
// levels of butterfly operation, since butterfly levels are hardcoded
// we need to check if polynomial size is big enough to require specific level
// of butterfly.
if constexpr (params::degree >= 256) {
// level 8
tid = threadIdx.x;
#pragma unroll
for (size_t i = 0; i < params::opt / 2; ++i) {
twid_id = tid / (params::degree / 256);
i1 = 2 * (params::degree / 256) * twid_id +
(tid & (params::degree / 256 - 1));
i2 = i1 + params::degree / 256;
w = negtwiddles[twid_id + 128];
u = A[i1];
v = A[i2] * w;
A[i1] += v;
A[i2] = u - v;
tid += params::degree / params::opt;
}
__syncthreads();
}
if constexpr (params::degree >= 512) {
// level 9
tid = threadIdx.x;
#pragma unroll
for (size_t i = 0; i < params::opt / 2; ++i) {
twid_id = tid / (params::degree / 512);
i1 = 2 * (params::degree / 512) * twid_id +
(tid & (params::degree / 512 - 1));
i2 = i1 + params::degree / 512;
w = negtwiddles[twid_id + 256];
u = A[i1];
v = A[i2] * w;
A[i1] += v;
A[i2] = u - v;
tid += params::degree / params::opt;
}
__syncthreads();
}
if constexpr (params::degree >= 1024) {
// level 10
tid = threadIdx.x;
#pragma unroll
for (size_t i = 0; i < params::opt / 2; ++i) {
twid_id = tid / (params::degree / 1024);
i1 = 2 * (params::degree / 1024) * twid_id +
(tid & (params::degree / 1024 - 1));
i2 = i1 + params::degree / 1024;
w = negtwiddles[twid_id + 512];
u = A[i1];
v = A[i2] * w;
A[i1] += v;
A[i2] = u - v;
tid += params::degree / params::opt;
}
__syncthreads();
}
if constexpr (params::degree >= 2048) {
// level 11
tid = threadIdx.x;
#pragma unroll
for (size_t i = 0; i < params::opt / 2; ++i) {
twid_id = tid / (params::degree / 2048);
i1 = 2 * (params::degree / 2048) * twid_id +
(tid & (params::degree / 2048 - 1));
i2 = i1 + params::degree / 2048;
w = negtwiddles[twid_id + 1024];
u = A[i1];
v = A[i2] * w;
A[i1] += v;
A[i2] = u - v;
tid += params::degree / params::opt;
}
__syncthreads();
}
if constexpr (params::degree >= 4096) {
// level 12
tid = threadIdx.x;
#pragma unroll
for (size_t i = 0; i < params::opt / 2; ++i) {
twid_id = tid / (params::degree / 4096);
i1 = 2 * (params::degree / 4096) * twid_id +
(tid & (params::degree / 4096 - 1));
i2 = i1 + params::degree / 4096;
w = negtwiddles[twid_id + 2048];
u = A[i1];
v = A[i2] * w;
A[i1] += v;
A[i2] = u - v;
tid += params::degree / params::opt;
}
__syncthreads();
}
// compressed size = 8192 is actual polynomial size = 16384.
// from this size, twiddles can't fit in constant memory,
// so from here, butterfly operation access device memory.
if constexpr (params::degree >= 8192) {
// level 13
tid = threadIdx.x;
#pragma unroll
for (size_t i = 0; i < params::opt / 2; ++i) {
twid_id = tid / (params::degree / 8192);
i1 = 2 * (params::degree / 8192) * twid_id +
(tid & (params::degree / 8192 - 1));
i2 = i1 + params::degree / 8192;
w = negtwiddles13[twid_id];
u = A[i1];
v = A[i2] * w;
A[i1] += v;
A[i2] = u - v;
tid += params::degree / params::opt;
}
__syncthreads();
}
}
/*
* negacyclic inverse fft
*/
template <class params> __device__ void NSMFFT_inverse(double2 *A) {
/* We don't make bit reverse here, since twiddles are already reversed
* Each thread is always in charge of "opt/2" pairs of coefficients,
* which is why we always loop through N/2 by N/opt strides
* The pragma unroll instruction tells the compiler to unroll the
* full loop, which should increase performance
*/
size_t tid = threadIdx.x;
size_t twid_id;
size_t i1, i2;
double2 u, w;
// divide input by compressed polynomial size
tid = threadIdx.x;
for (size_t i = 0; i < params::opt; ++i) {
A[tid] /= params::degree;
tid += params::degree / params::opt;
}
__syncthreads();
// none of the twiddles have equal real and imag part, so
// complete complex multiplication has to be done
// here we have more than one twiddle
// mapping in backward fft is reversed
// butterfly operation is started from last level
// compressed size = 8192 is actual polynomial size = 16384.
// twiddles for this size can't fit in constant memory so
// butterfly operation for this level access device memory to fetch
// twiddles
if constexpr (params::degree >= 8192) {
// level 13
tid = threadIdx.x;
#pragma unroll
for (size_t i = 0; i < params::opt / 2; ++i) {
twid_id = tid / (params::degree / 8192);
i1 = 2 * (params::degree / 8192) * twid_id +
(tid & (params::degree / 8192 - 1));
i2 = i1 + params::degree / 8192;
w = negtwiddles13[twid_id];
u = A[i1] - A[i2];
A[i1] += A[i2];
A[i2] = u * conjugate(w);
tid += params::degree / params::opt;
}
__syncthreads();
}
if constexpr (params::degree >= 4096) {
// level 12
tid = threadIdx.x;
#pragma unroll
for (size_t i = 0; i < params::opt / 2; ++i) {
twid_id = tid / (params::degree / 4096);
i1 = 2 * (params::degree / 4096) * twid_id +
(tid & (params::degree / 4096 - 1));
i2 = i1 + params::degree / 4096;
w = negtwiddles[twid_id + 2048];
u = A[i1] - A[i2];
A[i1] += A[i2];
A[i2] = u * conjugate(w);
tid += params::degree / params::opt;
}
__syncthreads();
}
if constexpr (params::degree >= 2048) {
// level 11
tid = threadIdx.x;
#pragma unroll
for (size_t i = 0; i < params::opt / 2; ++i) {
twid_id = tid / (params::degree / 2048);
i1 = 2 * (params::degree / 2048) * twid_id +
(tid & (params::degree / 2048 - 1));
i2 = i1 + params::degree / 2048;
w = negtwiddles[twid_id + 1024];
u = A[i1] - A[i2];
A[i1] += A[i2];
A[i2] = u * conjugate(w);
tid += params::degree / params::opt;
}
__syncthreads();
}
if constexpr (params::degree >= 1024) {
// level 10
tid = threadIdx.x;
#pragma unroll
for (size_t i = 0; i < params::opt / 2; ++i) {
twid_id = tid / (params::degree / 1024);
i1 = 2 * (params::degree / 1024) * twid_id +
(tid & (params::degree / 1024 - 1));
i2 = i1 + params::degree / 1024;
w = negtwiddles[twid_id + 512];
u = A[i1] - A[i2];
A[i1] += A[i2];
A[i2] = u * conjugate(w);
tid += params::degree / params::opt;
}
__syncthreads();
}
if constexpr (params::degree >= 512) {
// level 9
tid = threadIdx.x;
#pragma unroll
for (size_t i = 0; i < params::opt / 2; ++i) {
twid_id = tid / (params::degree / 512);
i1 = 2 * (params::degree / 512) * twid_id +
(tid & (params::degree / 512 - 1));
i2 = i1 + params::degree / 512;
w = negtwiddles[twid_id + 256];
u = A[i1] - A[i2];
A[i1] += A[i2];
A[i2] = u * conjugate(w);
tid += params::degree / params::opt;
}
__syncthreads();
}
if constexpr (params::degree >= 256) {
// level 8
tid = threadIdx.x;
#pragma unroll
for (size_t i = 0; i < params::opt / 2; ++i) {
twid_id = tid / (params::degree / 256);
i1 = 2 * (params::degree / 256) * twid_id +
(tid & (params::degree / 256 - 1));
i2 = i1 + params::degree / 256;
w = negtwiddles[twid_id + 128];
u = A[i1] - A[i2];
A[i1] += A[i2];
A[i2] = u * conjugate(w);
tid += params::degree / params::opt;
}
__syncthreads();
}
// below level 8, we don't need to check size of params degree, because we
// support minimum actual polynomial size = 256, when compressed size is
// halfed and minimum supported compressed size is 128, so we always need
// last 7 levels of butterfly operation, since butterfly levels are hardcoded
// we don't need to check if polynomial size is big enough to require
// specific level of butterfly.
// level 7
tid = threadIdx.x;
#pragma unroll
for (size_t i = 0; i < params::opt / 2; ++i) {
twid_id = tid / (params::degree / 128);
i1 = 2 * (params::degree / 128) * twid_id +
(tid & (params::degree / 128 - 1));
i2 = i1 + params::degree / 128;
w = negtwiddles[twid_id + 64];
u = A[i1] - A[i2];
A[i1] += A[i2];
A[i2] = u * conjugate(w);
tid += params::degree / params::opt;
}
__syncthreads();
// level 6
tid = threadIdx.x;
#pragma unroll
for (size_t i = 0; i < params::opt / 2; ++i) {
twid_id = tid / (params::degree / 64);
i1 =
2 * (params::degree / 64) * twid_id + (tid & (params::degree / 64 - 1));
i2 = i1 + params::degree / 64;
w = negtwiddles[twid_id + 32];
u = A[i1] - A[i2];
A[i1] += A[i2];
A[i2] = u * conjugate(w);
tid += params::degree / params::opt;
}
__syncthreads();
// level 5
tid = threadIdx.x;
#pragma unroll
for (size_t i = 0; i < params::opt / 2; ++i) {
twid_id = tid / (params::degree / 32);
i1 =
2 * (params::degree / 32) * twid_id + (tid & (params::degree / 32 - 1));
i2 = i1 + params::degree / 32;
w = negtwiddles[twid_id + 16];
u = A[i1] - A[i2];
A[i1] += A[i2];
A[i2] = u * conjugate(w);
tid += params::degree / params::opt;
}
__syncthreads();
// level 4
tid = threadIdx.x;
#pragma unroll
for (size_t i = 0; i < params::opt / 2; ++i) {
twid_id = tid / (params::degree / 16);
i1 =
2 * (params::degree / 16) * twid_id + (tid & (params::degree / 16 - 1));
i2 = i1 + params::degree / 16;
w = negtwiddles[twid_id + 8];
u = A[i1] - A[i2];
A[i1] += A[i2];
A[i2] = u * conjugate(w);
tid += params::degree / params::opt;
}
__syncthreads();
// level 3
tid = threadIdx.x;
#pragma unroll
for (size_t i = 0; i < params::opt / 2; ++i) {
twid_id = tid / (params::degree / 8);
i1 = 2 * (params::degree / 8) * twid_id + (tid & (params::degree / 8 - 1));
i2 = i1 + params::degree / 8;
w = negtwiddles[twid_id + 4];
u = A[i1] - A[i2];
A[i1] += A[i2];
A[i2] = u * conjugate(w);
tid += params::degree / params::opt;
}
__syncthreads();
// level 2
tid = threadIdx.x;
#pragma unroll
for (size_t i = 0; i < params::opt / 2; ++i) {
twid_id = tid / (params::degree / 4);
i1 = 2 * (params::degree / 4) * twid_id + (tid & (params::degree / 4 - 1));
i2 = i1 + params::degree / 4;
w = negtwiddles[twid_id + 2];
u = A[i1] - A[i2];
A[i1] += A[i2];
A[i2] = u * conjugate(w);
tid += params::degree / params::opt;
}
__syncthreads();
// level 1
tid = threadIdx.x;
#pragma unroll
for (size_t i = 0; i < params::opt / 2; ++i) {
twid_id = tid / (params::degree / 2);
i1 = 2 * (params::degree / 2) * twid_id + (tid & (params::degree / 2 - 1));
i2 = i1 + params::degree / 2;
w = negtwiddles[twid_id + 1];
u = A[i1] - A[i2];
A[i1] += A[i2];
A[i2] = u * conjugate(w);
tid += params::degree / params::opt;
}
__syncthreads();
}
/*
* global batch fft
* does fft in half size
* unrolling half size fft result in half size + 1 elements
* this function must be called with actual degree
* function takes as input already compressed input
*/
template <class params, sharedMemDegree SMD>
__global__ void batch_NSMFFT(double2 *d_input, double2 *d_output,
double2 *buffer) {
extern __shared__ double2 sharedMemoryFFT[];
double2 *fft = (SMD == NOSM) ? &buffer[blockIdx.x * params::degree / 2]
: sharedMemoryFFT;
int tid = threadIdx.x;
#pragma unroll
for (int i = 0; i < params::opt / 2; i++) {
fft[tid] = d_input[blockIdx.x * (params::degree / 2) + tid];
tid = tid + params::degree / params::opt;
}
__syncthreads();
NSMFFT_direct<HalfDegree<params>>(fft);
__syncthreads();
tid = threadIdx.x;
#pragma unroll
for (int i = 0; i < params::opt / 2; i++) {
d_output[blockIdx.x * (params::degree / 2) + tid] = fft[tid];
tid = tid + params::degree / params::opt;
}
}
/*
* global batch polynomial multiplication
* only used for fft tests
* d_input1 and d_output must not have the same pointer
* d_input1 can be modified inside the function
*/
template <class params, sharedMemDegree SMD>
__global__ void batch_polynomial_mul(double2 *d_input1, double2 *d_input2,
double2 *d_output, double2 *buffer) {
extern __shared__ double2 sharedMemoryFFT[];
double2 *fft = (SMD == NOSM) ? &buffer[blockIdx.x * params::degree / 2]
: sharedMemoryFFT;
// Move first polynomial into shared memory(if possible otherwise it will
// be moved in device buffer)
int tid = threadIdx.x;
#pragma unroll
for (int i = 0; i < params::opt / 2; i++) {
fft[tid] = d_input1[blockIdx.x * (params::degree / 2) + tid];
tid = tid + params::degree / params::opt;
}
// Perform direct negacyclic fourier transform
__syncthreads();
NSMFFT_direct<HalfDegree<params>>(fft);
__syncthreads();
// Put the result of direct fft inside input1
tid = threadIdx.x;
#pragma unroll
for (int i = 0; i < params::opt / 2; i++) {
d_input1[blockIdx.x * (params::degree / 2) + tid] = fft[tid];
tid = tid + params::degree / params::opt;
}
__syncthreads();
// Move first polynomial into shared memory(if possible otherwise it will
// be moved in device buffer)
tid = threadIdx.x;
#pragma unroll
for (int i = 0; i < params::opt / 2; i++) {
fft[tid] = d_input2[blockIdx.x * (params::degree / 2) + tid];
tid = tid + params::degree / params::opt;
}
// Perform direct negacyclic fourier transform on the second polynomial
__syncthreads();
NSMFFT_direct<HalfDegree<params>>(fft);
__syncthreads();
// calculate pointwise multiplication inside fft buffer
tid = threadIdx.x;
#pragma unroll
for (int i = 0; i < params::opt / 2; i++) {
fft[tid] *= d_input1[blockIdx.x * (params::degree / 2) + tid];
tid = tid + params::degree / params::opt;
}
// Perform backward negacyclic fourier transform
__syncthreads();
NSMFFT_inverse<HalfDegree<params>>(fft);
__syncthreads();
// copy results in output buffer
tid = threadIdx.x;
#pragma unroll
for (int i = 0; i < params::opt / 2; i++) {
d_output[blockIdx.x * (params::degree / 2) + tid] = fft[tid];
tid = tid + params::degree / params::opt;
}
}
#endif // GPU_BOOTSTRAP_FFT_CUH

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@@ -1,13 +0,0 @@
#ifndef GPU_BOOTSTRAP_TWIDDLES_CUH
#define GPU_BOOTSTRAP_TWIDDLES_CUH
/*
* 'negtwiddles' are stored in constant memory for faster access times
* because of it's limited size, only twiddles for up to 2^12 polynomial size
* can be stored there, twiddles for 2^13 are stored in device memory
* 'negtwiddles13'
*/
extern __constant__ double2 negtwiddles[4096];
extern __device__ double2 negtwiddles13[4096];
#endif

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@@ -1,51 +0,0 @@
#include "integer/bitwise_ops.cuh"
void scratch_cuda_integer_radix_bitop_kb_64(
cuda_stream_t *stream, int8_t **mem_ptr, uint32_t glwe_dimension,
uint32_t polynomial_size, uint32_t big_lwe_dimension,
uint32_t small_lwe_dimension, uint32_t ks_level, uint32_t ks_base_log,
uint32_t pbs_level, uint32_t pbs_base_log, uint32_t grouping_factor,
uint32_t lwe_ciphertext_count, uint32_t message_modulus,
uint32_t carry_modulus, PBS_TYPE pbs_type, BITOP_TYPE op_type,
bool allocate_gpu_memory) {
int_radix_params params(pbs_type, glwe_dimension, polynomial_size,
big_lwe_dimension, small_lwe_dimension, ks_level,
ks_base_log, pbs_level, pbs_base_log, grouping_factor,
message_modulus, carry_modulus);
scratch_cuda_integer_radix_bitop_kb<uint64_t>(
stream, (int_bitop_buffer<uint64_t> **)mem_ptr, lwe_ciphertext_count,
params, op_type, allocate_gpu_memory);
}
void cuda_bitop_integer_radix_ciphertext_kb_64(
cuda_stream_t *stream, void *lwe_array_out, void *lwe_array_1,
void *lwe_array_2, int8_t *mem_ptr, void *bsk, void *ksk,
uint32_t lwe_ciphertext_count) {
host_integer_radix_bitop_kb<uint64_t>(
stream, static_cast<uint64_t *>(lwe_array_out),
static_cast<uint64_t *>(lwe_array_1),
static_cast<uint64_t *>(lwe_array_2),
(int_bitop_buffer<uint64_t> *)mem_ptr, bsk, static_cast<uint64_t *>(ksk),
lwe_ciphertext_count);
}
void cuda_bitnot_integer_radix_ciphertext_kb_64(
cuda_stream_t *stream, void *lwe_array_out, void *lwe_array_in,
int8_t *mem_ptr, void *bsk, void *ksk, uint32_t lwe_ciphertext_count) {
host_integer_radix_bitnot_kb<uint64_t>(
stream, static_cast<uint64_t *>(lwe_array_out),
static_cast<uint64_t *>(lwe_array_in),
(int_bitop_buffer<uint64_t> *)mem_ptr, bsk, static_cast<uint64_t *>(ksk),
lwe_ciphertext_count);
}
void cleanup_cuda_integer_bitop(cuda_stream_t *stream, int8_t **mem_ptr_void) {
int_bitop_buffer<uint64_t> *mem_ptr =
(int_bitop_buffer<uint64_t> *)(*mem_ptr_void);
mem_ptr->release(stream);
}

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@@ -1,52 +0,0 @@
#ifndef CUDA_INTEGER_BITWISE_OPS_CUH
#define CUDA_INTEGER_BITWISE_OPS_CUH
#include "crypto/keyswitch.cuh"
#include "device.h"
#include "integer.cuh"
#include "integer.h"
#include "pbs/programmable_bootstrap_classic.cuh"
#include "pbs/programmable_bootstrap_multibit.cuh"
#include "polynomial/functions.cuh"
#include "utils/kernel_dimensions.cuh"
#include <omp.h>
template <typename Torus>
__host__ void
host_integer_radix_bitop_kb(cuda_stream_t *stream, Torus *lwe_array_out,
Torus *lwe_array_1, Torus *lwe_array_2,
int_bitop_buffer<Torus> *mem_ptr, void *bsk,
Torus *ksk, uint32_t num_radix_blocks) {
auto lut = mem_ptr->lut;
integer_radix_apply_bivariate_lookup_table_kb<Torus>(
stream, lwe_array_out, lwe_array_1, lwe_array_2, bsk, ksk,
num_radix_blocks, lut);
}
template <typename Torus>
__host__ void
host_integer_radix_bitnot_kb(cuda_stream_t *stream, Torus *lwe_array_out,
Torus *lwe_array_in,
int_bitop_buffer<Torus> *mem_ptr, void *bsk,
Torus *ksk, uint32_t num_radix_blocks) {
auto lut = mem_ptr->lut;
integer_radix_apply_univariate_lookup_table_kb<Torus>(
stream, lwe_array_out, lwe_array_in, bsk, ksk, num_radix_blocks, lut);
}
template <typename Torus>
__host__ void scratch_cuda_integer_radix_bitop_kb(
cuda_stream_t *stream, int_bitop_buffer<Torus> **mem_ptr,
uint32_t num_radix_blocks, int_radix_params params, BITOP_TYPE op,
bool allocate_gpu_memory) {
cudaSetDevice(stream->gpu_index);
*mem_ptr = new int_bitop_buffer<Torus>(stream, op, params, num_radix_blocks,
allocate_gpu_memory);
}
#endif

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@@ -1,45 +0,0 @@
#include "integer/cmux.cuh"
void scratch_cuda_integer_radix_cmux_kb_64(
cuda_stream_t *stream, int8_t **mem_ptr, uint32_t glwe_dimension,
uint32_t polynomial_size, uint32_t big_lwe_dimension,
uint32_t small_lwe_dimension, uint32_t ks_level, uint32_t ks_base_log,
uint32_t pbs_level, uint32_t pbs_base_log, uint32_t grouping_factor,
uint32_t lwe_ciphertext_count, uint32_t message_modulus,
uint32_t carry_modulus, PBS_TYPE pbs_type, bool allocate_gpu_memory) {
int_radix_params params(pbs_type, glwe_dimension, polynomial_size,
big_lwe_dimension, small_lwe_dimension, ks_level,
ks_base_log, pbs_level, pbs_base_log, grouping_factor,
message_modulus, carry_modulus);
std::function<uint64_t(uint64_t)> predicate_lut_f =
[](uint64_t x) -> uint64_t { return x == 1; };
scratch_cuda_integer_radix_cmux_kb(
stream, (int_cmux_buffer<uint64_t> **)mem_ptr, predicate_lut_f,
lwe_ciphertext_count, params, allocate_gpu_memory);
}
void cuda_cmux_integer_radix_ciphertext_kb_64(
cuda_stream_t *stream, void *lwe_array_out, void *lwe_condition,
void *lwe_array_true, void *lwe_array_false, int8_t *mem_ptr, void *bsk,
void *ksk, uint32_t lwe_ciphertext_count) {
host_integer_radix_cmux_kb<uint64_t>(
stream, static_cast<uint64_t *>(lwe_array_out),
static_cast<uint64_t *>(lwe_condition),
static_cast<uint64_t *>(lwe_array_true),
static_cast<uint64_t *>(lwe_array_false),
(int_cmux_buffer<uint64_t> *)mem_ptr, bsk, static_cast<uint64_t *>(ksk),
lwe_ciphertext_count);
}
void cleanup_cuda_integer_radix_cmux(cuda_stream_t *stream,
int8_t **mem_ptr_void) {
int_cmux_buffer<uint64_t> *mem_ptr =
(int_cmux_buffer<uint64_t> *)(*mem_ptr_void);
mem_ptr->release(stream);
}

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@@ -1,102 +0,0 @@
#ifndef CUDA_INTEGER_CMUX_CUH
#define CUDA_INTEGER_CMUX_CUH
#include "integer.cuh"
#include <omp.h>
template <typename Torus>
__host__ void zero_out_if(cuda_stream_t *stream, Torus *lwe_array_out,
Torus *lwe_array_input, Torus *lwe_condition,
int_zero_out_if_buffer<Torus> *mem_ptr,
int_radix_lut<Torus> *predicate, void *bsk,
Torus *ksk, uint32_t num_radix_blocks) {
cudaSetDevice(stream->gpu_index);
auto params = mem_ptr->params;
int big_lwe_size = params.big_lwe_dimension + 1;
// Left message is shifted
int num_blocks = 0, num_threads = 0;
int num_entries = (params.big_lwe_dimension + 1);
getNumBlocksAndThreads(num_entries, 512, num_blocks, num_threads);
// We can't use integer_radix_apply_bivariate_lookup_table_kb since the
// second operand is fixed
auto tmp_lwe_array_input = mem_ptr->tmp;
for (int i = 0; i < num_radix_blocks; i++) {
auto lwe_array_out_block = tmp_lwe_array_input + i * big_lwe_size;
auto lwe_array_input_block = lwe_array_input + i * big_lwe_size;
device_pack_bivariate_blocks<<<num_blocks, num_threads, 0,
stream->stream>>>(
lwe_array_out_block, predicate->lwe_indexes_in, lwe_array_input_block,
lwe_condition, predicate->lwe_indexes_in, params.big_lwe_dimension,
params.message_modulus, 1);
check_cuda_error(cudaGetLastError());
}
integer_radix_apply_univariate_lookup_table_kb<Torus>(
stream, lwe_array_out, tmp_lwe_array_input, bsk, ksk, num_radix_blocks,
predicate);
}
template <typename Torus>
__host__ void
host_integer_radix_cmux_kb(cuda_stream_t *stream, Torus *lwe_array_out,
Torus *lwe_condition, Torus *lwe_array_true,
Torus *lwe_array_false,
int_cmux_buffer<Torus> *mem_ptr, void *bsk,
Torus *ksk, uint32_t num_radix_blocks) {
auto params = mem_ptr->params;
// Since our CPU threads will be working on different streams we shall assert
// the work in the main stream is completed
stream->synchronize();
auto true_stream = mem_ptr->zero_if_true_buffer->local_stream;
auto false_stream = mem_ptr->zero_if_false_buffer->local_stream;
#pragma omp parallel sections
{
// Both sections may be executed in parallel
#pragma omp section
{
auto mem_true = mem_ptr->zero_if_true_buffer;
zero_out_if(true_stream, mem_ptr->tmp_true_ct, lwe_array_true,
lwe_condition, mem_true, mem_ptr->inverted_predicate_lut, bsk,
ksk, num_radix_blocks);
}
#pragma omp section
{
auto mem_false = mem_ptr->zero_if_false_buffer;
zero_out_if(false_stream, mem_ptr->tmp_false_ct, lwe_array_false,
lwe_condition, mem_false, mem_ptr->predicate_lut, bsk, ksk,
num_radix_blocks);
}
}
cuda_synchronize_stream(true_stream);
cuda_synchronize_stream(false_stream);
// 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
// have kept its value
auto added_cts = mem_ptr->tmp_true_ct;
host_addition(stream, added_cts, mem_ptr->tmp_true_ct, mem_ptr->tmp_false_ct,
params.big_lwe_dimension, num_radix_blocks);
integer_radix_apply_univariate_lookup_table_kb<Torus>(
stream, lwe_array_out, added_cts, bsk, ksk, num_radix_blocks,
mem_ptr->message_extract_lut);
}
template <typename Torus>
__host__ void scratch_cuda_integer_radix_cmux_kb(
cuda_stream_t *stream, int_cmux_buffer<Torus> **mem_ptr,
std::function<Torus(Torus)> predicate_lut_f, uint32_t num_radix_blocks,
int_radix_params params, bool allocate_gpu_memory) {
cudaSetDevice(stream->gpu_index);
*mem_ptr = new int_cmux_buffer<Torus>(stream, predicate_lut_f, params,
num_radix_blocks, allocate_gpu_memory);
}
#endif

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