Compare commits

...

78 Commits

Author SHA1 Message Date
Arthur Meyre
7043246c17 chore: update CODEOWNERS file 2026-01-09 16:12:50 +01:00
Theo Souchon
51735fb8ed chore(bench): code refactor and automation for hlapi 2026-01-09 16:09:27 +01:00
pgardratzama
23a348c9ae feat(hpu): new HPU bitstream RTL v2.2 2026-01-09 15:25:35 +01:00
Mayeul@Zama
61b616b784 chore(hlapi): add bench of oprf over any range 2026-01-09 15:19:08 +01:00
Mayeul@Zama
df48e176f3 feat(hlapi): add oprf over any range 2026-01-09 15:19:08 +01:00
Mayeul@Zama
dd2345df6b refactor(integer): use NonZeroU64 for excluded_upper_bound 2026-01-09 15:19:08 +01:00
Mayeul@Zama
933800ea6f doc(hlapi): fix documentation 2026-01-09 15:19:08 +01:00
Mayeul@Zama
3e4cee3a75 refactor(integer): split oprf_almost_uniformity_test 2026-01-09 15:19:08 +01:00
Mayeul@Zama
00ea9b8e07 refactor(shortint): improve error in uniformity_p_value 2026-01-09 15:19:08 +01:00
Mayeul@Zama
23ce85f6a2 fix(core): make sup_diff more permissive 2026-01-09 15:19:08 +01:00
Nicolas Sarlin
126a95e929 fix(js): unsafe coop bench was overwritting mt one 2026-01-08 16:48:18 +01:00
Nicolas Sarlin
23fffb1443 chore(deps): ignore unmaintained bincode cargo audit warning 2026-01-08 15:16:37 +01:00
Agnes Leroy
6d58a54266 chore(gpu): attempt to fix apt in ci 2026-01-08 14:54:03 +01:00
Baptiste Roux
9b8d5f5a43 chore(hpu): bump version of lru
Lru required version update following caro audit

Signed-off-by: Baptiste Roux <baptiste.roux@zama.ai>
2026-01-08 14:08:31 +01:00
dependabot[bot]
696f964ecf chore(deps): bump actions/cache from 4.3.0 to 5.0.1
Bumps [actions/cache](https://github.com/actions/cache) from 4.3.0 to 5.0.1.
- [Release notes](https://github.com/actions/cache/releases)
- [Changelog](https://github.com/actions/cache/blob/main/RELEASES.md)
- [Commits](0057852bfa...9255dc7a25)

---
updated-dependencies:
- dependency-name: actions/cache
  dependency-version: 5.0.1
  dependency-type: direct:production
  update-type: version-update:semver-major
...

Signed-off-by: dependabot[bot] <support@github.com>
2026-01-07 16:20:28 +01:00
Nicolas Sarlin
a5323d1edf chore(test-vectors): add vectors for karatsuba br 2026-01-07 10:19:30 +01:00
Nicolas Sarlin
2d500d0de6 feat(core): add karatsuba bootstrap
Co-authored-by: IceTDrinker <arthur.meyre@zama.ai>
2026-01-07 10:19:30 +01:00
pgardratzama
b1657876fb fix(hpu): fix double import when hpu feature is on 2026-01-06 18:01:14 +01:00
pgardratzama
d2a570bdd6 chore: uses if_then_zero only in HPU ERC20 whitepaper (to be updated when encrypt_trivial becomes available on HPU), adds test of if_then_zero for both CPU & HPU 2026-01-06 16:55:07 +01:00
pgardratzama
122ef489fd chore(hpu): make pcc happy 2026-01-06 16:55:07 +01:00
pgardratzama
ed84387bba chore: trying to insure GPU ERC20 bench are not impacted while CPU & HPU uses if_then_zero 2026-01-06 16:55:07 +01:00
Baptiste Roux
1f4ba33a50 fix(hpu): Correctly select adder configuration in ERC_20/ERC_20_SIMD
Add knobs to select ripple or kogge adder in ERC_20/ERC_20_SIMD.
Previously, it was hardcoded to ripple carry and thus degraded latency
performance of ERC_20.
2026-01-06 16:55:07 +01:00
Baptiste Roux
e645ee3397 feat: Add IfThenZero impl for Cpu 2026-01-06 16:55:07 +01:00
pgardratzama
569abd9a3b fix(hpu): fix whitepaper erc20 for HPU using if_then_zero 2026-01-06 16:55:07 +01:00
Nicolas Sarlin
917bb5e1ef chore(js): use smaller favicon for wasm tests 2026-01-06 16:42:43 +01:00
Nicolas Sarlin
509aadcad2 chore(js): add benchmark for unsafe coop context 2026-01-06 16:42:43 +01:00
David Testé
e20aea90df chore(bench): set ks32 parameters as default for integer benchmarks 2026-01-06 14:59:34 +01:00
dependabot[bot]
e8ab448454 chore(deps): bump tj-actions/changed-files from 47.0.0 to 47.0.1
Bumps [tj-actions/changed-files](https://github.com/tj-actions/changed-files) from 47.0.0 to 47.0.1.
- [Release notes](https://github.com/tj-actions/changed-files/releases)
- [Changelog](https://github.com/tj-actions/changed-files/blob/main/HISTORY.md)
- [Commits](24d32ffd49...e002140703)

---
updated-dependencies:
- dependency-name: tj-actions/changed-files
  dependency-version: 47.0.1
  dependency-type: direct:production
  update-type: version-update:semver-patch
...

Signed-off-by: dependabot[bot] <support@github.com>
2026-01-05 18:22:17 +01:00
dependabot[bot]
50f6773c82 chore(deps): bump codecov/codecov-action from 5.5.1 to 5.5.2
Bumps [codecov/codecov-action](https://github.com/codecov/codecov-action) from 5.5.1 to 5.5.2.
- [Release notes](https://github.com/codecov/codecov-action/releases)
- [Changelog](https://github.com/codecov/codecov-action/blob/main/CHANGELOG.md)
- [Commits](5a1091511a...671740ac38)

---
updated-dependencies:
- dependency-name: codecov/codecov-action
  dependency-version: 5.5.2
  dependency-type: direct:production
  update-type: version-update:semver-patch
...

Signed-off-by: dependabot[bot] <support@github.com>
2026-01-05 15:58:43 +01:00
dependabot[bot]
1eb8270812 chore(deps): bump peter-evans/create-pull-request from 7.0.9 to 8.0.0
Bumps [peter-evans/create-pull-request](https://github.com/peter-evans/create-pull-request) from 7.0.9 to 8.0.0.
- [Release notes](https://github.com/peter-evans/create-pull-request/releases)
- [Commits](84ae59a2cd...98357b18bf)

---
updated-dependencies:
- dependency-name: peter-evans/create-pull-request
  dependency-version: 8.0.0
  dependency-type: direct:production
  update-type: version-update:semver-major
...

Signed-off-by: dependabot[bot] <support@github.com>
2026-01-05 15:58:21 +01:00
Andrei Stoian
0fab6324b9 fix(gpu): memory sanitizer ci 2026-01-05 15:25:30 +01:00
David Testé
bb1c215951 chore(ci): fix naming on svg upload for backends comparison table
Comparison table generation is a special kind. There are no inputs
besides output filename. So if the regular name pattern is used
we'll get only underscores between the SHA and "tables" in the
artifact name.
2026-01-05 10:22:12 +01:00
Nicolas Sarlin
70a0021cbf chore: fix bincode dependency version 2026-01-02 18:57:32 +01:00
dependabot[bot]
36b6376cc4 chore(deps): bump zgosalvez/github-actions-ensure-sha-pinned-actions
Bumps [zgosalvez/github-actions-ensure-sha-pinned-actions](https://github.com/zgosalvez/github-actions-ensure-sha-pinned-actions) from 4.0.0 to 4.0.1.
- [Release notes](https://github.com/zgosalvez/github-actions-ensure-sha-pinned-actions/releases)
- [Commits](9e9574ef04...6124774845)

---
updated-dependencies:
- dependency-name: zgosalvez/github-actions-ensure-sha-pinned-actions
  dependency-version: 4.0.1
  dependency-type: direct:production
  update-type: version-update:semver-patch
...

Signed-off-by: dependabot[bot] <support@github.com>
2025-12-30 13:32:22 +01:00
dependabot[bot]
62d0d16f6d chore(deps): bump foundry-rs/foundry-toolchain from 1.5.0 to 1.6.0
Bumps [foundry-rs/foundry-toolchain](https://github.com/foundry-rs/foundry-toolchain) from 1.5.0 to 1.6.0.
- [Release notes](https://github.com/foundry-rs/foundry-toolchain/releases)
- [Changelog](https://github.com/foundry-rs/foundry-toolchain/blob/master/RELEASE.md)
- [Commits](50d5a8956f...8b0419c685)

---
updated-dependencies:
- dependency-name: foundry-rs/foundry-toolchain
  dependency-version: 1.6.0
  dependency-type: direct:production
  update-type: version-update:semver-minor
...

Signed-off-by: dependabot[bot] <support@github.com>
2025-12-30 13:32:14 +01:00
dependabot[bot]
c86deec683 chore(deps): bump actions/upload-artifact from 5.0.0 to 6.0.0
Bumps [actions/upload-artifact](https://github.com/actions/upload-artifact) from 5.0.0 to 6.0.0.
- [Release notes](https://github.com/actions/upload-artifact/releases)
- [Commits](330a01c490...b7c566a772)

---
updated-dependencies:
- dependency-name: actions/upload-artifact
  dependency-version: 6.0.0
  dependency-type: direct:production
  update-type: version-update:semver-major
...

Signed-off-by: dependabot[bot] <support@github.com>
2025-12-30 11:14:47 +01:00
dependabot[bot]
4d42425f4f chore(deps): bump actions/download-artifact from 6.0.0 to 7.0.0
Bumps [actions/download-artifact](https://github.com/actions/download-artifact) from 6.0.0 to 7.0.0.
- [Release notes](https://github.com/actions/download-artifact/releases)
- [Commits](018cc2cf5b...37930b1c2a)

---
updated-dependencies:
- dependency-name: actions/download-artifact
  dependency-version: 7.0.0
  dependency-type: direct:production
  update-type: version-update:semver-major
...

Signed-off-by: dependabot[bot] <support@github.com>
2025-12-30 11:13:33 +01:00
Guillermo Oyarzun
92df46f8f2 fix(gpu): return to 64 regs in multi-bit pbs 2025-12-23 11:51:00 +01:00
David Testé
effb7ada6d chore(ci): fix argument name passed to data_extractor 2025-12-18 18:09:34 +01:00
Agnes Leroy
49be544297 fix(gpu): fix cpu memory leak in expand and rerand 2025-12-18 16:33:23 +01:00
David Testé
23600eb8e1 chore(ci): split gpu documentation benchmarks execution
This is done to mitigate H100x8-SXM5 server scarcity.
2025-12-18 14:56:15 +01:00
Agnes Leroy
9708cc7fe9 chore(gpu): remove core crypto from valgrind run 2025-12-18 13:01:12 +01:00
dependabot[bot]
4cdfccb659 chore(deps): bump actions/setup-node from 6.0.0 to 6.1.0
Bumps [actions/setup-node](https://github.com/actions/setup-node) from 6.0.0 to 6.1.0.
- [Release notes](https://github.com/actions/setup-node/releases)
- [Commits](2028fbc5c2...395ad32622)

---
updated-dependencies:
- dependency-name: actions/setup-node
  dependency-version: 6.1.0
  dependency-type: direct:production
  update-type: version-update:semver-minor
...

Signed-off-by: dependabot[bot] <support@github.com>
2025-12-18 11:05:56 +01:00
dependabot[bot]
031c3fe34f chore(deps): bump actions/checkout from 6.0.0 to 6.0.1
Bumps [actions/checkout](https://github.com/actions/checkout) from 6.0.0 to 6.0.1.
- [Release notes](https://github.com/actions/checkout/releases)
- [Changelog](https://github.com/actions/checkout/blob/main/CHANGELOG.md)
- [Commits](1af3b93b68...8e8c483db8)

---
updated-dependencies:
- dependency-name: actions/checkout
  dependency-version: 6.0.1
  dependency-type: direct:production
  update-type: version-update:semver-patch
...

Signed-off-by: dependabot[bot] <support@github.com>
2025-12-18 11:05:47 +01:00
dependabot[bot]
ea99307cf5 chore(deps): bump actions/stale from 10.1.0 to 10.1.1
Bumps [actions/stale](https://github.com/actions/stale) from 10.1.0 to 10.1.1.
- [Release notes](https://github.com/actions/stale/releases)
- [Changelog](https://github.com/actions/stale/blob/main/CHANGELOG.md)
- [Commits](5f858e3efb...997185467f)

---
updated-dependencies:
- dependency-name: actions/stale
  dependency-version: 10.1.1
  dependency-type: direct:production
  update-type: version-update:semver-patch
...

Signed-off-by: dependabot[bot] <support@github.com>
2025-12-18 11:05:36 +01:00
Enzo Di Maria
ca2a79f1fb refactor(gpu): Threshold for multi-GPU with Classical PBS 2025-12-18 09:27:09 +01:00
Enzo Di Maria
0a59e86675 fix(gpu): Using tbc for classical 64 bits pbs on H100 2025-12-17 19:18:01 +01:00
Nicolas Sarlin
312ce494bf chore(zk): add 1 * 64 benches with production CRS 2025-12-17 15:06:37 +01:00
Nicolas Sarlin
5f2e7e31f1 chore(zk): align wasm bench and integer bench 2025-12-17 15:06:37 +01:00
Agnes Leroy
cfa53682ae fix(gpu): add missing sync before free in oprf 2025-12-16 09:42:11 +01:00
Agnes Leroy
006d6cc300 fix(gpu): fix some cpu memory leaks 2025-12-15 14:27:35 -03:00
David Testé
b950b551e6 chore(ci): update node version to 24.12
To be able to get npm version that allow trusted publishing
(>v11.5.1).
2025-12-15 16:08:29 +01:00
David Testé
95524966ca chore(ci): handle push to crates.io input in release workflow 2025-12-15 16:08:29 +01:00
Thomas Montaigu
d394af7f4d chore: bump dyn-stack to 0.13
Notable changes:
- StackReq methods no longer returns Result<StackReq, SizeOverflow>
  instead, StackReq contains the invalid state.
  Now, its when we create a PodBuffer that we can check/catch if the
  size req is invalid by catching errors when calling
  `PodBuffer::try_new`. Its also possible to manually check that
  `stack_req != StackReq::OVERFLOW`

- GlobalaPodBuffer is now PodBuffer
2025-12-15 10:02:17 +01:00
Andrei Stoian
78d1ce18c1 feat(gpu): support keyswitch 64/32 2025-12-12 22:01:49 +01:00
Arthur Meyre
14d49f0891 chore: add possibility to manually populate tfhe FFT plan cache 2025-12-12 19:06:47 +01:00
Nicolas Sarlin
e544dfc08e fix(integer): handle large string size in DataKind::num_blocks 2025-12-12 13:10:14 +01:00
Nicolas Sarlin
5891a4d78a fix(hl): handles empty compact lists 2025-12-12 13:10:14 +01:00
Nicolas Sarlin
f17cd9bd37 fix(integer): handle message mod 0 in num_blocks 2025-12-12 13:10:14 +01:00
Thomas Montaigu
c083eb826d fix(zk-pok): Check Modulus of deserialized Fp 2025-12-12 13:10:14 +01:00
Nicolas Sarlin
1479315725 fix(integer): handles num_blocks_per_integer is 0 in ct list upgrade 2025-12-12 13:10:14 +01:00
Nicolas Sarlin
b5e5058759 fix(core): handle lwe dim of 0 when computing ct list size 2025-12-12 13:10:14 +01:00
Nicolas Sarlin
d98033c71d fix(integer): check overflows when computing expected list size 2025-12-12 13:10:14 +01:00
Nicolas Sarlin
c7b869c956 fix(core): use saturating_* to convert from lwe dim and size 2025-12-12 13:10:14 +01:00
Nicolas Sarlin
50b76817c9 fix(shortint): use saturating_sub to get degree from message modulus 2025-12-12 13:10:14 +01:00
David Testé
238f7d51f6 chore(ci): fix data extraction on backends comparison for docs 2025-12-12 12:24:47 +01:00
Thomas Montaigu
aa49d141c7 feat: add MetaParameterFinder 2025-12-12 11:20:03 +01:00
Thomas Montaigu
be1de6ef2b chore: impl Versionize for MetaParameters 2025-12-12 11:20:03 +01:00
Guillermo Oyarzun
11579bd3d0 feat(gpu): create noise and pfail tests for pbs + ks + ms 2025-12-12 09:41:11 +01:00
Agnes Leroy
b7a706a3db chore(bench): remove constraint in pcc to not use trivial name in bench 2025-12-11 14:41:07 +01:00
Agnes Leroy
8e4bec0b2a chore(bench): modify whitepaper erc20 to match newest litepaper version 2025-12-11 14:41:07 +01:00
David Testé
641d4988d7 chore(ci): use run-name to distinguish benchmark runs
This would create a run name in the GitHub Actions tabs that will be based on the inputs provided rather than just displaying the workflow filename.
2025-12-11 13:32:46 +01:00
Arthur Meyre
403cabb70a chore: bump CSPRNG to 0.8.0 since MSRV was bumped 2025-12-11 13:12:36 +01:00
Arthur Meyre
63b46c3b99 chore: bump tfhe-versionable to 0.7 since the MSRV was changed 2025-12-11 13:12:36 +01:00
Arthur Meyre
a5aa3c366f chore: bump tfhe-hpu-backend 2025-12-11 13:12:36 +01:00
Arthur Meyre
5818b08f2c chore: bump tfhe-cuda-backend to 0.13.0 2025-12-11 13:12:36 +01:00
Arthur Meyre
de439ff6a1 chore: fix repo name in hpu README 2025-12-11 13:12:36 +01:00
Enzo Di Maria
cf969ff930 refactor(gpu): creating benchmarks for match_value 2025-12-11 12:01:43 +01:00
285 changed files with 8296 additions and 2918 deletions

View File

@@ -2,6 +2,8 @@
ignore = [
# Ignoring unmaintained 'paste' advisory as it is a widely used, low-risk build dependency.
"RUSTSEC-2024-0436",
# Ignoring unmaintained 'bincode' crate. Getting rid of it would be too complex on the short term.
"RUSTSEC-2025-0141",
]
[output]

View File

@@ -23,6 +23,8 @@ runs:
echo "${CMAKE_SCRIPT_SHA} cmake-${CMAKE_VERSION}-linux-x86_64.sh" > checksum
sha256sum -c checksum
sudo bash cmake-"${CMAKE_VERSION}"-linux-x86_64.sh --skip-license --prefix=/usr/ --exclude-subdir
sudo apt-get clean
sudo rm -rf /var/lib/apt/lists/*
sudo apt update
sudo apt remove -y unattended-upgrades
sudo apt install -y cmake-format libclang-dev

View File

@@ -66,7 +66,7 @@ jobs:
cancel-in-progress: ${{ github.ref != 'refs/heads/main' }}
steps:
- name: Checkout tfhe-rs
uses: actions/checkout@1af3b93b6815bc44a9784bd300feb67ff0d1eeb3
uses: actions/checkout@8e8c483db84b4bee98b60c0593521ed34d9990e8
with:
persist-credentials: 'true' # Needed to pull lfs data
token: ${{ env.CHECKOUT_TOKEN }}
@@ -80,7 +80,7 @@ jobs:
- name: Retrieve data from cache
id: retrieve-data-cache
uses: actions/cache/restore@0057852bfaa89a56745cba8c7296529d2fc39830 #v4.3.0
uses: actions/cache/restore@9255dc7a253b0ccc959486e2bca901246202afeb #v5.0.1
with:
path: |
utils/tfhe-backward-compat-data/**/*.cbor
@@ -109,7 +109,7 @@ jobs:
- name: Store data in cache
if: steps.retrieve-data-cache.outputs.cache-hit != 'true'
continue-on-error: true
uses: actions/cache/save@0057852bfaa89a56745cba8c7296529d2fc39830 #v4.3.0
uses: actions/cache/save@9255dc7a253b0ccc959486e2bca901246202afeb #v5.0.1
with:
path: |
utils/tfhe-backward-compat-data/**/*.cbor

View File

@@ -63,7 +63,7 @@ jobs:
any_file_changed: ${{ env.IS_PULL_REQUEST == 'false' || steps.aggregated-changes.outputs.any_changed }}
steps:
- name: Checkout tfhe-rs
uses: actions/checkout@1af3b93b6815bc44a9784bd300feb67ff0d1eeb3
uses: actions/checkout@8e8c483db84b4bee98b60c0593521ed34d9990e8
with:
fetch-depth: 0
persist-credentials: 'false'
@@ -71,7 +71,7 @@ jobs:
- name: Check for file changes
id: changed-files
uses: tj-actions/changed-files@24d32ffd492484c1d75e0c0b894501ddb9d30d62 # v47.0.0
uses: tj-actions/changed-files@e0021407031f5be11a464abee9a0776171c79891 # v47.0.1
with:
files_yaml: |
dependencies:
@@ -171,7 +171,7 @@ jobs:
runs-on: ${{ needs.setup-instance.outputs.runner-name }}
steps:
- name: Checkout tfhe-rs
uses: actions/checkout@1af3b93b6815bc44a9784bd300feb67ff0d1eeb3
uses: actions/checkout@8e8c483db84b4bee98b60c0593521ed34d9990e8
with:
persist-credentials: 'false'
token: ${{ env.CHECKOUT_TOKEN }}
@@ -219,7 +219,7 @@ jobs:
- name: Node cache restoration
id: node-cache
uses: actions/cache/restore@0057852bfaa89a56745cba8c7296529d2fc39830 #v4.3.0
uses: actions/cache/restore@9255dc7a253b0ccc959486e2bca901246202afeb #v5.0.1
with:
path: |
~/.nvm
@@ -232,7 +232,7 @@ jobs:
make install_node
- name: Node cache save
uses: actions/cache/save@0057852bfaa89a56745cba8c7296529d2fc39830 #v4.3.0
uses: actions/cache/save@9255dc7a253b0ccc959486e2bca901246202afeb #v5.0.1
if: steps.node-cache.outputs.cache-hit != 'true'
with:
path: |

View File

@@ -50,7 +50,7 @@ jobs:
steps.changed-files.outputs.integer_any_changed }}
steps:
- name: Checkout tfhe-rs
uses: actions/checkout@1af3b93b6815bc44a9784bd300feb67ff0d1eeb3
uses: actions/checkout@8e8c483db84b4bee98b60c0593521ed34d9990e8
with:
fetch-depth: 0
persist-credentials: 'false'
@@ -58,7 +58,7 @@ jobs:
- name: Check for file changes
id: changed-files
uses: tj-actions/changed-files@24d32ffd492484c1d75e0c0b894501ddb9d30d62 # v47.0.0
uses: tj-actions/changed-files@e0021407031f5be11a464abee9a0776171c79891 # v47.0.1
with:
files_yaml: |
integer:
@@ -112,7 +112,7 @@ jobs:
timeout-minutes: 480 # 8 hours
steps:
- name: Checkout tfhe-rs
uses: actions/checkout@1af3b93b6815bc44a9784bd300feb67ff0d1eeb3
uses: actions/checkout@8e8c483db84b4bee98b60c0593521ed34d9990e8
with:
persist-credentials: "false"
token: ${{ env.CHECKOUT_TOKEN }}

View File

@@ -60,7 +60,7 @@ jobs:
timeout-minutes: 1440
steps:
- name: Checkout tfhe-rs
uses: actions/checkout@1af3b93b6815bc44a9784bd300feb67ff0d1eeb3
uses: actions/checkout@8e8c483db84b4bee98b60c0593521ed34d9990e8
with:
persist-credentials: 'false'
token: ${{ env.CHECKOUT_TOKEN }}

View File

@@ -51,7 +51,7 @@ jobs:
steps.changed-files.outputs.integer_any_changed }}
steps:
- name: Checkout tfhe-rs
uses: actions/checkout@1af3b93b6815bc44a9784bd300feb67ff0d1eeb3
uses: actions/checkout@8e8c483db84b4bee98b60c0593521ed34d9990e8
with:
fetch-depth: 0
persist-credentials: 'false'
@@ -59,7 +59,7 @@ jobs:
- name: Check for file changes
id: changed-files
uses: tj-actions/changed-files@24d32ffd492484c1d75e0c0b894501ddb9d30d62 # v47.0.0
uses: tj-actions/changed-files@e0021407031f5be11a464abee9a0776171c79891 # v47.0.1
with:
files_yaml: |
integer:
@@ -112,7 +112,7 @@ jobs:
runs-on: ${{ needs.setup-instance.outputs.runner-name }}
steps:
- name: Checkout tfhe-rs
uses: actions/checkout@1af3b93b6815bc44a9784bd300feb67ff0d1eeb3
uses: actions/checkout@8e8c483db84b4bee98b60c0593521ed34d9990e8
with:
persist-credentials: "false"
token: ${{ env.CHECKOUT_TOKEN }}

View File

@@ -72,7 +72,7 @@ jobs:
any_file_changed: ${{ env.IS_PULL_REQUEST == 'false' || steps.aggregated-changes.outputs.any_changed }}
steps:
- name: Checkout tfhe-rs
uses: actions/checkout@1af3b93b6815bc44a9784bd300feb67ff0d1eeb3
uses: actions/checkout@8e8c483db84b4bee98b60c0593521ed34d9990e8
with:
fetch-depth: 0
persist-credentials: 'false'
@@ -80,7 +80,7 @@ jobs:
- name: Check for file changes
id: changed-files
uses: tj-actions/changed-files@24d32ffd492484c1d75e0c0b894501ddb9d30d62 # v47.0.0
uses: tj-actions/changed-files@e0021407031f5be11a464abee9a0776171c79891 # v47.0.1
with:
files_yaml: |
dependencies:
@@ -182,7 +182,7 @@ jobs:
runs-on: ${{ needs.setup-instance.outputs.runner-name }}
steps:
- name: Checkout tfhe-rs
uses: actions/checkout@1af3b93b6815bc44a9784bd300feb67ff0d1eeb3
uses: actions/checkout@8e8c483db84b4bee98b60c0593521ed34d9990e8
with:
persist-credentials: 'false'
token: ${{ env.CHECKOUT_TOKEN }}

View File

@@ -64,7 +64,7 @@ jobs:
runs-on: ${{ needs.setup-instance.outputs.runner-name }}
steps:
- name: Checkout tfhe-rs
uses: actions/checkout@1af3b93b6815bc44a9784bd300feb67ff0d1eeb3
uses: actions/checkout@8e8c483db84b4bee98b60c0593521ed34d9990e8
with:
persist-credentials: 'false'
token: ${{ env.CHECKOUT_TOKEN }}
@@ -80,7 +80,7 @@ jobs:
- name: Node cache restoration
id: node-cache
uses: actions/cache/restore@0057852bfaa89a56745cba8c7296529d2fc39830 #v4.3.0
uses: actions/cache/restore@9255dc7a253b0ccc959486e2bca901246202afeb #v5.0.1
with:
path: |
~/.nvm
@@ -93,7 +93,7 @@ jobs:
make install_node
- name: Node cache save
uses: actions/cache/save@0057852bfaa89a56745cba8c7296529d2fc39830 #v4.3.0
uses: actions/cache/save@9255dc7a253b0ccc959486e2bca901246202afeb #v5.0.1
if: steps.node-cache.outputs.cache-hit != 'true'
with:
path: |

View File

@@ -1,6 +1,8 @@
# Run benchmarks on an AWS instance and return parsed results to Slab CI bot.
name: benchmark_cpu
run-name: ${{ inputs.command }}::${{ inputs.bench_type}} (${{ inputs.op_flavor }}, ${{ inputs.precisions_set }}, ${{ inputs.params_type }})
on:
workflow_dispatch:
inputs:

View File

@@ -149,7 +149,7 @@ jobs:
params_type: ${{ fromJSON(needs.prepare-matrix.outputs.params_type) }}
steps:
- name: Checkout tfhe-rs repo with tags
uses: actions/checkout@1af3b93b6815bc44a9784bd300feb67ff0d1eeb3
uses: actions/checkout@8e8c483db84b4bee98b60c0593521ed34d9990e8
with:
fetch-depth: 0
persist-credentials: 'false'
@@ -223,13 +223,13 @@ jobs:
results_type: ${{ inputs.additional_results_type }}
- name: Upload parsed results artifact
uses: actions/upload-artifact@330a01c490aca151604b8cf639adc76d48f6c5d4
uses: actions/upload-artifact@b7c566a772e6b6bfb58ed0dc250532a479d7789f
with:
name: ${{ github.sha }}_${{ matrix.command }}_${{ matrix.op_flavor }}_${{ matrix.bench_type }}_${{ matrix.params_type }}
path: ${{ env.RESULTS_FILENAME }}
- name: Checkout Slab repo
uses: actions/checkout@1af3b93b6815bc44a9784bd300feb67ff0d1eeb3
uses: actions/checkout@8e8c483db84b4bee98b60c0593521ed34d9990e8
with:
repository: zama-ai/slab
path: slab

View File

@@ -49,7 +49,7 @@ jobs:
runs-on: ${{ needs.setup-instance.outputs.runner-name }}
steps:
- name: Checkout tfhe-rs repo with tags
uses: actions/checkout@1af3b93b6815bc44a9784bd300feb67ff0d1eeb3
uses: actions/checkout@8e8c483db84b4bee98b60c0593521ed34d9990e8
with:
fetch-depth: 0
persist-credentials: 'false'
@@ -99,13 +99,13 @@ jobs:
--append-results
- name: Upload parsed results artifact
uses: actions/upload-artifact@330a01c490aca151604b8cf639adc76d48f6c5d4
uses: actions/upload-artifact@b7c566a772e6b6bfb58ed0dc250532a479d7789f
with:
name: ${{ github.sha }}_ct_key_sizes
path: ${{ env.RESULTS_FILENAME }}
- name: Checkout Slab repo
uses: actions/checkout@1af3b93b6815bc44a9784bd300feb67ff0d1eeb3
uses: actions/checkout@8e8c483db84b4bee98b60c0593521ed34d9990e8
with:
repository: zama-ai/slab
path: slab

View File

@@ -8,8 +8,13 @@ on:
description: "Run CPU benchmarks"
type: boolean
default: true
run-gpu-benchmarks:
description: "Run GPU benchmarks"
# GPU benchmarks are split because of resource scarcity.
run-gpu-integer-benchmarks:
description: "Run GPU integer benchmarks"
type: boolean
default: true
run-gpu-core-crypto-benchmarks:
description: "Run GPU core-crypto benchmarks"
type: boolean
default: true
run-hpu-benchmarks:
@@ -52,7 +57,7 @@ jobs:
run-benchmarks-gpu-integer:
name: benchmark_documentation/run-benchmarks-gpu-integer
uses: ./.github/workflows/benchmark_gpu_common.yml
if: inputs.run-gpu-benchmarks
if: inputs.run-gpu-integer-benchmarks
with:
profile: multi-h100-sxm5
hardware_name: n3-H100-SXM5x8
@@ -113,7 +118,7 @@ jobs:
run-benchmarks-gpu-core-crypto:
name: benchmark_documentation/run-benchmarks-gpu-core-crypto
uses: ./.github/workflows/benchmark_gpu_common.yml
if: inputs.run-gpu-benchmarks
if: inputs.run-gpu-core-crypto-benchmarks
with:
profile: multi-h100-sxm5
hardware_name: n3-H100-SXM5x8
@@ -133,7 +138,7 @@ jobs:
generate-svgs-with-benchmarks-run:
name: benchmark-documentation/generate-svgs-with-benchmarks-run
if: ${{ always() &&
(inputs.run-cpu-benchmarks || inputs.run-gpu-benchmarks ||inputs.run-hpu-benchmarks) &&
(inputs.run-cpu-benchmarks || inputs.run-gpu-integer-benchmarks || inputs.run-gpu-core-crypto-benchmarks ||inputs.run-hpu-benchmarks) &&
inputs.generate-svgs }}
needs: [
run-benchmarks-cpu-integer, run-benchmarks-gpu-integer, run-benchmarks-hpu-integer,
@@ -143,7 +148,7 @@ jobs:
with:
time_span_days: 5
generate-cpu-svgs: ${{ inputs.run-cpu-benchmarks }}
generate-gpu-svgs: ${{ inputs.run-gpu-benchmarks }}
generate-gpu-svgs: ${{ inputs.run-gpu-integer-benchmarks || inputs.run-gpu-core-crypto-benchmarks }}
generate-hpu-svgs: ${{ inputs.run-hpu-benchmarks }}
secrets:
DATA_EXTRACTOR_DATABASE_USER: ${{ secrets.DATA_EXTRACTOR_DATABASE_USER }}
@@ -152,7 +157,7 @@ jobs:
generate-svgs-without-benchmarks-run:
name: benchmark-documentation/generate-svgs-without-benchmarks-run
if: ${{ !(inputs.run-cpu-benchmarks || inputs.run-gpu-benchmarks || inputs.run-hpu-benchmarks) &&
if: ${{ !(inputs.run-cpu-benchmarks || inputs.run-gpu-integer-benchmarks || inputs.run-gpu-core-crypto-benchmarks || inputs.run-hpu-benchmarks) &&
inputs.generate-svgs }}
uses: ./.github/workflows/generate_svgs.yml
with:
@@ -175,12 +180,12 @@ jobs:
PATH_TO_DOC_ASSETS: tfhe/docs/.gitbook/assets
steps:
- name: Checkout tfhe-rs
uses: actions/checkout@1af3b93b6815bc44a9784bd300feb67ff0d1eeb3
uses: actions/checkout@8e8c483db84b4bee98b60c0593521ed34d9990e8
with:
persist-credentials: 'false'
- name: Download SVG tables
uses: actions/download-artifact@018cc2cf5baa6db3ef3c5f8a56943fffe632ef53 # v6.0.0
uses: actions/download-artifact@37930b1c2abaa49bbe596cd826c3c89aef350131 # v7.0.0
with:
path: svg_tables
merge-multiple: 'true'
@@ -198,7 +203,7 @@ jobs:
echo "date=$(date '+%g_%m_%d_%Hh%Mm%Ss')" >> "${GITHUB_OUTPUT}"
- name: Create pull-request
uses: peter-evans/create-pull-request@84ae59a2cdc2258d6fa0732dd66352dddae2a412 # v7.0.9
uses: peter-evans/create-pull-request@98357b18bf14b5342f975ff684046ec3b2a07725 # v8.0.0
with:
sign-commits: true # Commit will be signed by github-actions bot
add-paths: ${{ env.PATH_TO_DOC_ASSETS }}/*.svg

View File

@@ -1,6 +1,8 @@
# Run CUDA benchmarks on a Hyperstack VM and return parsed results to Slab CI bot.
name: benchmark_gpu
run-name: ${{ inputs.command }}::${{ inputs.bench_type}} (${{ inputs.profile }}, ${{ inputs.op_flavor }}, ${{ inputs.precisions_set }}, ${{ inputs.params_type }})
on:
workflow_dispatch:
inputs:

View File

@@ -40,7 +40,7 @@ jobs:
timeout-minutes: 1440 # 24 hours
steps:
- name: Checkout tfhe-rs
uses: actions/checkout@1af3b93b6815bc44a9784bd300feb67ff0d1eeb3
uses: actions/checkout@8e8c483db84b4bee98b60c0593521ed34d9990e8
with:
fetch-depth: 0
persist-credentials: 'false'
@@ -63,7 +63,7 @@ jobs:
toolchain: nightly
- name: Checkout Slab repo
uses: actions/checkout@1af3b93b6815bc44a9784bd300feb67ff0d1eeb3
uses: actions/checkout@8e8c483db84b4bee98b60c0593521ed34d9990e8
with:
repository: zama-ai/slab
path: slab
@@ -89,7 +89,7 @@ jobs:
REF_NAME: ${{ github.ref_name }}
- name: Upload parsed results artifact
uses: actions/upload-artifact@330a01c490aca151604b8cf639adc76d48f6c5d4
uses: actions/upload-artifact@b7c566a772e6b6bfb58ed0dc250532a479d7789f
with:
name: ${{ github.sha }}_integer_multi_bit_gpu_default
path: ${{ env.RESULTS_FILENAME }}
@@ -123,7 +123,7 @@ jobs:
steps:
- name: Checkout tfhe-rs
uses: actions/checkout@1af3b93b6815bc44a9784bd300feb67ff0d1eeb3
uses: actions/checkout@8e8c483db84b4bee98b60c0593521ed34d9990e8
with:
fetch-depth: 0
persist-credentials: 'false'
@@ -146,7 +146,7 @@ jobs:
toolchain: nightly
- name: Checkout Slab repo
uses: actions/checkout@1af3b93b6815bc44a9784bd300feb67ff0d1eeb3
uses: actions/checkout@8e8c483db84b4bee98b60c0593521ed34d9990e8
with:
repository: zama-ai/slab
path: slab
@@ -173,7 +173,7 @@ jobs:
REF_NAME: ${{ github.ref_name }}
- name: Upload parsed results artifact
uses: actions/upload-artifact@330a01c490aca151604b8cf639adc76d48f6c5d4
uses: actions/upload-artifact@b7c566a772e6b6bfb58ed0dc250532a479d7789f
with:
name: ${{ github.sha }}_core_crypto
path: ${{ env.RESULTS_FILENAME }}

View File

@@ -175,7 +175,7 @@ jobs:
gcc: 11
steps:
- name: Checkout tfhe-rs repo
uses: actions/checkout@1af3b93b6815bc44a9784bd300feb67ff0d1eeb3
uses: actions/checkout@8e8c483db84b4bee98b60c0593521ed34d9990e8
with:
fetch-depth: 0
persist-credentials: 'false'
@@ -209,7 +209,7 @@ jobs:
CUDA_PATH: /usr/local/cuda-${{ matrix.cuda }}
steps:
- name: Checkout tfhe-rs repo with tags
uses: actions/checkout@1af3b93b6815bc44a9784bd300feb67ff0d1eeb3
uses: actions/checkout@8e8c483db84b4bee98b60c0593521ed34d9990e8
with:
fetch-depth: 0
persist-credentials: 'false'
@@ -281,13 +281,13 @@ jobs:
BENCH_TYPE: ${{ matrix.bench_type }}
- name: Upload parsed results artifact
uses: actions/upload-artifact@330a01c490aca151604b8cf639adc76d48f6c5d4
uses: actions/upload-artifact@b7c566a772e6b6bfb58ed0dc250532a479d7789f
with:
name: ${{ github.sha }}_${{ matrix.command }}_${{ matrix.op_flavor }}_${{ inputs.profile }}_${{ matrix.bench_type }}_${{ matrix.params_type }}
path: ${{ env.RESULTS_FILENAME }}
- name: Checkout Slab repo
uses: actions/checkout@1af3b93b6815bc44a9784bd300feb67ff0d1eeb3
uses: actions/checkout@8e8c483db84b4bee98b60c0593521ed34d9990e8
with:
repository: zama-ai/slab
path: slab

View File

@@ -130,7 +130,7 @@ jobs:
git lfs install
- name: Checkout tfhe-rs
uses: actions/checkout@1af3b93b6815bc44a9784bd300feb67ff0d1eeb3 # v6.0.0
uses: actions/checkout@8e8c483db84b4bee98b60c0593521ed34d9990e8 # v6.0.1
with:
path: tfhe-rs
persist-credentials: false
@@ -141,7 +141,7 @@ jobs:
ls
- name: Checkout fhevm
uses: actions/checkout@1af3b93b6815bc44a9784bd300feb67ff0d1eeb3 # v6.0.0
uses: actions/checkout@8e8c483db84b4bee98b60c0593521ed34d9990e8 # v6.0.1
with:
repository: zama-ai/fhevm
persist-credentials: 'false'
@@ -192,10 +192,10 @@ jobs:
cargo install sqlx-cli
- name: Install foundry
uses: foundry-rs/foundry-toolchain@50d5a8956f2e319df19e6b57539d7e2acb9f8c1e
uses: foundry-rs/foundry-toolchain@8b0419c685ef46cb79ec93fbdc131174afceb730
- name: Cache cargo
uses: actions/cache@0057852bfaa89a56745cba8c7296529d2fc39830 # v4.3.0
uses: actions/cache@9255dc7a253b0ccc959486e2bca901246202afeb # v5.0.1
with:
path: |
~/.cargo/registry
@@ -223,7 +223,7 @@ jobs:
working-directory: fhevm/coprocessor/fhevm-engine/tfhe-worker
- name: Use Node.js
uses: actions/setup-node@2028fbc5c25fe9cf00d9f06a71cc4710d4507903 # v6.0.0
uses: actions/setup-node@395ad3262231945c25e8478fd5baf05154b1d79f # v6.1.0
with:
node-version: 20.x
@@ -262,7 +262,7 @@ jobs:
- name: Upload profile artifact
env:
REPORT_NAME: ${{ steps.nsys_profile_name.outputs.profile }}
uses: actions/upload-artifact@330a01c490aca151604b8cf639adc76d48f6c5d4
uses: actions/upload-artifact@b7c566a772e6b6bfb58ed0dc250532a479d7789f
with:
name: ${{ env.REPORT_NAME }}
path: fhevm/coprocessor/fhevm-engine/tfhe-worker/${{ env.REPORT_NAME }}
@@ -293,13 +293,13 @@ jobs:
working-directory: fhevm/
- name: Upload parsed results artifact
uses: actions/upload-artifact@330a01c490aca151604b8cf639adc76d48f6c5d4
uses: actions/upload-artifact@b7c566a772e6b6bfb58ed0dc250532a479d7789f
with:
name: ${COMMIT_SHA}_${BENCHMARKS}_${{ needs.parse-inputs.outputs.profile }}
path: fhevm/$${{ env.RESULTS_FILENAME }}
- name: Checkout Slab repo
uses: actions/checkout@1af3b93b6815bc44a9784bd300feb67ff0d1eeb3
uses: actions/checkout@8e8c483db84b4bee98b60c0593521ed34d9990e8
with:
repository: zama-ai/slab
path: slab

View File

@@ -1,6 +1,8 @@
# Run benchmarks on a permanent HPU instance and return parsed results to Slab CI bot.
name: benchmark_hpu
run-name: ${{ inputs.command }}::${{ inputs.bench_type}} (${{ inputs.op_flavor }}, ${{ inputs.precisions_set }})
on:
workflow_dispatch:
inputs:

View File

@@ -126,7 +126,7 @@ jobs:
ssh-private-key: ${{ secrets.SSH_PRIVATE_KEY }}
- name: Checkout tfhe-rs repo with tags
uses: actions/checkout@1af3b93b6815bc44a9784bd300feb67ff0d1eeb3
uses: actions/checkout@8e8c483db84b4bee98b60c0593521ed34d9990e8
with:
fetch-depth: 0
persist-credentials: 'false'
@@ -185,13 +185,13 @@ jobs:
BENCH_TYPE: ${{ matrix.bench_type }}
- name: Upload parsed results artifact
uses: actions/upload-artifact@330a01c490aca151604b8cf639adc76d48f6c5d4
uses: actions/upload-artifact@b7c566a772e6b6bfb58ed0dc250532a479d7789f
with:
name: ${{ github.sha }}_${{ matrix.bench_type }}_integer_benchmarks
path: ${{ env.RESULTS_FILENAME }}
- name: Checkout Slab repo
uses: actions/checkout@1af3b93b6815bc44a9784bd300feb67ff0d1eeb3
uses: actions/checkout@8e8c483db84b4bee98b60c0593521ed34d9990e8
with:
repository: zama-ai/slab
path: slab

View File

@@ -50,7 +50,7 @@ jobs:
pull-requests: write # Needed to write a comment in a pull-request
steps:
- name: Checkout tfhe-rs repo
uses: actions/checkout@1af3b93b6815bc44a9784bd300feb67ff0d1eeb3
uses: actions/checkout@8e8c483db84b4bee98b60c0593521ed34d9990e8
with:
persist-credentials: 'false'
token: ${{ secrets.REPO_CHECKOUT_TOKEN }}
@@ -164,7 +164,7 @@ jobs:
gcc: 11
steps:
- name: Checkout tfhe-rs repo
uses: actions/checkout@1af3b93b6815bc44a9784bd300feb67ff0d1eeb3
uses: actions/checkout@8e8c483db84b4bee98b60c0593521ed34d9990e8
with:
persist-credentials: 'false'
token: ${{ secrets.REPO_CHECKOUT_TOKEN }}
@@ -191,7 +191,7 @@ jobs:
command: ${{ fromJson(needs.prepare-benchmarks.outputs.commands) }}
steps:
- name: Checkout tfhe-rs repo
uses: actions/checkout@1af3b93b6815bc44a9784bd300feb67ff0d1eeb3
uses: actions/checkout@8e8c483db84b4bee98b60c0593521ed34d9990e8
with:
fetch-depth: 0 # Needed to get commit hash
persist-credentials: 'false'
@@ -245,7 +245,7 @@ jobs:
toolchain: nightly
- name: Checkout Slab repo
uses: actions/checkout@1af3b93b6815bc44a9784bd300feb67ff0d1eeb3
uses: actions/checkout@8e8c483db84b4bee98b60c0593521ed34d9990e8
with:
repository: zama-ai/slab
path: slab
@@ -280,7 +280,7 @@ jobs:
BENCH_TYPE: ${{ env.__TFHE_RS_BENCH_TYPE }}
- name: Upload parsed results artifact
uses: actions/upload-artifact@330a01c490aca151604b8cf639adc76d48f6c5d4
uses: actions/upload-artifact@b7c566a772e6b6bfb58ed0dc250532a479d7789f
with:
name: ${{ github.sha }}_regression_${{ env.RESULTS_FILE_SHA }} # RESULT_FILE_SHA is needed to avoid collision between matrix.command runs
path: ${{ env.RESULTS_FILENAME }}
@@ -305,7 +305,7 @@ jobs:
REF_NAME: ${{ github.head_ref || github.ref_name }}
steps:
- name: Checkout tfhe-rs repo
uses: actions/checkout@1af3b93b6815bc44a9784bd300feb67ff0d1eeb3
uses: actions/checkout@8e8c483db84b4bee98b60c0593521ed34d9990e8
with:
persist-credentials: 'false'
token: ${{ secrets.REPO_CHECKOUT_TOKEN }}

View File

@@ -55,7 +55,7 @@ jobs:
runs-on: ${{ needs.setup-instance.outputs.runner-name }}
steps:
- name: Checkout tfhe-rs repo with tags
uses: actions/checkout@1af3b93b6815bc44a9784bd300feb67ff0d1eeb3
uses: actions/checkout@8e8c483db84b4bee98b60c0593521ed34d9990e8
with:
fetch-depth: 0
persist-credentials: 'false'
@@ -96,13 +96,13 @@ jobs:
REF_NAME: ${{ github.ref_name }}
- name: Upload parsed results artifact
uses: actions/upload-artifact@330a01c490aca151604b8cf639adc76d48f6c5d4
uses: actions/upload-artifact@b7c566a772e6b6bfb58ed0dc250532a479d7789f
with:
name: ${{ github.sha }}_fft
path: ${{ env.RESULTS_FILENAME }}
- name: Checkout Slab repo
uses: actions/checkout@1af3b93b6815bc44a9784bd300feb67ff0d1eeb3
uses: actions/checkout@8e8c483db84b4bee98b60c0593521ed34d9990e8
with:
repository: zama-ai/slab
path: slab

View File

@@ -55,7 +55,7 @@ jobs:
runs-on: ${{ needs.setup-instance.outputs.runner-name }}
steps:
- name: Checkout tfhe-rs repo with tags
uses: actions/checkout@1af3b93b6815bc44a9784bd300feb67ff0d1eeb3
uses: actions/checkout@8e8c483db84b4bee98b60c0593521ed34d9990e8
with:
fetch-depth: 0
persist-credentials: 'false'
@@ -96,13 +96,13 @@ jobs:
REF_NAME: ${{ github.ref_name }}
- name: Upload parsed results artifact
uses: actions/upload-artifact@330a01c490aca151604b8cf639adc76d48f6c5d4
uses: actions/upload-artifact@b7c566a772e6b6bfb58ed0dc250532a479d7789f
with:
name: ${{ github.sha }}_ntt
path: ${{ env.RESULTS_FILENAME }}
- name: Checkout Slab repo
uses: actions/checkout@1af3b93b6815bc44a9784bd300feb67ff0d1eeb3
uses: actions/checkout@8e8c483db84b4bee98b60c0593521ed34d9990e8
with:
repository: zama-ai/slab
path: slab

View File

@@ -39,7 +39,7 @@ jobs:
wasm_bench: ${{ steps.changed-files.outputs.wasm_bench_any_changed }}
steps:
- name: Checkout tfhe-rs
uses: actions/checkout@1af3b93b6815bc44a9784bd300feb67ff0d1eeb3
uses: actions/checkout@8e8c483db84b4bee98b60c0593521ed34d9990e8
with:
fetch-depth: 0
persist-credentials: 'false'
@@ -47,7 +47,7 @@ jobs:
- name: Check for file changes
id: changed-files
uses: tj-actions/changed-files@24d32ffd492484c1d75e0c0b894501ddb9d30d62 # v47.0.0
uses: tj-actions/changed-files@e0021407031f5be11a464abee9a0776171c79891 # v47.0.1
with:
files_yaml: |
wasm_bench:
@@ -91,7 +91,7 @@ jobs:
browser: [ chrome, firefox ]
steps:
- name: Checkout tfhe-rs repo with tags
uses: actions/checkout@1af3b93b6815bc44a9784bd300feb67ff0d1eeb3
uses: actions/checkout@8e8c483db84b4bee98b60c0593521ed34d9990e8
with:
fetch-depth: 0
persist-credentials: 'false'
@@ -119,7 +119,7 @@ jobs:
- name: Node cache restoration
id: node-cache
uses: actions/cache/restore@0057852bfaa89a56745cba8c7296529d2fc39830 #v4.3.0
uses: actions/cache/restore@9255dc7a253b0ccc959486e2bca901246202afeb #v5.0.1
with:
path: |
~/.nvm
@@ -132,7 +132,7 @@ jobs:
make install_node
- name: Node cache save
uses: actions/cache/save@0057852bfaa89a56745cba8c7296529d2fc39830 #v4.3.0
uses: actions/cache/save@9255dc7a253b0ccc959486e2bca901246202afeb #v5.0.1
if: steps.node-cache.outputs.cache-hit != 'true'
with:
path: |
@@ -153,6 +153,12 @@ jobs:
env:
BROWSER: ${{ matrix.browser }}
- name: Run benchmarks (unsafe coop)
run: |
make bench_web_js_api_unsafe_coop_"${BROWSER}"_ci
env:
BROWSER: ${{ matrix.browser }}
- name: Parse results
run: |
make parse_wasm_benchmarks
@@ -169,13 +175,13 @@ jobs:
REF_NAME: ${{ github.ref_name }}
- name: Upload parsed results artifact
uses: actions/upload-artifact@330a01c490aca151604b8cf639adc76d48f6c5d4
uses: actions/upload-artifact@b7c566a772e6b6bfb58ed0dc250532a479d7789f
with:
name: ${{ github.sha }}_wasm_${{ matrix.browser }}
path: ${{ env.RESULTS_FILENAME }}
- name: Checkout Slab repo
uses: actions/checkout@1af3b93b6815bc44a9784bd300feb67ff0d1eeb3
uses: actions/checkout@8e8c483db84b4bee98b60c0593521ed34d9990e8
with:
repository: zama-ai/slab
path: slab

View File

@@ -26,7 +26,7 @@ jobs:
name: cargo_audit/audit
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@1af3b93b6815bc44a9784bd300feb67ff0d1eeb3
- uses: actions/checkout@8e8c483db84b4bee98b60c0593521ed34d9990e8
with:
persist-credentials: 'false'
token: ${{ env.CHECKOUT_TOKEN }}

View File

@@ -24,7 +24,7 @@ jobs:
outputs:
matrix_command: ${{ steps.set-pcc-commands-matrix.outputs.commands }}
steps:
- uses: actions/checkout@1af3b93b6815bc44a9784bd300feb67ff0d1eeb3
- uses: actions/checkout@8e8c483db84b4bee98b60c0593521ed34d9990e8
with:
persist-credentials: "false"
token: ${{ env.CHECKOUT_TOKEN }}

View File

@@ -140,7 +140,7 @@ jobs:
result: ${{ steps.set_builds_result.outputs.result }}
steps:
- name: Checkout tfhe-rs repo
uses: actions/checkout@1af3b93b6815bc44a9784bd300feb67ff0d1eeb3
uses: actions/checkout@8e8c483db84b4bee98b60c0593521ed34d9990e8
with:
persist-credentials: 'false'
token: ${{ env.CHECKOUT_TOKEN }}

View File

@@ -26,7 +26,7 @@ jobs:
fail-fast: false
steps:
- uses: actions/checkout@1af3b93b6815bc44a9784bd300feb67ff0d1eeb3
- uses: actions/checkout@8e8c483db84b4bee98b60c0593521ed34d9990e8
with:
persist-credentials: 'false'
token: ${{ env.CHECKOUT_TOKEN }}

View File

@@ -24,7 +24,7 @@ jobs:
os: [ubuntu-latest, macos-latest, windows-latest]
fail-fast: false
steps:
- uses: actions/checkout@1af3b93b6815bc44a9784bd300feb67ff0d1eeb3
- uses: actions/checkout@8e8c483db84b4bee98b60c0593521ed34d9990e8
with:
persist-credentials: 'false'
token: ${{ env.CHECKOUT_TOKEN }}

View File

@@ -29,7 +29,7 @@ jobs:
fft_test: ${{ env.IS_PULL_REQUEST == 'false' || steps.changed-files.outputs.fft_any_changed }}
steps:
- name: Checkout tfhe-rs
uses: actions/checkout@1af3b93b6815bc44a9784bd300feb67ff0d1eeb3
uses: actions/checkout@8e8c483db84b4bee98b60c0593521ed34d9990e8
with:
fetch-depth: 0
persist-credentials: 'false'
@@ -37,7 +37,7 @@ jobs:
- name: Check for file changes
id: changed-files
uses: tj-actions/changed-files@24d32ffd492484c1d75e0c0b894501ddb9d30d62 # v47.0.0
uses: tj-actions/changed-files@e0021407031f5be11a464abee9a0776171c79891 # v47.0.1
with:
files_yaml: |
fft:
@@ -56,7 +56,7 @@ jobs:
runner_type: [ ubuntu-latest, macos-latest, windows-latest ]
fail-fast: false
steps:
- uses: actions/checkout@1af3b93b6815bc44a9784bd300feb67ff0d1eeb3
- uses: actions/checkout@8e8c483db84b4bee98b60c0593521ed34d9990e8
with:
persist-credentials: 'false'
token: ${{ env.CHECKOUT_TOKEN }}
@@ -92,7 +92,7 @@ jobs:
if: needs.should-run.outputs.fft_test == 'true'
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@1af3b93b6815bc44a9784bd300feb67ff0d1eeb3
- uses: actions/checkout@8e8c483db84b4bee98b60c0593521ed34d9990e8
with:
persist-credentials: 'false'
token: ${{ env.CHECKOUT_TOKEN }}

View File

@@ -31,7 +31,7 @@ jobs:
ntt_test: ${{ env.IS_PULL_REQUEST == 'false' || steps.changed-files.outputs.ntt_any_changed }}
steps:
- name: Checkout tfhe-rs
uses: actions/checkout@1af3b93b6815bc44a9784bd300feb67ff0d1eeb3
uses: actions/checkout@8e8c483db84b4bee98b60c0593521ed34d9990e8
with:
fetch-depth: 0
persist-credentials: "false"
@@ -39,7 +39,7 @@ jobs:
- name: Check for file changes
id: changed-files
uses: tj-actions/changed-files@24d32ffd492484c1d75e0c0b894501ddb9d30d62 # v47.0.0
uses: tj-actions/changed-files@e0021407031f5be11a464abee9a0776171c79891 # v47.0.1
with:
files_yaml: |
ntt:
@@ -87,7 +87,7 @@ jobs:
os: ${{fromJson(needs.setup-instance.outputs.matrix_os)}}
fail-fast: false
steps:
- uses: actions/checkout@1af3b93b6815bc44a9784bd300feb67ff0d1eeb3
- uses: actions/checkout@8e8c483db84b4bee98b60c0593521ed34d9990e8
with:
persist-credentials: "false"
token: ${{ env.CHECKOUT_TOKEN }}

View File

@@ -20,7 +20,7 @@ jobs:
runs-on: ubuntu-latest
steps:
- name: Checkout tfhe-rs
uses: actions/checkout@1af3b93b6815bc44a9784bd300feb67ff0d1eeb3
uses: actions/checkout@8e8c483db84b4bee98b60c0593521ed34d9990e8
with:
persist-credentials: 'false'
token: ${{ env.CHECKOUT_TOKEN }}
@@ -50,7 +50,7 @@ jobs:
version: ${{ steps.get_zizmor.outputs.version }}
- name: Ensure SHA pinned actions
uses: zgosalvez/github-actions-ensure-sha-pinned-actions@9e9574ef04ea69da568d6249bd69539ccc704e74 # v4.0.0
uses: zgosalvez/github-actions-ensure-sha-pinned-actions@6124774845927d14c601359ab8138699fa5b70c3 # v4.0.1
with:
allowlist: |
slsa-framework/slsa-github-generator

View File

@@ -50,7 +50,7 @@ jobs:
timeout-minutes: 5760 # 4 days
steps:
- name: Checkout tfhe-rs
uses: actions/checkout@1af3b93b6815bc44a9784bd300feb67ff0d1eeb3
uses: actions/checkout@8e8c483db84b4bee98b60c0593521ed34d9990e8
with:
persist-credentials: 'false'
token: ${{ env.CHECKOUT_TOKEN }}
@@ -62,7 +62,7 @@ jobs:
- name: Check for file changes
id: changed-files
uses: tj-actions/changed-files@24d32ffd492484c1d75e0c0b894501ddb9d30d62 # v47.0.0
uses: tj-actions/changed-files@e0021407031f5be11a464abee9a0776171c79891 # v47.0.1
with:
files_yaml: |
tfhe:
@@ -92,7 +92,7 @@ jobs:
make test_shortint_cov
- name: Upload tfhe coverage to Codecov
uses: codecov/codecov-action@5a1091511ad55cbe89839c7260b706298ca349f7
uses: codecov/codecov-action@671740ac38dd9b0130fbe1cec585b89eea48d3de
if: steps.changed-files.outputs.tfhe_any_changed == 'true'
with:
token: ${{ secrets.CODECOV_TOKEN }}
@@ -106,7 +106,7 @@ jobs:
make test_integer_cov
- name: Upload tfhe coverage to Codecov
uses: codecov/codecov-action@5a1091511ad55cbe89839c7260b706298ca349f7
uses: codecov/codecov-action@671740ac38dd9b0130fbe1cec585b89eea48d3de
if: steps.changed-files.outputs.tfhe_any_changed == 'true'
with:
token: ${{ secrets.CODECOV_TOKEN }}

View File

@@ -62,7 +62,7 @@ jobs:
runs-on: ${{ needs.setup-instance.outputs.runner-name }}
steps:
- name: Checkout tfhe-rs
uses: actions/checkout@1af3b93b6815bc44a9784bd300feb67ff0d1eeb3
uses: actions/checkout@8e8c483db84b4bee98b60c0593521ed34d9990e8
with:
persist-credentials: 'false'
token: ${{ env.CHECKOUT_TOKEN }}

View File

@@ -43,7 +43,7 @@ jobs:
runs-on: ubuntu-latest
steps:
- name: Checkout tfhe-rs
uses: actions/checkout@1af3b93b6815bc44a9784bd300feb67ff0d1eeb3
uses: actions/checkout@8e8c483db84b4bee98b60c0593521ed34d9990e8
with:
persist-credentials: 'false'
@@ -75,13 +75,22 @@ jobs:
DATA_EXTRACTOR_DATABASE_HOST: ${{ secrets.DATA_EXTRACTOR_DATABASE_HOST }}
DATA_EXTRACTOR_DATABASE_PASSWORD: ${{ secrets.DATA_EXTRACTOR_DATABASE_PASSWORD }}
- name: Upload tables
if: inputs.backend_comparison == false
uses: actions/upload-artifact@b7c566a772e6b6bfb58ed0dc250532a479d7789f
with:
name: ${{ github.sha }}_${{ inputs.backend }}_${{ inputs.layer }}_${{ inputs.pbs_kind }}_${{ inputs.bench_type }}_tables
# This will upload all the file generated
path: ${{ inputs.output_filename }}*.svg
retention-days: 60
- name: Produce backends comparison table from database
if: inputs.backend_comparison == true
run: |
python3 -m pip install -r ci/data_extractor/requirements.txt
python3 ci/data_extractor/src/data_extractor.py "${OUTPUT_FILENAME}" \
--generate-svg \
--backend-comparison\
--backends-comparison \
--time-span-days "${TIME_SPAN}"
env:
OUTPUT_FILENAME: ${{ inputs.output_filename }}
@@ -90,10 +99,11 @@ jobs:
DATA_EXTRACTOR_DATABASE_HOST: ${{ secrets.DATA_EXTRACTOR_DATABASE_HOST }}
DATA_EXTRACTOR_DATABASE_PASSWORD: ${{ secrets.DATA_EXTRACTOR_DATABASE_PASSWORD }}
- name: Upload tables
uses: actions/upload-artifact@330a01c490aca151604b8cf639adc76d48f6c5d4
- name: Upload comparison tables
if: inputs.backend_comparison == true
uses: actions/upload-artifact@b7c566a772e6b6bfb58ed0dc250532a479d7789f
with:
name: ${{ github.sha }}_${{ inputs.backend }}_${{ inputs.layer }}_${{ inputs.pbs_kind }}_${{ inputs.bench_type }}_tables
name: ${{ github.sha }}_backends_comparison_tables
# This will upload all the file generated
path: ${{ inputs.output_filename }}*.svg
retention-days: 60

View File

@@ -41,7 +41,7 @@ jobs:
steps:
- name: Checkout tfhe-rs
uses: actions/checkout@1af3b93b6815bc44a9784bd300feb67ff0d1eeb3
uses: actions/checkout@8e8c483db84b4bee98b60c0593521ed34d9990e8
with:
persist-credentials: 'false'
token: ${{ env.CHECKOUT_TOKEN }}

View File

@@ -23,8 +23,8 @@ on:
# Allows you to run this workflow manually from the Actions tab as an alternative.
workflow_dispatch:
schedule:
# every 3 months
- cron: "0 0 1 */3 *"
# every month
- cron: "0 0 1 * *"
permissions:
contents: read
@@ -50,7 +50,7 @@ jobs:
slab-url: ${{ secrets.SLAB_BASE_URL }}
job-secret: ${{ secrets.JOB_SECRET }}
backend: hyperstack
profile: gpu-test
profile: single-h100
# This instance will be spawned especially for pull-request from forked repository
- name: Start GitHub instance
@@ -79,7 +79,7 @@ jobs:
gcc: 11
steps:
- name: Checkout tfhe-rs
uses: actions/checkout@1af3b93b6815bc44a9784bd300feb67ff0d1eeb3
uses: actions/checkout@8e8c483db84b4bee98b60c0593521ed34d9990e8
with:
persist-credentials: 'false'
token: ${{ env.CHECKOUT_TOKEN }}

View File

@@ -40,7 +40,7 @@ jobs:
gpu_test: ${{ env.IS_PULL_REQUEST == 'false' || steps.changed-files.outputs.gpu_any_changed }}
steps:
- name: Checkout tfhe-rs
uses: actions/checkout@1af3b93b6815bc44a9784bd300feb67ff0d1eeb3
uses: actions/checkout@8e8c483db84b4bee98b60c0593521ed34d9990e8
with:
fetch-depth: 0
persist-credentials: 'false'
@@ -48,7 +48,7 @@ jobs:
- name: Check for file changes
id: changed-files
uses: tj-actions/changed-files@24d32ffd492484c1d75e0c0b894501ddb9d30d62 # v47.0.0
uses: tj-actions/changed-files@e0021407031f5be11a464abee9a0776171c79891 # v47.0.1
with:
files_yaml: |
gpu:
@@ -129,7 +129,7 @@ jobs:
gcc: 11
steps:
- name: Checkout tfhe-rs
uses: actions/checkout@1af3b93b6815bc44a9784bd300feb67ff0d1eeb3
uses: actions/checkout@8e8c483db84b4bee98b60c0593521ed34d9990e8
with:
persist-credentials: 'false'
token: ${{ env.CHECKOUT_TOKEN }}

View File

@@ -39,7 +39,7 @@ jobs:
gpu_test: ${{ env.IS_PULL_REQUEST == 'false' || steps.changed-files.outputs.gpu_any_changed }}
steps:
- name: Checkout tfhe-rs
uses: actions/checkout@1af3b93b6815bc44a9784bd300feb67ff0d1eeb3
uses: actions/checkout@8e8c483db84b4bee98b60c0593521ed34d9990e8
with:
fetch-depth: 0
persist-credentials: 'false'
@@ -47,7 +47,7 @@ jobs:
- name: Check for file changes
id: changed-files
uses: tj-actions/changed-files@24d32ffd492484c1d75e0c0b894501ddb9d30d62 # v47.0.0
uses: tj-actions/changed-files@e0021407031f5be11a464abee9a0776171c79891 # v47.0.1
with:
files_yaml: |
gpu:
@@ -114,7 +114,7 @@ jobs:
gcc: 11
steps:
- name: Checkout tfhe-rs
uses: actions/checkout@1af3b93b6815bc44a9784bd300feb67ff0d1eeb3
uses: actions/checkout@8e8c483db84b4bee98b60c0593521ed34d9990e8
with:
persist-credentials: 'false'
token: ${{ env.CHECKOUT_TOKEN }}

View File

@@ -68,7 +68,7 @@ jobs:
gcc: 11
steps:
- name: Checkout tfhe-rs
uses: actions/checkout@1af3b93b6815bc44a9784bd300feb67ff0d1eeb3
uses: actions/checkout@8e8c483db84b4bee98b60c0593521ed34d9990e8
with:
persist-credentials: 'false'
token: ${{ secrets.REPO_CHECKOUT_TOKEN }}

View File

@@ -40,7 +40,7 @@ jobs:
gpu_test: ${{ env.IS_PULL_REQUEST == 'false' || steps.changed-files.outputs.gpu_any_changed }}
steps:
- name: Checkout tfhe-rs
uses: actions/checkout@1af3b93b6815bc44a9784bd300feb67ff0d1eeb3
uses: actions/checkout@8e8c483db84b4bee98b60c0593521ed34d9990e8
with:
fetch-depth: 0
persist-credentials: 'false'
@@ -48,7 +48,7 @@ jobs:
- name: Check for file changes
id: changed-files
uses: tj-actions/changed-files@24d32ffd492484c1d75e0c0b894501ddb9d30d62 # v47.0.0
uses: tj-actions/changed-files@e0021407031f5be11a464abee9a0776171c79891 # v47.0.1
with:
files_yaml: |
gpu:
@@ -116,7 +116,7 @@ jobs:
gcc: 11
steps:
- name: Checkout tfhe-rs
uses: actions/checkout@1af3b93b6815bc44a9784bd300feb67ff0d1eeb3
uses: actions/checkout@8e8c483db84b4bee98b60c0593521ed34d9990e8
with:
persist-credentials: 'false'
token: ${{ env.CHECKOUT_TOKEN }}

View File

@@ -65,7 +65,7 @@ jobs:
timeout-minutes: 4320 # 72 hours
steps:
- name: Checkout tfhe-rs
uses: actions/checkout@1af3b93b6815bc44a9784bd300feb67ff0d1eeb3
uses: actions/checkout@8e8c483db84b4bee98b60c0593521ed34d9990e8
with:
persist-credentials: 'false'
token: ${{ env.CHECKOUT_TOKEN }}

View File

@@ -78,7 +78,7 @@ jobs:
gcc: 11
steps:
- name: Checkout tfhe-rs
uses: actions/checkout@1af3b93b6815bc44a9784bd300feb67ff0d1eeb3
uses: actions/checkout@8e8c483db84b4bee98b60c0593521ed34d9990e8
with:
persist-credentials: 'false'
token: ${{ env.CHECKOUT_TOKEN }}

View File

@@ -78,7 +78,7 @@ jobs:
gcc: 11
steps:
- name: Checkout tfhe-rs
uses: actions/checkout@1af3b93b6815bc44a9784bd300feb67ff0d1eeb3
uses: actions/checkout@8e8c483db84b4bee98b60c0593521ed34d9990e8
with:
persist-credentials: 'false'
token: ${{ env.CHECKOUT_TOKEN }}

View File

@@ -74,7 +74,7 @@ jobs:
steps:
- name: Checkout tfhe-rs
uses: actions/checkout@1af3b93b6815bc44a9784bd300feb67ff0d1eeb3
uses: actions/checkout@8e8c483db84b4bee98b60c0593521ed34d9990e8
with:
persist-credentials: 'false'
token: ${{ env.CHECKOUT_TOKEN }}

View File

@@ -40,7 +40,7 @@ jobs:
gpu_test: ${{ env.IS_PULL_REQUEST == 'false' || steps.changed-files.outputs.gpu_any_changed }}
steps:
- name: Checkout tfhe-rs
uses: actions/checkout@1af3b93b6815bc44a9784bd300feb67ff0d1eeb3
uses: actions/checkout@8e8c483db84b4bee98b60c0593521ed34d9990e8
with:
fetch-depth: 0
persist-credentials: 'false'
@@ -48,7 +48,7 @@ jobs:
- name: Check for file changes
id: changed-files
uses: tj-actions/changed-files@24d32ffd492484c1d75e0c0b894501ddb9d30d62 # v47.0.0
uses: tj-actions/changed-files@e0021407031f5be11a464abee9a0776171c79891 # v47.0.1
with:
files_yaml: |
gpu:
@@ -116,7 +116,7 @@ jobs:
gcc: 11
steps:
- name: Checkout tfhe-rs
uses: actions/checkout@1af3b93b6815bc44a9784bd300feb67ff0d1eeb3
uses: actions/checkout@8e8c483db84b4bee98b60c0593521ed34d9990e8
with:
persist-credentials: 'false'
token: ${{ env.CHECKOUT_TOKEN }}

View File

@@ -40,7 +40,7 @@ jobs:
gpu_test: ${{ env.IS_PULL_REQUEST == 'false' || steps.changed-files.outputs.gpu_any_changed }}
steps:
- name: Checkout tfhe-rs
uses: actions/checkout@1af3b93b6815bc44a9784bd300feb67ff0d1eeb3
uses: actions/checkout@8e8c483db84b4bee98b60c0593521ed34d9990e8
with:
fetch-depth: 0
persist-credentials: 'false'
@@ -48,7 +48,7 @@ jobs:
- name: Check for file changes
id: changed-files
uses: tj-actions/changed-files@24d32ffd492484c1d75e0c0b894501ddb9d30d62 # v47.0.0
uses: tj-actions/changed-files@e0021407031f5be11a464abee9a0776171c79891 # v47.0.1
with:
files_yaml: |
gpu:
@@ -129,7 +129,7 @@ jobs:
gcc: 11
steps:
- name: Checkout tfhe-rs
uses: actions/checkout@1af3b93b6815bc44a9784bd300feb67ff0d1eeb3
uses: actions/checkout@8e8c483db84b4bee98b60c0593521ed34d9990e8
with:
persist-credentials: 'false'
token: ${{ env.CHECKOUT_TOKEN }}

View File

@@ -41,7 +41,7 @@ jobs:
gpu_test: ${{ env.IS_PULL_REQUEST == 'false' || steps.changed-files.outputs.gpu_any_changed }}
steps:
- name: Checkout tfhe-rs
uses: actions/checkout@1af3b93b6815bc44a9784bd300feb67ff0d1eeb3
uses: actions/checkout@8e8c483db84b4bee98b60c0593521ed34d9990e8
with:
fetch-depth: 0
persist-credentials: 'false'
@@ -49,7 +49,7 @@ jobs:
- name: Check for file changes
id: changed-files
uses: tj-actions/changed-files@24d32ffd492484c1d75e0c0b894501ddb9d30d62 # v47.0.0
uses: tj-actions/changed-files@e0021407031f5be11a464abee9a0776171c79891 # v47.0.1
with:
files_yaml: |
gpu:
@@ -117,7 +117,7 @@ jobs:
gcc: 11
steps:
- name: Checkout tfhe-rs
uses: actions/checkout@1af3b93b6815bc44a9784bd300feb67ff0d1eeb3
uses: actions/checkout@8e8c483db84b4bee98b60c0593521ed34d9990e8
with:
persist-credentials: 'false'
token: ${{ env.CHECKOUT_TOKEN }}

View File

@@ -40,7 +40,7 @@ jobs:
gpu_test: ${{ env.IS_PULL_REQUEST == 'false' || steps.changed-files.outputs.gpu_any_changed }}
steps:
- name: Checkout tfhe-rs
uses: actions/checkout@1af3b93b6815bc44a9784bd300feb67ff0d1eeb3
uses: actions/checkout@8e8c483db84b4bee98b60c0593521ed34d9990e8
with:
fetch-depth: 0
persist-credentials: 'false'
@@ -48,7 +48,7 @@ jobs:
- name: Check for file changes
id: changed-files
uses: tj-actions/changed-files@24d32ffd492484c1d75e0c0b894501ddb9d30d62 # v47.0.0
uses: tj-actions/changed-files@e0021407031f5be11a464abee9a0776171c79891 # v47.0.1
with:
files_yaml: |
gpu:
@@ -116,7 +116,7 @@ jobs:
gcc: 11
steps:
- name: Checkout tfhe-rs
uses: actions/checkout@1af3b93b6815bc44a9784bd300feb67ff0d1eeb3
uses: actions/checkout@8e8c483db84b4bee98b60c0593521ed34d9990e8
with:
persist-credentials: 'false'
token: ${{ env.CHECKOUT_TOKEN }}

View File

@@ -40,7 +40,7 @@ jobs:
gpu_test: ${{ env.IS_PULL_REQUEST == 'false' || steps.changed-files.outputs.gpu_any_changed }}
steps:
- name: Checkout tfhe-rs
uses: actions/checkout@1af3b93b6815bc44a9784bd300feb67ff0d1eeb3
uses: actions/checkout@8e8c483db84b4bee98b60c0593521ed34d9990e8
with:
fetch-depth: 0
persist-credentials: 'false'
@@ -48,7 +48,7 @@ jobs:
- name: Check for file changes
id: changed-files
uses: tj-actions/changed-files@24d32ffd492484c1d75e0c0b894501ddb9d30d62 # v47.0.0
uses: tj-actions/changed-files@e0021407031f5be11a464abee9a0776171c79891 # v47.0.1
with:
files_yaml: |
gpu:
@@ -129,7 +129,7 @@ jobs:
gcc: 11
steps:
- name: Checkout tfhe-rs
uses: actions/checkout@1af3b93b6815bc44a9784bd300feb67ff0d1eeb3
uses: actions/checkout@8e8c483db84b4bee98b60c0593521ed34d9990e8
with:
persist-credentials: 'false'
token: ${{ env.CHECKOUT_TOKEN }}

View File

@@ -41,7 +41,7 @@ jobs:
gpu_test: ${{ env.IS_PULL_REQUEST == 'false' || steps.changed-files.outputs.gpu_any_changed }}
steps:
- name: Checkout tfhe-rs
uses: actions/checkout@1af3b93b6815bc44a9784bd300feb67ff0d1eeb3
uses: actions/checkout@8e8c483db84b4bee98b60c0593521ed34d9990e8
with:
fetch-depth: 0
persist-credentials: 'false'
@@ -49,7 +49,7 @@ jobs:
- name: Check for file changes
id: changed-files
uses: tj-actions/changed-files@24d32ffd492484c1d75e0c0b894501ddb9d30d62 # v47.0.0
uses: tj-actions/changed-files@e0021407031f5be11a464abee9a0776171c79891 # v47.0.1
with:
files_yaml: |
gpu:
@@ -117,7 +117,7 @@ jobs:
gcc: 11
steps:
- name: Checkout tfhe-rs
uses: actions/checkout@1af3b93b6815bc44a9784bd300feb67ff0d1eeb3
uses: actions/checkout@8e8c483db84b4bee98b60c0593521ed34d9990e8
with:
persist-credentials: 'false'
token: ${{ env.CHECKOUT_TOKEN }}

View File

@@ -32,7 +32,7 @@ jobs:
hpu_test: ${{ env.IS_PULL_REQUEST == 'false' || steps.changed-files.outputs.hpu_any_changed }}
steps:
- name: Checkout tfhe-rs
uses: actions/checkout@1af3b93b6815bc44a9784bd300feb67ff0d1eeb3
uses: actions/checkout@8e8c483db84b4bee98b60c0593521ed34d9990e8
with:
fetch-depth: 0
persist-credentials: 'false'
@@ -40,7 +40,7 @@ jobs:
- name: Check for file changes
id: changed-files
uses: tj-actions/changed-files@24d32ffd492484c1d75e0c0b894501ddb9d30d62 # v47.0.0
uses: tj-actions/changed-files@e0021407031f5be11a464abee9a0776171c79891 # v47.0.1
with:
files_yaml: |
hpu:
@@ -83,7 +83,7 @@ jobs:
needs: setup-instance
runs-on: ${{ needs.setup-instance.outputs.runner-name }}
steps:
- uses: actions/checkout@1af3b93b6815bc44a9784bd300feb67ff0d1eeb3
- uses: actions/checkout@8e8c483db84b4bee98b60c0593521ed34d9990e8
with:
persist-credentials: 'false'
token: ${{ env.CHECKOUT_TOKEN }}

View File

@@ -53,7 +53,7 @@ jobs:
timeout-minutes: 4320 # 72 hours
steps:
- name: Checkout tfhe-rs
uses: actions/checkout@1af3b93b6815bc44a9784bd300feb67ff0d1eeb3
uses: actions/checkout@8e8c483db84b4bee98b60c0593521ed34d9990e8
with:
persist-credentials: 'false'
token: ${{ secrets.REPO_CHECKOUT_TOKEN }}

View File

@@ -41,7 +41,7 @@ jobs:
timeout-minutes: 720
steps:
- uses: actions/checkout@1af3b93b6815bc44a9784bd300feb67ff0d1eeb3
- uses: actions/checkout@8e8c483db84b4bee98b60c0593521ed34d9990e8
with:
persist-credentials: "false"
token: ${{ env.CHECKOUT_TOKEN }}

View File

@@ -52,7 +52,7 @@ jobs:
hash: ${{ steps.hash.outputs.hash }}
steps:
- name: Checkout
uses: actions/checkout@1af3b93b6815bc44a9784bd300feb67ff0d1eeb3 # v6.0.0
uses: actions/checkout@8e8c483db84b4bee98b60c0593521ed34d9990e8 # v6.0.1
with:
fetch-depth: 0
persist-credentials: 'false'
@@ -62,7 +62,7 @@ jobs:
PACKAGE: ${{ inputs.package-name }}
run: |
cargo package -p "${PACKAGE}"
- uses: actions/upload-artifact@330a01c490aca151604b8cf639adc76d48f6c5d4 # v5.0.0
- uses: actions/upload-artifact@b7c566a772e6b6bfb58ed0dc250532a479d7789f # v6.0.0
with:
name: crate-${{ inputs.package-name }}
path: target/package/*.crate
@@ -93,14 +93,14 @@ jobs:
id-token: write # Needed for OIDC token exchange on crates.io
steps:
- name: Checkout
uses: actions/checkout@1af3b93b6815bc44a9784bd300feb67ff0d1eeb3 # v6.0.0
uses: actions/checkout@8e8c483db84b4bee98b60c0593521ed34d9990e8 # v6.0.1
with:
fetch-depth: 0
persist-credentials: 'false'
token: ${{ secrets.REPO_CHECKOUT_TOKEN }}
- name: Download artifact
uses: actions/download-artifact@018cc2cf5baa6db3ef3c5f8a56943fffe632ef53 # v6.0.0
uses: actions/download-artifact@37930b1c2abaa49bbe596cd826c3c89aef350131 # v7.0.0
with:
name: crate-${{ inputs.package-name }}
path: target/package

View File

@@ -64,7 +64,7 @@ jobs:
CUDA_PATH: /usr/local/cuda-${{ matrix.cuda }}
steps:
- name: Checkout
uses: actions/checkout@1af3b93b6815bc44a9784bd300feb67ff0d1eeb3 # v6.0.0
uses: actions/checkout@8e8c483db84b4bee98b60c0593521ed34d9990e8 # v6.0.1
with:
fetch-depth: 0
persist-credentials: "false"
@@ -104,7 +104,7 @@ jobs:
run: |
cargo package -p tfhe-cuda-backend
- uses: actions/upload-artifact@330a01c490aca151604b8cf639adc76d48f6c5d4 # v5.0.0
- uses: actions/upload-artifact@b7c566a772e6b6bfb58ed0dc250532a479d7789f # v6.0.0
with:
name: crate-tfhe-cuda-backend
path: target/package/*.crate
@@ -174,7 +174,7 @@ jobs:
GCC_VERSION: ${{ matrix.gcc }}
- name: Download artifact
uses: actions/download-artifact@018cc2cf5baa6db3ef3c5f8a56943fffe632ef53 # v6.0.0
uses: actions/download-artifact@37930b1c2abaa49bbe596cd826c3c89aef350131 # v7.0.0
with:
name: crate-tfhe-cuda-backend
path: target/package

View File

@@ -41,6 +41,7 @@ jobs:
make-release:
name: make_release_tfhe/make-release
uses: ./.github/workflows/make_release_common.yml
if: ${{ inputs.push_to_crates }}
with:
package-name: "tfhe"
dry-run: ${{ inputs.dry_run }}
@@ -59,6 +60,7 @@ jobs:
make-release-js:
name: make_release_tfhe/make-release-js
needs: make-release
if: ${{ always() && needs.make-release.result != 'failure' }}
runs-on: ubuntu-latest
# For provenance of npmjs publish
permissions:
@@ -66,7 +68,7 @@ jobs:
id-token: write # also needed for OIDC token exchange on crates.io and npmjs.com
steps:
- name: Checkout
uses: actions/checkout@1af3b93b6815bc44a9784bd300feb67ff0d1eeb3 # v6.0.0
uses: actions/checkout@8e8c483db84b4bee98b60c0593521ed34d9990e8 # v6.0.1
with:
fetch-depth: 0
persist-credentials: 'false'
@@ -83,9 +85,9 @@ jobs:
make build_web_js_api_parallel
- name: Authenticate on NPM
uses: actions/setup-node@2028fbc5c25fe9cf00d9f06a71cc4710d4507903 # v6.0.0
uses: actions/setup-node@395ad3262231945c25e8478fd5baf05154b1d79f # v6.1.0
with:
node-version: '22'
node-version: '24'
registry-url: 'https://registry.npmjs.org'
- name: Publish web package

View File

@@ -60,7 +60,7 @@ jobs:
runs-on: ${{ needs.setup-instance.outputs.runner-name }}
steps:
- name: Checkout tfhe-rs
uses: actions/checkout@1af3b93b6815bc44a9784bd300feb67ff0d1eeb3
uses: actions/checkout@8e8c483db84b4bee98b60c0593521ed34d9990e8
with:
persist-credentials: 'false'
token: ${{ secrets.REPO_CHECKOUT_TOKEN }}
@@ -71,7 +71,7 @@ jobs:
toolchain: stable
- name: Checkout lattice-estimator
uses: actions/checkout@1af3b93b6815bc44a9784bd300feb67ff0d1eeb3
uses: actions/checkout@8e8c483db84b4bee98b60c0593521ed34d9990e8
with:
repository: malb/lattice-estimator
path: lattice_estimator

View File

@@ -17,7 +17,7 @@ jobs:
issues: read # Needed to fetch all issues
pull-requests: write # Needed to write message and close the PR
steps:
- uses: actions/stale@5f858e3efba33a5ca4407a664cc011ad407f2008 # v10.1.0
- uses: actions/stale@997185467fa4f803885201cee163a9f38240193d # v10.1.1
with:
stale-pr-message: 'This PR is unverified and has been open for 2 days, it will now be closed. If you want to contribute please sign the CLA as indicated by the bot.'
days-before-stale: 2

1
.gitignore vendored
View File

@@ -10,6 +10,7 @@ target/
**/*.rmeta
**/Cargo.lock
**/*.bin
**/.DS_Store
# Some of our bench outputs
/tfhe/benchmarks_parameters

View File

@@ -11,7 +11,7 @@
/tfhe/src/core_crypto/gpu @agnesLeroy
/tfhe/src/core_crypto/hpu @zama-ai/hardware
/tfhe/src/shortint/ @mayeul-zama
/tfhe/src/shortint/ @mayeul-zama @nsarlin-zama
/tfhe/src/integer/ @tmontaigu
/tfhe/src/integer/gpu @agnesLeroy
@@ -19,8 +19,12 @@
/tfhe/src/high_level_api/ @tmontaigu
/tfhe-zk-pok/ @nsarlin-zama
/tfhe-benchmark/ @soonum
/utils/ @nsarlin-zama
/Makefile @IceTDrinker @soonum
/mockups/tfhe-hpu-mockup @zama-ai/hardware

View File

@@ -27,7 +27,7 @@ rust-version = "1.91.1"
[workspace.dependencies]
aligned-vec = { version = "0.6", default-features = false }
bytemuck = "1.24"
dyn-stack = { version = "0.11", default-features = false }
dyn-stack = { version = "0.13", default-features = false }
itertools = "0.14"
num-complex = "0.4"
pulp = { version = "0.22", default-features = false }
@@ -36,6 +36,8 @@ rayon = "1.11"
serde = { version = "1.0", default-features = false }
wasm-bindgen = "0.2.101"
getrandom = "0.2.8"
# The project maintainers consider that this is the last version of the 1.3 branch, any newer version should not be trusted
bincode = "=1.3.3"
[profile.bench]
lto = "fat"

View File

@@ -20,7 +20,7 @@ BENCH_TYPE?=latency
BENCH_PARAM_TYPE?=classical
BENCH_PARAMS_SET?=default
BENCH_CUSTOM_COMMAND:=
NODE_VERSION=22.6
NODE_VERSION=24.12
BACKWARD_COMPAT_DATA_DIR=utils/tfhe-backward-compat-data
BACKWARD_COMPAT_DATA_GEN_VERSION:=$(TFHE_VERSION)
TEST_VECTORS_DIR=apps/test-vectors
@@ -996,6 +996,15 @@ test_noise_check:
--features=boolean,shortint,integer -p tfhe -- noise_check \
--test-threads=1 --nocapture
.PHONY: test_noise_check_gpu # Run dedicated noise and pfail check tests on gpu backend
test_noise_check_gpu:
@# First run the sanity checks to make sure the atomic patterns are correct
RUSTFLAGS="$(RUSTFLAGS)" cargo test --profile $(CARGO_PROFILE) \
--features=boolean,shortint,integer,gpu -p tfhe -- gpu_sanity_check
RUSTFLAGS="$(RUSTFLAGS)" cargo test --profile $(CARGO_PROFILE) \
--features=boolean,shortint,integer,gpu -p tfhe -- gpu_noise_check \
--test-threads=1 --nocapture
.PHONY: test_safe_serialization # Run the tests for safe serialization
test_safe_serialization: install_cargo_nextest
RUSTFLAGS="$(RUSTFLAGS)" cargo test --profile $(CARGO_PROFILE) \
@@ -1291,13 +1300,14 @@ run_web_js_api_parallel: build_web_js_api_parallel setup_venv
--browser-path $(browser_path) \
--driver-path $(driver_path) \
--browser-kind $(browser_kind) \
--server-cmd "npm run server" \
--server-cmd $(server_cmd) \
--server-workdir "$(WEB_SERVER_DIR)" \
--id-pattern $(filter)
test_web_js_api_parallel_chrome: browser_path = "$(WEB_RUNNER_DIR)/chrome/chrome-linux64/chrome"
test_web_js_api_parallel_chrome: driver_path = "$(WEB_RUNNER_DIR)/chrome/chromedriver-linux64/chromedriver"
test_web_js_api_parallel_chrome: browser_kind = chrome
test_web_js_api_parallel_chrome: server_cmd = "npm run server:multithreaded"
test_web_js_api_parallel_chrome: filter = Test
.PHONY: test_web_js_api_parallel_chrome # Run tests for the web wasm api on Chrome
@@ -1313,6 +1323,7 @@ test_web_js_api_parallel_chrome_ci: setup_venv
test_web_js_api_parallel_firefox: browser_path = "$(WEB_RUNNER_DIR)/firefox/firefox/firefox"
test_web_js_api_parallel_firefox: driver_path = "$(WEB_RUNNER_DIR)/firefox/geckodriver"
test_web_js_api_parallel_firefox: browser_kind = firefox
test_web_js_api_parallel_firefox: server_cmd = "npm run server:multithreaded"
test_web_js_api_parallel_firefox: filter = Test
.PHONY: test_web_js_api_parallel_firefox # Run tests for the web wasm api on Firefox
@@ -1343,7 +1354,6 @@ dieharder_csprng: install_dieharder build_tfhe_csprng
.PHONY: clippy_bench # Run clippy lints on tfhe-benchmark
clippy_bench: install_rs_check_toolchain
! (grep --recursive "trivial" tfhe-benchmark && echo "trivial found in benches")
RUSTFLAGS="$(RUSTFLAGS)" cargo "$(CARGO_RS_CHECK_TOOLCHAIN)" clippy --all-targets \
--features=boolean,shortint,integer,internal-keycache,pbs-stats,zk-pok \
-p tfhe-benchmark -- --no-deps -D warnings
@@ -1563,6 +1573,7 @@ bench_pbs128_gpu: install_rs_check_toolchain
bench_web_js_api_parallel_chrome: browser_path = "$(WEB_RUNNER_DIR)/chrome/chrome-linux64/chrome"
bench_web_js_api_parallel_chrome: driver_path = "$(WEB_RUNNER_DIR)/chrome/chromedriver-linux64/chromedriver"
bench_web_js_api_parallel_chrome: browser_kind = chrome
bench_web_js_api_parallel_chrome: server_cmd = "npm run server:multithreaded"
bench_web_js_api_parallel_chrome: filter = Bench
.PHONY: bench_web_js_api_parallel_chrome # Run benchmarks for the web wasm api
@@ -1578,6 +1589,7 @@ bench_web_js_api_parallel_chrome_ci: setup_venv
bench_web_js_api_parallel_firefox: browser_path = "$(WEB_RUNNER_DIR)/firefox/firefox/firefox"
bench_web_js_api_parallel_firefox: driver_path = "$(WEB_RUNNER_DIR)/firefox/geckodriver"
bench_web_js_api_parallel_firefox: browser_kind = firefox
bench_web_js_api_parallel_firefox: server_cmd = "npm run server:multithreaded"
bench_web_js_api_parallel_firefox: filter = Bench
.PHONY: bench_web_js_api_parallel_firefox # Run benchmarks for the web wasm api
@@ -1590,6 +1602,38 @@ bench_web_js_api_parallel_firefox_ci: setup_venv
nvm use $(NODE_VERSION) && \
$(MAKE) bench_web_js_api_parallel_firefox
bench_web_js_api_unsafe_coop_chrome: browser_path = "$(WEB_RUNNER_DIR)/chrome/chrome-linux64/chrome"
bench_web_js_api_unsafe_coop_chrome: driver_path = "$(WEB_RUNNER_DIR)/chrome/chromedriver-linux64/chromedriver"
bench_web_js_api_unsafe_coop_chrome: browser_kind = chrome
bench_web_js_api_unsafe_coop_chrome: server_cmd = "npm run server:unsafe-coop"
bench_web_js_api_unsafe_coop_chrome: filter = ZeroKnowledgeBench # Only bench zk with unsafe coop
.PHONY: bench_web_js_api_unsafe_coop_chrome # Run benchmarks for the web wasm api without cross-origin isolation
bench_web_js_api_unsafe_coop_chrome: run_web_js_api_parallel
.PHONY: bench_web_js_api_unsafe_coop_chrome_ci # Run benchmarks for the web wasm api without cross-origin isolation
bench_web_js_api_unsafe_coop_chrome_ci: setup_venv
source ~/.nvm/nvm.sh && \
nvm install $(NODE_VERSION) && \
nvm use $(NODE_VERSION) && \
$(MAKE) bench_web_js_api_unsafe_coop_chrome
bench_web_js_api_unsafe_coop_firefox: browser_path = "$(WEB_RUNNER_DIR)/firefox/firefox/firefox"
bench_web_js_api_unsafe_coop_firefox: driver_path = "$(WEB_RUNNER_DIR)/firefox/geckodriver"
bench_web_js_api_unsafe_coop_firefox: browser_kind = firefox
bench_web_js_api_unsafe_coop_firefox: server_cmd = "npm run server:unsafe-coop"
bench_web_js_api_unsafe_coop_firefox: filter = ZeroKnowledgeBench # Only bench zk with unsafe coop
.PHONY: bench_web_js_api_unsafe_coop_firefox # Run benchmarks for the web wasm api without cross-origin isolation
bench_web_js_api_unsafe_coop_firefox: run_web_js_api_parallel
.PHONY: bench_web_js_api_unsafe_coop_firefox_ci # Run benchmarks for the web wasm api without cross-origin isolation
bench_web_js_api_unsafe_coop_firefox_ci: setup_venv
source ~/.nvm/nvm.sh && \
nvm install $(NODE_VERSION) && \
nvm use $(NODE_VERSION) && \
$(MAKE) bench_web_js_api_unsafe_coop_firefox
.PHONY: bench_hlapi # Run benchmarks for integer operations
bench_hlapi: install_rs_check_toolchain
RUSTFLAGS="$(RUSTFLAGS)" __TFHE_RS_BENCH_BIT_SIZES_SET=$(BIT_SIZES_SET) \

View File

@@ -1,24 +1,32 @@
08f31a47c29cc4d72ad32c0b5411fa20b3deef5b84558dd2fb892d3cdf90528a data/toy_params/glwe_after_id_br_karatsuba.cbor
29b6e3e7d27700004b70dca24d225816500490e2d6ee49b9af05837fd421896b data/valid_params_128/lwe_after_spec_pbs.cbor
2c70d1d78cc3760733850a353ace2b9c4705e840141b75841739e90e51247e18 data/valid_params_128/small_lwe_secret_key.cbor
2fb4bb45c259b8383da10fc8f9459c40a6972c49b1696eb107f0a75640724be5 data/toy_params/lwe_after_id_pbs_karatsuba.cbor
36c9080b636475fcacca503ce041bbfeee800fd3e1890dee559ea18defff9fe8 data/toy_params/glwe_after_id_br.cbor
377761beeb4216cf5aa2624a8b64b8259f5a75c32d28e850be8bced3a0cdd6f5 data/toy_params/ksk.cbor
59dba26d457f96478eda130cab5301fce86f23c6a8807de42f2a1e78c4985ca7 data/valid_params_128/lwe_ks.cbor
5d80dd93fefae4f4f89484dfcd65bbe99cc32e7e3b0a90c33dd0d77516c0a023 data/valid_params_128/glwe_after_id_br_karatsuba.cbor
656f0009c7834c5bcb61621e222047516054b9bc5d0593d474ab8f1c086b67a6 data/valid_params_128/lwe_after_id_pbs.cbor
699580ca92b9c2f9e1f57fb1e312c9e8cb29714f7acdef9d2ba05f798546751f data/toy_params/lwe_sum.cbor
6e54ab41056984595b077baff70236d934308cf5c0c33b4482fbfb129b3756c6 data/valid_params_128/glwe_after_id_br.cbor
70f5e5728822de05b49071efb5ec28551b0f5cc87aa709a455d8e7f04b9c96ee data/toy_params/lwe_after_id_pbs.cbor
76a5c52cab7fec1dc167da676c6cd39479cda6b2bb9f4e0573cb7d99c2692faa data/valid_params_128/lwe_after_id_pbs_karatsuba.cbor
7cc6803f5fbc3d5a1bf597f2b979ce17eecd3d6baca12183dea21022a7b65c52 data/toy_params/bsk.cbor
7f3c40a134623b44779a556212477fea26eaed22450f3b6faeb8721d63699972 data/valid_params_128/lwe_sum.cbor
837b3bd3245d4d0534ed255fdef896fb4fa6998a258a14543dfdadd0bfc9b6dd data/toy_params/lwe_prod.cbor
9ece8ca9c1436258b94e8c5e629b8722f9b18fdd415dd5209b6167a9dde8491c data/toy_params/glwe_after_spec_br_karatsuba.cbor
aa44aea29efd6d9e4d35a21a625d9cba155672e3f7ed3eddee1e211e62ad146b data/valid_params_128/lwe_ms.cbor
b7a037b9eaa88d6385167579b93e26a0cb6976d9b8967416fd1173e113bda199 data/valid_params_128/large_lwe_secret_key.cbor
b7b8e3586128887bd682120f3e3a43156139bce5e3fe0b03284f8753a864d647 data/toy_params/lwe_after_spec_pbs_karatsuba.cbor
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c7d5a864d5616a7d8ad50bbf40416e41e6c9b60c546dc14d4aa8fc40a418baa7 data/toy_params/large_lwe_secret_key.cbor
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d6da5baef0e787f6be56e218d8354e26904652602db964844156fdff08350ce6 data/toy_params/lwe_ks.cbor
e591ab9af1b6a0aede273f9a3abb65a4c387feb5fa06a6959e9314058ca0f7e5 data/valid_params_128/ksk.cbor
e59b002df3a9b01ad321ec51cf076fa35131ab9dbef141d1c54b717d61426c92 data/valid_params_128/glwe_after_spec_br_karatsuba.cbor
e628354c81508a2d888016e8282df363dd12f1e19190b6475d4eb9d7ab8ae007 data/valid_params_128/glwe_after_spec_br.cbor
e69d2d2c064fc8c0460b39191ca65338146990349954f5ec5ebd01d93610e7eb data/valid_params_128/lwe_a.cbor
e76c24b2a0c9a842ad13dda35473c2514f9e7d20983b5ea0759c4521a91626d9 data/valid_params_128/lwe_prod.cbor

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@@ -39,6 +39,9 @@ The following values are generated:
| `glwe_after_spec_br` | The glwe returned by the application of the spec blind rotation on the mod switched ciphertexts. | `GlweCiphertext<Vec<u64>>` | rot spec LUT |
| `lwe_after_spec_pbs` | The lwe returned by the application of the sample extract operation on the output of the spec blind rotation | `LweCiphertext<Vec<u64>>` | `spec(A)` |
Ciphertexts with the `_karatsuba` suffix are generated using the Karatsuba polynomial multiplication algorithm in the blind rotation, while default ciphertexts are generated using an FFT multiplication.
This makes it easier to reproduce bit exact results.
### Encodings
#### Non native encoding
Warning: TFHE-rs uses a specific encoding for non native (ie: u32, u64) power of two ciphertext modulus. This encoding puts the encoded value in the high bits of the native integer.

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@@ -0,0 +1,3 @@
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@@ -0,0 +1,3 @@
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size 18493

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@@ -265,6 +265,7 @@ fn generate_test_vectors<P: AsRef<Path>>(
let mut id_lut = encoding.encode_lut(glwe_dimension, polynomial_size, ID_LUT);
assert_data_not_zero(&id_lut);
let mut id_lut_karatsuba = id_lut.clone();
blind_rotate_assign(&modswitched, &mut id_lut, &fourier_bsk);
assert_data_not_zero(&id_lut);
@@ -287,8 +288,32 @@ fn generate_test_vectors<P: AsRef<Path>>(
assert_data_not_zero(&lwe_pbs_id);
store_data(path, &lwe_pbs_id, "lwe_after_id_pbs");
blind_rotate_karatsuba_assign(&modswitched, &mut id_lut_karatsuba, &bsk);
store_data(path, &id_lut_karatsuba, "glwe_after_id_br_karatsuba");
let mut lwe_pbs_karatsuba_id = LweCiphertext::new(
0u64,
glwe_dimension
.to_equivalent_lwe_dimension(polynomial_size)
.to_lwe_size(),
encoding.ciphertext_modulus,
);
extract_lwe_sample_from_glwe_ciphertext(
&id_lut_karatsuba,
&mut lwe_pbs_karatsuba_id,
MonomialDegree(0),
);
let decrypted_pbs_id = decrypt_lwe_ciphertext(&large_lwe_secret_key, &lwe_pbs_karatsuba_id);
let res = encoding.decode(decrypted_pbs_id);
assert_eq!(res, MSG_A);
store_data(path, &lwe_pbs_karatsuba_id, "lwe_after_id_pbs_karatsuba");
let mut spec_lut = encoding.encode_lut(glwe_dimension, polynomial_size, SPEC_LUT);
assert_data_not_zero(&spec_lut);
let mut spec_lut_karatsuba = spec_lut.clone();
blind_rotate_assign(&modswitched, &mut spec_lut, &fourier_bsk);
assert_data_not_zero(&spec_lut);
@@ -310,6 +335,33 @@ fn generate_test_vectors<P: AsRef<Path>>(
assert_eq!(res, SPEC_LUT(MSG_A));
assert_data_not_zero(&lwe_pbs_spec);
store_data(path, &lwe_pbs_spec, "lwe_after_spec_pbs");
blind_rotate_karatsuba_assign(&modswitched, &mut spec_lut_karatsuba, &bsk);
store_data(path, &spec_lut_karatsuba, "glwe_after_spec_br_karatsuba");
let mut lwe_pbs_karatsuba_spec = LweCiphertext::new(
0u64,
glwe_dimension
.to_equivalent_lwe_dimension(polynomial_size)
.to_lwe_size(),
encoding.ciphertext_modulus,
);
extract_lwe_sample_from_glwe_ciphertext(
&spec_lut_karatsuba,
&mut lwe_pbs_karatsuba_spec,
MonomialDegree(0),
);
let decrypted_pbs_spec = decrypt_lwe_ciphertext(&large_lwe_secret_key, &lwe_pbs_karatsuba_spec);
let res = encoding.decode(decrypted_pbs_spec);
assert_eq!(res, SPEC_LUT(MSG_A));
store_data(
path,
&lwe_pbs_karatsuba_spec,
"lwe_after_spec_pbs_karatsuba",
);
}
fn rm_dir_except_readme<P: AsRef<Path>>(dir: P) {

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@@ -1,6 +1,6 @@
[package]
name = "tfhe-cuda-backend"
version = "0.12.0"
version = "0.13.0"
edition = "2021"
authors = ["Zama team"]
license = "BSD-3-Clause-Clear"

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@@ -35,7 +35,8 @@ template <typename Torus> struct int_aes_lut_buffers {
params.glwe_dimension, params.polynomial_size, params.message_modulus,
params.carry_modulus, and_lambda, allocate_gpu_memory);
auto active_streams_and_lut = streams.active_gpu_subset(
SBOX_MAX_AND_GATES * num_aes_inputs * sbox_parallelism);
SBOX_MAX_AND_GATES * num_aes_inputs * sbox_parallelism,
params.pbs_type);
this->and_lut->broadcast_lut(active_streams_and_lut);
this->and_lut->setup_gemm_batch_ks_temp_buffers(size_tracker);
@@ -50,8 +51,8 @@ template <typename Torus> struct int_aes_lut_buffers {
this->flush_lut->get_degree(0), this->flush_lut->get_max_degree(0),
params.glwe_dimension, params.polynomial_size, params.message_modulus,
params.carry_modulus, flush_lambda, allocate_gpu_memory);
auto active_streams_flush_lut =
streams.active_gpu_subset(AES_STATE_BITS * num_aes_inputs);
auto active_streams_flush_lut = streams.active_gpu_subset(
AES_STATE_BITS * num_aes_inputs, params.pbs_type);
this->flush_lut->broadcast_lut(active_streams_flush_lut);
this->flush_lut->setup_gemm_batch_ks_temp_buffers(size_tracker);
@@ -65,7 +66,8 @@ template <typename Torus> struct int_aes_lut_buffers {
this->carry_lut->get_degree(0), this->carry_lut->get_max_degree(0),
params.glwe_dimension, params.polynomial_size, params.message_modulus,
params.carry_modulus, carry_lambda, allocate_gpu_memory);
auto active_streams_carry_lut = streams.active_gpu_subset(num_aes_inputs);
auto active_streams_carry_lut =
streams.active_gpu_subset(num_aes_inputs, params.pbs_type);
this->carry_lut->broadcast_lut(active_streams_carry_lut);
this->carry_lut->setup_gemm_batch_ks_temp_buffers(size_tracker);
}

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@@ -35,17 +35,9 @@ void cuda_centered_modulus_switch_64(void *stream, uint32_t gpu_index,
uint32_t lwe_dimension,
uint32_t log_modulus);
void cuda_improve_noise_modulus_switch_64(
void *stream, uint32_t gpu_index, void *lwe_array_out,
void const *lwe_array_in, void const *lwe_array_indexes,
void const *encrypted_zeros, uint32_t lwe_size, uint32_t num_lwes,
uint32_t num_zeros, double input_variance, double r_sigma, double bound,
uint32_t log_modulus);
void cuda_glwe_sample_extract_128(
void *stream, uint32_t gpu_index, void *lwe_array_out,
void const *glwe_array_in, uint32_t const *nth_array, uint32_t num_nths,
uint32_t lwe_per_glwe, uint32_t glwe_dimension, uint32_t polynomial_size);
}
#endif

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@@ -8,7 +8,8 @@
extern std::mutex m;
extern bool p2p_enabled;
extern const int THRESHOLD_MULTI_GPU;
extern const int THRESHOLD_MULTI_GPU_WITH_MULTI_BIT_PARAMS;
extern const int THRESHOLD_MULTI_GPU_WITH_CLASSICAL_PARAMS;
extern "C" {
int32_t cuda_setup_multi_gpu(int device_0_id);
@@ -39,7 +40,8 @@ get_variant_element(const std::variant<std::vector<Torus>, Torus> &variant,
}
}
uint32_t get_active_gpu_count(uint32_t num_inputs, uint32_t gpu_count);
uint32_t get_active_gpu_count(uint32_t num_inputs, uint32_t gpu_count,
PBS_TYPE pbs_type);
int get_num_inputs_on_gpu(int total_num_inputs, int gpu_index, int gpu_count);
@@ -73,9 +75,10 @@ public:
// Returns a subset of this set as an active subset. An active subset is one
// that is temporarily used to perform some computation
CudaStreams active_gpu_subset(int num_radix_blocks) {
return CudaStreams(_streams, _gpu_indexes,
get_active_gpu_count(num_radix_blocks, _gpu_count));
CudaStreams active_gpu_subset(int num_radix_blocks, PBS_TYPE pbs_type) {
return CudaStreams(
_streams, _gpu_indexes,
get_active_gpu_count(num_radix_blocks, _gpu_count, pbs_type));
}
// Returns a CudaStreams struct containing only the ith stream

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@@ -20,7 +20,8 @@ template <typename Torus> struct boolean_bitop_buffer {
gpu_memory_allocated = allocate_gpu_memory;
this->op = op;
this->params = params;
auto active_streams = streams.active_gpu_subset(lwe_ciphertext_count);
auto active_streams =
streams.active_gpu_subset(lwe_ciphertext_count, params.pbs_type);
this->unchecked = is_unchecked;
switch (op) {
case BITAND:
@@ -119,7 +120,8 @@ template <typename Torus> struct int_bitop_buffer {
gpu_memory_allocated = allocate_gpu_memory;
this->op = op;
this->params = params;
auto active_streams = streams.active_gpu_subset(num_radix_blocks);
auto active_streams =
streams.active_gpu_subset(num_radix_blocks, params.pbs_type);
switch (op) {
case BITAND:
case BITOR:
@@ -216,7 +218,8 @@ template <typename Torus> struct boolean_bitnot_buffer {
message_extract_lut->get_max_degree(0), params.glwe_dimension,
params.polynomial_size, params.message_modulus, params.carry_modulus,
lut_f_message_extract, gpu_memory_allocated);
auto active_streams = streams.active_gpu_subset(lwe_ciphertext_count);
auto active_streams =
streams.active_gpu_subset(lwe_ciphertext_count, params.pbs_type);
message_extract_lut->broadcast_lut(active_streams);
}
}

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@@ -39,7 +39,8 @@ template <typename Torus> struct int_extend_radix_with_sign_msb_buffer {
},
allocate_gpu_memory);
auto active_streams = streams.active_gpu_subset(num_radix_blocks);
auto active_streams =
streams.active_gpu_subset(num_radix_blocks, params.pbs_type);
lut->broadcast_lut(active_streams);
this->last_block = new CudaRadixCiphertextFFI;

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@@ -14,7 +14,8 @@ template <typename Torus> struct int_zero_out_if_buffer {
uint64_t &size_tracker) {
gpu_memory_allocated = allocate_gpu_memory;
this->params = params;
auto active_streams = streams.active_gpu_subset(num_radix_blocks);
auto active_streams =
streams.active_gpu_subset(num_radix_blocks, params.pbs_type);
tmp = new CudaRadixCiphertextFFI;
create_zero_radix_ciphertext_async<Torus>(
@@ -114,9 +115,11 @@ template <typename Torus> struct int_cmux_buffer {
predicate_lut->get_lut_indexes(0, 0), h_lut_indexes,
2 * num_radix_blocks * sizeof(Torus), streams.stream(0),
streams.gpu_index(0), allocate_gpu_memory);
auto active_streams_pred = streams.active_gpu_subset(2 * num_radix_blocks);
auto active_streams_pred =
streams.active_gpu_subset(2 * num_radix_blocks, params.pbs_type);
predicate_lut->broadcast_lut(active_streams_pred);
auto active_streams_msg = streams.active_gpu_subset(num_radix_blocks);
auto active_streams_msg =
streams.active_gpu_subset(num_radix_blocks, params.pbs_type);
message_extract_lut->broadcast_lut(active_streams_msg);
}

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@@ -52,7 +52,8 @@ template <typename Torus> struct int_are_all_block_true_buffer {
params.glwe_dimension, params.polynomial_size, params.message_modulus,
params.carry_modulus, is_max_value_f, gpu_memory_allocated);
auto active_streams = streams.active_gpu_subset(max_chunks);
auto active_streams =
streams.active_gpu_subset(max_chunks, params.pbs_type);
is_max_value->broadcast_lut(active_streams);
}
@@ -108,7 +109,8 @@ template <typename Torus> struct int_comparison_eq_buffer {
params.glwe_dimension, params.polynomial_size, params.message_modulus,
params.carry_modulus, is_non_zero_lut_f, gpu_memory_allocated);
auto active_streams = streams.active_gpu_subset(num_radix_blocks);
auto active_streams =
streams.active_gpu_subset(num_radix_blocks, params.pbs_type);
is_non_zero_lut->broadcast_lut(active_streams);
// Scalar may have up to num_radix_blocks blocks
@@ -238,7 +240,8 @@ template <typename Torus> struct int_tree_sign_reduction_buffer {
tree_inner_leaf_lut->get_max_degree(0), params.glwe_dimension,
params.polynomial_size, params.message_modulus, params.carry_modulus,
block_selector_f, gpu_memory_allocated);
auto active_streams = streams.active_gpu_subset(num_radix_blocks);
auto active_streams =
streams.active_gpu_subset(num_radix_blocks, params.pbs_type);
tree_inner_leaf_lut->broadcast_lut(active_streams);
}
@@ -390,7 +393,8 @@ template <typename Torus> struct int_comparison_buffer {
this->op = op;
this->is_signed = is_signed;
auto active_streams = streams.active_gpu_subset(num_radix_blocks);
auto active_streams =
streams.active_gpu_subset(num_radix_blocks, params.pbs_type);
identity_lut_f = [](Torus x) -> Torus { return x; };
@@ -523,7 +527,7 @@ template <typename Torus> struct int_comparison_buffer {
signed_lut->get_degree(0), signed_lut->get_max_degree(0),
params.glwe_dimension, params.polynomial_size, params.message_modulus,
params.carry_modulus, signed_lut_f, gpu_memory_allocated);
auto active_streams = streams.active_gpu_subset(1);
auto active_streams = streams.active_gpu_subset(1, params.pbs_type);
signed_lut->broadcast_lut(active_streams);
}
preallocated_h_lut = (Torus *)malloc(

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@@ -116,7 +116,8 @@ template <typename Torus> struct int_decompression {
effective_compression_carry_modulus,
encryption_params.message_modulus, encryption_params.carry_modulus,
decompression_rescale_f, gpu_memory_allocated);
auto active_streams = streams.active_gpu_subset(num_blocks_to_decompress);
auto active_streams = streams.active_gpu_subset(
num_blocks_to_decompress, decompression_rescale_lut->params.pbs_type);
decompression_rescale_lut->broadcast_lut(active_streams);
}
}

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@@ -356,7 +356,8 @@ template <typename Torus> struct unsigned_int_div_rem_2_2_memory {
luts[j]->get_degree(0), luts[j]->get_max_degree(0),
params.glwe_dimension, params.polynomial_size, params.message_modulus,
params.carry_modulus, lut_f_message_extract, gpu_memory_allocated);
auto active_streams = streams.active_gpu_subset(num_blocks);
auto active_streams =
streams.active_gpu_subset(num_blocks, params.pbs_type);
luts[j]->broadcast_lut(active_streams);
}
}
@@ -1012,7 +1013,7 @@ template <typename Torus> struct unsigned_int_div_rem_memory {
masking_luts_1[i]->get_max_degree(0), params.glwe_dimension,
params.polynomial_size, params.message_modulus, params.carry_modulus,
lut_f_masking, gpu_memory_allocated);
auto active_streams_1 = streams.active_gpu_subset(1);
auto active_streams_1 = streams.active_gpu_subset(1, params.pbs_type);
masking_luts_1[i]->broadcast_lut(active_streams_1);
generate_device_accumulator<Torus>(
@@ -1021,7 +1022,8 @@ template <typename Torus> struct unsigned_int_div_rem_memory {
masking_luts_2[i]->get_max_degree(0), params.glwe_dimension,
params.polynomial_size, params.message_modulus, params.carry_modulus,
lut_f_masking, gpu_memory_allocated);
auto active_streams_2 = streams.active_gpu_subset(num_blocks);
auto active_streams_2 =
streams.active_gpu_subset(num_blocks, params.pbs_type);
masking_luts_2[i]->broadcast_lut(active_streams_2);
}
@@ -1040,7 +1042,8 @@ template <typename Torus> struct unsigned_int_div_rem_memory {
int_radix_lut<Torus> *luts[2] = {message_extract_lut_1,
message_extract_lut_2};
auto active_streams = streams.active_gpu_subset(num_blocks);
auto active_streams =
streams.active_gpu_subset(num_blocks, params.pbs_type);
for (int j = 0; j < 2; j++) {
generate_device_accumulator<Torus>(
streams.stream(0), streams.gpu_index(0), luts[j]->get_lut(0, 0),
@@ -1128,7 +1131,8 @@ template <typename Torus> struct unsigned_int_div_rem_memory {
// merge_overflow_flags_luts
merge_overflow_flags_luts = new int_radix_lut<Torus> *[num_bits_in_message];
auto active_gpu_count_for_bits = streams.active_gpu_subset(1);
auto active_gpu_count_for_bits =
streams.active_gpu_subset(1, params.pbs_type);
for (int i = 0; i < num_bits_in_message; i++) {
auto lut_f_bit = [i](Torus x, Torus y) -> Torus {
return (x == 0 && y == 0) << i;
@@ -1152,7 +1156,8 @@ template <typename Torus> struct unsigned_int_div_rem_memory {
uint32_t num_blocks, bool allocate_gpu_memory,
uint64_t &size_tracker) {
gpu_memory_allocated = allocate_gpu_memory;
auto active_streams = streams.active_gpu_subset(2 * num_blocks);
auto active_streams =
streams.active_gpu_subset(2 * num_blocks, params.pbs_type);
this->params = params;
if (params.message_modulus == 4 && params.carry_modulus == 4 &&
@@ -1473,7 +1478,8 @@ template <typename Torus> struct int_div_rem_memory {
bool allocate_gpu_memory, uint64_t &size_tracker) {
gpu_memory_allocated = allocate_gpu_memory;
this->active_streams = streams.active_gpu_subset(num_blocks);
this->active_streams =
streams.active_gpu_subset(num_blocks, params.pbs_type);
this->params = params;
this->is_signed = is_signed;
@@ -1559,7 +1565,7 @@ template <typename Torus> struct int_div_rem_memory {
params.polynomial_size, params.message_modulus, params.carry_modulus,
f_compare_extracted_signed_bits, gpu_memory_allocated);
auto active_gpu_count_cmp =
streams.active_gpu_subset(1); // only 1 block needed
streams.active_gpu_subset(1, params.pbs_type); // only 1 block needed
compare_signed_bits_lut->broadcast_lut(active_gpu_count_cmp);
}
}

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@@ -20,7 +20,8 @@ template <typename Torus> struct int_prepare_count_of_consecutive_bits_buffer {
this->allocate_gpu_memory = allocate_gpu_memory;
this->direction = direction;
this->bit_value = bit_value;
auto active_streams = streams.active_gpu_subset(num_radix_blocks);
auto active_streams =
streams.active_gpu_subset(num_radix_blocks, params.pbs_type);
this->univ_lut_mem =
new int_radix_lut<Torus>(streams, params, 1, num_radix_blocks,
allocate_gpu_memory, size_tracker);
@@ -246,7 +247,8 @@ template <typename Torus> struct int_ilog2_buffer {
params.glwe_dimension, params.polynomial_size,
params.message_modulus, params.carry_modulus,
lut_message_lambda, allocate_gpu_memory);
auto active_streams = streams.active_gpu_subset(counter_num_blocks);
auto active_streams =
streams.active_gpu_subset(counter_num_blocks, params.pbs_type);
lut_message_not->broadcast_lut(active_streams);
this->lut_carry_not =

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@@ -883,6 +883,10 @@ void cuda_unchecked_first_index_in_clears_64(
uint32_t num_unique, uint32_t num_blocks, uint32_t num_blocks_index,
int8_t *mem, void *const *bsks, void *const *ksks);
void cuda_small_scalar_multiplication_integer_64_inplace(
CudaStreamsFFI streams, CudaRadixCiphertextFFI *lwe_array, uint64_t scalar,
const uint32_t message_modulus, const uint32_t carry_modulus);
void cleanup_cuda_unchecked_first_index_in_clears_64(CudaStreamsFFI streams,
int8_t **mem_ptr_void);

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@@ -43,6 +43,8 @@ public:
"parameters"); \
} else if ((msg_mod) == 0 && (carry_mod) == 0) { \
break; \
} else if ((msg_mod) == 4 && (carry_mod) == 32) { \
break; \
} else { \
PANIC("Invalid message modulus or carry modulus") \
} \
@@ -369,7 +371,8 @@ struct int_radix_lut_custom_input_output {
this->num_input_blocks = num_input_blocks;
this->gpu_memory_allocated = allocate_gpu_memory;
this->active_streams = streams.active_gpu_subset(num_radix_blocks);
this->active_streams =
streams.active_gpu_subset(num_radix_blocks, params.pbs_type);
}
void setup_degrees() {
@@ -380,14 +383,18 @@ struct int_radix_lut_custom_input_output {
void allocate_pbs_buffers(int_radix_params params, uint32_t num_radix_blocks,
bool allocate_gpu_memory, uint64_t &size_tracker) {
int threshold = (params.pbs_type == PBS_TYPE::MULTI_BIT)
? THRESHOLD_MULTI_GPU_WITH_MULTI_BIT_PARAMS
: THRESHOLD_MULTI_GPU_WITH_CLASSICAL_PARAMS;
for (uint i = 0; i < active_streams.count(); i++) {
cuda_set_device(active_streams.gpu_index(i));
int8_t *gpu_pbs_buffer;
auto num_blocks_on_gpu =
std::min((int)num_radix_blocks,
std::max(THRESHOLD_MULTI_GPU,
get_num_inputs_on_gpu(num_radix_blocks, i,
active_streams.count())));
auto num_blocks_on_gpu = std::min(
(int)num_radix_blocks,
std::max(threshold, get_num_inputs_on_gpu(num_radix_blocks, i,
active_streams.count())));
uint64_t size = 0;
execute_scratch_pbs<OutputTorus>(
@@ -422,18 +429,22 @@ struct int_radix_lut_custom_input_output {
/// back to the original indexing
multi_gpu_alloc_lwe_async(active_streams, lwe_array_in_vec,
num_radix_blocks, params.big_lwe_dimension + 1,
size_tracker, allocate_gpu_memory);
size_tracker, params.pbs_type,
allocate_gpu_memory);
multi_gpu_alloc_lwe_async(active_streams, lwe_after_ks_vec,
num_radix_blocks, params.small_lwe_dimension + 1,
size_tracker, allocate_gpu_memory);
size_tracker, params.pbs_type,
allocate_gpu_memory);
if (num_many_lut > 1) {
multi_gpu_alloc_lwe_many_lut_output_async(
active_streams, lwe_after_pbs_vec, num_radix_blocks, num_many_lut,
params.big_lwe_dimension + 1, size_tracker, allocate_gpu_memory);
params.big_lwe_dimension + 1, size_tracker, params.pbs_type,
allocate_gpu_memory);
} else {
multi_gpu_alloc_lwe_async(active_streams, lwe_after_pbs_vec,
num_radix_blocks, params.big_lwe_dimension + 1,
size_tracker, allocate_gpu_memory);
size_tracker, params.pbs_type,
allocate_gpu_memory);
}
multi_gpu_alloc_array_async(active_streams, lwe_trivial_indexes_vec,
num_radix_blocks, size_tracker,
@@ -449,12 +460,14 @@ struct int_radix_lut_custom_input_output {
}
void setup_gemm_batch_ks_temp_buffers(uint64_t &size_tracker) {
int threshold = (params.pbs_type == PBS_TYPE::MULTI_BIT)
? THRESHOLD_MULTI_GPU_WITH_MULTI_BIT_PARAMS
: THRESHOLD_MULTI_GPU_WITH_CLASSICAL_PARAMS;
auto inputs_on_gpu =
std::min((int)num_input_blocks,
std::max(THRESHOLD_MULTI_GPU,
get_num_inputs_on_gpu(num_input_blocks, 0,
active_streams.count())));
auto inputs_on_gpu = std::min(
(int)num_input_blocks,
std::max(threshold, get_num_inputs_on_gpu(num_input_blocks, 0,
active_streams.count())));
if (inputs_on_gpu >= get_threshold_ks_gemm()) {
for (auto i = 0; i < active_streams.count(); ++i) {
@@ -796,16 +809,20 @@ struct int_radix_lut_custom_input_output {
void allocate_lwe_vector_for_non_trivial_indexes(
CudaStreams streams, uint64_t max_num_radix_blocks,
uint64_t &size_tracker, bool allocate_gpu_memory) {
int threshold = (params.pbs_type == PBS_TYPE::MULTI_BIT)
? THRESHOLD_MULTI_GPU_WITH_MULTI_BIT_PARAMS
: THRESHOLD_MULTI_GPU_WITH_CLASSICAL_PARAMS;
// We need to create the auxiliary array only in GPU 0
if (active_streams.count() > 1) {
lwe_aligned_vec.resize(active_streams.count());
for (uint i = 0; i < active_streams.count(); i++) {
uint64_t size_tracker_on_array_i = 0;
auto inputs_on_gpu =
std::min((int)max_num_radix_blocks,
std::max(THRESHOLD_MULTI_GPU,
get_num_inputs_on_gpu(max_num_radix_blocks, i,
active_streams.count())));
auto inputs_on_gpu = std::min(
(int)max_num_radix_blocks,
std::max(threshold, get_num_inputs_on_gpu(max_num_radix_blocks, i,
active_streams.count())));
InputTorus *d_array =
(InputTorus *)cuda_malloc_with_size_tracking_async(
inputs_on_gpu * (params.big_lwe_dimension + 1) *
@@ -996,8 +1013,8 @@ template <typename Torus> struct int_bit_extract_luts_buffer {
num_radix_blocks * bits_per_block * sizeof(Torus), streams.stream(0),
streams.gpu_index(0), allocate_gpu_memory);
auto active_streams =
streams.active_gpu_subset(bits_per_block * num_radix_blocks);
auto active_streams = streams.active_gpu_subset(
bits_per_block * num_radix_blocks, params.pbs_type);
lut->broadcast_lut(active_streams);
/**
@@ -1264,7 +1281,8 @@ template <typename Torus> struct int_sum_ciphertexts_vec_memory {
luts_message_carry->get_max_degree(1), params.glwe_dimension,
params.polynomial_size, message_modulus, params.carry_modulus,
lut_f_carry, gpu_memory_allocated);
auto active_gpu_count_mc = streams.active_gpu_subset(pbs_count);
auto active_gpu_count_mc =
streams.active_gpu_subset(pbs_count, params.pbs_type);
luts_message_carry->broadcast_lut(active_gpu_count_mc);
}
}
@@ -1434,7 +1452,8 @@ template <typename Torus> struct int_seq_group_prop_memory {
cuda_memcpy_with_size_tracking_async_to_gpu(
seq_lut_indexes, h_seq_lut_indexes, num_seq_luts * sizeof(Torus),
streams.stream(0), streams.gpu_index(0), allocate_gpu_memory);
auto active_streams = streams.active_gpu_subset(num_seq_luts);
auto active_streams =
streams.active_gpu_subset(num_seq_luts, params.pbs_type);
lut_sequential_algorithm->broadcast_lut(active_streams);
free(h_seq_lut_indexes);
};
@@ -1488,7 +1507,8 @@ template <typename Torus> struct int_hs_group_prop_memory {
lut_hillis_steele->get_max_degree(0), glwe_dimension, polynomial_size,
message_modulus, carry_modulus, f_lut_hillis_steele,
gpu_memory_allocated);
auto active_streams = streams.active_gpu_subset(num_groups);
auto active_streams =
streams.active_gpu_subset(num_groups, params.pbs_type);
lut_hillis_steele->broadcast_lut(active_streams);
};
void release(CudaStreams streams) {
@@ -1665,7 +1685,8 @@ template <typename Torus> struct int_shifted_blocks_and_states_memory {
lut_indexes, h_lut_indexes, lut_indexes_size, streams.stream(0),
streams.gpu_index(0), allocate_gpu_memory);
// Do I need to do something else for the multi-gpu?
auto active_streams = streams.active_gpu_subset(num_radix_blocks);
auto active_streams =
streams.active_gpu_subset(num_radix_blocks, params.pbs_type);
luts_array_first_step->broadcast_lut(active_streams);
};
void release(CudaStreams streams) {
@@ -1930,7 +1951,8 @@ template <typename Torus> struct int_prop_simu_group_carries_memory {
scalar_array_cum_sum, h_scalar_array_cum_sum,
num_radix_blocks * sizeof(Torus), streams.stream(0),
streams.gpu_index(0), allocate_gpu_memory);
auto active_streams = streams.active_gpu_subset(num_radix_blocks);
auto active_streams =
streams.active_gpu_subset(num_radix_blocks, params.pbs_type);
luts_array_second_step->broadcast_lut(active_streams);
if (use_sequential_algorithm_to_resolve_group_carries) {
@@ -1955,7 +1977,8 @@ template <typename Torus> struct int_prop_simu_group_carries_memory {
cuda_memcpy_with_size_tracking_async_gpu_to_gpu(
lut_indexes, new_lut_indexes, new_num_blocks * sizeof(Torus),
streams.stream(0), streams.gpu_index(0), gpu_memory_allocated);
auto new_active_streams = streams.active_gpu_subset(new_num_blocks);
auto new_active_streams = streams.active_gpu_subset(
new_num_blocks, luts_array_second_step->params.pbs_type);
// We just need to update the lut indexes so we use false here
luts_array_second_step->broadcast_lut(new_active_streams, false);
@@ -2122,7 +2145,7 @@ template <typename Torus> struct int_sc_prop_memory {
polynomial_size, message_modulus, carry_modulus, f_overflow_fp,
gpu_memory_allocated);
auto active_streams = streams.active_gpu_subset(1);
auto active_streams = streams.active_gpu_subset(1, params.pbs_type);
lut_overflow_flag_prep->broadcast_lut(active_streams);
}
@@ -2194,7 +2217,8 @@ template <typename Torus> struct int_sc_prop_memory {
(num_radix_blocks + 1) * sizeof(Torus), streams.stream(0),
streams.gpu_index(0), allocate_gpu_memory);
}
auto active_streams = streams.active_gpu_subset(num_radix_blocks + 1);
auto active_streams =
streams.active_gpu_subset(num_radix_blocks + 1, params.pbs_type);
lut_message_extract->broadcast_lut(active_streams);
};
@@ -2391,7 +2415,8 @@ template <typename Torus> struct int_shifted_blocks_and_borrow_states_memory {
lut_indexes, h_lut_indexes, lut_indexes_size, streams.stream(0),
streams.gpu_index(0), allocate_gpu_memory);
// Do I need to do something else for the multi-gpu?
auto active_streams = streams.active_gpu_subset(num_radix_blocks);
auto active_streams =
streams.active_gpu_subset(num_radix_blocks, params.pbs_type);
luts_array_first_step->broadcast_lut(active_streams);
};
@@ -2402,7 +2427,8 @@ template <typename Torus> struct int_shifted_blocks_and_borrow_states_memory {
cuda_memcpy_with_size_tracking_async_gpu_to_gpu(
lut_indexes, new_lut_indexes, new_num_blocks * sizeof(Torus),
streams.stream(0), streams.gpu_index(0), gpu_memory_allocated);
auto new_active_streams = streams.active_gpu_subset(new_num_blocks);
auto new_active_streams = streams.active_gpu_subset(
new_num_blocks, luts_array_first_step->params.pbs_type);
// We just need to update the lut indexes so we use false here
luts_array_first_step->broadcast_lut(new_active_streams, false);
}
@@ -2497,7 +2523,8 @@ template <typename Torus> struct int_borrow_prop_memory {
lut_message_extract->get_max_degree(0), glwe_dimension, polynomial_size,
message_modulus, carry_modulus, f_message_extract,
gpu_memory_allocated);
active_streams = streams.active_gpu_subset(num_radix_blocks);
active_streams =
streams.active_gpu_subset(num_radix_blocks, params.pbs_type);
lut_message_extract->broadcast_lut(active_streams);
@@ -2518,7 +2545,8 @@ template <typename Torus> struct int_borrow_prop_memory {
lut_borrow_flag->broadcast_lut(active_streams);
}
active_streams = streams.active_gpu_subset(num_radix_blocks);
active_streams =
streams.active_gpu_subset(num_radix_blocks, params.pbs_type);
internal_streams.create_internal_cuda_streams_on_same_gpus(active_streams,
2);
};

View File

@@ -45,7 +45,8 @@ template <typename Torus> struct int_mul_memory {
params.polynomial_size, params.message_modulus, params.carry_modulus,
zero_out_predicate_lut_f, gpu_memory_allocated);
auto active_streams = streams.active_gpu_subset(num_radix_blocks);
auto active_streams =
streams.active_gpu_subset(num_radix_blocks, params.pbs_type);
zero_out_predicate_lut->broadcast_lut(active_streams);
zero_out_mem = new int_zero_out_if_buffer<Torus>(
@@ -122,7 +123,8 @@ template <typename Torus> struct int_mul_memory {
streams.stream(0), streams.gpu_index(0),
luts_array->get_lut_indexes(0, lsb_vector_block_count), 1,
msb_vector_block_count);
auto active_streams = streams.active_gpu_subset(total_block_count);
auto active_streams =
streams.active_gpu_subset(total_block_count, params.pbs_type);
luts_array->broadcast_lut(active_streams);
// create memory object for sum ciphertexts
sum_ciphertexts_mem = new int_sum_ciphertexts_vec_memory<Torus>(

View File

@@ -126,9 +126,11 @@ template <typename Torus> struct int_grouped_oprf_memory {
luts->get_lut_indexes(0, 0), this->h_lut_indexes,
num_blocks_to_process * sizeof(Torus), streams.stream(0),
streams.gpu_index(0), allocate_gpu_memory);
auto active_streams = streams.active_gpu_subset(num_blocks_to_process);
auto active_streams =
streams.active_gpu_subset(num_blocks_to_process, params.pbs_type);
luts->broadcast_lut(active_streams);
cuda_synchronize_stream(streams.stream(0), streams.gpu_index(0));
free(h_corrections);
}

View File

@@ -6,6 +6,8 @@ void release_radix_ciphertext_async(cudaStream_t const stream,
CudaRadixCiphertextFFI *data,
const bool gpu_memory_allocated);
void release_cpu_radix_ciphertext_async(CudaRadixCiphertextFFI *data);
void reset_radix_ciphertext_blocks(CudaRadixCiphertextFFI *data,
uint32_t new_num_blocks);

View File

@@ -91,7 +91,8 @@ template <typename Torus> struct int_logical_scalar_shift_buffer {
cur_lut_bivariate->get_max_degree(0), params.glwe_dimension,
params.polynomial_size, params.message_modulus, params.carry_modulus,
shift_lut_f, gpu_memory_allocated);
auto active_streams = streams.active_gpu_subset(num_radix_blocks);
auto active_streams =
streams.active_gpu_subset(num_radix_blocks, params.pbs_type);
cur_lut_bivariate->broadcast_lut(active_streams);
lut_buffers_bivariate.push_back(cur_lut_bivariate);
@@ -177,7 +178,8 @@ template <typename Torus> struct int_logical_scalar_shift_buffer {
cur_lut_bivariate->get_max_degree(0), params.glwe_dimension,
params.polynomial_size, params.message_modulus, params.carry_modulus,
shift_lut_f, gpu_memory_allocated);
auto active_streams = streams.active_gpu_subset(num_radix_blocks);
auto active_streams =
streams.active_gpu_subset(num_radix_blocks, params.pbs_type);
cur_lut_bivariate->broadcast_lut(active_streams);
lut_buffers_bivariate.push_back(cur_lut_bivariate);
@@ -220,7 +222,7 @@ template <typename Torus> struct int_arithmetic_scalar_shift_buffer {
uint64_t &size_tracker) {
gpu_memory_allocated = allocate_gpu_memory;
auto active_streams = streams.active_gpu_subset(1);
auto active_streams = streams.active_gpu_subset(1, params.pbs_type);
// In the arithmetic shift, a PBS has to be applied to the last rotated
// block twice: once to shift it, once to compute the padding block to be
// copied onto all blocks to the left of the last rotated block
@@ -276,7 +278,8 @@ template <typename Torus> struct int_arithmetic_scalar_shift_buffer {
shift_last_block_lut_univariate->get_max_degree(0),
params.glwe_dimension, params.polynomial_size, params.message_modulus,
params.carry_modulus, last_block_lut_f, gpu_memory_allocated);
auto active_streams_shift_last = streams.active_gpu_subset(1);
auto active_streams_shift_last =
streams.active_gpu_subset(1, params.pbs_type);
shift_last_block_lut_univariate->broadcast_lut(active_streams_shift_last);
lut_buffers_univariate.push_back(shift_last_block_lut_univariate);
@@ -302,7 +305,7 @@ template <typename Torus> struct int_arithmetic_scalar_shift_buffer {
padding_block_lut_univariate->get_max_degree(0), params.glwe_dimension,
params.polynomial_size, params.message_modulus, params.carry_modulus,
padding_block_lut_f, gpu_memory_allocated);
// auto active_streams = streams.active_gpu_subset(1);
// auto active_streams = streams.active_gpu_subset(1, params.pbs_type);
padding_block_lut_univariate->broadcast_lut(active_streams);
lut_buffers_univariate.push_back(padding_block_lut_univariate);
@@ -344,7 +347,7 @@ template <typename Torus> struct int_arithmetic_scalar_shift_buffer {
params.polynomial_size, params.message_modulus, params.carry_modulus,
blocks_lut_f, gpu_memory_allocated);
auto active_streams_shift_blocks =
streams.active_gpu_subset(num_radix_blocks);
streams.active_gpu_subset(num_radix_blocks, params.pbs_type);
shift_blocks_lut_bivariate->broadcast_lut(active_streams_shift_blocks);
lut_buffers_bivariate.push_back(shift_blocks_lut_bivariate);

View File

@@ -119,8 +119,8 @@ template <typename Torus> struct int_shift_and_rotate_buffer {
mux_lut->get_degree(0), mux_lut->get_max_degree(0),
params.glwe_dimension, params.polynomial_size, params.message_modulus,
params.carry_modulus, mux_lut_f, gpu_memory_allocated);
auto active_gpu_count_mux =
streams.active_gpu_subset(bits_per_block * num_radix_blocks);
auto active_gpu_count_mux = streams.active_gpu_subset(
bits_per_block * num_radix_blocks, params.pbs_type);
mux_lut->broadcast_lut(active_gpu_count_mux);
auto cleaning_lut_f = [params](Torus x) -> Torus {
@@ -132,7 +132,7 @@ template <typename Torus> struct int_shift_and_rotate_buffer {
params.glwe_dimension, params.polynomial_size, params.message_modulus,
params.carry_modulus, cleaning_lut_f, gpu_memory_allocated);
auto active_gpu_count_cleaning =
streams.active_gpu_subset(num_radix_blocks);
streams.active_gpu_subset(num_radix_blocks, params.pbs_type);
cleaning_lut->broadcast_lut(active_gpu_count_cleaning);
}

View File

@@ -108,7 +108,8 @@ template <typename Torus> struct int_overflowing_sub_memory {
glwe_dimension, polynomial_size, message_modulus, carry_modulus,
f_message_acc, gpu_memory_allocated);
auto active_streams = streams.active_gpu_subset(num_radix_blocks);
auto active_streams =
streams.active_gpu_subset(num_radix_blocks, params.pbs_type);
luts_array->broadcast_lut(active_streams);
luts_borrow_propagation_sum->broadcast_lut(active_streams);
message_acc->broadcast_lut(active_streams);

View File

@@ -38,7 +38,8 @@ template <typename Torus> struct int_unchecked_all_eq_slices_buffer {
num_streams_to_use = 1;
this->num_streams = num_streams_to_use;
this->active_streams = streams.active_gpu_subset(num_blocks);
this->active_streams =
streams.active_gpu_subset(num_blocks, params.pbs_type);
uint32_t num_gpus = active_streams.count();

View File

@@ -40,7 +40,8 @@ template <typename Torus> struct int_equality_selectors_buffer {
this->num_streams = num_streams_to_use;
this->active_streams = streams.active_gpu_subset(num_blocks);
this->active_streams =
streams.active_gpu_subset(num_blocks, params.pbs_type);
this->internal_cuda_streams.create_internal_cuda_streams_on_same_gpus(
active_streams, num_streams_to_use);
@@ -154,7 +155,8 @@ template <typename Torus> struct int_possible_results_buffer {
this->num_streams = num_streams_to_use;
this->active_streams = streams.active_gpu_subset(num_blocks);
this->active_streams =
streams.active_gpu_subset(num_blocks, params.pbs_type);
this->internal_cuda_streams.create_internal_cuda_streams_on_same_gpus(
active_streams, num_streams_to_use);
@@ -207,7 +209,8 @@ template <typename Torus> struct int_possible_results_buffer {
params.message_modulus, params.carry_modulus, fns,
allocate_gpu_memory);
current_lut->broadcast_lut(streams.active_gpu_subset(1));
current_lut->broadcast_lut(
streams.active_gpu_subset(1, params.pbs_type));
stream_luts[lut_count++] = current_lut;
lut_value_start += luts_in_this_call;
}
@@ -282,7 +285,8 @@ template <typename Torus> struct int_aggregate_one_hot_buffer {
this->num_streams = num_streams_to_use;
this->active_streams = streams.active_gpu_subset(num_blocks);
this->active_streams =
streams.active_gpu_subset(num_blocks, params.pbs_type);
this->internal_cuda_streams.create_internal_cuda_streams_on_same_gpus(
active_streams, num_streams);
@@ -300,7 +304,8 @@ template <typename Torus> struct int_aggregate_one_hot_buffer {
params.polynomial_size, params.message_modulus, params.carry_modulus,
id_fn, allocate_gpu_memory);
lut->broadcast_lut(streams.active_gpu_subset(num_blocks));
lut->broadcast_lut(
streams.active_gpu_subset(num_blocks, params.pbs_type));
this->stream_identity_luts[i] = lut;
}
@@ -321,7 +326,7 @@ template <typename Torus> struct int_aggregate_one_hot_buffer {
params.polynomial_size, params.message_modulus, params.carry_modulus,
msg_fn, allocate_gpu_memory);
this->message_extract_lut->broadcast_lut(
streams.active_gpu_subset(num_blocks));
streams.active_gpu_subset(num_blocks, params.pbs_type));
this->carry_extract_lut = new int_radix_lut<Torus>(
streams, params, 1, num_blocks, allocate_gpu_memory, size_tracker);
@@ -333,7 +338,7 @@ template <typename Torus> struct int_aggregate_one_hot_buffer {
params.polynomial_size, params.message_modulus, params.carry_modulus,
carry_fn, allocate_gpu_memory);
this->carry_extract_lut->broadcast_lut(
streams.active_gpu_subset(num_blocks));
streams.active_gpu_subset(num_blocks, params.pbs_type));
this->partial_aggregated_vectors =
new CudaRadixCiphertextFFI *[num_streams];
@@ -628,7 +633,8 @@ template <typename Torus> struct int_unchecked_contains_buffer {
num_streams_to_use = 1;
this->num_streams = num_streams_to_use;
this->active_streams = streams.active_gpu_subset(num_blocks);
this->active_streams =
streams.active_gpu_subset(num_blocks, params.pbs_type);
this->internal_cuda_streams.create_internal_cuda_streams_on_same_gpus(
active_streams, num_streams_to_use);
@@ -703,7 +709,8 @@ template <typename Torus> struct int_unchecked_contains_clear_buffer {
num_streams_to_use = 1;
this->num_streams = num_streams_to_use;
this->active_streams = streams.active_gpu_subset(num_blocks);
this->active_streams =
streams.active_gpu_subset(num_blocks, params.pbs_type);
this->internal_cuda_streams.create_internal_cuda_streams_on_same_gpus(
active_streams, num_streams_to_use);
@@ -1094,7 +1101,8 @@ template <typename Torus> struct int_unchecked_first_index_of_clear_buffer {
num_streams_to_use = 1;
this->num_streams = num_streams_to_use;
this->active_streams = streams.active_gpu_subset(num_blocks);
this->active_streams =
streams.active_gpu_subset(num_blocks, params.pbs_type);
this->internal_cuda_streams.create_internal_cuda_streams_on_same_gpus(
active_streams, num_streams_to_use);
@@ -1184,7 +1192,8 @@ template <typename Torus> struct int_unchecked_first_index_of_clear_buffer {
this->prefix_sum_lut->get_max_degree(0), params.glwe_dimension,
params.polynomial_size, params.message_modulus, params.carry_modulus,
prefix_sum_fn, allocate_gpu_memory);
this->prefix_sum_lut->broadcast_lut(streams.active_gpu_subset(num_inputs));
this->prefix_sum_lut->broadcast_lut(
streams.active_gpu_subset(num_inputs, params.pbs_type));
auto cleanup_fn = [ALREADY_SEEN, params](Torus x) -> Torus {
Torus val = x % params.message_modulus;
@@ -1200,7 +1209,8 @@ template <typename Torus> struct int_unchecked_first_index_of_clear_buffer {
this->cleanup_lut->get_max_degree(0), params.glwe_dimension,
params.polynomial_size, params.message_modulus, params.carry_modulus,
cleanup_fn, allocate_gpu_memory);
this->cleanup_lut->broadcast_lut(streams.active_gpu_subset(num_inputs));
this->cleanup_lut->broadcast_lut(
streams.active_gpu_subset(num_inputs, params.pbs_type));
}
void release(CudaStreams streams) {
@@ -1292,7 +1302,8 @@ template <typename Torus> struct int_unchecked_first_index_of_buffer {
num_streams_to_use = 1;
this->num_streams = num_streams_to_use;
this->active_streams = streams.active_gpu_subset(num_blocks);
this->active_streams =
streams.active_gpu_subset(num_blocks, params.pbs_type);
this->internal_cuda_streams.create_internal_cuda_streams_on_same_gpus(
active_streams, num_streams_to_use);
@@ -1372,7 +1383,8 @@ template <typename Torus> struct int_unchecked_first_index_of_buffer {
this->prefix_sum_lut->get_max_degree(0), params.glwe_dimension,
params.polynomial_size, params.message_modulus, params.carry_modulus,
prefix_sum_fn, allocate_gpu_memory);
this->prefix_sum_lut->broadcast_lut(streams.active_gpu_subset(num_inputs));
this->prefix_sum_lut->broadcast_lut(
streams.active_gpu_subset(num_inputs, params.pbs_type));
auto cleanup_fn = [ALREADY_SEEN, params](Torus x) -> Torus {
Torus val = x % params.message_modulus;
@@ -1388,7 +1400,8 @@ template <typename Torus> struct int_unchecked_first_index_of_buffer {
this->cleanup_lut->get_max_degree(0), params.glwe_dimension,
params.polynomial_size, params.message_modulus, params.carry_modulus,
cleanup_fn, allocate_gpu_memory);
this->cleanup_lut->broadcast_lut(streams.active_gpu_subset(num_inputs));
this->cleanup_lut->broadcast_lut(
streams.active_gpu_subset(num_inputs, params.pbs_type));
}
void release(CudaStreams streams) {
@@ -1462,7 +1475,8 @@ template <typename Torus> struct int_unchecked_index_of_buffer {
num_streams_to_use = 1;
this->num_streams = num_streams_to_use;
this->active_streams = streams.active_gpu_subset(num_blocks);
this->active_streams =
streams.active_gpu_subset(num_blocks, params.pbs_type);
this->internal_cuda_streams.create_internal_cuda_streams_on_same_gpus(
active_streams, num_streams_to_use);
@@ -1523,7 +1537,8 @@ template <typename Torus> struct int_unchecked_index_of_clear_buffer {
num_streams_to_use = 1;
this->num_streams = num_streams_to_use;
this->active_streams = streams.active_gpu_subset(num_blocks);
this->active_streams =
streams.active_gpu_subset(num_blocks, params.pbs_type);
this->internal_cuda_streams.create_internal_cuda_streams_on_same_gpus(
active_streams, num_streams_to_use);

View File

@@ -5,21 +5,14 @@
extern "C" {
void cuda_keyswitch_lwe_ciphertext_vector_32(
void cuda_keyswitch_lwe_ciphertext_vector_64_64(
void *stream, uint32_t gpu_index, void *lwe_array_out,
void const *lwe_output_indexes, void const *lwe_array_in,
void const *lwe_input_indexes, void const *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_gemm_lwe_ciphertext_vector_64(
void *stream, uint32_t gpu_index, void *lwe_array_out,
void const *lwe_output_indexes, void const *lwe_array_in,
void const *lwe_input_indexes, void const *ksk, uint32_t lwe_dimension_in,
uint32_t lwe_dimension_out, uint32_t base_log, uint32_t level_count,
uint32_t num_samples, const void *ks_tmp_buffer, bool uses_trivial_indexes);
void cuda_keyswitch_lwe_ciphertext_vector_64(
void cuda_keyswitch_lwe_ciphertext_vector_64_32(
void *stream, uint32_t gpu_index, void *lwe_array_out,
void const *lwe_output_indexes, void const *lwe_array_in,
void const *lwe_input_indexes, void const *ksk, uint32_t lwe_dimension_in,
@@ -31,6 +24,20 @@ uint64_t scratch_packing_keyswitch_lwe_list_to_glwe_64(
uint32_t lwe_dimension, uint32_t glwe_dimension, uint32_t polynomial_size,
uint32_t num_lwes, bool allocate_gpu_memory);
void cuda_keyswitch_gemm_lwe_ciphertext_vector_64_64(
void *stream, uint32_t gpu_index, void *lwe_array_out,
void const *lwe_output_indexes, void const *lwe_array_in,
void const *lwe_input_indexes, void const *ksk, uint32_t lwe_dimension_in,
uint32_t lwe_dimension_out, uint32_t base_log, uint32_t level_count,
uint32_t num_samples, const void *ks_tmp_buffer, bool uses_trivial_indexes);
void cuda_keyswitch_gemm_lwe_ciphertext_vector_64_32(
void *stream, uint32_t gpu_index, void *lwe_array_out,
void const *lwe_output_indexes, void const *lwe_array_in,
void const *lwe_input_indexes, void const *ksk, uint32_t lwe_dimension_in,
uint32_t lwe_dimension_out, uint32_t base_log, uint32_t level_count,
uint32_t num_samples, const void *ks_tmp_buffer, bool uses_trivial_indexes);
uint64_t scratch_cuda_keyswitch_gemm_64(void *stream, uint32_t gpu_index,
void **ks_tmp_memory,
uint32_t lwe_dimension_in,
@@ -65,6 +72,10 @@ void cleanup_packing_keyswitch_lwe_list_to_glwe(void *stream,
uint32_t gpu_index,
int8_t **fp_ks_buffer,
bool gpu_memory_allocated);
void cuda_closest_representable_64(void *stream, uint32_t gpu_index,
void const *input, void *output,
uint32_t base_log, uint32_t level_count);
}
#endif // CNCRT_KS_H_

View File

@@ -47,7 +47,7 @@ template <typename Torus> struct compact_lwe_list {
template <typename Torus> struct flattened_compact_lwe_lists {
Torus *d_ptr;
Torus **d_ptr_to_compact_list;
Torus **ptr_array_to_d_compact_list;
const uint32_t *h_num_lwes_per_compact_list;
uint32_t num_compact_lists;
uint32_t lwe_dimension;
@@ -59,13 +59,13 @@ template <typename Torus> struct flattened_compact_lwe_lists {
uint32_t lwe_dimension)
: d_ptr(d_ptr), h_num_lwes_per_compact_list(h_num_lwes_per_compact_list),
num_compact_lists(num_compact_lists), lwe_dimension(lwe_dimension) {
d_ptr_to_compact_list =
static_cast<Torus **>(malloc(num_compact_lists * sizeof(Torus **)));
ptr_array_to_d_compact_list =
static_cast<Torus **>(malloc(num_compact_lists * sizeof(Torus *)));
total_num_lwes = 0;
auto curr_list = d_ptr;
for (auto i = 0; i < num_compact_lists; ++i) {
total_num_lwes += h_num_lwes_per_compact_list[i];
d_ptr_to_compact_list[i] = curr_list;
ptr_array_to_d_compact_list[i] = curr_list;
curr_list += lwe_dimension + h_num_lwes_per_compact_list[i];
}
}
@@ -75,10 +75,12 @@ template <typename Torus> struct flattened_compact_lwe_lists {
PANIC("index out of range in flattened_compact_lwe_lists::get");
}
return compact_lwe_list(d_ptr_to_compact_list[compact_list_index],
return compact_lwe_list(ptr_array_to_d_compact_list[compact_list_index],
lwe_dimension,
h_num_lwes_per_compact_list[compact_list_index]);
}
void release() { free(ptr_array_to_d_compact_list); }
};
/*
@@ -121,7 +123,6 @@ template <typename Torus> struct zk_expand_mem {
: computing_params(computing_params), casting_params(casting_params),
num_compact_lists(num_compact_lists),
casting_key_type(casting_key_type) {
gpu_memory_allocated = allocate_gpu_memory;
// We copy num_lwes_per_compact_list so we get protection against
@@ -289,7 +290,8 @@ template <typename Torus> struct zk_expand_mem {
lut_indexes, h_lut_indexes, num_packed_msgs * num_lwes * sizeof(Torus),
streams.stream(0), streams.gpu_index(0), allocate_gpu_memory);
auto active_streams = streams.active_gpu_subset(2 * num_lwes);
auto active_streams =
streams.active_gpu_subset(2 * num_lwes, params.pbs_type);
message_and_carry_extract_luts->broadcast_lut(active_streams);
message_and_carry_extract_luts->allocate_lwe_vector_for_non_trivial_indexes(
@@ -313,7 +315,6 @@ template <typename Torus> struct zk_expand_mem {
}
void release(CudaStreams streams) {
message_and_carry_extract_luts->release(streams);
delete message_and_carry_extract_luts;

View File

@@ -105,11 +105,11 @@ aes_xor(CudaStreams streams, int_aes_encrypt_buffer<Torus> *mem,
* result.
*
*/
template <typename Torus>
template <typename Torus, typename KSTorus>
__host__ __forceinline__ void
aes_flush_inplace(CudaStreams streams, CudaRadixCiphertextFFI *data,
int_aes_encrypt_buffer<Torus> *mem, void *const *bsks,
Torus *const *ksks) {
KSTorus *const *ksks) {
integer_radix_apply_univariate_lookup_table<Torus>(streams, data, data, bsks,
ksks, mem->luts->flush_lut,
@@ -121,10 +121,12 @@ aes_flush_inplace(CudaStreams streams, CudaRadixCiphertextFFI *data,
* ciphertext, then flushes the result to ensure it's a valid bit.
*
*/
template <typename Torus>
__host__ __forceinline__ void aes_scalar_add_one_flush_inplace(
CudaStreams streams, CudaRadixCiphertextFFI *data,
int_aes_encrypt_buffer<Torus> *mem, void *const *bsks, Torus *const *ksks) {
template <typename Torus, typename KSTorus>
__host__ __forceinline__ void
aes_scalar_add_one_flush_inplace(CudaStreams streams,
CudaRadixCiphertextFFI *data,
int_aes_encrypt_buffer<Torus> *mem,
void *const *bsks, KSTorus *const *ksks) {
host_add_scalar_one_inplace<Torus>(streams, data, mem->params.message_modulus,
mem->params.carry_modulus);
@@ -142,11 +144,11 @@ __host__ __forceinline__ void aes_scalar_add_one_flush_inplace(
* ciphertext locations.
*
*/
template <typename Torus>
template <typename Torus, typename KSTorus>
__host__ void
batch_vec_flush_inplace(CudaStreams streams, CudaRadixCiphertextFFI **targets,
size_t count, int_aes_encrypt_buffer<Torus> *mem,
void *const *bsks, Torus *const *ksks) {
void *const *bsks, KSTorus *const *ksks) {
uint32_t num_radix_blocks = targets[0]->num_radix_blocks;
@@ -185,13 +187,13 @@ batch_vec_flush_inplace(CudaStreams streams, CudaRadixCiphertextFFI **targets,
* Batches multiple "and" operations into a single, large launch.
*
*/
template <typename Torus>
template <typename Torus, typename KSTorus>
__host__ void batch_vec_and_inplace(CudaStreams streams,
CudaRadixCiphertextFFI **outs,
CudaRadixCiphertextFFI **lhs,
CudaRadixCiphertextFFI **rhs, size_t count,
int_aes_encrypt_buffer<Torus> *mem,
void *const *bsks, Torus *const *ksks) {
void *const *bsks, KSTorus *const *ksks) {
uint32_t num_aes_inputs = outs[0]->num_radix_blocks;
@@ -274,13 +276,13 @@ __host__ void batch_vec_and_inplace(CudaStreams streams,
* [ptr] -> [R2b0, R2b1, R2b2, R2b3, R2b4, R2b5, R2b6, R2b7]
* ...
*/
template <typename Torus>
template <typename Torus, typename KSTorus>
__host__ void vectorized_sbox_n_bytes(CudaStreams streams,
CudaRadixCiphertextFFI **sbox_io_bytes,
uint32_t num_bytes_parallel,
uint32_t num_aes_inputs,
int_aes_encrypt_buffer<Torus> *mem,
void *const *bsks, Torus *const *ksks) {
void *const *bsks, KSTorus *const *ksks) {
uint32_t num_sbox_blocks = num_bytes_parallel * num_aes_inputs;
@@ -702,12 +704,12 @@ __host__ void vectorized_mul_by_2(CudaStreams streams,
* [ s'_3 ] [ 03 01 01 02 ] [ s_3 ]
*
*/
template <typename Torus>
template <typename Torus, typename KSTorus>
__host__ void vectorized_mix_columns(CudaStreams streams,
CudaRadixCiphertextFFI *s_bits,
uint32_t num_aes_inputs,
int_aes_encrypt_buffer<Torus> *mem,
void *const *bsks, Torus *const *ksks) {
void *const *bsks, KSTorus *const *ksks) {
constexpr uint32_t BITS_PER_BYTE = 8;
constexpr uint32_t BYTES_PER_COLUMN = 4;
@@ -842,11 +844,12 @@ __host__ void vectorized_mix_columns(CudaStreams streams,
* - AddRoundKey
*
*/
template <typename Torus>
template <typename Torus, typename KSTorus>
__host__ void vectorized_aes_encrypt_inplace(
CudaStreams streams, CudaRadixCiphertextFFI *all_states_bitsliced,
CudaRadixCiphertextFFI const *round_keys, uint32_t num_aes_inputs,
int_aes_encrypt_buffer<Torus> *mem, void *const *bsks, Torus *const *ksks) {
int_aes_encrypt_buffer<Torus> *mem, void *const *bsks,
KSTorus *const *ksks) {
constexpr uint32_t BITS_PER_BYTE = 8;
constexpr uint32_t STATE_BYTES = 16;
@@ -987,11 +990,12 @@ __host__ void vectorized_aes_encrypt_inplace(
* The "transposed_states" buffer is updated in-place with the sum bits $S_i$.
*
*/
template <typename Torus>
template <typename Torus, typename KSTorus>
__host__ void vectorized_aes_full_adder_inplace(
CudaStreams streams, CudaRadixCiphertextFFI *transposed_states,
const Torus *counter_bits_le_all_blocks, uint32_t num_aes_inputs,
int_aes_encrypt_buffer<Torus> *mem, void *const *bsks, Torus *const *ksks) {
int_aes_encrypt_buffer<Torus> *mem, void *const *bsks,
KSTorus *const *ksks) {
constexpr uint32_t NUM_BITS = 128;
@@ -1091,12 +1095,13 @@ __host__ void vectorized_aes_full_adder_inplace(
* +---------------------------------+
*
*/
template <typename Torus>
template <typename Torus, typename KSTorus>
__host__ void host_integer_aes_ctr_encrypt(
CudaStreams streams, CudaRadixCiphertextFFI *output,
CudaRadixCiphertextFFI const *iv, CudaRadixCiphertextFFI const *round_keys,
const Torus *counter_bits_le_all_blocks, uint32_t num_aes_inputs,
int_aes_encrypt_buffer<Torus> *mem, void *const *bsks, Torus *const *ksks) {
int_aes_encrypt_buffer<Torus> *mem, void *const *bsks,
KSTorus *const *ksks) {
constexpr uint32_t NUM_BITS = 128;
@@ -1148,13 +1153,13 @@ uint64_t scratch_cuda_integer_key_expansion(
* - If (i % 4 == 0): w_i = w_{i-4} + SubWord(RotWord(w_{i-1})) + Rcon[i/4]
* - If (i % 4 != 0): w_i = w_{i-4} + w_{i-1}
*/
template <typename Torus>
template <typename Torus, typename KSTorus>
__host__ void host_integer_key_expansion(CudaStreams streams,
CudaRadixCiphertextFFI *expanded_keys,
CudaRadixCiphertextFFI const *key,
int_key_expansion_buffer<Torus> *mem,
void *const *bsks,
Torus *const *ksks) {
KSTorus *const *ksks) {
constexpr uint32_t BITS_PER_WORD = 32;
constexpr uint32_t BITS_PER_BYTE = 8;

View File

@@ -2,26 +2,9 @@
#include "keyswitch/keyswitch.h"
#include "packing_keyswitch.cuh"
/* 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(
void *stream, uint32_t gpu_index, 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 *ksk_tmp_buffer, bool uses_trivial_indices) {
host_gemm_keyswitch_lwe_ciphertext_vector<uint32_t>(
static_cast<cudaStream_t>(stream), gpu_index,
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,
static_cast<uint32_t *>(ksk_tmp_buffer), uses_trivial_indices);
}
/* Perform keyswitch on a batch of 64 bits input LWE ciphertexts.
/* Perform keyswitch on a batch of 64 bits input LWE ciphertexts
* using a 64-b key-switching key. Uses the GEMM approach which
* achieves good throughput on large batches (128 LWEs on H100)
*
* - `v_stream` is a void pointer to the Cuda stream to be used in the kernel
* launch
@@ -37,7 +20,7 @@ void cuda_keyswitch_lwe_ciphertext_vector_32(
* This function calls a wrapper to a device kernel that performs the keyswitch
* - num_samples blocks of threads are launched
*/
void cuda_keyswitch_gemm_lwe_ciphertext_vector_64(
void cuda_keyswitch_gemm_lwe_ciphertext_vector_64_64(
void *stream, uint32_t gpu_index, void *lwe_array_out,
void const *lwe_output_indexes, void const *lwe_array_in,
void const *lwe_input_indexes, void const *ksk, uint32_t lwe_dimension_in,
@@ -45,7 +28,7 @@ void cuda_keyswitch_gemm_lwe_ciphertext_vector_64(
uint32_t num_samples, const void *ks_tmp_buffer,
bool uses_trivial_indices) {
host_gemm_keyswitch_lwe_ciphertext_vector<uint64_t>(
host_gemm_keyswitch_lwe_ciphertext_vector<uint64_t, uint64_t>(
static_cast<cudaStream_t>(stream), gpu_index,
static_cast<uint64_t *>(lwe_array_out),
static_cast<const uint64_t *>(lwe_output_indexes),
@@ -57,13 +40,37 @@ void cuda_keyswitch_gemm_lwe_ciphertext_vector_64(
uses_trivial_indices);
}
void cuda_keyswitch_lwe_ciphertext_vector_64(
/* Perform keyswitch on a batch of 64 bits input LWE ciphertexts
* using a 32-b key-switching key, producing 32-bit LWE outputs.
* Uses the GEMM approach which achieves good throughput on large batches
*/
void cuda_keyswitch_gemm_lwe_ciphertext_vector_64_32(
void *stream, uint32_t gpu_index, void *lwe_array_out,
void const *lwe_output_indexes, void const *lwe_array_in,
void const *lwe_input_indexes, void const *ksk, uint32_t lwe_dimension_in,
uint32_t lwe_dimension_out, uint32_t base_log, uint32_t level_count,
uint32_t num_samples, const void *ks_tmp_buffer,
bool uses_trivial_indices) {
host_gemm_keyswitch_lwe_ciphertext_vector<uint64_t, uint32_t>(
static_cast<cudaStream_t>(stream), gpu_index,
static_cast<uint32_t *>(lwe_array_out),
static_cast<const uint64_t *>(lwe_output_indexes),
static_cast<const uint64_t *>(lwe_array_in),
static_cast<const uint64_t *>(lwe_input_indexes),
static_cast<const uint32_t *>(ksk), lwe_dimension_in, lwe_dimension_out,
base_log, level_count, num_samples,
static_cast<const ks_mem<uint64_t> *>(ks_tmp_buffer)->d_buffer,
uses_trivial_indices);
}
void cuda_keyswitch_lwe_ciphertext_vector_64_64(
void *stream, uint32_t gpu_index, void *lwe_array_out,
void const *lwe_output_indexes, void const *lwe_array_in,
void const *lwe_input_indexes, void const *ksk, uint32_t lwe_dimension_in,
uint32_t lwe_dimension_out, uint32_t base_log, uint32_t level_count,
uint32_t num_samples) {
host_keyswitch_lwe_ciphertext_vector<uint64_t>(
host_keyswitch_lwe_ciphertext_vector<uint64_t, uint64_t>(
static_cast<cudaStream_t>(stream), gpu_index,
static_cast<uint64_t *>(lwe_array_out),
static_cast<uint64_t const *>(lwe_output_indexes),
@@ -73,6 +80,22 @@ void cuda_keyswitch_lwe_ciphertext_vector_64(
base_log, level_count, num_samples);
}
void cuda_keyswitch_lwe_ciphertext_vector_64_32(
void *stream, uint32_t gpu_index, void *lwe_array_out,
void const *lwe_output_indexes, void const *lwe_array_in,
void const *lwe_input_indexes, void const *ksk, uint32_t lwe_dimension_in,
uint32_t lwe_dimension_out, uint32_t base_log, uint32_t level_count,
uint32_t num_samples) {
host_keyswitch_lwe_ciphertext_vector<uint64_t, uint32_t>(
static_cast<cudaStream_t>(stream), gpu_index,
static_cast<uint32_t *>(lwe_array_out),
static_cast<const uint64_t *>(lwe_output_indexes),
static_cast<const uint64_t *>(lwe_array_in),
static_cast<const uint64_t *>(lwe_input_indexes),
static_cast<const uint32_t *>(ksk), lwe_dimension_in, lwe_dimension_out,
base_log, level_count, num_samples);
}
uint64_t scratch_packing_keyswitch_lwe_list_to_glwe_64(
void *stream, uint32_t gpu_index, int8_t **fp_ks_buffer,
uint32_t lwe_dimension, uint32_t glwe_dimension, uint32_t polynomial_size,
@@ -159,3 +182,12 @@ void cuda_packing_keyswitch_lwe_list_to_glwe_128(
input_lwe_dimension, output_glwe_dimension, output_polynomial_size,
base_log, level_count, num_lwes);
}
void cuda_closest_representable_64(void *stream, uint32_t gpu_index,
void const *input, void *output,
uint32_t base_log, uint32_t level_count) {
host_cuda_closest_representable(static_cast<cudaStream_t>(stream), gpu_index,
static_cast<const uint64_t *>(input),
static_cast<uint64_t *>(output), base_log,
level_count);
}

View File

@@ -12,7 +12,6 @@
#include "utils/helper.cuh"
#include "utils/kernel_dimensions.cuh"
#include <thread>
#include <unistd.h>
#include <vector>
const int BLOCK_SIZE_DECOMP = 8;
@@ -46,10 +45,42 @@ __device__ Torus *get_ith_block(Torus *ksk, int i, int level,
return ptr;
}
template <typename T>
__device__ T closest_repr(T input, uint32_t base_log, uint32_t level_count) {
T minus_2 = static_cast<T>(-2);
const T rep_bit_count = level_count * base_log; // 32
const T non_rep_bit_count = sizeof(T) * 8 - rep_bit_count; // 32
auto shift = (non_rep_bit_count - 1); // 31
T res = input >> shift;
res++;
res &= minus_2;
res <<= shift;
return res;
}
template <typename T>
__global__ void closest_representable(const T *input, T *output,
uint32_t base_log, uint32_t level_count) {
output[0] = closest_repr(input[0], base_log, level_count);
}
template <typename T>
__host__ void
host_cuda_closest_representable(cudaStream_t stream, uint32_t gpu_index,
const T *input, T *output, uint32_t base_log,
uint32_t level_count) {
dim3 grid(1, 1, 1);
dim3 threads(1, 1, 1);
cuda_set_device(gpu_index);
closest_representable<<<grid, threads, 0, stream>>>(input, output, base_log,
level_count);
}
// Initialize decomposition by performing rounding
// and decomposing one level of an array of Torus LWEs. Only
// decomposes the mask elements of the incoming LWEs.
template <typename Torus>
template <typename Torus, typename KSTorus>
__global__ void decompose_vectorize_init(Torus const *lwe_in, Torus *lwe_out,
uint32_t lwe_dimension,
uint32_t num_lwe, uint32_t base_log,
@@ -76,7 +107,9 @@ __global__ void decompose_vectorize_init(Torus const *lwe_in, Torus *lwe_out,
Torus state = init_decomposer_state(a_i, base_log, level_count);
Torus mod_b_mask = (1ll << base_log) - 1ll;
lwe_out[write_val_idx] = decompose_one<Torus>(state, mod_b_mask, base_log);
KSTorus *kst_ptr_lwe_out = (KSTorus *)lwe_out;
kst_ptr_lwe_out[write_val_idx] =
decompose_one<Torus>(state, mod_b_mask, base_log);
__syncthreads();
lwe_out[write_state_idx] = state;
}
@@ -86,7 +119,7 @@ __global__ void decompose_vectorize_init(Torus const *lwe_in, Torus *lwe_out,
// from num_lwe. The maximum index should be <= total_lwe. num_lwe is the number
// of LWEs to decompose The output buffer should have space for num_lwe LWEs.
// These will be sorted according to the input indices.
template <typename Torus>
template <typename Torus, typename KSTorus>
__global__ void decompose_vectorize_init_with_indices(
Torus const *lwe_in, const Torus *__restrict__ lwe_input_indices,
Torus *lwe_out, uint32_t lwe_dimension, uint32_t num_lwe, uint32_t base_log,
@@ -114,7 +147,9 @@ __global__ void decompose_vectorize_init_with_indices(
Torus state = init_decomposer_state(a_i, base_log, level_count);
Torus mod_b_mask = (1ll << base_log) - 1ll;
lwe_out[write_val_idx] = decompose_one<Torus>(state, mod_b_mask, base_log);
KSTorus *kst_ptr_lwe_out = (KSTorus *)lwe_out;
kst_ptr_lwe_out[write_val_idx] =
decompose_one<Torus>(state, mod_b_mask, base_log);
__syncthreads();
lwe_out[write_state_idx] = state;
}
@@ -122,7 +157,7 @@ __global__ void decompose_vectorize_init_with_indices(
// Continue decomposition of an array of Torus elements in place. Supposes
// that the array contains already decomposed elements and
// computes the new decomposed level in place.
template <typename Torus>
template <typename Torus, typename KSTorus>
__global__ void
decompose_vectorize_step_inplace(Torus *buffer_in, uint32_t lwe_dimension,
uint32_t num_lwe, uint32_t base_log,
@@ -144,15 +179,22 @@ decompose_vectorize_step_inplace(Torus *buffer_in, uint32_t lwe_dimension,
Torus mod_b_mask = (1ll << base_log) - 1ll;
buffer_in[val_idx] = decompose_one<Torus>(state, mod_b_mask, base_log);
KSTorus *kst_ptr_lwe_out = (KSTorus *)buffer_in;
kst_ptr_lwe_out[val_idx] = decompose_one<Torus>(state, mod_b_mask, base_log);
__syncthreads();
buffer_in[state_idx] = state;
}
template <typename Torus>
/* LWEs inputs to the keyswitch function are stored as a_0,...,a_{lwe_dim},b,
* where a_i are mask elements and b is the message. We initialize
* the output keyswitched LWEs to 0, ..., 0, -b. The GEMM keyswitch is computed
* as:
* -(-b + sum(a_i A_KSK))
*/
template <typename Torus, typename KSTorus>
__global__ void keyswitch_gemm_copy_negated_message_with_indices(
const Torus *__restrict__ lwe_in,
const Torus *__restrict__ lwe_input_indices, Torus *__restrict__ lwe_out,
const Torus *__restrict__ lwe_input_indices, KSTorus *__restrict__ lwe_out,
const Torus *__restrict__ lwe_output_indices,
uint32_t lwe_dimension_in, uint32_t num_lwes, uint32_t lwe_dimension_out) {
@@ -165,16 +207,39 @@ __global__ void keyswitch_gemm_copy_negated_message_with_indices(
uint32_t lwe_in_idx = lwe_input_indices[lwe_id];
uint32_t lwe_out_idx = lwe_output_indices[lwe_id];
Torus body_in =
lwe_in[lwe_in_idx * (lwe_dimension_in + 1) + lwe_dimension_in];
Torus body_out;
if constexpr (std::is_same_v<KSTorus, Torus>) {
body_out = -body_in;
} else {
body_out = closest_repr(
lwe_in[lwe_in_idx * (lwe_dimension_in + 1) + lwe_dimension_in],
sizeof(KSTorus) * 8, 1);
// Power of two are encoded in the MSBs of the types so we need to scale
// the type to the other one without having to worry about the moduli
static_assert(sizeof(Torus) >= sizeof(KSTorus),
"Cannot compile keyswitch with given input/output dtypes");
Torus input_to_output_scaling_factor =
(sizeof(Torus) - sizeof(KSTorus)) * 8;
auto rounded_downscaled_body =
(KSTorus)(body_out >> input_to_output_scaling_factor);
body_out = -rounded_downscaled_body;
}
lwe_out[lwe_out_idx * (lwe_dimension_out + 1) + lwe_dimension_out] =
-lwe_in[lwe_in_idx * (lwe_dimension_in + 1) + lwe_dimension_in];
(KSTorus)body_out;
}
// Finishes the KS computation by negating all elements in the array
// using output indices. The array contains -b + SUM(a_i x LWE_i)
// and this final step computes b - SUM(a_i x LWE_i)
template <typename Torus>
// The GEMM keyswitch is computed as: -(-b + sum(a_i A_KSK)).
// This function finishes the KS computation by negating all elements in the
// array using output indices. The array contains -b + SUM(a_i x LWE_i) and this
// final step computes b - SUM(a_i x LWE_i).
template <typename Torus, typename KSTorus>
__global__ void keyswitch_negate_with_output_indices(
Torus *buffer_in, const Torus *__restrict__ lwe_output_indices,
KSTorus *buffer_in, const Torus *__restrict__ lwe_output_indices,
uint32_t lwe_size, uint32_t num_lwe) {
// index of this LWE ct in the buffer
@@ -191,9 +256,9 @@ __global__ void keyswitch_negate_with_output_indices(
buffer_in[val_idx] = -val;
}
template <typename Torus>
template <typename Torus, typename KSTorus>
__global__ void keyswitch_zero_output_with_output_indices(
Torus *buffer_in, const Torus *__restrict__ lwe_output_indices,
KSTorus *buffer_in, const Torus *__restrict__ lwe_output_indices,
uint32_t lwe_size, uint32_t num_lwe) {
// index of this LWE ct in the buffer
@@ -235,12 +300,12 @@ __global__ void keyswitch_zero_output_with_output_indices(
// in two parts, a constant part is calculated before the loop, and a variable
// part is calculated inside the loop. This seems to help with the register
// pressure as well.
template <typename Torus>
template <typename Torus, typename KSTorus>
__global__ void
keyswitch(Torus *lwe_array_out, const Torus *__restrict__ lwe_output_indexes,
keyswitch(KSTorus *lwe_array_out, const Torus *__restrict__ lwe_output_indexes,
const Torus *__restrict__ lwe_array_in,
const Torus *__restrict__ lwe_input_indexes,
const Torus *__restrict__ ksk, uint32_t lwe_dimension_in,
const KSTorus *__restrict__ ksk, uint32_t lwe_dimension_in,
uint32_t lwe_dimension_out, uint32_t base_log, uint32_t level_count) {
const int tid = threadIdx.x + blockIdx.y * blockDim.x;
const int shmem_index = threadIdx.x + threadIdx.y * blockDim.x;
@@ -252,12 +317,27 @@ keyswitch(Torus *lwe_array_out, const Torus *__restrict__ lwe_output_indexes,
if (tid <= lwe_dimension_out) {
Torus local_lwe_out = 0;
KSTorus local_lwe_out = 0;
auto block_lwe_array_in = get_chunk(
lwe_array_in, lwe_input_indexes[blockIdx.x], lwe_dimension_in + 1);
if (tid == lwe_dimension_out && threadIdx.y == 0) {
local_lwe_out = -block_lwe_array_in[lwe_dimension_in];
if constexpr (std::is_same_v<KSTorus, Torus>) {
local_lwe_out = -block_lwe_array_in[lwe_dimension_in];
} else {
auto new_body = closest_repr(block_lwe_array_in[lwe_dimension_in],
sizeof(KSTorus) * 8, 1);
// Power of two are encoded in the MSBs of the types so we need to scale
// the type to the other one without having to worry about the moduli
Torus input_to_output_scaling_factor =
(sizeof(Torus) - sizeof(KSTorus)) * 8;
auto rounded_downscaled_body =
(KSTorus)(new_body >> input_to_output_scaling_factor);
local_lwe_out = -rounded_downscaled_body;
}
}
const Torus mask_mod_b = (1ll << base_log) - 1ll;
@@ -273,9 +353,10 @@ keyswitch(Torus *lwe_array_out, const Torus *__restrict__ lwe_output_indexes,
uint32_t offset = i * level_count * (lwe_dimension_out + 1);
for (int j = 0; j < level_count; j++) {
Torus decomposed = decompose_one<Torus>(state, mask_mod_b, base_log);
KSTorus decomposed = decompose_one<Torus>(state, mask_mod_b, base_log);
local_lwe_out +=
(Torus)ksk[tid + j * (lwe_dimension_out + 1) + offset] * decomposed;
(KSTorus)ksk[tid + j * (lwe_dimension_out + 1) + offset] *
decomposed;
}
}
@@ -294,13 +375,13 @@ keyswitch(Torus *lwe_array_out, const Torus *__restrict__ lwe_output_indexes,
}
}
template <typename Torus>
template <typename Torus, typename KSTorus>
__host__ void host_keyswitch_lwe_ciphertext_vector(
cudaStream_t stream, uint32_t gpu_index, Torus *lwe_array_out,
cudaStream_t stream, uint32_t gpu_index, KSTorus *lwe_array_out,
Torus const *lwe_output_indexes, Torus const *lwe_array_in,
Torus const *lwe_input_indexes, Torus const *ksk, uint32_t lwe_dimension_in,
uint32_t lwe_dimension_out, uint32_t base_log, uint32_t level_count,
uint32_t num_samples) {
Torus const *lwe_input_indexes, KSTorus const *ksk,
uint32_t lwe_dimension_in, uint32_t lwe_dimension_out, uint32_t base_log,
uint32_t level_count, uint32_t num_samples) {
cuda_set_device(gpu_index);
@@ -322,29 +403,36 @@ __host__ void host_keyswitch_lwe_ciphertext_vector(
dim3 grid(num_samples, num_blocks_per_sample, 1);
dim3 threads(num_threads_x, num_threads_y, 1);
keyswitch<Torus><<<grid, threads, shared_mem, stream>>>(
keyswitch<Torus, KSTorus><<<grid, threads, shared_mem, stream>>>(
lwe_array_out, lwe_output_indexes, lwe_array_in, lwe_input_indexes, ksk,
lwe_dimension_in, lwe_dimension_out, base_log, level_count);
check_cuda_error(cudaGetLastError());
}
template <typename Torus>
// The GEMM keyswitch is computed as: -(-b + sum(a_i A_KSK))
template <typename Torus, typename KSTorus>
__host__ void host_gemm_keyswitch_lwe_ciphertext_vector(
cudaStream_t stream, uint32_t gpu_index, Torus *lwe_array_out,
cudaStream_t stream, uint32_t gpu_index, KSTorus *lwe_array_out,
Torus const *lwe_output_indices, Torus const *lwe_array_in,
Torus const *lwe_input_indices, Torus const *ksk, uint32_t lwe_dimension_in,
uint32_t lwe_dimension_out, uint32_t base_log, uint32_t level_count,
uint32_t num_samples, Torus *fp_tmp_buffer, bool uses_trivial_indices) {
Torus const *lwe_input_indices, KSTorus const *ksk,
uint32_t lwe_dimension_in, uint32_t lwe_dimension_out, uint32_t base_log,
uint32_t level_count, uint32_t num_samples, Torus *fp_tmp_buffer,
bool uses_trivial_indices) {
cuda_set_device(gpu_index);
check_cuda_error(cudaGetLastError());
auto d_mem_0 = fp_tmp_buffer; // keeps decomposed value
// fp_tmp_buffer contains 2x the space to store the input LWE masks without
// the body the first half can be interpreted with a smaller dtype when
// performing 64->32 KS the second half, storing decomposition state, must be
// interpreted as Torus* (usually 64b)
KSTorus *d_mem_0 =
(KSTorus *)fp_tmp_buffer; // keeps decomposed value (in KSTorus type)
// Set the scratch buffer to 0 as it is used to accumulate
// decomposition temporary results
if (uses_trivial_indices) {
cuda_memset_async(lwe_array_out, 0,
num_samples * (lwe_dimension_out + 1) * sizeof(Torus),
num_samples * (lwe_dimension_out + 1) * sizeof(KSTorus),
stream, gpu_index);
} else {
// gemm to ks the individual LWEs to GLWEs
@@ -352,7 +440,7 @@ __host__ void host_gemm_keyswitch_lwe_ciphertext_vector(
CEIL_DIV(num_samples, BLOCK_SIZE_DECOMP));
dim3 threads_zero(BLOCK_SIZE_DECOMP, BLOCK_SIZE_DECOMP);
keyswitch_zero_output_with_output_indices<Torus>
keyswitch_zero_output_with_output_indices<Torus, KSTorus>
<<<grid_zero, threads_zero, 0, stream>>>(
lwe_array_out, lwe_output_indices, lwe_dimension_out + 1,
num_samples);
@@ -364,8 +452,8 @@ __host__ void host_gemm_keyswitch_lwe_ciphertext_vector(
// lwe_array_out is num_samples x (lwe_dimension_out + 1). copy the bodies
// lwe_array_in[:,lwe_dimension_in] to lwe_array_out[:,lwe_dimension_out]
// and negate
keyswitch_gemm_copy_negated_message_with_indices<Torus>
// and negates them
keyswitch_gemm_copy_negated_message_with_indices<Torus, KSTorus>
<<<grid_copy, threads_copy, 0, stream>>>(
lwe_array_in, lwe_input_indices, lwe_array_out, lwe_output_indices,
lwe_dimension_in, num_samples, lwe_dimension_out);
@@ -394,21 +482,21 @@ __host__ void host_gemm_keyswitch_lwe_ciphertext_vector(
dim3 threads_gemm(BLOCK_SIZE_GEMM_KS * THREADS_GEMM_KS);
// decompose first level (skips the body in the input buffer)
decompose_vectorize_init_with_indices<Torus>
decompose_vectorize_init_with_indices<Torus, KSTorus>
<<<grid_decomp, threads_decomp, 0, stream>>>(
lwe_array_in, lwe_input_indices, fp_tmp_buffer, lwe_dimension_in,
num_samples, base_log, level_count);
check_cuda_error(cudaGetLastError());
if (uses_trivial_indices) {
tgemm<Torus, BLOCK_SIZE_GEMM_KS, THREADS_GEMM_KS>
tgemm<KSTorus, BLOCK_SIZE_GEMM_KS, THREADS_GEMM_KS>
<<<grid_gemm, threads_gemm, shared_mem_size, stream>>>(
num_samples, (lwe_dimension_out + 1), lwe_dimension_in, d_mem_0,
ksk, stride_KSK_buffer, lwe_array_out, lwe_dimension_out + 1);
check_cuda_error(cudaGetLastError());
} else {
tgemm_with_indices<Torus, BLOCK_SIZE_GEMM_KS, THREADS_GEMM_KS>
tgemm_with_indices<KSTorus, Torus, BLOCK_SIZE_GEMM_KS, THREADS_GEMM_KS>
<<<grid_gemm, threads_gemm, shared_mem_size, stream>>>(
num_samples, (lwe_dimension_out + 1), lwe_dimension_in, d_mem_0,
ksk, stride_KSK_buffer, lwe_array_out, lwe_dimension_out + 1,
@@ -419,14 +507,14 @@ __host__ void host_gemm_keyswitch_lwe_ciphertext_vector(
auto ksk_block_size = (lwe_dimension_out + 1);
for (int li = 1; li < level_count; ++li) {
decompose_vectorize_step_inplace<Torus>
decompose_vectorize_step_inplace<Torus, KSTorus>
<<<grid_decomp, threads_decomp, 0, stream>>>(
fp_tmp_buffer, lwe_dimension_in, num_samples, base_log,
level_count);
check_cuda_error(cudaGetLastError());
if (uses_trivial_indices) {
tgemm<Torus, BLOCK_SIZE_GEMM_KS, THREADS_GEMM_KS>
tgemm<KSTorus, BLOCK_SIZE_GEMM_KS, THREADS_GEMM_KS>
<<<grid_gemm, threads_gemm, shared_mem_size, stream>>>(
num_samples, (lwe_dimension_out + 1), lwe_dimension_in, d_mem_0,
ksk + li * ksk_block_size, stride_KSK_buffer, lwe_array_out,
@@ -434,7 +522,7 @@ __host__ void host_gemm_keyswitch_lwe_ciphertext_vector(
check_cuda_error(cudaGetLastError());
} else {
tgemm_with_indices<Torus, BLOCK_SIZE_GEMM_KS, THREADS_GEMM_KS>
tgemm_with_indices<KSTorus, Torus, BLOCK_SIZE_GEMM_KS, THREADS_GEMM_KS>
<<<grid_gemm, threads_gemm, shared_mem_size, stream>>>(
num_samples, (lwe_dimension_out + 1), lwe_dimension_in, d_mem_0,
ksk + li * ksk_block_size, stride_KSK_buffer, lwe_array_out,
@@ -447,20 +535,22 @@ __host__ void host_gemm_keyswitch_lwe_ciphertext_vector(
dim3 grid_negate(CEIL_DIV(lwe_dimension_out + 1, BLOCK_SIZE_DECOMP),
CEIL_DIV(num_samples, BLOCK_SIZE_DECOMP));
dim3 threads_negate(BLOCK_SIZE_DECOMP, BLOCK_SIZE_DECOMP);
// Negate all outputs in the LWE
keyswitch_negate_with_output_indices<Torus>
// Negate all outputs in the output LWEs. This is the final step in the GEMM
// keyswitch computed as: -(-b + sum(a_i A_KSK))
keyswitch_negate_with_output_indices<Torus, KSTorus>
<<<grid_negate, threads_negate, 0, stream>>>(
lwe_array_out, lwe_output_indices, lwe_dimension_out + 1,
num_samples);
check_cuda_error(cudaGetLastError());
}
template <typename Torus>
template <typename Torus, typename KSTorus>
void execute_keyswitch_async(
CudaStreams streams, const LweArrayVariant<Torus> &lwe_array_out,
const LweArrayVariant<Torus> &lwe_output_indexes,
const LweArrayVariant<Torus> &lwe_array_in,
const LweArrayVariant<Torus> &lwe_input_indexes, Torus *const *ksks,
const LweArrayVariant<Torus> &lwe_input_indexes, KSTorus *const *ksks,
uint32_t lwe_dimension_in, uint32_t lwe_dimension_out, uint32_t base_log,
uint32_t level_count, uint32_t num_samples, bool uses_trivial_indices,
const std::vector<ks_mem<Torus> *> &fp_tmp_buffer) {

View File

@@ -124,8 +124,10 @@ __host__ void host_packing_keyswitch_lwe_list_to_glwe(
dim3 threads_decomp(BLOCK_SIZE_DECOMP, BLOCK_SIZE_DECOMP);
// decompose first level
decompose_vectorize_init<Torus><<<grid_decomp, threads_decomp, 0, stream>>>(
lwe_array_in, d_mem_0, lwe_dimension, num_lwes, base_log, level_count);
decompose_vectorize_init<Torus, Torus>
<<<grid_decomp, threads_decomp, 0, stream>>>(lwe_array_in, d_mem_0,
lwe_dimension, num_lwes,
base_log, level_count);
check_cuda_error(cudaGetLastError());
// gemm to ks the individual LWEs to GLWEs
@@ -151,7 +153,7 @@ __host__ void host_packing_keyswitch_lwe_list_to_glwe(
auto ksk_block_size = glwe_accumulator_size;
for (int li = 1; li < level_count; ++li) {
decompose_vectorize_step_inplace<Torus>
decompose_vectorize_step_inplace<Torus, Torus>
<<<grid_decomp, threads_decomp, 0, stream>>>(
d_mem_0, lwe_dimension, num_lwes, base_log, level_count);
check_cuda_error(cudaGetLastError());

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