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Ref. + AVX code & generic tests + benches (#85)

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This commit is contained in:
Jean-Philippe Bossuat
2025-09-15 16:16:11 +02:00
committed by GitHub
parent 99b9e3e10e
commit 56dbd29c59
286 changed files with 27797 additions and 7270 deletions
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42
poulpy-core/src/encryption/compressed/gglwe_tsk.rs
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@@ -1,9 +1,9 @@
use poulpy_hal::{
api::{
DFT, IDFTConsume, IDFTTmpA, ScratchAvailable, SvpApply, SvpApplyInplace, SvpPPolAlloc, SvpPPolAllocBytes, SvpPrepare,
TakeScalarZnx, TakeVecZnx, TakeVecZnxBig, TakeVecZnxDft, VecZnxAddInplace, VecZnxAddNormal, VecZnxAddScalarInplace,
VecZnxBigAllocBytes, VecZnxBigNormalize, VecZnxDftAllocBytes, VecZnxFillUniform, VecZnxNormalize, VecZnxNormalizeInplace,
VecZnxNormalizeTmpBytes, VecZnxSub, VecZnxSubABInplace, VecZnxSwithcDegree,
ScratchAvailable, SvpApplyDftToDft, SvpApplyDftToDftInplace, SvpPPolAlloc, SvpPPolAllocBytes, SvpPrepare, TakeScalarZnx,
TakeVecZnx, TakeVecZnxBig, TakeVecZnxDft, VecZnxAddInplace, VecZnxAddNormal, VecZnxAddScalarInplace, VecZnxBigAllocBytes,
VecZnxBigNormalize, VecZnxDftAllocBytes, VecZnxDftApply, VecZnxFillUniform, VecZnxIdftApplyConsume, VecZnxIdftApplyTmpA,
VecZnxNormalize, VecZnxNormalizeInplace, VecZnxNormalizeTmpBytes, VecZnxSub, VecZnxSubABInplace, VecZnxSwitchRing,
},
layouts::{Backend, DataMut, DataRef, Module, Scratch},
source::Source,
@@ -33,13 +33,13 @@ impl<DataSelf: DataMut> GGLWETensorKeyCompressed<DataSelf> {
source_xe: &mut Source,
scratch: &mut Scratch<B>,
) where
Module<B>: SvpApply<B>
+ IDFTTmpA<B>
Module<B>: SvpApplyDftToDft<B>
+ VecZnxIdftApplyTmpA<B>
+ VecZnxDftAllocBytes
+ VecZnxBigNormalize<B>
+ DFT<B>
+ SvpApplyInplace<B>
+ IDFTConsume<B>
+ VecZnxDftApply<B>
+ SvpApplyDftToDftInplace<B>
+ VecZnxIdftApplyConsume<B>
+ VecZnxNormalizeTmpBytes
+ VecZnxFillUniform
+ VecZnxSubABInplace
@@ -48,7 +48,7 @@ impl<DataSelf: DataMut> GGLWETensorKeyCompressed<DataSelf> {
+ VecZnxAddNormal
+ VecZnxNormalize<B>
+ VecZnxSub
+ VecZnxSwithcDegree
+ VecZnxSwitchRing
+ VecZnxAddScalarInplace
+ SvpPrepare<B>
+ SvpPPolAllocBytes
@@ -70,39 +70,39 @@ impl<DataSelf: DataMut> GGLWETensorKeyCompressed<DataSelf> {
let n: usize = sk.n();
let rank: usize = self.rank();
let (mut sk_dft_prep, scratch1) = scratch.take_glwe_secret_prepared(n, rank);
sk_dft_prep.prepare(module, sk, scratch1);
let (mut sk_dft_prep, scratch_1) = scratch.take_glwe_secret_prepared(n, rank);
sk_dft_prep.prepare(module, sk, scratch_1);
let (mut sk_dft, scratch2) = scratch1.take_vec_znx_dft(n, rank, 1);
let (mut sk_dft, scratch_2) = scratch_1.take_vec_znx_dft(n, rank, 1);
(0..rank).for_each(|i| {
module.dft(1, 0, &mut sk_dft, i, &sk.data.as_vec_znx(), i);
module.vec_znx_dft_apply(1, 0, &mut sk_dft, i, &sk.data.as_vec_znx(), i);
});
let (mut sk_ij_big, scratch3) = scratch2.take_vec_znx_big(n, 1, 1);
let (mut sk_ij, scratch4) = scratch3.take_glwe_secret(n, 1);
let (mut sk_ij_dft, scratch5) = scratch4.take_vec_znx_dft(n, 1, 1);
let (mut sk_ij_big, scratch_3) = scratch_2.take_vec_znx_big(n, 1, 1);
let (mut sk_ij, scratch_4) = scratch_3.take_glwe_secret(n, 1);
let (mut sk_ij_dft, scratch_5) = scratch_4.take_vec_znx_dft(n, 1, 1);
let mut source_xa: Source = Source::new(seed_xa);
(0..rank).for_each(|i| {
(i..rank).for_each(|j| {
module.svp_apply(&mut sk_ij_dft, 0, &sk_dft_prep.data, j, &sk_dft, i);
module.svp_apply_dft_to_dft(&mut sk_ij_dft, 0, &sk_dft_prep.data, j, &sk_dft, i);
module.idft_tmp_a(&mut sk_ij_big, 0, &mut sk_ij_dft, 0);
module.vec_znx_idft_apply_tmpa(&mut sk_ij_big, 0, &mut sk_ij_dft, 0);
module.vec_znx_big_normalize(
self.basek(),
&mut sk_ij.data.as_vec_znx_mut(),
0,
&sk_ij_big,
0,
scratch5,
scratch_5,
);
let (seed_xa_tmp, _) = source_xa.branch();
self.at_mut(i, j)
.encrypt_sk(module, &sk_ij, sk, seed_xa_tmp, source_xe, scratch5);
.encrypt_sk(module, &sk_ij, sk, seed_xa_tmp, source_xe, scratch_5);
});
})
}