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https://github.com/arnaucube/poulpy.git
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Small optimization + more fixes
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@@ -348,7 +348,6 @@ impl<DataSelf: AsMut<[u8]> + AsRef<[u8]>> GGSWCiphertext<DataSelf, FFT64> {
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let (mut tmp_dft_i, scratch1) = scratch.tmp_vec_znx_dft(module, cols, tsk.size());
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let (mut tmp_a, scratch2) = scratch1.tmp_vec_znx_dft(module, 1, (ci_dft.size() + digits - 1) / digits);
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let res_size: usize = res.to_mut().size();
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{
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// Performs a key-switch for each combination of s[i]*s[j], i.e. for a0, a1, a2
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@@ -363,23 +362,21 @@ impl<DataSelf: AsMut<[u8]> + AsRef<[u8]>> GGSWCiphertext<DataSelf, FFT64> {
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// =
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// (-(x0s0 + x1s1 + x2s2) + s0(a0s0 + a1s1 + a2s2), x0, x1, x2)
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(1..cols).for_each(|col_i| {
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let pmat: &MatZnxDft<DataTsk, FFT64> = &tsk.at(col_i - 1, col_j - 1).0.data; // Selects Enc(s[i]s[j])
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// Extracts a[i] and multipies with Enc(s[i]s[j])
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(0..digits).for_each(|di| {
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tmp_a.set_size((ci_dft.size() + di) / digits);
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// Small optimization for digits > 2
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// VMP produce some error e, and since we aggregate vmp * 2^{di * B}, then
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// we also aggregate ei * 2^{di * B}, with the largest error being ei * 2^{(digits-1) * B}.
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// As such we can ignore the last digits-2 limbs safely of the sum of vmp products.
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// It is possible to further ignore the last digits-1 limbs, but this introduce
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// It is possible to further ignore the last digits-1 limbs, but this introduce
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// ~0.5 to 1 bit of additional noise, and thus not chosen here to ensure that the same
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// noise is kept with respect to the ideal functionality.
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//tmp_dft_i.set_size(res_size - ((digits - di) as isize - 2).max(0) as usize);
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tmp_dft_i.set_size(tsk.size() - ((digits - di) as isize - 2).max(0) as usize);
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module.vec_znx_dft_copy(digits, digits - 1 - di, &mut tmp_a, 0, ci_dft, col_i);
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if di == 0 && col_i == 1 {
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module.vmp_apply(&mut tmp_dft_i, &tmp_a, pmat, scratch2);
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@@ -1,5 +1,7 @@
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use backend::{
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AddNormal, Backend, FillUniform, MatZnxDftOps, MatZnxDftScratch, Module, ScalarZnxAlloc, ScalarZnxDftAlloc, ScalarZnxDftOps, Scratch, VecZnx, VecZnxAlloc, VecZnxBig, VecZnxBigAlloc, VecZnxBigOps, VecZnxBigScratch, VecZnxDftAlloc, VecZnxDftOps, VecZnxOps, VecZnxToMut, VecZnxToRef, ZnxZero, FFT64
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AddNormal, Backend, FFT64, FillUniform, MatZnxDftOps, MatZnxDftScratch, Module, ScalarZnxAlloc, ScalarZnxDftAlloc,
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ScalarZnxDftOps, Scratch, VecZnx, VecZnxAlloc, VecZnxBig, VecZnxBigAlloc, VecZnxBigOps, VecZnxBigScratch, VecZnxDftAlloc,
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VecZnxDftOps, VecZnxOps, VecZnxToMut, VecZnxToRef, ZnxZero,
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};
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use sampling::source::Source;
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@@ -500,17 +502,16 @@ impl<DataSelf: AsRef<[u8]> + AsMut<[u8]>> GLWECiphertext<DataSelf> {
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ai_dft.zero();
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{
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(0..digits).for_each(|di| {
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ai_dft.set_size((lhs.size() + di) / digits);
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// Small optimization for digits > 2
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// VMP produce some error e, and since we aggregate vmp * 2^{di * B}, then
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// we also aggregate ei * 2^{di * B}, with the largest error being ei * 2^{(digits-1) * B}.
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// As such we can ignore the last digits-2 limbs safely of the sum of vmp products.
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// It is possible to further ignore the last digits-1 limbs, but this introduce
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// It is possible to further ignore the last digits-1 limbs, but this introduce
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// ~0.5 to 1 bit of additional noise, and thus not chosen here to ensure that the same
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// noise is kept with respect to the ideal functionality.
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//res_dft.set_size(rhs.size() - ((digits - di) as isize - 2).max(0) as usize);
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res_dft.set_size(rhs.size() - ((digits - di) as isize - 2).max(0) as usize);
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(0..cols_in).for_each(|col_i| {
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module.vec_znx_dft(
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@@ -598,7 +599,7 @@ impl<DataSelf: AsRef<[u8]> + AsMut<[u8]>> GLWECiphertext<DataSelf> {
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let digits: usize = rhs.digits();
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let (mut res_dft, scratch1) = scratch.tmp_vec_znx_dft(module, cols, rhs.size()); // Todo optimise
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let (mut a_dft, scratch2) = scratch1.tmp_vec_znx_dft(module, cols, (lhs.size() + digits-1) / digits);
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let (mut a_dft, scratch2) = scratch1.tmp_vec_znx_dft(module, cols, (lhs.size() + digits - 1) / digits);
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{
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(0..digits).for_each(|di| {
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@@ -609,10 +610,10 @@ impl<DataSelf: AsRef<[u8]> + AsMut<[u8]>> GLWECiphertext<DataSelf> {
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// VMP produce some error e, and since we aggregate vmp * 2^{di * B}, then
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// we also aggregate ei * 2^{di * B}, with the largest error being ei * 2^{(digits-1) * B}.
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// As such we can ignore the last digits-2 limbs safely of the sum of vmp products.
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// It is possible to further ignore the last digits-1 limbs, but this introduce
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// It is possible to further ignore the last digits-1 limbs, but this introduce
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// ~0.5 to 1 bit of additional noise, and thus not chosen here to ensure that the same
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// noise is kept with respect to the ideal functionality.
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//res_dft.set_size(rhs.size() - ((digits - di) as isize - 2).max(0) as usize);
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res_dft.set_size(rhs.size() - ((digits - di) as isize - 2).max(0) as usize);
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(0..cols).for_each(|col_i| {
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module.vec_znx_dft(digits, digits - 1 - di, &mut a_dft, col_i, &lhs.data, col_i);
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@@ -199,17 +199,23 @@ impl<DataSelf: AsMut<[u8]> + AsRef<[u8]>> GLWECiphertextFourier<DataSelf, FFT64>
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let cols: usize = rhs.rank() + 1;
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let digits = rhs.digits();
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// Space for VMP result in DFT domain and high precision
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let (mut res_dft, scratch1) = scratch.tmp_vec_znx_dft(module, cols, rhs.size());
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let (mut a_dft, scratch2) = scratch1.tmp_vec_znx_dft(module, cols, (lhs.size() + digits - 1) / digits);
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{
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(0..digits).for_each(|di| {
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a_dft.set_size((lhs.size() + di) / digits);
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res_dft.set_size(rhs.size() - (digits - di - 1));
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// Small optimization for digits > 2
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// VMP produce some error e, and since we aggregate vmp * 2^{di * B}, then
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// we also aggregate ei * 2^{di * B}, with the largest error being ei * 2^{(digits-1) * B}.
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// As such we can ignore the last digits-2 limbs safely of the sum of vmp products.
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// It is possible to further ignore the last digits-1 limbs, but this introduce
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// ~0.5 to 1 bit of additional noise, and thus not chosen here to ensure that the same
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// noise is kept with respect to the ideal functionality.
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res_dft.set_size(rhs.size() - ((digits - di) as isize - 2).max(0) as usize);
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(0..cols).for_each(|col_i| {
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module.vec_znx_dft_copy(digits, digits - 1 - di, &mut a_dft, col_i, &lhs.data, col_i);
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});
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