diff --git a/backends/tfhe-cuda-backend/build.rs b/backends/tfhe-cuda-backend/build.rs index b51756d30d..41b856a25c 100644 --- a/backends/tfhe-cuda-backend/build.rs +++ b/backends/tfhe-cuda-backend/build.rs @@ -62,6 +62,7 @@ fn main() { "cuda/include/integer/integer.h", "cuda/include/keyswitch.h", "cuda/include/linear_algebra.h", + "cuda/include/pbs/fft.h", "cuda/include/pbs/programmable_bootstrap.h", "cuda/include/pbs/programmable_bootstrap_multibit.h", ]; diff --git a/backends/tfhe-cuda-backend/cuda/include/pbs/fft.h b/backends/tfhe-cuda-backend/cuda/include/pbs/fft.h new file mode 100644 index 0000000000..b89a50e935 --- /dev/null +++ b/backends/tfhe-cuda-backend/cuda/include/pbs/fft.h @@ -0,0 +1,6 @@ +#include +extern "C" { +void fourier_transform_forward_f128(void *stream, uint32_t gpu_index, void *re0, + void *re1, void *im0, void *im1, + void const *standard, uint32_t const N); +} \ No newline at end of file diff --git a/backends/tfhe-cuda-backend/cuda/src/fft128/f128.cuh b/backends/tfhe-cuda-backend/cuda/src/fft128/f128.cuh new file mode 100644 index 0000000000..e140412d12 --- /dev/null +++ b/backends/tfhe-cuda-backend/cuda/src/fft128/f128.cuh @@ -0,0 +1,208 @@ + +#ifndef TFHE_RS_BACKENDS_TFHE_CUDA_BACKEND_CUDA_SRC_FFT128_F128_CUH_ +#define TFHE_RS_BACKENDS_TFHE_CUDA_BACKEND_CUDA_SRC_FFT128_F128_CUH_ + +struct alignas(16) f128 { + double hi; + double lo; + + // Default and parameterized constructors + __host__ __device__ f128() : hi(0.0), lo(0.0) {} + __host__ __device__ f128(double high, double low) : hi(high), lo(low) {} + + // Quick two-sum + __host__ __device__ __forceinline__ static f128 quick_two_sum(double a, + double b) { + double s = a + b; + return f128(s, b - (s - a)); + } + + // Two-sum + __host__ __device__ __forceinline__ static f128 two_sum(double a, double b) { + double s = a + b; + double bb = s - a; + return f128(s, (a - (s - bb)) + (b - bb)); + } + + // Two-product + __host__ __device__ __forceinline__ static f128 two_prod(double a, double b) { + double p = a * b; +#ifdef __CUDA_ARCH__ + return f128(p, __fma_rn(a, b, -p)); +#else + return f128(p, fma(a, b, -p)); +#endif + } + + __host__ __device__ __forceinline__ static f128 two_diff(double a, double b) { + double s = a - b; + double bb = s - a; + return f128(s, (a - (s - bb)) - (b + bb)); + } + + // Addition + __host__ __device__ static f128 add(const f128 &a, const f128 &b) { + auto s = two_sum(a.hi, b.hi); + auto t = two_sum(a.lo, b.lo); + + double hi = s.hi; + double lo = s.lo + t.hi; + hi = hi + lo; + lo = lo - (hi - s.hi); + + return f128(hi, lo + t.lo); + } + + // Addition with estimate + __host__ __device__ static f128 add_estimate(const f128 &a, const f128 &b) { + auto se = two_sum(a.hi, b.hi); + double hi = se.hi; + double lo = se.lo + a.lo + b.lo; + + hi = hi + lo; + lo = lo - (hi - se.hi); + + return f128(hi, lo); + } + + // Subtraction with estimate + __host__ __device__ static f128 sub_estimate(const f128 &a, const f128 &b) { + f128 se = two_diff(a.hi, b.hi); + se.lo += a.lo; + se.lo -= b.lo; + return quick_two_sum(se.hi, se.lo); + } + + // Subtraction + __host__ __device__ static f128 sub(const f128 &a, const f128 &b) { + auto s = two_diff(a.hi, b.hi); + auto t = two_diff(a.lo, b.lo); + s = quick_two_sum(s.hi, s.lo + t.hi); + return quick_two_sum(s.hi, s.lo + t.lo); + } + + // Multiplication + __host__ __device__ static f128 mul(const f128 &a, const f128 &b) { + double hi, lo; + auto p = two_prod(a.hi, b.hi); + hi = p.hi; + lo = p.lo + (a.hi * b.lo + a.lo * b.hi); + + hi = hi + lo; + lo = lo - (hi - p.hi); + + return f128(hi, lo); + } + + __host__ __device__ static void + cplx_f128_mul_assign(f128 &c_re, f128 &c_im, const f128 &a_re, + const f128 &a_im, const f128 &b_re, const f128 &b_im) { + auto a_re_x_b_re = mul(a_re, b_re); + auto a_re_x_b_im = mul(a_re, b_im); + auto a_im_x_b_re = mul(a_im, b_re); + auto a_im_x_b_im = mul(a_im, b_im); + + c_re = add_estimate(a_re_x_b_re, a_im_x_b_im); + c_im = sub_estimate(a_im_x_b_re, a_re_x_b_im); + } +}; + +struct f128x2 { + f128 re; + f128 im; + + __host__ __device__ f128x2() : re(), im() {} + + __host__ __device__ f128x2(const f128 &real, const f128 &imag) + : re(real), im(imag) {} + + __host__ __device__ f128x2(double real, double imag) + : re(real, 0.0), im(imag, 0.0) {} + + __host__ __device__ explicit f128x2(double real) + : re(real, 0.0), im(0.0, 0.0) {} + + __host__ __device__ f128x2(const f128x2 &other) + : re(other.re), im(other.im) {} + + __host__ __device__ f128x2(f128x2 &&other) noexcept + : re(std::move(other.re)), im(std::move(other.im)) {} + + __host__ __device__ f128x2 &operator=(const f128x2 &other) { + if (this != &other) { + re = other.re; + im = other.im; + } + return *this; + } + + __host__ __device__ f128x2 &operator=(f128x2 &&other) noexcept { + if (this != &other) { + re = std::move(other.re); + im = std::move(other.im); + } + return *this; + } + + __host__ __device__ f128x2 conjugate() const { + return f128x2(re, f128(-im.hi, -im.lo)); + } + + __host__ __device__ f128 norm_squared() const { + return f128::add(f128::mul(re, re), f128::mul(im, im)); + } + + __host__ __device__ void zero() { + re = f128(0.0, 0.0); + im = f128(0.0, 0.0); + } + + // Addition + __host__ __device__ friend f128x2 operator+(const f128x2 &a, + const f128x2 &b) { + return f128x2(f128::add(a.re, b.re), f128::add(a.im, b.im)); + } + + // Subtraction + __host__ __device__ friend f128x2 operator-(const f128x2 &a, + const f128x2 &b) { + return f128x2(f128::add(a.re, f128(-b.re.hi, -b.re.lo)), + f128::add(a.im, f128(-b.im.hi, -b.im.lo))); + } + + // Multiplication (complex multiplication) + __host__ __device__ friend f128x2 operator*(const f128x2 &a, + const f128x2 &b) { + f128 real_part = + f128::add(f128::mul(a.re, b.re), + f128(-f128::mul(a.im, b.im).hi, -f128::mul(a.im, b.im).lo)); + f128 imag_part = f128::add(f128::mul(a.re, b.im), f128::mul(a.im, b.re)); + return f128x2(real_part, imag_part); + } + + // Addition-assignment operator + __host__ __device__ f128x2 &operator+=(const f128x2 &other) { + re = f128::add(re, other.re); + im = f128::add(im, other.im); + return *this; + } + + // Subtraction-assignment operator + __host__ __device__ f128x2 &operator-=(const f128x2 &other) { + re = f128::add(re, f128(-other.re.hi, -other.re.lo)); + im = f128::add(im, f128(-other.im.hi, -other.im.lo)); + return *this; + } + + // Multiplication-assignment operator + __host__ __device__ f128x2 &operator*=(const f128x2 &other) { + f128 new_re = + f128::add(f128::mul(re, other.re), f128(-f128::mul(im, other.im).hi, + -f128::mul(im, other.im).lo)); + f128 new_im = f128::add(f128::mul(re, other.im), f128::mul(im, other.re)); + re = new_re; + im = new_im; + return *this; + } +}; +#endif diff --git a/backends/tfhe-cuda-backend/cuda/src/fft128/fft128.cu b/backends/tfhe-cuda-backend/cuda/src/fft128/fft128.cu new file mode 100644 index 0000000000..f6aac4f600 --- /dev/null +++ b/backends/tfhe-cuda-backend/cuda/src/fft128/fft128.cu @@ -0,0 +1,42 @@ +#include "fft128.cuh" + +void fourier_transform_forward_f128(void *stream, uint32_t gpu_index, void *re0, + void *re1, void *im0, void *im1, + void const *standard, uint32_t const N) { + switch (N) { + case 256: + host_fourier_transform_forward_f128_split_input>( + static_cast(stream), gpu_index, (double *)re0, + (double *)re1, (double *)im1, (double *)im1, + (__uint128_t const *)standard, N); + break; + case 512: + host_fourier_transform_forward_f128_split_input>( + static_cast(stream), gpu_index, (double *)re0, + (double *)re1, (double *)im1, (double *)im1, + (__uint128_t const *)standard, N); + break; + case 1024: + host_fourier_transform_forward_f128_split_input>( + static_cast(stream), gpu_index, (double *)re0, + (double *)re1, (double *)im1, (double *)im1, + (__uint128_t const *)standard, N); + break; + case 2048: + host_fourier_transform_forward_f128_split_input>( + static_cast(stream), gpu_index, (double *)re0, + (double *)re1, (double *)im1, (double *)im1, + (__uint128_t const *)standard, N); + break; + case 4096: + host_fourier_transform_forward_f128_split_input>( + static_cast(stream), gpu_index, (double *)re0, + (double *)re1, (double *)im1, (double *)im1, + (__uint128_t const *)standard, N); + break; + default: + PANIC("Cuda error (f128 fft): unsupported polynomial size. Supported " + "N's are powers of two" + " in the interval [256..4096].") + } +} \ No newline at end of file diff --git a/backends/tfhe-cuda-backend/cuda/src/fft128/fft128.cuh b/backends/tfhe-cuda-backend/cuda/src/fft128/fft128.cuh new file mode 100644 index 0000000000..f612eab479 --- /dev/null +++ b/backends/tfhe-cuda-backend/cuda/src/fft128/fft128.cuh @@ -0,0 +1,248 @@ +#ifndef TFHE_RS_BACKENDS_TFHE_CUDA_BACKEND_CUDA_SRC_FFT128_FFT128_CUH_ +#define TFHE_RS_BACKENDS_TFHE_CUDA_BACKEND_CUDA_SRC_FFT128_FFT128_CUH_ + +#include "f128.cuh" +#include "pbs/fft.h" +#include "polynomial/functions.cuh" +#include "polynomial/parameters.cuh" +#include "twiddles.cuh" +#include "types/complex/operations.cuh" +#include + +using Index = unsigned; + +#define NEG_TWID(i) \ + f128x2(f128(neg_twiddles_re_hi[(i)], neg_twiddles_re_lo[(i)]), \ + f128(neg_twiddles_im_hi[(i)], neg_twiddles_im_lo[(i)])) + +#define F64x4_TO_F128x2(f128x2_reg, ind) \ + f128x2_reg.re.hi = dt_re_hi[ind]; \ + f128x2_reg.re.lo = dt_re_lo[ind]; \ + f128x2_reg.im.hi = dt_im_hi[ind]; \ + f128x2_reg.im.lo = dt_im_lo[ind]; + +#define F128x2_TO_F64x4(f128x2_reg, ind) \ + dt_re_hi[ind] = f128x2_reg.re.hi; \ + dt_re_lo[ind] = f128x2_reg.re.lo; \ + dt_im_hi[ind] = f128x2_reg.im.hi; \ + dt_im_lo[ind] = f128x2_reg.im.lo; + +// zl - left part of butterfly operation +// zr - right part of butterfly operation +// re - real part +// im - imaginary part +// hi - high bits +// lo - low bits +// dt - list +// cf - single coefficient +template +__device__ void negacyclic_forward_fft_f128(double *dt_re_hi, double *dt_re_lo, + double *dt_im_hi, + double *dt_im_lo) { + + __syncthreads(); + constexpr Index BUTTERFLY_DEPTH = params::opt >> 1; + constexpr Index LOG2_DEGREE = params::log2_degree; + constexpr Index HALF_DEGREE = params::degree >> 1; + constexpr Index STRIDE = params::degree / params::opt; + + f128x2 u[BUTTERFLY_DEPTH], v[BUTTERFLY_DEPTH], w; + + Index tid = threadIdx.x; + + // load into registers +#pragma unroll + for (Index i = 0; i < BUTTERFLY_DEPTH; ++i) { + F64x4_TO_F128x2(u[i], tid); + F64x4_TO_F128x2(v[i], tid + HALF_DEGREE); + tid += STRIDE; + } + + // level 1 + // we don't make actual complex multiplication on level1 since we have only + // one twiddle, it's real and image parts are equal, so we can multiply + // it with simpler operations + +#pragma unroll + for (Index i = 0; i < BUTTERFLY_DEPTH; ++i) { + w = v[i] * NEG_TWID(1); + v[i] = u[i] - w; + u[i] = u[i] + w; + } + + Index twiddle_shift = 1; + for (Index l = LOG2_DEGREE - 1; l >= 1; --l) { + Index lane_mask = 1 << (l - 1); + Index thread_mask = (1 << l) - 1; + twiddle_shift <<= 1; + + tid = threadIdx.x; + __syncthreads(); +#pragma unroll + for (Index i = 0; i < BUTTERFLY_DEPTH; i++) { + Index rank = tid & thread_mask; + bool u_stays_in_register = rank < lane_mask; + F128x2_TO_F64x4((u_stays_in_register) ? v[i] : u[i], tid); + tid = tid + STRIDE; + } + __syncthreads(); + + tid = threadIdx.x; +#pragma unroll + for (Index i = 0; i < BUTTERFLY_DEPTH; i++) { + Index rank = tid & thread_mask; + bool u_stays_in_register = rank < lane_mask; + F64x4_TO_F128x2(w, tid ^ lane_mask); + u[i] = (u_stays_in_register) ? u[i] : w; + v[i] = (u_stays_in_register) ? w : v[i]; + w = NEG_TWID(tid / lane_mask + twiddle_shift); + + w *= v[i]; + + v[i] = u[i] - w; + u[i] = u[i] + w; + tid = tid + STRIDE; + } + } + __syncthreads(); + + // store registers in SM + tid = threadIdx.x; +#pragma unroll + for (Index i = 0; i < BUTTERFLY_DEPTH; i++) { + F128x2_TO_F64x4(u[i], tid * 2); + F128x2_TO_F64x4(v[i], tid * 2 + 1); + tid = tid + STRIDE; + } + __syncthreads(); +} + +template +__device__ void negacyclic_inverse_fft_f128(double *dt_re_hi, double *dt_re_lo, + double *dt_im_hi, + double *dt_im_lo) { + __syncthreads(); + constexpr Index BUTTERFLY_DEPTH = params::opt >> 1; + constexpr Index LOG2_DEGREE = params::log2_degree; + constexpr Index DEGREE = params::degree; + constexpr Index HALF_DEGREE = params::degree >> 1; + constexpr Index STRIDE = params::degree / params::opt; + + size_t tid = threadIdx.x; + f128x2 u[BUTTERFLY_DEPTH], v[BUTTERFLY_DEPTH], w; + + // load into registers and divide by compressed polynomial size +#pragma unroll + for (Index i = 0; i < BUTTERFLY_DEPTH; ++i) { + + F64x4_TO_F128x2(u[i], 2 * tid); + F64x4_TO_F128x2(v[i], 2 * tid + 1); + + // TODO f128 / double and f128x2/double + // u[i] /= DEGREE; + // v[i] /= DEGREE; + + tid += STRIDE; + } + + Index twiddle_shift = DEGREE; + for (Index l = 1; l <= LOG2_DEGREE - 1; ++l) { + Index lane_mask = 1 << (l - 1); + Index thread_mask = (1 << l) - 1; + tid = threadIdx.x; + twiddle_shift >>= 1; + + // at this point registers are ready for the butterfly + tid = threadIdx.x; + __syncthreads(); +#pragma unroll + for (Index i = 0; i < BUTTERFLY_DEPTH; ++i) { + w = (u[i] - v[i]); + u[i] += v[i]; + v[i] = w * NEG_TWID(tid / lane_mask + twiddle_shift).conjugate(); + + // keep one of the register for next iteration and store another one in sm + Index rank = tid & thread_mask; + bool u_stays_in_register = rank < lane_mask; + F128x2_TO_F64x4((u_stays_in_register) ? v[i] : u[i], tid); + + tid = tid + STRIDE; + } + __syncthreads(); + + // prepare registers for next butterfly iteration + tid = threadIdx.x; +#pragma unroll + for (Index i = 0; i < BUTTERFLY_DEPTH; ++i) { + Index rank = tid & thread_mask; + bool u_stays_in_register = rank < lane_mask; + F64x4_TO_F128x2(w, tid ^ lane_mask); + + u[i] = (u_stays_in_register) ? u[i] : w; + v[i] = (u_stays_in_register) ? w : v[i]; + + tid = tid + STRIDE; + } + } + + // last iteration + for (Index i = 0; i < BUTTERFLY_DEPTH; ++i) { + w = (u[i] - v[i]); + u[i] = u[i] + v[i]; + v[i] = w * NEG_TWID(1).conjugate(); + } + __syncthreads(); + // store registers in SM + tid = threadIdx.x; +#pragma unroll + for (Index i = 0; i < BUTTERFLY_DEPTH; i++) { + F128x2_TO_F64x4(u[i], tid); + F128x2_TO_F64x4(v[i], tid + HALF_DEGREE); + + tid = tid + STRIDE; + } + __syncthreads(); +} + +void print_uint128_bits(__uint128_t value) { + char buffer[129]; // 128 bits + null terminator + buffer[128] = '\0'; // Null-terminate the string + + for (int i = 127; i >= 0; --i) { + buffer[i] = (value & 1) ? '1' : '0'; // Extract the least significant bit + value >>= 1; // Shift right by 1 bit + } + + printf("%s\n", buffer); +} + +template +__host__ void host_fourier_transform_forward_f128_split_input( + cudaStream_t stream, uint32_t gpu_index, double *re0, double *re1, + double *im0, double *im1, __uint128_t const *standard, uint32_t const N) { + + printf("cpp_poly_host\n"); + for (int i = 0; i < N; i++) { + print_uint128_bits(standard[i]); + } + printf("check #1\n"); + + double *d_re0, *d_re1, *d_im0, *d_im1; + __uint128_t *d_standard; + + check_cuda_error(cudaMalloc((void **)&d_re0, N * sizeof(double))); + check_cuda_error(cudaMalloc((void **)&d_re1, N * sizeof(double))); + check_cuda_error(cudaMalloc((void **)&d_im0, N * sizeof(double))); + check_cuda_error(cudaMalloc((void **)&d_im1, N * sizeof(double))); + + check_cuda_error(cudaMalloc((void **)&d_standard, N * sizeof(__uint128_t))); + + check_cuda_error(cudaFree(d_re0)); + check_cuda_error(cudaFree(d_re1)); + check_cuda_error(cudaFree(d_im0)); + check_cuda_error(cudaFree(d_im1)); + + cudaFree(d_standard); +} + +#endif // TFHE_RS_BACKENDS_TFHE_CUDA_BACKEND_CUDA_SRC_FFT128_FFT128_CUH_ diff --git a/backends/tfhe-cuda-backend/cuda/src/fft128/twiddles.cu b/backends/tfhe-cuda-backend/cuda/src/fft128/twiddles.cu new file mode 100644 index 0000000000..9b0597d100 --- /dev/null +++ b/backends/tfhe-cuda-backend/cuda/src/fft128/twiddles.cu @@ -0,0 +1,5476 @@ + +__device__ double neg_twiddles_re_hi[4096] = { + 0.00000000000000000000, 0.70710678118654757274, 0.92387953251128673848, + -0.38268343236508978178, 0.98078528040323043058, -0.19509032201612827584, + 0.55557023301960217765, -0.83146961230254523567, 0.99518472667219692873, + -0.09801714032956060363, 0.63439328416364548779, -0.77301045336273699338, + 0.88192126434835504956, -0.47139673682599764204, 0.29028467725446238656, + -0.95694033573220882438, 0.99879545620517240501, -0.04906767432741801493, + 0.67155895484701844111, -0.74095112535495910588, 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GPU_BOOTSTRAP_128_TWIDDLES_CUH +#define GPU_BOOTSTRAP_128_TWIDDLES_CUH + +/* + * 'negtwiddles' are stored in device memory to profit caching + */ +extern __device__ double neg_twiddles_re_hi[4096]; +extern __device__ double neg_twiddles_re_lo[4096]; +extern __device__ double neg_twiddles_im_hi[4096]; +extern __device__ double neg_twiddles_im_lo[4096]; +#endif diff --git a/backends/tfhe-cuda-backend/src/bindings.rs b/backends/tfhe-cuda-backend/src/bindings.rs index df0f91ab23..22eae4f837 100644 --- a/backends/tfhe-cuda-backend/src/bindings.rs +++ b/backends/tfhe-cuda-backend/src/bindings.rs @@ -1238,6 +1238,18 @@ extern "C" { input_lwe_ciphertext_count: u32, ); } +extern "C" { + pub fn fourier_transform_forward_f128( + stream: *mut ffi::c_void, + gpu_index: u32, + re0: *mut ffi::c_void, + re1: *mut ffi::c_void, + im0: *mut ffi::c_void, + im1: *mut ffi::c_void, + standard: *const ffi::c_void, + N: u32, + ); +} extern "C" { pub fn cuda_fourier_polynomial_mul( stream: *mut ffi::c_void, diff --git a/backends/tfhe-cuda-backend/wrapper.h b/backends/tfhe-cuda-backend/wrapper.h index 4c04d45c29..7bd959a4ea 100644 --- a/backends/tfhe-cuda-backend/wrapper.h +++ b/backends/tfhe-cuda-backend/wrapper.h @@ -4,5 +4,6 @@ #include "cuda/include/integer/integer.h" #include "cuda/include/keyswitch.h" #include "cuda/include/linear_algebra.h" +#include "cuda/include/pbs/fft.h" #include "cuda/include/pbs/programmable_bootstrap.h" #include "cuda/include/pbs/programmable_bootstrap_multibit.h" diff --git a/parse_f128_twiddles.py b/parse_f128_twiddles.py new file mode 100644 index 0000000000..caaa905772 --- /dev/null +++ b/parse_f128_twiddles.py @@ -0,0 +1,35 @@ +import sys + +def generate_twiddles(file_path): + try: + with open(file_path, "r") as file: + lines = file.readlines() + + # Parse n + n_line = lines[0].strip() + n = int(n_line.split('=')[1].strip()) + + # Parse twiddle data + twiddles = [] + for line in lines[1:]: + if "twid_re_hi" in line: + parts = line.split(':')[1].strip().split(',') + hex_val = parts[0].strip() + float_val = parts[1].strip() + twiddles.append((hex_val, float_val)) + + # Generate C++ code + cpp_code = f"double negtwiddles[{n}] = {{\n" + for hex_val, float_val in twiddles: + cpp_code += f" {float_val},\n" + cpp_code += "};\n" + + print(cpp_code) + except Exception as e: + print(f"Error: {e}") + +if __name__ == "__main__": + if len(sys.argv) != 2: + print("Usage: python generate_twiddles.py ") + else: + generate_twiddles(sys.argv[1]) diff --git a/tfhe/src/core_crypto/fft_impl/fft128/math/fft/tests.rs b/tfhe/src/core_crypto/fft_impl/fft128/math/fft/tests.rs index 25fd1b0c93..9e5f0e5320 100644 --- a/tfhe/src/core_crypto/fft_impl/fft128/math/fft/tests.rs +++ b/tfhe/src/core_crypto/fft_impl/fft128/math/fft/tests.rs @@ -19,6 +19,7 @@ fn test_roundtrip() { let mut fourier_im0 = avec![0.0f64; fourier_size].into_boxed_slice(); let mut fourier_im1 = avec![0.0f64; fourier_size].into_boxed_slice(); + println!("sizeof_scalar: {:?}", Scalar::BITS); for x in poly.as_mut().iter_mut() { *x = generator.random_uniform(); } diff --git a/tfhe/src/core_crypto/gpu/algorithms/test/fft.rs b/tfhe/src/core_crypto/gpu/algorithms/test/fft.rs new file mode 100644 index 0000000000..6991f20659 --- /dev/null +++ b/tfhe/src/core_crypto/gpu/algorithms/test/fft.rs @@ -0,0 +1,245 @@ +use super::*; +use crate::core_crypto::commons::test_tools::{modular_distance, new_random_generator}; +use crate::core_crypto::commons::utils::izip; +use crate::core_crypto::gpu::{fourier_transform_forward_f128_async, CudaStreams}; +use aligned_vec::avec; +use dyn_stack::{GlobalPodBuffer, PodStack, ReborrowMut}; + +fn test_roundtrip() { + let mut generator = new_random_generator(); + for size_log in 13..=13 { + let size = 1_usize << size_log; + let fourier_size = PolynomialSize(size).to_fourier_polynomial_size().0; + + let fft = Fft128::new(PolynomialSize(size)); + let fft = fft.as_view(); + + let mut poly = avec![Scalar::ZERO; size].into_boxed_slice(); + let mut roundtrip = avec![Scalar::ZERO; size].into_boxed_slice(); + let mut fourier_re0 = avec![0.0f64; fourier_size].into_boxed_slice(); + let mut fourier_re1 = avec![0.0f64; fourier_size].into_boxed_slice(); + let mut fourier_im0 = avec![0.0f64; fourier_size].into_boxed_slice(); + let mut fourier_im1 = avec![0.0f64; fourier_size].into_boxed_slice(); + + println!("sizeof_scalar: {:?}", Scalar::BITS); + for x in poly.as_mut().iter_mut() { + *x = generator.random_uniform(); + } + + let mut mem = GlobalPodBuffer::new(fft.backward_scratch().unwrap()); + let mut stack = PodStack::new(&mut mem); + + fft.forward_as_torus( + &mut fourier_re0, + &mut fourier_re1, + &mut fourier_im0, + &mut fourier_im1, + &poly, + ); + let gpu_index = 0; + let stream = CudaStreams::new_single_gpu(gpu_index); + + unsafe { + println!("size: {:?}", size); + println!("poly.len: {:?}", poly.len()); + println!("rust poly"); + for coefficient in poly.iter() { + println!( + "{:0width$b}", + coefficient, + width = std::mem::size_of::() * 8 + ); + } + fourier_transform_forward_f128_async( + &stream, + &mut fourier_re0, + &mut fourier_re1, + &mut fourier_im0, + &mut fourier_im1, + &poly, + poly.len() as u32, + ); + } + + fft.backward_as_torus( + &mut roundtrip, + &fourier_re0, + &fourier_re1, + &fourier_im0, + &fourier_im1, + stack.rb_mut(), + ); + + for (expected, actual) in izip!(poly.as_ref().iter(), roundtrip.as_ref().iter()) { + if Scalar::BITS <= 64 { + assert_eq!(*expected, *actual); + } else { + let abs_diff = modular_distance(*expected, *actual); + let threshold = Scalar::ONE << (128 - 100); + assert!( + abs_diff < threshold, + "abs_diff: {abs_diff}, threshold: {threshold}", + ); + } + } + } +} + +// fn test_product() { +// fn convolution_naive( +// out: &mut [Scalar], +// lhs: &[Scalar], +// rhs: &[Scalar], +// ) { +// assert_eq!(out.len(), lhs.len()); +// assert_eq!(out.len(), rhs.len()); +// let n = out.len(); +// let mut full_prod = vec![Scalar::ZERO; 2 * n]; +// for i in 0..n { +// for j in 0..n { +// full_prod[i + j] = full_prod[i + j].wrapping_add(lhs[i].wrapping_mul(rhs[j])); +// } +// } +// for i in 0..n { +// out[i] = full_prod[i].wrapping_sub(full_prod[i + n]); +// } +// } +// +// let mut generator = new_random_generator(); +// for size_log in 6..=14 { +// for _ in 0..10 { +// let size = 1_usize << size_log; +// let fourier_size = PolynomialSize(size).to_fourier_polynomial_size().0; +// +// let fft = Fft128::new(PolynomialSize(size)); +// let fft = fft.as_view(); +// +// let mut poly0 = avec![Scalar::ZERO; size].into_boxed_slice(); +// let mut poly1 = avec![Scalar::ZERO; size].into_boxed_slice(); +// +// let mut convolution_from_fft = avec![Scalar::ZERO; size].into_boxed_slice(); +// let mut convolution_from_naive = avec![Scalar::ZERO; size].into_boxed_slice(); +// +// let mut fourier0_re0 = avec![0.0f64; fourier_size].into_boxed_slice(); +// let mut fourier0_re1 = avec![0.0f64; fourier_size].into_boxed_slice(); +// let mut fourier0_im0 = avec![0.0f64; fourier_size].into_boxed_slice(); +// let mut fourier0_im1 = avec![0.0f64; fourier_size].into_boxed_slice(); +// +// let mut fourier1_re0 = avec![0.0f64; fourier_size].into_boxed_slice(); +// let mut fourier1_re1 = avec![0.0f64; fourier_size].into_boxed_slice(); +// let mut fourier1_im0 = avec![0.0f64; fourier_size].into_boxed_slice(); +// let mut fourier1_im1 = avec![0.0f64; fourier_size].into_boxed_slice(); +// +// let integer_magnitude = 16; +// for (x, y) in izip!(poly0.as_mut().iter_mut(), poly1.as_mut().iter_mut()) { +// *x = generator.random_uniform(); +// *y = generator.random_uniform(); +// +// *y >>= Scalar::BITS - integer_magnitude; +// } +// +// let mut mem = GlobalPodBuffer::new(fft.backward_scratch().unwrap()); +// let mut stack = PodStack::new(&mut mem); +// +// fft.forward_as_torus( +// &mut fourier0_re0, +// &mut fourier0_re1, +// &mut fourier0_im0, +// &mut fourier0_im1, +// &poly0, +// ); +// fft.forward_as_integer( +// &mut fourier1_re0, +// &mut fourier1_re1, +// &mut fourier1_im0, +// &mut fourier1_im1, +// &poly1, +// ); +// +// for (f0_re0, f0_re1, f0_im0, f0_im1, f1_re0, f1_re1, f1_im0, f1_im1) in izip!( +// &mut *fourier0_re0, +// &mut *fourier0_re1, +// &mut *fourier0_im0, +// &mut *fourier0_im1, +// &*fourier1_re0, +// &*fourier1_re1, +// &*fourier1_im0, +// &*fourier1_im1, +// ) { +// let f0_re = f128(*f0_re0, *f0_re1); +// let f0_im = f128(*f0_im0, *f0_im1); +// let f1_re = f128(*f1_re0, *f1_re1); +// let f1_im = f128(*f1_im0, *f1_im1); +// +// f128(*f0_re0, *f0_re1) = f0_re * f1_re - f0_im * f1_im; +// f128(*f0_im0, *f0_im1) = f0_im * f1_re + f0_re * f1_im; +// } +// +// fft.backward_as_torus( +// &mut convolution_from_fft, +// &fourier0_re0, +// &fourier0_re1, +// &fourier0_im0, +// &fourier0_im1, +// stack.rb_mut(), +// ); +// convolution_naive( +// convolution_from_naive.as_mut(), +// poly0.as_ref(), +// poly1.as_ref(), +// ); +// +// for (expected, actual) in izip!( +// convolution_from_naive.as_ref().iter(), +// convolution_from_fft.as_ref().iter() +// ) { +// let threshold = Scalar::ONE +// << (Scalar::BITS.saturating_sub(100 - integer_magnitude - size_log)); +// let abs_diff = modular_distance(*expected, *actual); +// assert!( +// abs_diff <= threshold, +// "abs_diff: {abs_diff}, threshold: {threshold}", +// ); +// } +// } +// } +// } + +// #[test] +// fn test_roundtrip_u32() { +// test_roundtrip::(); +// } +// #[test] +// fn test_roundtrip_u64() { +// test_roundtrip::(); +// } + +#[test] +fn test_roundtrip_u128() { + test_roundtrip::(); +} + +// fn test_roundtrip_u128< +// Scalar: UnsignedTorus + Sync + Send + CastFrom + CastInto, +// >( +// params: ClassicTestParams, +// ) { +// test_roundtrip::(); +// } + +// create_gpu_parametrized_test!(test_roundtrip_u128); + +// #[test] +// fn test_product_u32() { +// test_product::(); +// } +// +// #[test] +// fn test_product_u64() { +// test_product::(); +// } +// +// #[test] +// fn test_product_u128() { +// test_product::(); +// } diff --git a/tfhe/src/core_crypto/gpu/algorithms/test/mod.rs b/tfhe/src/core_crypto/gpu/algorithms/test/mod.rs index 779a419702..edf3180060 100644 --- a/tfhe/src/core_crypto/gpu/algorithms/test/mod.rs +++ b/tfhe/src/core_crypto/gpu/algorithms/test/mod.rs @@ -1,5 +1,6 @@ use crate::core_crypto::algorithms::test::*; +mod fft; mod glwe_sample_extraction; mod lwe_keyswitch; mod lwe_linear_algebra; diff --git a/tfhe/src/core_crypto/gpu/mod.rs b/tfhe/src/core_crypto/gpu/mod.rs index b25cde608f..959a33c9f9 100644 --- a/tfhe/src/core_crypto/gpu/mod.rs +++ b/tfhe/src/core_crypto/gpu/mod.rs @@ -630,6 +630,27 @@ pub unsafe fn mult_lwe_ciphertext_vector_cleartext_vector( ); } +#[allow(clippy::too_many_arguments)] +pub unsafe fn fourier_transform_forward_f128_async( + streams: &CudaStreams, + re0: &mut [f64], + re1: &mut [f64], + im0: &mut [f64], + im1: &mut [f64], + standard: &[T], + fft_size: u32, +) { + fourier_transform_forward_f128( + streams.ptr[0], + streams.gpu_indexes[0], + re0.as_mut_ptr() as *mut c_void, + re1.as_mut_ptr() as *mut c_void, + im0.as_mut_ptr() as *mut c_void, + im1.as_mut_ptr() as *mut c_void, + standard.as_ptr() as *const c_void, + fft_size, + ); +} #[derive(Debug)] pub struct CudaLweList { // Pointer to GPU data