#include "fft.h" #include "gf.h" #include "parameters.h" #include #include /** * @file fft.c * Implementation of the additive FFT and its transpose. * This implementation is based on the paper from Gao and Mateer:
* Shuhong Gao and Todd Mateer, Additive Fast Fourier Transforms over Finite Fields, * IEEE Transactions on Information Theory 56 (2010), 6265--6272. * http://www.math.clemson.edu/~sgao/papers/GM10.pdf
* and includes improvements proposed by Bernstein, Chou and Schwabe here: * https://binary.cr.yp.to/mcbits-20130616.pdf */ static void compute_fft_betas(uint16_t *betas); static void compute_subset_sums(uint16_t *subset_sums, const uint16_t *set, size_t set_size); static void radix(uint16_t *f0, uint16_t *f1, const uint16_t *f, uint32_t m_f); static void radix_big(uint16_t *f0, uint16_t *f1, const uint16_t *f, uint32_t m_f); static void fft_rec(uint16_t *w, uint16_t *f, size_t f_coeffs, uint8_t m, uint32_t m_f, const uint16_t *betas); /** * @brief Computes the basis of betas (omitting 1) used in the additive FFT and its transpose * * @param[out] betas Array of size PARAM_M-1 */ static void compute_fft_betas(uint16_t *betas) { size_t i; for (i = 0; i < PARAM_M - 1; ++i) { betas[i] = 1 << (PARAM_M - 1 - i); } } /** * @brief Computes the subset sums of the given set * * The array subset_sums is such that its ith element is * the subset sum of the set elements given by the binary form of i. * * @param[out] subset_sums Array of size 2^set_size receiving the subset sums * @param[in] set Array of set_size elements * @param[in] set_size Size of the array set */ static void compute_subset_sums(uint16_t *subset_sums, const uint16_t *set, size_t set_size) { size_t i, j; subset_sums[0] = 0; for (i = 0; i < set_size; ++i) { for (j = 0; j < (1U << i); ++j) { subset_sums[(1 << i) + j] = set[i] ^ subset_sums[j]; } } } /** * @brief Computes the radix conversion of a polynomial f in GF(2^m)[x] * * Computes f0 and f1 such that f(x) = f0(x^2-x) + x.f1(x^2-x) * as proposed by Bernstein, Chou and Schwabe: * https://binary.cr.yp.to/mcbits-20130616.pdf * * @param[out] f0 Array half the size of f * @param[out] f1 Array half the size of f * @param[in] f Array of size a power of 2 * @param[in] m_f 2^{m_f} is the smallest power of 2 greater or equal to the number of coefficients of f */ static void radix(uint16_t *f0, uint16_t *f1, const uint16_t *f, uint32_t m_f) { switch (m_f) { case 4: f0[4] = f[8] ^ f[12]; f0[6] = f[12] ^ f[14]; f0[7] = f[14] ^ f[15]; f1[5] = f[11] ^ f[13]; f1[6] = f[13] ^ f[14]; f1[7] = f[15]; f0[5] = f[10] ^ f[12] ^ f1[5]; f1[4] = f[9] ^ f[13] ^ f0[5]; f0[0] = f[0]; f1[3] = f[7] ^ f[11] ^ f[15]; f0[3] = f[6] ^ f[10] ^ f[14] ^ f1[3]; f0[2] = f[4] ^ f0[4] ^ f0[3] ^ f1[3]; f1[1] = f[3] ^ f[5] ^ f[9] ^ f[13] ^ f1[3]; f1[2] = f[3] ^ f1[1] ^ f0[3]; f0[1] = f[2] ^ f0[2] ^ f1[1]; f1[0] = f[1] ^ f0[1]; break; case 3: f0[0] = f[0]; f0[2] = f[4] ^ f[6]; f0[3] = f[6] ^ f[7]; f1[1] = f[3] ^ f[5] ^ f[7]; f1[2] = f[5] ^ f[6]; f1[3] = f[7]; f0[1] = f[2] ^ f0[2] ^ f1[1]; f1[0] = f[1] ^ f0[1]; break; case 2: f0[0] = f[0]; f0[1] = f[2] ^ f[3]; f1[0] = f[1] ^ f0[1]; f1[1] = f[3]; break; case 1: f0[0] = f[0]; f1[0] = f[1]; break; default: radix_big(f0, f1, f, m_f); break; } } static void radix_big(uint16_t *f0, uint16_t *f1, const uint16_t *f, uint32_t m_f) { uint16_t Q[2 * (1 << (PARAM_FFT - 2))] = {0}; uint16_t R[2 * (1 << (PARAM_FFT - 2))] = {0}; uint16_t Q0[1 << (PARAM_FFT - 2)] = {0}; uint16_t Q1[1 << (PARAM_FFT - 2)] = {0}; uint16_t R0[1 << (PARAM_FFT - 2)] = {0}; uint16_t R1[1 << (PARAM_FFT - 2)] = {0}; size_t i, n; n = 1 << (m_f - 2); memcpy(Q, f + 3 * n, 2 * n); memcpy(Q + n, f + 3 * n, 2 * n); memcpy(R, f, 4 * n); for (i = 0; i < n; ++i) { Q[i] ^= f[2 * n + i]; R[n + i] ^= Q[i]; } radix(Q0, Q1, Q, m_f - 1); radix(R0, R1, R, m_f - 1); memcpy(f0, R0, 2 * n); memcpy(f0 + n, Q0, 2 * n); memcpy(f1, R1, 2 * n); memcpy(f1 + n, Q1, 2 * n); } /** * @brief Evaluates f at all subset sums of a given set * * This function is a subroutine of the function fft. * * @param[out] w Array * @param[in] f Array * @param[in] f_coeffs Number of coefficients of f * @param[in] m Number of betas * @param[in] m_f Number of coefficients of f (one more than its degree) * @param[in] betas FFT constants */ static void fft_rec(uint16_t *w, uint16_t *f, size_t f_coeffs, uint8_t m, uint32_t m_f, const uint16_t *betas) { uint16_t f0[1 << (PARAM_FFT - 2)] = {0}; uint16_t f1[1 << (PARAM_FFT - 2)] = {0}; uint16_t gammas[PARAM_M - 2] = {0}; uint16_t deltas[PARAM_M - 2] = {0}; uint16_t gammas_sums[1 << (PARAM_M - 2)] = {0}; uint16_t u[1 << (PARAM_M - 2)] = {0}; uint16_t v[1 << (PARAM_M - 2)] = {0}; uint16_t tmp[PARAM_M - (PARAM_FFT - 1)] = {0}; uint16_t beta_m_pow; size_t i, j, k; // Step 1 if (m_f == 1) { for (i = 0; i < m; ++i) { tmp[i] = PQCLEAN_HQCRMRS128_AVX2_gf_mul(betas[i], f[1]); } w[0] = f[0]; for (j = 0; j < m; ++j) { for (k = 0; k < (1U << j); ++k) { w[(1 << j) + k] = w[k] ^ tmp[j]; } } return; } // Step 2: compute g if (betas[m - 1] != 1) { beta_m_pow = 1; for (i = 1; i < (1U << m_f); ++i) { beta_m_pow = PQCLEAN_HQCRMRS128_AVX2_gf_mul(beta_m_pow, betas[m - 1]); f[i] = PQCLEAN_HQCRMRS128_AVX2_gf_mul(beta_m_pow, f[i]); } } // Step 3 radix(f0, f1, f, m_f); // Step 4: compute gammas and deltas for (i = 0; i + 1 < m; ++i) { gammas[i] = PQCLEAN_HQCRMRS128_AVX2_gf_mul(betas[i], PQCLEAN_HQCRMRS128_AVX2_gf_inverse(betas[m - 1])); deltas[i] = PQCLEAN_HQCRMRS128_AVX2_gf_square(gammas[i]) ^ gammas[i]; } // Compute gammas sums compute_subset_sums(gammas_sums, gammas, m - 1); // Step 5 fft_rec(u, f0, (f_coeffs + 1) / 2, m - 1, m_f - 1, deltas); k = 1 << ((m - 1) & 0xf); // &0xf is to let the compiler know that m-1 is small. if (f_coeffs <= 3) { // 3-coefficient polynomial f case: f1 is constant w[0] = u[0]; w[k] = u[0] ^ f1[0]; for (i = 1; i < k; ++i) { w[i] = u[i] ^ PQCLEAN_HQCRMRS128_AVX2_gf_mul(gammas_sums[i], f1[0]); w[k + i] = w[i] ^ f1[0]; } } else { fft_rec(v, f1, f_coeffs / 2, m - 1, m_f - 1, deltas); // Step 6 memcpy(w + k, v, 2 * k); w[0] = u[0]; w[k] ^= u[0]; for (i = 1; i < k; ++i) { w[i] = u[i] ^ PQCLEAN_HQCRMRS128_AVX2_gf_mul(gammas_sums[i], v[i]); w[k + i] ^= w[i]; } } } /** * @brief Evaluates f on all fields elements using an additive FFT algorithm * * f_coeffs is the number of coefficients of f (one less than its degree).
* The FFT proceeds recursively to evaluate f at all subset sums of a basis B.
* This implementation is based on the paper from Gao and Mateer:
* Shuhong Gao and Todd Mateer, Additive Fast Fourier Transforms over Finite Fields, * IEEE Transactions on Information Theory 56 (2010), 6265--6272. * http://www.math.clemson.edu/~sgao/papers/GM10.pdf
* and includes improvements proposed by Bernstein, Chou and Schwabe here: * https://binary.cr.yp.to/mcbits-20130616.pdf
* Note that on this first call (as opposed to the recursive calls to fft_rec), gammas are equal to betas, * meaning the first gammas subset sums are actually the subset sums of betas (except 1).
* Also note that f is altered during computation (twisted at each level). * * @param[out] w Array * @param[in] f Array of 2^PARAM_FFT elements * @param[in] f_coeffs Number coefficients of f (i.e. deg(f)+1) */ void PQCLEAN_HQCRMRS128_AVX2_fft(uint16_t *w, const uint16_t *f, size_t f_coeffs) { uint16_t betas[PARAM_M - 1] = {0}; uint16_t betas_sums[1 << (PARAM_M - 1)] = {0}; uint16_t f0[1 << (PARAM_FFT - 1)] = {0}; uint16_t f1[1 << (PARAM_FFT - 1)] = {0}; uint16_t deltas[PARAM_M - 1] = {0}; uint16_t u[1 << (PARAM_M - 1)] = {0}; uint16_t v[1 << (PARAM_M - 1)] = {0}; size_t i, k; // Follows Gao and Mateer algorithm compute_fft_betas(betas); // Step 1: PARAM_FFT > 1, nothing to do // Compute gammas sums compute_subset_sums(betas_sums, betas, PARAM_M - 1); // Step 2: beta_m = 1, nothing to do // Step 3 radix(f0, f1, f, PARAM_FFT); // Step 4: Compute deltas for (i = 0; i < PARAM_M - 1; ++i) { deltas[i] = PQCLEAN_HQCRMRS128_AVX2_gf_square(betas[i]) ^ betas[i]; } // Step 5 fft_rec(u, f0, (f_coeffs + 1) / 2, PARAM_M - 1, PARAM_FFT - 1, deltas); fft_rec(v, f1, f_coeffs / 2, PARAM_M - 1, PARAM_FFT - 1, deltas); k = 1 << (PARAM_M - 1); // Step 6, 7 and error polynomial computation memcpy(w + k, v, 2 * k); // Check if 0 is root w[0] = u[0]; // Check if 1 is root w[k] ^= u[0]; // Find other roots for (i = 1; i < k; ++i) { w[i] = u[i] ^ PQCLEAN_HQCRMRS128_AVX2_gf_mul(betas_sums[i], v[i]); w[k + i] ^= w[i]; } } /** * @brief Retrieves the error polynomial error from the evaluations w of the ELP (Error Locator Polynomial) on all field elements. * * @param[out] error Array with the error * @param[out] error_compact Array with the error in a compact form * @param[in] w Array of size 2^PARAM_M */ void PQCLEAN_HQCRMRS128_AVX2_fft_retrieve_error_poly(uint8_t *error, const uint16_t *w) { uint16_t gammas[PARAM_M - 1] = {0}; uint16_t gammas_sums[1 << (PARAM_M - 1)] = {0}; size_t i, k, index; compute_fft_betas(gammas); compute_subset_sums(gammas_sums, gammas, PARAM_M - 1); k = 1 << (PARAM_M - 1); error[0] ^= 1 ^ ((uint16_t) - w[0] >> 15); error[0] ^= 1 ^ ((uint16_t) - w[k] >> 15); for (i = 1; i < k; ++i) { index = PARAM_GF_MUL_ORDER - PQCLEAN_HQCRMRS128_AVX2_gf_log(gammas_sums[i]); error[index] ^= 1 ^ ((uint16_t) - w[i] >> 15); index = PARAM_GF_MUL_ORDER - PQCLEAN_HQCRMRS128_AVX2_gf_log(gammas_sums[i] ^ 1); error[index] ^= 1 ^ ((uint16_t) - w[k + i] >> 15); } }