| // This file is part of Eigen, a lightweight C++ template library |
| // for linear algebra. |
| // |
| // This Source Code Form is subject to the terms of the Mozilla |
| // Public License v. 2.0. If a copy of the MPL was not distributed |
| // with this file, You can obtain one at http://mozilla.org/MPL/2.0/. |
| // |
| // The algorithm below is a re-implementation of \src\LU\Inverse_SSE.h using NEON |
| // intrinsics. inv(M) = M#/|M|, where inv(M), M# and |M| denote the inverse of M, |
| // adjugate of M and determinant of M respectively. M# is computed block-wise |
| // using specific formulae. For proof, see: |
| // https://lxjk.github.io/2017/09/03/Fast-4x4-Matrix-Inverse-with-SSE-SIMD-Explained.html |
| // Variable names are adopted from \src\LU\Inverse_SSE.h. |
| |
| // TODO: Unify implementations of different data types (i.e. float and double) and |
| // different sets of instrinsics (i.e. SSE and NEON) |
| #ifndef EIGEN_INVERSE_NEON_H |
| #define EIGEN_INVERSE_NEON_H |
| |
| namespace Eigen |
| { |
| namespace internal |
| { |
| template <typename MatrixType, typename ResultType> |
| struct compute_inverse_size4<Architecture::NEON, float, MatrixType, ResultType> |
| { |
| enum |
| { |
| MatrixAlignment = traits<MatrixType>::Alignment, |
| ResultAlignment = traits<ResultType>::Alignment, |
| StorageOrdersMatch = (MatrixType::Flags & RowMajorBit) == (ResultType::Flags & RowMajorBit) |
| }; |
| typedef typename conditional<(MatrixType::Flags & LinearAccessBit), MatrixType const &, typename MatrixType::PlainObject>::type ActualMatrixType; |
| |
| // fuctionally equivalent to _mm_shuffle_ps in SSE when interleave |
| // == false (i.e. shuffle(m, n, mask, false) equals _mm_shuffle_ps(m, n, mask)), |
| // interleave m and n when interleave == true |
| static Packet4f shuffle(const Packet4f &m, const Packet4f &n, int mask, bool interleave = false) |
| { |
| const float *a = reinterpret_cast<const float *>(&m); |
| const float *b = reinterpret_cast<const float *>(&n); |
| if (!interleave) |
| { |
| Packet4f res = {*(a + (mask & 3)), *(a + ((mask >> 2) & 3)), *(b + ((mask >> 4) & 3)), *(b + ((mask >> 6) & 3))}; |
| return res; |
| } |
| else |
| { |
| Packet4f res = {*(a + (mask & 3)), *(b + ((mask >> 2) & 3)), *(a + ((mask >> 4) & 3)), *(b + ((mask >> 6) & 3))}; |
| return res; |
| } |
| } |
| |
| static void run(const MatrixType &mat, ResultType &result) |
| { |
| ActualMatrixType matrix(mat); |
| |
| Packet4f _L1 = matrix.template packet<MatrixAlignment>(0); |
| Packet4f _L2 = matrix.template packet<MatrixAlignment>(4); |
| Packet4f _L3 = matrix.template packet<MatrixAlignment>(8); |
| Packet4f _L4 = matrix.template packet<MatrixAlignment>(12); |
| |
| // Four 2x2 sub-matrices of the input matrix |
| // input = [[A, B], |
| // [C, D]] |
| Packet4f A, B, C, D; |
| |
| if (!StorageOrdersMatch) |
| { |
| A = shuffle(_L1, _L2, 0x50, true); |
| B = shuffle(_L3, _L4, 0x50, true); |
| C = shuffle(_L1, _L2, 0xFA, true); |
| D = shuffle(_L3, _L4, 0xFA, true); |
| } |
| else |
| { |
| A = shuffle(_L1, _L2, 0x44); |
| B = shuffle(_L1, _L2, 0xEE); |
| C = shuffle(_L3, _L4, 0x44); |
| D = shuffle(_L3, _L4, 0xEE); |
| } |
| |
| Packet4f AB, DC, temp; |
| |
| // AB = A# * B, where A# denotes the adjugate of A, and * denotes matrix product. |
| AB = shuffle(A, A, 0x0F); |
| AB = pmul(AB, B); |
| |
| temp = shuffle(A, A, 0xA5); |
| temp = pmul(temp, shuffle(B, B, 0x4E)); |
| AB = psub(AB, temp); |
| |
| // DC = D#*C |
| DC = shuffle(D, D, 0x0F); |
| DC = pmul(DC, C); |
| temp = shuffle(D, D, 0xA5); |
| temp = pmul(temp, shuffle(C, C, 0x4E)); |
| DC = psub(DC, temp); |
| |
| // determinants of the sub-matrices |
| Packet4f dA, dB, dC, dD; |
| |
| dA = pmul(shuffle(A, A, 0x5F), A); |
| dA = psub(dA, shuffle(dA, dA, 0xEE)); |
| |
| dB = pmul(shuffle(B, B, 0x5F), B); |
| dB = psub(dB, shuffle(dB, dB, 0xEE)); |
| |
| dC = pmul(shuffle(C, C, 0x5F), C); |
| dC = psub(dC, shuffle(dC, dC, 0xEE)); |
| |
| dD = pmul(shuffle(D, D, 0x5F), D); |
| dD = psub(dD, shuffle(dD, dD, 0xEE)); |
| |
| Packet4f d, d1, d2; |
| Packet2f sum; |
| temp = shuffle(DC, DC, 0xD8); |
| d = pmul(temp, AB); |
| sum = vpadd_f32(vadd_f32(vget_low_f32(d), vget_high_f32(d)), vadd_f32(vget_low_f32(d), vget_high_f32(d))); |
| d = vdupq_lane_f32(sum, 0); |
| d1 = pmul(dA, dD); |
| d2 = pmul(dB, dC); |
| |
| // determinant of the input matrix, det = |A||D| + |B||C| - trace(A#*B*D#*C) |
| Packet4f det = psub(padd(d1, d2), d); |
| |
| // reciprocal of the determinant of the input matrix, rd = 1/det |
| Packet4f rd = pdiv(vdupq_n_f32(float32_t(1.0)), det); |
| |
| // Four sub-matrices of the inverse |
| Packet4f iA, iB, iC, iD; |
| |
| // iD = D*|A| - C*A#*B |
| temp = shuffle(C, C, 0xA0); |
| temp = pmul(temp, shuffle(AB, AB, 0x44)); |
| iD = shuffle(C, C, 0xF5); |
| iD = pmul(iD, shuffle(AB, AB, 0xEE)); |
| iD = padd(iD, temp); |
| iD = psub(vmulq_lane_f32(D, vget_low_f32(dA), 0), iD); |
| |
| // iA = A*|D| - B*D#*C |
| temp = shuffle(B, B, 0xA0); |
| temp = pmul(temp, shuffle(DC, DC, 0x44)); |
| iA = shuffle(B, B, 0xF5); |
| iA = pmul(iA, shuffle(DC, DC, 0xEE)); |
| iA = padd(iA, temp); |
| iA = psub(vmulq_lane_f32(A, vget_low_f32(dD), 0), iA); |
| |
| // iB = C*|B| - D * (A#B)# = C*|B| - D*B#*A |
| iB = pmul(D, shuffle(AB, AB, 0x33)); |
| iB = psub(iB, pmul(shuffle(D, D, 0xB1), shuffle(AB, AB, 0x66))); |
| iB = psub(vmulq_lane_f32(C, vget_low_f32(dB), 0), iB); |
| |
| // iC = B*|C| - A * (D#C)# = B*|C| - A*C#*D |
| iC = pmul(A, shuffle(DC, DC, 0x33)); |
| iC = psub(iC, pmul(shuffle(A, A, 0xB1), shuffle(DC, DC, 0x66))); |
| iC = psub(vmulq_lane_f32(B, vget_low_f32(dC), 0), iC); |
| |
| const Packet4f coeff = {1.0, -1.0, -1.0, 1.0}; |
| rd = pmul(vdupq_lane_f32(vget_low_f32(rd), 0), coeff); |
| iA = pmul(iA, rd); |
| iB = pmul(iB, rd); |
| iC = pmul(iC, rd); |
| iD = pmul(iD, rd); |
| |
| Index res_stride = result.outerStride(); |
| float *res = result.data(); |
| |
| pstoret<float, Packet4f, ResultAlignment>(res + 0, shuffle(iA, iB, 0x77)); |
| pstoret<float, Packet4f, ResultAlignment>(res + res_stride, shuffle(iA, iB, 0x22)); |
| pstoret<float, Packet4f, ResultAlignment>(res + 2 * res_stride, shuffle(iC, iD, 0x77)); |
| pstoret<float, Packet4f, ResultAlignment>(res + 3 * res_stride, shuffle(iC, iD, 0x22)); |
| } |
| }; |
| |
| #if EIGEN_ARCH_ARM64 && !EIGEN_APPLE_DOUBLE_NEON_BUG |
| |
| // same algorithm as above, except that each operand is split into |
| // halves for two registers to hold. |
| template <typename MatrixType, typename ResultType> |
| struct compute_inverse_size4<Architecture::NEON, double, MatrixType, ResultType> |
| { |
| enum |
| { |
| MatrixAlignment = traits<MatrixType>::Alignment, |
| ResultAlignment = traits<ResultType>::Alignment, |
| StorageOrdersMatch = (MatrixType::Flags & RowMajorBit) == (ResultType::Flags & RowMajorBit) |
| }; |
| typedef typename conditional<(MatrixType::Flags & LinearAccessBit), |
| MatrixType const &, |
| typename MatrixType::PlainObject>::type |
| ActualMatrixType; |
| |
| // fuctionally equivalent to _mm_shuffle_pd in SSE (i.e. shuffle(m, n, mask) equals _mm_shuffle_pd(m,n,mask)) |
| static Packet2d shuffle(const Packet2d &m, const Packet2d &n, int mask) |
| { |
| const double *a = reinterpret_cast<const double *>(&m); |
| const double *b = reinterpret_cast<const double *>(&n); |
| Packet2d res = {*(a + (mask & 1)), *(b + ((mask >> 1) & 1))}; |
| return res; |
| } |
| |
| static void run(const MatrixType &mat, ResultType &result) |
| { |
| ActualMatrixType matrix(mat); |
| |
| // Four 2x2 sub-matrices of the input matrix, each is further divided into upper and lower |
| // row e.g. A1, upper row of A, A2, lower row of A |
| // input = [[A, B], = [[[A1, [B1, |
| // [C, D]] A2], B2]], |
| // [[C1, [D1, |
| // C2], D2]]] |
| |
| Packet2d A1, A2, B1, B2, C1, C2, D1, D2; |
| |
| if (StorageOrdersMatch) |
| { |
| A1 = matrix.template packet<MatrixAlignment>(0); |
| B1 = matrix.template packet<MatrixAlignment>(2); |
| A2 = matrix.template packet<MatrixAlignment>(4); |
| B2 = matrix.template packet<MatrixAlignment>(6); |
| C1 = matrix.template packet<MatrixAlignment>(8); |
| D1 = matrix.template packet<MatrixAlignment>(10); |
| C2 = matrix.template packet<MatrixAlignment>(12); |
| D2 = matrix.template packet<MatrixAlignment>(14); |
| } |
| else |
| { |
| Packet2d temp; |
| A1 = matrix.template packet<MatrixAlignment>(0); |
| C1 = matrix.template packet<MatrixAlignment>(2); |
| A2 = matrix.template packet<MatrixAlignment>(4); |
| C2 = matrix.template packet<MatrixAlignment>(6); |
| |
| temp = A1; |
| A1 = shuffle(A1, A2, 0); |
| A2 = shuffle(temp, A2, 3); |
| |
| temp = C1; |
| C1 = shuffle(C1, C2, 0); |
| C2 = shuffle(temp, C2, 3); |
| |
| B1 = matrix.template packet<MatrixAlignment>(8); |
| D1 = matrix.template packet<MatrixAlignment>(10); |
| B2 = matrix.template packet<MatrixAlignment>(12); |
| D2 = matrix.template packet<MatrixAlignment>(14); |
| |
| temp = B1; |
| B1 = shuffle(B1, B2, 0); |
| B2 = shuffle(temp, B2, 3); |
| |
| temp = D1; |
| D1 = shuffle(D1, D2, 0); |
| D2 = shuffle(temp, D2, 3); |
| } |
| |
| // determinants of the sub-matrices |
| Packet2d dA, dB, dC, dD; |
| |
| dA = shuffle(A2, A2, 1); |
| dA = pmul(A1, dA); |
| dA = psub(dA, vdupq_laneq_f64(dA, 1)); |
| |
| dB = shuffle(B2, B2, 1); |
| dB = pmul(B1, dB); |
| dB = psub(dB, vdupq_laneq_f64(dB, 1)); |
| |
| dC = shuffle(C2, C2, 1); |
| dC = pmul(C1, dC); |
| dC = psub(dC, vdupq_laneq_f64(dC, 1)); |
| |
| dD = shuffle(D2, D2, 1); |
| dD = pmul(D1, dD); |
| dD = psub(dD, vdupq_laneq_f64(dD, 1)); |
| |
| Packet2d DC1, DC2, AB1, AB2; |
| |
| // AB = A# * B, where A# denotes the adjugate of A, and * denotes matrix product. |
| AB1 = pmul(B1, vdupq_laneq_f64(A2, 1)); |
| AB2 = pmul(B2, vdupq_laneq_f64(A1, 0)); |
| AB1 = psub(AB1, pmul(B2, vdupq_laneq_f64(A1, 1))); |
| AB2 = psub(AB2, pmul(B1, vdupq_laneq_f64(A2, 0))); |
| |
| // DC = D#*C |
| DC1 = pmul(C1, vdupq_laneq_f64(D2, 1)); |
| DC2 = pmul(C2, vdupq_laneq_f64(D1, 0)); |
| DC1 = psub(DC1, pmul(C2, vdupq_laneq_f64(D1, 1))); |
| DC2 = psub(DC2, pmul(C1, vdupq_laneq_f64(D2, 0))); |
| |
| Packet2d d1, d2; |
| |
| // determinant of the input matrix, det = |A||D| + |B||C| - trace(A#*B*D#*C) |
| Packet2d det; |
| |
| // reciprocal of the determinant of the input matrix, rd = 1/det |
| Packet2d rd; |
| |
| d1 = pmul(AB1, shuffle(DC1, DC2, 0)); |
| d2 = pmul(AB2, shuffle(DC1, DC2, 3)); |
| rd = padd(d1, d2); |
| rd = padd(rd, vdupq_laneq_f64(rd, 1)); |
| |
| d1 = pmul(dA, dD); |
| d2 = pmul(dB, dC); |
| |
| det = padd(d1, d2); |
| det = psub(det, rd); |
| det = vdupq_laneq_f64(det, 0); |
| rd = pdiv(vdupq_n_f64(float64_t(1.0)), det); |
| |
| // rows of four sub-matrices of the inverse |
| Packet2d iA1, iA2, iB1, iB2, iC1, iC2, iD1, iD2; |
| |
| // iD = D*|A| - C*A#*B |
| iD1 = pmul(AB1, vdupq_laneq_f64(C1, 0)); |
| iD2 = pmul(AB1, vdupq_laneq_f64(C2, 0)); |
| iD1 = padd(iD1, pmul(AB2, vdupq_laneq_f64(C1, 1))); |
| iD2 = padd(iD2, pmul(AB2, vdupq_laneq_f64(C2, 1))); |
| dA = vdupq_laneq_f64(dA, 0); |
| iD1 = psub(pmul(D1, dA), iD1); |
| iD2 = psub(pmul(D2, dA), iD2); |
| |
| // iA = A*|D| - B*D#*C |
| iA1 = pmul(DC1, vdupq_laneq_f64(B1, 0)); |
| iA2 = pmul(DC1, vdupq_laneq_f64(B2, 0)); |
| iA1 = padd(iA1, pmul(DC2, vdupq_laneq_f64(B1, 1))); |
| iA2 = padd(iA2, pmul(DC2, vdupq_laneq_f64(B2, 1))); |
| dD = vdupq_laneq_f64(dD, 0); |
| iA1 = psub(pmul(A1, dD), iA1); |
| iA2 = psub(pmul(A2, dD), iA2); |
| |
| // iB = C*|B| - D * (A#B)# = C*|B| - D*B#*A |
| iB1 = pmul(D1, shuffle(AB2, AB1, 1)); |
| iB2 = pmul(D2, shuffle(AB2, AB1, 1)); |
| iB1 = psub(iB1, pmul(shuffle(D1, D1, 1), shuffle(AB2, AB1, 2))); |
| iB2 = psub(iB2, pmul(shuffle(D2, D2, 1), shuffle(AB2, AB1, 2))); |
| dB = vdupq_laneq_f64(dB, 0); |
| iB1 = psub(pmul(C1, dB), iB1); |
| iB2 = psub(pmul(C2, dB), iB2); |
| |
| // iC = B*|C| - A * (D#C)# = B*|C| - A*C#*D |
| iC1 = pmul(A1, shuffle(DC2, DC1, 1)); |
| iC2 = pmul(A2, shuffle(DC2, DC1, 1)); |
| iC1 = psub(iC1, pmul(shuffle(A1, A1, 1), shuffle(DC2, DC1, 2))); |
| iC2 = psub(iC2, pmul(shuffle(A2, A2, 1), shuffle(DC2, DC1, 2))); |
| dC = vdupq_laneq_f64(dC, 0); |
| iC1 = psub(pmul(B1, dC), iC1); |
| iC2 = psub(pmul(B2, dC), iC2); |
| |
| const Packet2d PN = {1.0, -1.0}; |
| const Packet2d NP = {-1.0, 1.0}; |
| d1 = pmul(PN, rd); |
| d2 = pmul(NP, rd); |
| |
| Index res_stride = result.outerStride(); |
| double *res = result.data(); |
| pstoret<double, Packet2d, ResultAlignment>(res + 0, pmul(shuffle(iA2, iA1, 3), d1)); |
| pstoret<double, Packet2d, ResultAlignment>(res + res_stride, pmul(shuffle(iA2, iA1, 0), d2)); |
| pstoret<double, Packet2d, ResultAlignment>(res + 2, pmul(shuffle(iB2, iB1, 3), d1)); |
| pstoret<double, Packet2d, ResultAlignment>(res + res_stride + 2, pmul(shuffle(iB2, iB1, 0), d2)); |
| pstoret<double, Packet2d, ResultAlignment>(res + 2 * res_stride, pmul(shuffle(iC2, iC1, 3), d1)); |
| pstoret<double, Packet2d, ResultAlignment>(res + 3 * res_stride, pmul(shuffle(iC2, iC1, 0), d2)); |
| pstoret<double, Packet2d, ResultAlignment>(res + 2 * res_stride + 2, pmul(shuffle(iD2, iD1, 3), d1)); |
| pstoret<double, Packet2d, ResultAlignment>(res + 3 * res_stride + 2, pmul(shuffle(iD2, iD1, 0), d2)); |
| } |
| }; |
| |
| #endif // EIGEN_ARCH_ARM64 && !EIGEN_APPLE_DOUBLE_NEON_BUG |
| |
| } // namespace internal |
| } // namespace Eigen |
| #endif |