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// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2009 Gael Guennebaud <gael.guennebaud@inria.fr>
//
// 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/.
#ifndef EIGEN_SELFADJOINT_MATRIX_MATRIX_H
#define EIGEN_SELFADJOINT_MATRIX_MATRIX_H
// IWYU pragma: private
#include "../InternalHeaderCheck.h"
namespace Eigen {
namespace internal {
// pack a selfadjoint block diagonal for use with the gebp_kernel
template <typename Scalar, typename Index, int Pack1, int Pack2_dummy, int StorageOrder>
struct symm_pack_lhs {
template <int BlockRows>
inline void pack(Scalar* blockA, const const_blas_data_mapper<Scalar, Index, StorageOrder>& lhs, Index cols, Index i,
Index& count) {
// normal copy
for (Index k = 0; k < i; k++)
for (Index w = 0; w < BlockRows; w++) blockA[count++] = lhs(i + w, k); // normal
// symmetric copy
Index h = 0;
for (Index k = i; k < i + BlockRows; k++) {
for (Index w = 0; w < h; w++) blockA[count++] = numext::conj(lhs(k, i + w)); // transposed
blockA[count++] = numext::real(lhs(k, k)); // real (diagonal)
for (Index w = h + 1; w < BlockRows; w++) blockA[count++] = lhs(i + w, k); // normal
++h;
}
// transposed copy
for (Index k = i + BlockRows; k < cols; k++)
for (Index w = 0; w < BlockRows; w++) blockA[count++] = numext::conj(lhs(k, i + w)); // transposed
}
void operator()(Scalar* blockA, const Scalar* lhs_, Index lhsStride, Index cols, Index rows) {
typedef typename unpacket_traits<typename packet_traits<Scalar>::type>::half HalfPacket;
typedef typename unpacket_traits<typename unpacket_traits<typename packet_traits<Scalar>::type>::half>::half
QuarterPacket;
enum {
PacketSize = packet_traits<Scalar>::size,
HalfPacketSize = unpacket_traits<HalfPacket>::size,
QuarterPacketSize = unpacket_traits<QuarterPacket>::size,
HasHalf = (int)HalfPacketSize < (int)PacketSize,
HasQuarter = (int)QuarterPacketSize < (int)HalfPacketSize
};
const_blas_data_mapper<Scalar, Index, StorageOrder> lhs(lhs_, lhsStride);
Index count = 0;
// Index peeled_mc3 = (rows/Pack1)*Pack1;
const Index peeled_mc3 = Pack1 >= 3 * PacketSize ? (rows / (3 * PacketSize)) * (3 * PacketSize) : 0;
const Index peeled_mc2 =
Pack1 >= 2 * PacketSize ? peeled_mc3 + ((rows - peeled_mc3) / (2 * PacketSize)) * (2 * PacketSize) : 0;
const Index peeled_mc1 =
Pack1 >= 1 * PacketSize ? peeled_mc2 + ((rows - peeled_mc2) / (1 * PacketSize)) * (1 * PacketSize) : 0;
const Index peeled_mc_half =
Pack1 >= HalfPacketSize ? peeled_mc1 + ((rows - peeled_mc1) / (HalfPacketSize)) * (HalfPacketSize) : 0;
const Index peeled_mc_quarter =
Pack1 >= QuarterPacketSize
? peeled_mc_half + ((rows - peeled_mc_half) / (QuarterPacketSize)) * (QuarterPacketSize)
: 0;
if (Pack1 >= 3 * PacketSize)
for (Index i = 0; i < peeled_mc3; i += 3 * PacketSize) pack<3 * PacketSize>(blockA, lhs, cols, i, count);
if (Pack1 >= 2 * PacketSize)
for (Index i = peeled_mc3; i < peeled_mc2; i += 2 * PacketSize) pack<2 * PacketSize>(blockA, lhs, cols, i, count);
if (Pack1 >= 1 * PacketSize)
for (Index i = peeled_mc2; i < peeled_mc1; i += 1 * PacketSize) pack<1 * PacketSize>(blockA, lhs, cols, i, count);
if (HasHalf && Pack1 >= HalfPacketSize)
for (Index i = peeled_mc1; i < peeled_mc_half; i += HalfPacketSize)
pack<HalfPacketSize>(blockA, lhs, cols, i, count);
if (HasQuarter && Pack1 >= QuarterPacketSize)
for (Index i = peeled_mc_half; i < peeled_mc_quarter; i += QuarterPacketSize)
pack<QuarterPacketSize>(blockA, lhs, cols, i, count);
// do the same with mr==1
for (Index i = peeled_mc_quarter; i < rows; i++) {
for (Index k = 0; k < i; k++) blockA[count++] = lhs(i, k); // normal
blockA[count++] = numext::real(lhs(i, i)); // real (diagonal)
for (Index k = i + 1; k < cols; k++) blockA[count++] = numext::conj(lhs(k, i)); // transposed
}
}
};
template <typename Scalar, typename Index, int nr, int StorageOrder>
struct symm_pack_rhs {
enum { PacketSize = packet_traits<Scalar>::size };
void operator()(Scalar* blockB, const Scalar* rhs_, Index rhsStride, Index rows, Index cols, Index k2) {
Index end_k = k2 + rows;
Index count = 0;
const_blas_data_mapper<Scalar, Index, StorageOrder> rhs(rhs_, rhsStride);
Index packet_cols8 = nr >= 8 ? (cols / 8) * 8 : 0;
Index packet_cols4 = nr >= 4 ? (cols / 4) * 4 : 0;
// first part: normal case
for (Index j2 = 0; j2 < k2; j2 += nr) {
for (Index k = k2; k < end_k; k++) {
blockB[count + 0] = rhs(k, j2 + 0);
blockB[count + 1] = rhs(k, j2 + 1);
if (nr >= 4) {
blockB[count + 2] = rhs(k, j2 + 2);
blockB[count + 3] = rhs(k, j2 + 3);
}
if (nr >= 8) {
blockB[count + 4] = rhs(k, j2 + 4);
blockB[count + 5] = rhs(k, j2 + 5);
blockB[count + 6] = rhs(k, j2 + 6);
blockB[count + 7] = rhs(k, j2 + 7);
}
count += nr;
}
}
// second part: diagonal block
Index end8 = nr >= 8 ? (std::min)(k2 + rows, packet_cols8) : k2;
if (nr >= 8) {
for (Index j2 = k2; j2 < end8; j2 += 8) {
// again we can split vertically in three different parts (transpose, symmetric, normal)
// transpose
for (Index k = k2; k < j2; k++) {
blockB[count + 0] = numext::conj(rhs(j2 + 0, k));
blockB[count + 1] = numext::conj(rhs(j2 + 1, k));
blockB[count + 2] = numext::conj(rhs(j2 + 2, k));
blockB[count + 3] = numext::conj(rhs(j2 + 3, k));
blockB[count + 4] = numext::conj(rhs(j2 + 4, k));
blockB[count + 5] = numext::conj(rhs(j2 + 5, k));
blockB[count + 6] = numext::conj(rhs(j2 + 6, k));
blockB[count + 7] = numext::conj(rhs(j2 + 7, k));
count += 8;
}
// symmetric
Index h = 0;
for (Index k = j2; k < j2 + 8; k++) {
// normal
for (Index w = 0; w < h; ++w) blockB[count + w] = rhs(k, j2 + w);
blockB[count + h] = numext::real(rhs(k, k));
// transpose
for (Index w = h + 1; w < 8; ++w) blockB[count + w] = numext::conj(rhs(j2 + w, k));
count += 8;
++h;
}
// normal
for (Index k = j2 + 8; k < end_k; k++) {
blockB[count + 0] = rhs(k, j2 + 0);
blockB[count + 1] = rhs(k, j2 + 1);
blockB[count + 2] = rhs(k, j2 + 2);
blockB[count + 3] = rhs(k, j2 + 3);
blockB[count + 4] = rhs(k, j2 + 4);
blockB[count + 5] = rhs(k, j2 + 5);
blockB[count + 6] = rhs(k, j2 + 6);
blockB[count + 7] = rhs(k, j2 + 7);
count += 8;
}
}
}
if (nr >= 4) {
for (Index j2 = end8; j2 < (std::min)(k2 + rows, packet_cols4); j2 += 4) {
// again we can split vertically in three different parts (transpose, symmetric, normal)
// transpose
for (Index k = k2; k < j2; k++) {
blockB[count + 0] = numext::conj(rhs(j2 + 0, k));
blockB[count + 1] = numext::conj(rhs(j2 + 1, k));
blockB[count + 2] = numext::conj(rhs(j2 + 2, k));
blockB[count + 3] = numext::conj(rhs(j2 + 3, k));
count += 4;
}
// symmetric
Index h = 0;
for (Index k = j2; k < j2 + 4; k++) {
// normal
for (Index w = 0; w < h; ++w) blockB[count + w] = rhs(k, j2 + w);
blockB[count + h] = numext::real(rhs(k, k));
// transpose
for (Index w = h + 1; w < 4; ++w) blockB[count + w] = numext::conj(rhs(j2 + w, k));
count += 4;
++h;
}
// normal
for (Index k = j2 + 4; k < end_k; k++) {
blockB[count + 0] = rhs(k, j2 + 0);
blockB[count + 1] = rhs(k, j2 + 1);
blockB[count + 2] = rhs(k, j2 + 2);
blockB[count + 3] = rhs(k, j2 + 3);
count += 4;
}
}
}
// third part: transposed
if (nr >= 8) {
for (Index j2 = k2 + rows; j2 < packet_cols8; j2 += 8) {
for (Index k = k2; k < end_k; k++) {
blockB[count + 0] = numext::conj(rhs(j2 + 0, k));
blockB[count + 1] = numext::conj(rhs(j2 + 1, k));
blockB[count + 2] = numext::conj(rhs(j2 + 2, k));
blockB[count + 3] = numext::conj(rhs(j2 + 3, k));
blockB[count + 4] = numext::conj(rhs(j2 + 4, k));
blockB[count + 5] = numext::conj(rhs(j2 + 5, k));
blockB[count + 6] = numext::conj(rhs(j2 + 6, k));
blockB[count + 7] = numext::conj(rhs(j2 + 7, k));
count += 8;
}
}
}
if (nr >= 4) {
for (Index j2 = (std::max)(packet_cols8, k2 + rows); j2 < packet_cols4; j2 += 4) {
for (Index k = k2; k < end_k; k++) {
blockB[count + 0] = numext::conj(rhs(j2 + 0, k));
blockB[count + 1] = numext::conj(rhs(j2 + 1, k));
blockB[count + 2] = numext::conj(rhs(j2 + 2, k));
blockB[count + 3] = numext::conj(rhs(j2 + 3, k));
count += 4;
}
}
}
// copy the remaining columns one at a time (=> the same with nr==1)
for (Index j2 = packet_cols4; j2 < cols; ++j2) {
// transpose
Index half = (std::min)(end_k, j2);
for (Index k = k2; k < half; k++) {
blockB[count] = numext::conj(rhs(j2, k));
count += 1;
}
if (half == j2 && half < k2 + rows) {
blockB[count] = numext::real(rhs(j2, j2));
count += 1;
} else
half--;
// normal
for (Index k = half + 1; k < k2 + rows; k++) {
blockB[count] = rhs(k, j2);
count += 1;
}
}
}
};
/* Optimized selfadjoint matrix * matrix (_SYMM) product built on top of
* the general matrix matrix product.
*/
template <typename Scalar, typename Index, int LhsStorageOrder, bool LhsSelfAdjoint, bool ConjugateLhs,
int RhsStorageOrder, bool RhsSelfAdjoint, bool ConjugateRhs, int ResStorageOrder, int ResInnerStride>
struct product_selfadjoint_matrix;
template <typename Scalar, typename Index, int LhsStorageOrder, bool LhsSelfAdjoint, bool ConjugateLhs,
int RhsStorageOrder, bool RhsSelfAdjoint, bool ConjugateRhs, int ResInnerStride>
struct product_selfadjoint_matrix<Scalar, Index, LhsStorageOrder, LhsSelfAdjoint, ConjugateLhs, RhsStorageOrder,
RhsSelfAdjoint, ConjugateRhs, RowMajor, ResInnerStride> {
static EIGEN_STRONG_INLINE void run(Index rows, Index cols, const Scalar* lhs, Index lhsStride, const Scalar* rhs,
Index rhsStride, Scalar* res, Index resIncr, Index resStride, const Scalar& alpha,
level3_blocking<Scalar, Scalar>& blocking) {
product_selfadjoint_matrix<
Scalar, Index, logical_xor(RhsSelfAdjoint, RhsStorageOrder == RowMajor) ? ColMajor : RowMajor, RhsSelfAdjoint,
NumTraits<Scalar>::IsComplex && logical_xor(RhsSelfAdjoint, ConjugateRhs),
logical_xor(LhsSelfAdjoint, LhsStorageOrder == RowMajor) ? ColMajor : RowMajor, LhsSelfAdjoint,
NumTraits<Scalar>::IsComplex && logical_xor(LhsSelfAdjoint, ConjugateLhs), ColMajor,
ResInnerStride>::run(cols, rows, rhs, rhsStride, lhs, lhsStride, res, resIncr, resStride, alpha, blocking);
}
};
template <typename Scalar, typename Index, int LhsStorageOrder, bool ConjugateLhs, int RhsStorageOrder,
bool ConjugateRhs, int ResInnerStride>
struct product_selfadjoint_matrix<Scalar, Index, LhsStorageOrder, true, ConjugateLhs, RhsStorageOrder, false,
ConjugateRhs, ColMajor, ResInnerStride> {
static EIGEN_DONT_INLINE void run(Index rows, Index cols, const Scalar* lhs_, Index lhsStride, const Scalar* rhs_,
Index rhsStride, Scalar* res, Index resIncr, Index resStride, const Scalar& alpha,
level3_blocking<Scalar, Scalar>& blocking);
};
template <typename Scalar, typename Index, int LhsStorageOrder, bool ConjugateLhs, int RhsStorageOrder,
bool ConjugateRhs, int ResInnerStride>
EIGEN_DONT_INLINE void
product_selfadjoint_matrix<Scalar, Index, LhsStorageOrder, true, ConjugateLhs, RhsStorageOrder, false, ConjugateRhs,
ColMajor, ResInnerStride>::run(Index rows, Index cols, const Scalar* lhs_, Index lhsStride,
const Scalar* rhs_, Index rhsStride, Scalar* res_,
Index resIncr, Index resStride, const Scalar& alpha,
level3_blocking<Scalar, Scalar>& blocking) {
Index size = rows;
typedef gebp_traits<Scalar, Scalar> Traits;
typedef const_blas_data_mapper<Scalar, Index, LhsStorageOrder> LhsMapper;
typedef const_blas_data_mapper<Scalar, Index, (LhsStorageOrder == RowMajor) ? ColMajor : RowMajor> LhsTransposeMapper;
typedef const_blas_data_mapper<Scalar, Index, RhsStorageOrder> RhsMapper;
typedef blas_data_mapper<typename Traits::ResScalar, Index, ColMajor, Unaligned, ResInnerStride> ResMapper;
LhsMapper lhs(lhs_, lhsStride);
LhsTransposeMapper lhs_transpose(lhs_, lhsStride);
RhsMapper rhs(rhs_, rhsStride);
ResMapper res(res_, resStride, resIncr);
Index kc = blocking.kc(); // cache block size along the K direction
Index mc = (std::min)(rows, blocking.mc()); // cache block size along the M direction
// kc must be smaller than mc
kc = (std::min)(kc, mc);
std::size_t sizeA = kc * mc;
std::size_t sizeB = kc * cols;
ei_declare_aligned_stack_constructed_variable(Scalar, blockA, sizeA, blocking.blockA());
ei_declare_aligned_stack_constructed_variable(Scalar, blockB, sizeB, blocking.blockB());
gebp_kernel<Scalar, Scalar, Index, ResMapper, Traits::mr, Traits::nr, ConjugateLhs, ConjugateRhs> gebp_kernel;
symm_pack_lhs<Scalar, Index, Traits::mr, Traits::LhsProgress, LhsStorageOrder> pack_lhs;
gemm_pack_rhs<Scalar, Index, RhsMapper, Traits::nr, RhsStorageOrder> pack_rhs;
gemm_pack_lhs<Scalar, Index, LhsTransposeMapper, Traits::mr, Traits::LhsProgress, typename Traits::LhsPacket4Packing,
LhsStorageOrder == RowMajor ? ColMajor : RowMajor, true>
pack_lhs_transposed;
for (Index k2 = 0; k2 < size; k2 += kc) {
const Index actual_kc = (std::min)(k2 + kc, size) - k2;
// we have selected one row panel of rhs and one column panel of lhs
// pack rhs's panel into a sequential chunk of memory
// and expand each coeff to a constant packet for further reuse
pack_rhs(blockB, rhs.getSubMapper(k2, 0), actual_kc, cols);
// the select lhs's panel has to be split in three different parts:
// 1 - the transposed panel above the diagonal block => transposed packed copy
// 2 - the diagonal block => special packed copy
// 3 - the panel below the diagonal block => generic packed copy
for (Index i2 = 0; i2 < k2; i2 += mc) {
const Index actual_mc = (std::min)(i2 + mc, k2) - i2;
// transposed packed copy
pack_lhs_transposed(blockA, lhs_transpose.getSubMapper(i2, k2), actual_kc, actual_mc);
gebp_kernel(res.getSubMapper(i2, 0), blockA, blockB, actual_mc, actual_kc, cols, alpha);
}
// the block diagonal
{
const Index actual_mc = (std::min)(k2 + kc, size) - k2;
// symmetric packed copy
pack_lhs(blockA, &lhs(k2, k2), lhsStride, actual_kc, actual_mc);
gebp_kernel(res.getSubMapper(k2, 0), blockA, blockB, actual_mc, actual_kc, cols, alpha);
}
for (Index i2 = k2 + kc; i2 < size; i2 += mc) {
const Index actual_mc = (std::min)(i2 + mc, size) - i2;
gemm_pack_lhs<Scalar, Index, LhsMapper, Traits::mr, Traits::LhsProgress, typename Traits::LhsPacket4Packing,
LhsStorageOrder, false>()(blockA, lhs.getSubMapper(i2, k2), actual_kc, actual_mc);
gebp_kernel(res.getSubMapper(i2, 0), blockA, blockB, actual_mc, actual_kc, cols, alpha);
}
}
}
// matrix * selfadjoint product
template <typename Scalar, typename Index, int LhsStorageOrder, bool ConjugateLhs, int RhsStorageOrder,
bool ConjugateRhs, int ResInnerStride>
struct product_selfadjoint_matrix<Scalar, Index, LhsStorageOrder, false, ConjugateLhs, RhsStorageOrder, true,
ConjugateRhs, ColMajor, ResInnerStride> {
static EIGEN_DONT_INLINE void run(Index rows, Index cols, const Scalar* lhs_, Index lhsStride, const Scalar* rhs_,
Index rhsStride, Scalar* res, Index resIncr, Index resStride, const Scalar& alpha,
level3_blocking<Scalar, Scalar>& blocking);
};
template <typename Scalar, typename Index, int LhsStorageOrder, bool ConjugateLhs, int RhsStorageOrder,
bool ConjugateRhs, int ResInnerStride>
EIGEN_DONT_INLINE void
product_selfadjoint_matrix<Scalar, Index, LhsStorageOrder, false, ConjugateLhs, RhsStorageOrder, true, ConjugateRhs,
ColMajor, ResInnerStride>::run(Index rows, Index cols, const Scalar* lhs_, Index lhsStride,
const Scalar* rhs_, Index rhsStride, Scalar* res_,
Index resIncr, Index resStride, const Scalar& alpha,
level3_blocking<Scalar, Scalar>& blocking) {
Index size = cols;
typedef gebp_traits<Scalar, Scalar> Traits;
typedef const_blas_data_mapper<Scalar, Index, LhsStorageOrder> LhsMapper;
typedef blas_data_mapper<typename Traits::ResScalar, Index, ColMajor, Unaligned, ResInnerStride> ResMapper;
LhsMapper lhs(lhs_, lhsStride);
ResMapper res(res_, resStride, resIncr);
Index kc = blocking.kc(); // cache block size along the K direction
Index mc = (std::min)(rows, blocking.mc()); // cache block size along the M direction
std::size_t sizeA = kc * mc;
std::size_t sizeB = kc * cols;
ei_declare_aligned_stack_constructed_variable(Scalar, blockA, sizeA, blocking.blockA());
ei_declare_aligned_stack_constructed_variable(Scalar, blockB, sizeB, blocking.blockB());
gebp_kernel<Scalar, Scalar, Index, ResMapper, Traits::mr, Traits::nr, ConjugateLhs, ConjugateRhs> gebp_kernel;
gemm_pack_lhs<Scalar, Index, LhsMapper, Traits::mr, Traits::LhsProgress, typename Traits::LhsPacket4Packing,
LhsStorageOrder>
pack_lhs;
symm_pack_rhs<Scalar, Index, Traits::nr, RhsStorageOrder> pack_rhs;
for (Index k2 = 0; k2 < size; k2 += kc) {
const Index actual_kc = (std::min)(k2 + kc, size) - k2;
pack_rhs(blockB, rhs_, rhsStride, actual_kc, cols, k2);
// => GEPP
for (Index i2 = 0; i2 < rows; i2 += mc) {
const Index actual_mc = (std::min)(i2 + mc, rows) - i2;
pack_lhs(blockA, lhs.getSubMapper(i2, k2), actual_kc, actual_mc);
gebp_kernel(res.getSubMapper(i2, 0), blockA, blockB, actual_mc, actual_kc, cols, alpha);
}
}
}
} // end namespace internal
/***************************************************************************
* Wrapper to product_selfadjoint_matrix
***************************************************************************/
namespace internal {
template <typename Lhs, int LhsMode, typename Rhs, int RhsMode>
struct selfadjoint_product_impl<Lhs, LhsMode, false, Rhs, RhsMode, false> {
typedef typename Product<Lhs, Rhs>::Scalar Scalar;
typedef internal::blas_traits<Lhs> LhsBlasTraits;
typedef typename LhsBlasTraits::DirectLinearAccessType ActualLhsType;
typedef internal::blas_traits<Rhs> RhsBlasTraits;
typedef typename RhsBlasTraits::DirectLinearAccessType ActualRhsType;
enum {
LhsIsUpper = (LhsMode & (Upper | Lower)) == Upper,
LhsIsSelfAdjoint = (LhsMode & SelfAdjoint) == SelfAdjoint,
RhsIsUpper = (RhsMode & (Upper | Lower)) == Upper,
RhsIsSelfAdjoint = (RhsMode & SelfAdjoint) == SelfAdjoint
};
template <typename Dest>
static void run(Dest& dst, const Lhs& a_lhs, const Rhs& a_rhs, const Scalar& alpha) {
eigen_assert(dst.rows() == a_lhs.rows() && dst.cols() == a_rhs.cols());
add_const_on_value_type_t<ActualLhsType> lhs = LhsBlasTraits::extract(a_lhs);
add_const_on_value_type_t<ActualRhsType> rhs = RhsBlasTraits::extract(a_rhs);
Scalar actualAlpha = alpha * LhsBlasTraits::extractScalarFactor(a_lhs) * RhsBlasTraits::extractScalarFactor(a_rhs);
typedef internal::gemm_blocking_space<(Dest::Flags & RowMajorBit) ? RowMajor : ColMajor, Scalar, Scalar,
Lhs::MaxRowsAtCompileTime, Rhs::MaxColsAtCompileTime,
Lhs::MaxColsAtCompileTime, 1>
BlockingType;
BlockingType blocking(lhs.rows(), rhs.cols(), lhs.cols(), 1, false);
internal::product_selfadjoint_matrix<
Scalar, Index,
internal::logical_xor(LhsIsUpper, internal::traits<Lhs>::Flags & RowMajorBit) ? RowMajor : ColMajor,
LhsIsSelfAdjoint,
NumTraits<Scalar>::IsComplex && internal::logical_xor(LhsIsUpper, bool(LhsBlasTraits::NeedToConjugate)),
internal::logical_xor(RhsIsUpper, internal::traits<Rhs>::Flags & RowMajorBit) ? RowMajor : ColMajor,
RhsIsSelfAdjoint,
NumTraits<Scalar>::IsComplex && internal::logical_xor(RhsIsUpper, bool(RhsBlasTraits::NeedToConjugate)),
internal::traits<Dest>::Flags & RowMajorBit ? RowMajor : ColMajor,
Dest::InnerStrideAtCompileTime>::run(lhs.rows(), rhs.cols(), // sizes
&lhs.coeffRef(0, 0), lhs.outerStride(), // lhs info
&rhs.coeffRef(0, 0), rhs.outerStride(), // rhs info
&dst.coeffRef(0, 0), dst.innerStride(), dst.outerStride(), // result info
actualAlpha, blocking // alpha
);
}
};
} // end namespace internal
} // end namespace Eigen
#endif // EIGEN_SELFADJOINT_MATRIX_MATRIX_H