trsm.hpp

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/*!
 * 
 *
 * \brief       -
 *
 * \author      O. Krause
 * \date        2011
 *
 *
 * \par Copyright 1995-2015 Shark Development Team
 * 
 * <BR><HR>
 * This file is part of Shark.
 * <http://image.diku.dk/shark/>
 * 
 * Shark is free software: you can redistribute it and/or modify
 * it under the terms of the GNU Lesser General Public License as published 
 * by the Free Software Foundation, either version 3 of the License, or
 * (at your option) any later version.
 * 
 * Shark is distributed in the hope that it will be useful,
 * but WITHOUT ANY WARRANTY; without even the implied warranty of
 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
 * GNU Lesser General Public License for more details.
 * 
 * You should have received a copy of the GNU Lesser General Public License
 * along with Shark.  If not, see <http://www.gnu.org/licenses/>.
 *
 */
 
#ifndef REMORA_KERNELS_CBLAS_TRSM_HPP
#define REMORA_KERNELS_CBLAS_TRSM_HPP
 
#include "cblas_inc.hpp"
#include "../../proxy_expressions.hpp"
#include <type_traits>
///solves systems of triangular matrices
 
namespace remora{namespace bindings {
inline void trsm(
    CBLAS_ORDER order, CBLAS_UPLO uplo,CBLAS_TRANSPOSE transA, 
    CBLAS_SIDE side, CBLAS_DIAG unit,
    int n, int nRHS,
    float const *A, int lda, float *B, int ldb
) {
    cblas_strsm(order, side, uplo, transA, unit,n, nRHS, 1.0, A, lda, B, ldb);
}
 
inline void trsm(
    CBLAS_ORDER order, CBLAS_UPLO uplo,CBLAS_TRANSPOSE transA, 
    CBLAS_SIDE side, CBLAS_DIAG unit,
    int n, int nRHS,
    double const *A, int lda, double *B, int ldb
) {
    cblas_dtrsm(order, side, uplo, transA, unit,n, nRHS, 1.0, A, lda, B, ldb);
}
 
inline void trsm(
    CBLAS_ORDER order, CBLAS_UPLO uplo,CBLAS_TRANSPOSE transA, 
    CBLAS_SIDE side, CBLAS_DIAG unit,
    int n, int nRHS,
    std::complex<float> const *A, int lda, std::complex<float> *B, int ldb
) {
    std::complex<float> alpha(1.0,0);
    cblas_ctrsm(order, side, uplo, transA, unit,n, nRHS,
        reinterpret_cast<cblas_float_complex_type const *>(&alpha),
            reinterpret_cast<cblas_float_complex_type const *>(A), lda,
            reinterpret_cast<cblas_float_complex_type *>(B), ldb);
}
inline void trsm(
    CBLAS_ORDER order, CBLAS_UPLO uplo,CBLAS_TRANSPOSE transA, 
    CBLAS_SIDE side, CBLAS_DIAG unit,
    int n, int nRHS,
    std::complex<double> const *A, int lda, std::complex<double> *B, int ldb
) {
    std::complex<double> alpha(1.0,0);
    cblas_ztrsm(order, side, uplo, transA, unit,n, nRHS,
        reinterpret_cast<cblas_double_complex_type const *>(&alpha),
            reinterpret_cast<cblas_double_complex_type const *>(A), lda,
            reinterpret_cast<cblas_double_complex_type *>(B), ldb);
}
 
// trsm(): solves A system of linear equations A * X = B
//             when A is a triangular matrix
template <class Triangular, typename MatA, typename MatB>
void trsm_impl(
    matrix_expression<MatA, cpu_tag> const &A,
    matrix_expression<MatB, cpu_tag> &B,
    std::true_type, left
){
    REMORA_SIZE_CHECK(A().size1() == A().size2());
    REMORA_SIZE_CHECK(A().size1() == B().size1());
    
    //orientation is defined by the second argument
    CBLAS_ORDER const storOrd = (CBLAS_ORDER)storage_order<typename MatB::orientation>::value;
    //if orientations do not match, wecan interpret this as transposing A
    bool transposeA =  !std::is_same<typename MatA::orientation,typename MatB::orientation>::value;
    
    CBLAS_DIAG cblasUnit = Triangular::is_unit?CblasUnit:CblasNonUnit;
    CBLAS_UPLO cblasUplo = (Triangular::is_upper != transposeA)?CblasUpper:CblasLower;
    CBLAS_TRANSPOSE transA = transposeA?CblasTrans:CblasNoTrans;
    
    int m = B().size1();
    int nrhs = B().size2();
    auto storageA = A().raw_storage();
    auto storageB = B().raw_storage();
    trsm(storOrd, cblasUplo, transA, CblasLeft,cblasUnit, m, nrhs,
        storageA.values,
            storageA.leading_dimension,
        storageB.values,
            storageB.leading_dimension
    );
}
 
template <class Triangular, typename MatA, typename MatB>
void trsm_impl(
    matrix_expression<MatA, cpu_tag> const &A,
    matrix_expression<MatB, cpu_tag> &B,
    std::true_type, right
){
    auto transB = trans(B);
    trsm_impl<typename Triangular::transposed_orientation>(trans(A), transB, std::true_type(),  left());
}
 
template <class Triangular, class Side, typename MatA, typename MatB>
void trsm(
    matrix_expression<MatA, cpu_tag> const &A,
    matrix_expression<MatB, cpu_tag> &B,
    std::true_type
){
    trsm_impl<Triangular>(A,B, std::true_type(),  Side());
}
 
template<class M1, class M2>
struct has_optimized_trsm: std::integral_constant<bool,
    allowed_cblas_type<typename M1::value_type>::type::value
    && std::is_same<typename M1::value_type, typename M2::value_type>::value
    && std::is_base_of<dense_tag, typename M1::storage_type::storage_tag>::value
    && std::is_base_of<dense_tag, typename M2::storage_type::storage_tag>::value 
>{};
 
}}
#endif