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+/*
+ Copyright (c) 2011, Intel Corporation. All rights reserved.
+
+ Redistribution and use in source and binary forms, with or without modification,
+ are permitted provided that the following conditions are met:
+
+ * Redistributions of source code must retain the above copyright notice, this
+ list of conditions and the following disclaimer.
+ * Redistributions in binary form must reproduce the above copyright notice,
+ this list of conditions and the following disclaimer in the documentation
+ and/or other materials provided with the distribution.
+ * Neither the name of Intel Corporation nor the names of its contributors may
+ be used to endorse or promote products derived from this software without
+ specific prior written permission.
+
+ THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
+ ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
+ WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
+ DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR
+ ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
+ (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
+ LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON
+ ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
+ (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
+ SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+
+ ********************************************************************************
+ * Content : Eigen bindings to Intel(R) MKL
+ * Triangular matrix-vector product functionality based on ?TRMV.
+ ********************************************************************************
+*/
+
+#ifndef EIGEN_TRIANGULAR_MATRIX_VECTOR_MKL_H
+#define EIGEN_TRIANGULAR_MATRIX_VECTOR_MKL_H
+
+namespace Eigen {
+
+namespace internal {
+
+/**********************************************************************
+* This file implements triangular matrix-vector multiplication using BLAS
+**********************************************************************/
+
+// trmv/hemv specialization
+
+template<typename Index, int Mode, typename LhsScalar, bool ConjLhs, typename RhsScalar, bool ConjRhs, int StorageOrder>
+struct triangular_matrix_vector_product_trmv :
+ triangular_matrix_vector_product<Index,Mode,LhsScalar,ConjLhs,RhsScalar,ConjRhs,StorageOrder,BuiltIn> {};
+
+#define EIGEN_MKL_TRMV_SPECIALIZE(Scalar) \
+template<typename Index, int Mode, bool ConjLhs, bool ConjRhs> \
+struct triangular_matrix_vector_product<Index,Mode,Scalar,ConjLhs,Scalar,ConjRhs,ColMajor,Specialized> { \
+ static EIGEN_DONT_INLINE void run(Index _rows, Index _cols, const Scalar* _lhs, Index lhsStride, \
+ const Scalar* _rhs, Index rhsIncr, Scalar* _res, Index resIncr, Scalar alpha) { \
+ triangular_matrix_vector_product_trmv<Index,Mode,Scalar,ConjLhs,Scalar,ConjRhs,ColMajor>::run( \
+ _rows, _cols, _lhs, lhsStride, _rhs, rhsIncr, _res, resIncr, alpha); \
+ } \
+}; \
+template<typename Index, int Mode, bool ConjLhs, bool ConjRhs> \
+struct triangular_matrix_vector_product<Index,Mode,Scalar,ConjLhs,Scalar,ConjRhs,RowMajor,Specialized> { \
+ static EIGEN_DONT_INLINE void run(Index _rows, Index _cols, const Scalar* _lhs, Index lhsStride, \
+ const Scalar* _rhs, Index rhsIncr, Scalar* _res, Index resIncr, Scalar alpha) { \
+ triangular_matrix_vector_product_trmv<Index,Mode,Scalar,ConjLhs,Scalar,ConjRhs,RowMajor>::run( \
+ _rows, _cols, _lhs, lhsStride, _rhs, rhsIncr, _res, resIncr, alpha); \
+ } \
+};
+
+EIGEN_MKL_TRMV_SPECIALIZE(double)
+EIGEN_MKL_TRMV_SPECIALIZE(float)
+EIGEN_MKL_TRMV_SPECIALIZE(dcomplex)
+EIGEN_MKL_TRMV_SPECIALIZE(scomplex)
+
+// implements col-major: res += alpha * op(triangular) * vector
+#define EIGEN_MKL_TRMV_CM(EIGTYPE, MKLTYPE, EIGPREFIX, MKLPREFIX) \
+template<typename Index, int Mode, bool ConjLhs, bool ConjRhs> \
+struct triangular_matrix_vector_product_trmv<Index,Mode,EIGTYPE,ConjLhs,EIGTYPE,ConjRhs,ColMajor> { \
+ enum { \
+ IsLower = (Mode&Lower) == Lower, \
+ SetDiag = (Mode&(ZeroDiag|UnitDiag)) ? 0 : 1, \
+ IsUnitDiag = (Mode&UnitDiag) ? 1 : 0, \
+ IsZeroDiag = (Mode&ZeroDiag) ? 1 : 0, \
+ LowUp = IsLower ? Lower : Upper \
+ }; \
+ static EIGEN_DONT_INLINE void run(Index _rows, Index _cols, const EIGTYPE* _lhs, Index lhsStride, \
+ const EIGTYPE* _rhs, Index rhsIncr, EIGTYPE* _res, Index resIncr, EIGTYPE alpha, level3_blocking<EIGTYPE,EIGTYPE>& blocking) \
+ { \
+ if (ConjLhs || IsZeroDiag) { \
+ triangular_matrix_vector_product<Index,Mode,EIGTYPE,ConjLhs,EIGTYPE,ConjRhs,ColMajor,BuiltIn>::run( \
+ _rows, _cols, _lhs, lhsStride, _rhs, rhsIncr, _res, resIncr, alpha, blocking); \
+ return; \
+ }\
+ Index size = (std::min)(_rows,_cols); \
+ Index rows = IsLower ? _rows : size; \
+ Index cols = IsLower ? size : _cols; \
+\
+ typedef VectorX##EIGPREFIX VectorRhs; \
+ EIGTYPE *x, *y;\
+\
+/* Set x*/ \
+ Map<const VectorRhs, 0, InnerStride<> > rhs(_rhs,cols,InnerStride<>(rhsIncr)); \
+ VectorRhs x_tmp; \
+ if (ConjRhs) x_tmp = rhs.conjugate(); else x_tmp = rhs; \
+ x = x_tmp.data(); \
+\
+/* Square part handling */\
+\
+ char trans, uplo, diag; \
+ MKL_INT m, n, lda, incx, incy; \
+ EIGTYPE const *a; \
+ MKLTYPE alpha_, beta_; \
+ assign_scalar_eig2mkl<MKLTYPE, EIGTYPE>(alpha_, alpha); \
+ assign_scalar_eig2mkl<MKLTYPE, EIGTYPE>(beta_, EIGTYPE(1)); \
+\
+/* Set m, n */ \
+ n = (MKL_INT)size; \
+ lda = lhsStride; \
+ incx = 1; \
+ incy = resIncr; \
+\
+/* Set uplo, trans and diag*/ \
+ trans = 'N'; \
+ uplo = IsLower ? 'L' : 'U'; \
+ diag = IsUnitDiag ? 'U' : 'N'; \
+\
+/* call ?TRMV*/ \
+ MKLPREFIX##trmv(&uplo, &trans, &diag, &n, (const MKLTYPE*)_lhs, &lda, (MKLTYPE*)x, &incx); \
+\
+/* Add op(a_tr)rhs into res*/ \
+ MKLPREFIX##axpy(&n, &alpha_,(const MKLTYPE*)x, &incx, (MKLTYPE*)_res, &incy); \
+/* Non-square case - doesn't fit to MKL ?TRMV. Fall to default triangular product*/ \
+ if (size<(std::max)(rows,cols)) { \
+ typedef Matrix<EIGTYPE, Dynamic, Dynamic> MatrixLhs; \
+ if (ConjRhs) x_tmp = rhs.conjugate(); else x_tmp = rhs; \
+ x = x_tmp.data(); \
+ if (size<rows) { \
+ y = _res + size*resIncr; \
+ a = _lhs + size; \
+ m = rows-size; \
+ n = size; \
+ } \
+ else { \
+ x += size; \
+ y = _res; \
+ a = _lhs + size*lda; \
+ m = size; \
+ n = cols-size; \
+ } \
+ MKLPREFIX##gemv(&trans, &m, &n, &alpha_, (const MKLTYPE*)a, &lda, (const MKLTYPE*)x, &incx, &beta_, (MKLTYPE*)y, &incy); \
+ } \
+ } \
+};
+
+EIGEN_MKL_TRMV_CM(double, double, d, d)
+EIGEN_MKL_TRMV_CM(dcomplex, MKL_Complex16, cd, z)
+EIGEN_MKL_TRMV_CM(float, float, f, s)
+EIGEN_MKL_TRMV_CM(scomplex, MKL_Complex8, cf, c)
+
+// implements row-major: res += alpha * op(triangular) * vector
+#define EIGEN_MKL_TRMV_RM(EIGTYPE, MKLTYPE, EIGPREFIX, MKLPREFIX) \
+template<typename Index, int Mode, bool ConjLhs, bool ConjRhs> \
+struct triangular_matrix_vector_product_trmv<Index,Mode,EIGTYPE,ConjLhs,EIGTYPE,ConjRhs,RowMajor> { \
+ enum { \
+ IsLower = (Mode&Lower) == Lower, \
+ SetDiag = (Mode&(ZeroDiag|UnitDiag)) ? 0 : 1, \
+ IsUnitDiag = (Mode&UnitDiag) ? 1 : 0, \
+ IsZeroDiag = (Mode&ZeroDiag) ? 1 : 0, \
+ LowUp = IsLower ? Lower : Upper \
+ }; \
+ static EIGEN_DONT_INLINE void run(Index _rows, Index _cols, const EIGTYPE* _lhs, Index lhsStride, \
+ const EIGTYPE* _rhs, Index rhsIncr, EIGTYPE* _res, Index resIncr, EIGTYPE alpha, level3_blocking<EIGTYPE,EIGTYPE>& blocking) \
+ { \
+ if (IsZeroDiag) { \
+ triangular_matrix_vector_product<Index,Mode,EIGTYPE,ConjLhs,EIGTYPE,ConjRhs,RowMajor,BuiltIn>::run( \
+ _rows, _cols, _lhs, lhsStride, _rhs, rhsIncr, _res, resIncr, alpha, blocking); \
+ return; \
+ }\
+ Index size = (std::min)(_rows,_cols); \
+ Index rows = IsLower ? _rows : size; \
+ Index cols = IsLower ? size : _cols; \
+\
+ typedef VectorX##EIGPREFIX VectorRhs; \
+ EIGTYPE *x, *y;\
+\
+/* Set x*/ \
+ Map<const VectorRhs, 0, InnerStride<> > rhs(_rhs,cols,InnerStride<>(rhsIncr)); \
+ VectorRhs x_tmp; \
+ if (ConjRhs) x_tmp = rhs.conjugate(); else x_tmp = rhs; \
+ x = x_tmp.data(); \
+\
+/* Square part handling */\
+\
+ char trans, uplo, diag; \
+ MKL_INT m, n, lda, incx, incy; \
+ EIGTYPE const *a; \
+ MKLTYPE alpha_, beta_; \
+ assign_scalar_eig2mkl<MKLTYPE, EIGTYPE>(alpha_, alpha); \
+ assign_scalar_eig2mkl<MKLTYPE, EIGTYPE>(beta_, EIGTYPE(1)); \
+\
+/* Set m, n */ \
+ n = (MKL_INT)size; \
+ lda = lhsStride; \
+ incx = 1; \
+ incy = resIncr; \
+\
+/* Set uplo, trans and diag*/ \
+ trans = ConjLhs ? 'C' : 'T'; \
+ uplo = IsLower ? 'U' : 'L'; \
+ diag = IsUnitDiag ? 'U' : 'N'; \
+\
+/* call ?TRMV*/ \
+ MKLPREFIX##trmv(&uplo, &trans, &diag, &n, (const MKLTYPE*)_lhs, &lda, (MKLTYPE*)x, &incx); \
+\
+/* Add op(a_tr)rhs into res*/ \
+ MKLPREFIX##axpy(&n, &alpha_,(const MKLTYPE*)x, &incx, (MKLTYPE*)_res, &incy); \
+/* Non-square case - doesn't fit to MKL ?TRMV. Fall to default triangular product*/ \
+ if (size<(std::max)(rows,cols)) { \
+ typedef Matrix<EIGTYPE, Dynamic, Dynamic> MatrixLhs; \
+ if (ConjRhs) x_tmp = rhs.conjugate(); else x_tmp = rhs; \
+ x = x_tmp.data(); \
+ if (size<rows) { \
+ y = _res + size*resIncr; \
+ a = _lhs + size*lda; \
+ m = rows-size; \
+ n = size; \
+ } \
+ else { \
+ x += size; \
+ y = _res; \
+ a = _lhs + size; \
+ m = size; \
+ n = cols-size; \
+ } \
+ MKLPREFIX##gemv(&trans, &n, &m, &alpha_, (const MKLTYPE*)a, &lda, (const MKLTYPE*)x, &incx, &beta_, (MKLTYPE*)y, &incy); \
+ } \
+ } \
+};
+
+EIGEN_MKL_TRMV_RM(double, double, d, d)
+EIGEN_MKL_TRMV_RM(dcomplex, MKL_Complex16, cd, z)
+EIGEN_MKL_TRMV_RM(float, float, f, s)
+EIGEN_MKL_TRMV_RM(scomplex, MKL_Complex8, cf, c)
+
+} // end namespase internal
+
+} // end namespace Eigen
+
+#endif // EIGEN_TRIANGULAR_MATRIX_VECTOR_MKL_H