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+// SPDX-License-Identifier: Apache-2.0
+//
+// Copyright 2008-2016 Conrad Sanderson (http://conradsanderson.id.au)
+// Copyright 2008-2016 National ICT Australia (NICTA)
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+// http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+// ------------------------------------------------------------------------
+
+
+//! \addtogroup gemm_mixed
+//! @{
+
+
+
+//! \brief
+//! Matrix multplication where the matrices have differing element types.
+//! Uses caching for speedup.
+//! Matrix 'C' is assumed to have been set to the correct size (ie. taking into account transposes)
+
+template<const bool do_trans_A=false, const bool do_trans_B=false, const bool use_alpha=false, const bool use_beta=false>
+class gemm_mixed_large
+ {
+ public:
+
+ template<typename out_eT, typename in_eT1, typename in_eT2>
+ arma_hot
+ inline
+ static
+ void
+ apply
+ (
+ Mat<out_eT>& C,
+ const Mat<in_eT1>& A,
+ const Mat<in_eT2>& B,
+ const out_eT alpha = out_eT(1),
+ const out_eT beta = out_eT(0)
+ )
+ {
+ arma_extra_debug_sigprint();
+
+ const uword A_n_rows = A.n_rows;
+ const uword A_n_cols = A.n_cols;
+
+ const uword B_n_rows = B.n_rows;
+ const uword B_n_cols = B.n_cols;
+
+ if( (do_trans_A == false) && (do_trans_B == false) )
+ {
+ podarray<in_eT1> tmp(A_n_cols);
+ in_eT1* A_rowdata = tmp.memptr();
+
+ #if defined(ARMA_USE_OPENMP)
+ const bool use_mp = (B_n_cols >= 2) && (B.n_elem >= 8192) && (mp_thread_limit::in_parallel() == false);
+ #else
+ const bool use_mp = false;
+ #endif
+
+ if(use_mp)
+ {
+ #if defined(ARMA_USE_OPENMP)
+ {
+ const int n_threads = int( (std::min)( uword(mp_thread_limit::get()), uword(B_n_cols) ) );
+
+ for(uword row_A=0; row_A < A_n_rows; ++row_A)
+ {
+ tmp.copy_row(A, row_A);
+
+ #pragma omp parallel for schedule(static) num_threads(n_threads)
+ for(uword col_B=0; col_B < B_n_cols; ++col_B)
+ {
+ const in_eT2* B_coldata = B.colptr(col_B);
+
+ out_eT acc = out_eT(0);
+ for(uword i=0; i < B_n_rows; ++i)
+ {
+ acc += upgrade_val<in_eT1,in_eT2>::apply(A_rowdata[i]) * upgrade_val<in_eT1,in_eT2>::apply(B_coldata[i]);
+ }
+
+ if( (use_alpha == false) && (use_beta == false) ) { C.at(row_A,col_B) = acc; }
+ else if( (use_alpha == true ) && (use_beta == false) ) { C.at(row_A,col_B) = alpha*acc; }
+ else if( (use_alpha == false) && (use_beta == true ) ) { C.at(row_A,col_B) = acc + beta*C.at(row_A,col_B); }
+ else if( (use_alpha == true ) && (use_beta == true ) ) { C.at(row_A,col_B) = alpha*acc + beta*C.at(row_A,col_B); }
+ }
+ }
+ }
+ #endif
+ }
+ else
+ {
+ for(uword row_A=0; row_A < A_n_rows; ++row_A)
+ {
+ tmp.copy_row(A, row_A);
+
+ for(uword col_B=0; col_B < B_n_cols; ++col_B)
+ {
+ const in_eT2* B_coldata = B.colptr(col_B);
+
+ out_eT acc = out_eT(0);
+ for(uword i=0; i < B_n_rows; ++i)
+ {
+ acc += upgrade_val<in_eT1,in_eT2>::apply(A_rowdata[i]) * upgrade_val<in_eT1,in_eT2>::apply(B_coldata[i]);
+ }
+
+ if( (use_alpha == false) && (use_beta == false) ) { C.at(row_A,col_B) = acc; }
+ else if( (use_alpha == true ) && (use_beta == false) ) { C.at(row_A,col_B) = alpha*acc; }
+ else if( (use_alpha == false) && (use_beta == true ) ) { C.at(row_A,col_B) = acc + beta*C.at(row_A,col_B); }
+ else if( (use_alpha == true ) && (use_beta == true ) ) { C.at(row_A,col_B) = alpha*acc + beta*C.at(row_A,col_B); }
+ }
+ }
+ }
+ }
+ else
+ if( (do_trans_A == true) && (do_trans_B == false) )
+ {
+ #if defined(ARMA_USE_OPENMP)
+ const bool use_mp = (B_n_cols >= 2) && (B.n_elem >= 8192) && (mp_thread_limit::in_parallel() == false);
+ #else
+ const bool use_mp = false;
+ #endif
+
+ if(use_mp)
+ {
+ #if defined(ARMA_USE_OPENMP)
+ {
+ const int n_threads = int( (std::min)( uword(mp_thread_limit::get()), uword(B_n_cols) ) );
+
+ for(uword col_A=0; col_A < A_n_cols; ++col_A)
+ {
+ // col_A is interpreted as row_A when storing the results in matrix C
+
+ const in_eT1* A_coldata = A.colptr(col_A);
+
+ #pragma omp parallel for schedule(static) num_threads(n_threads)
+ for(uword col_B=0; col_B < B_n_cols; ++col_B)
+ {
+ const in_eT2* B_coldata = B.colptr(col_B);
+
+ out_eT acc = out_eT(0);
+ for(uword i=0; i < B_n_rows; ++i)
+ {
+ acc += upgrade_val<in_eT1,in_eT2>::apply(A_coldata[i]) * upgrade_val<in_eT1,in_eT2>::apply(B_coldata[i]);
+ }
+
+ if( (use_alpha == false) && (use_beta == false) ) { C.at(col_A,col_B) = acc; }
+ else if( (use_alpha == true ) && (use_beta == false) ) { C.at(col_A,col_B) = alpha*acc; }
+ else if( (use_alpha == false) && (use_beta == true ) ) { C.at(col_A,col_B) = acc + beta*C.at(col_A,col_B); }
+ else if( (use_alpha == true ) && (use_beta == true ) ) { C.at(col_A,col_B) = alpha*acc + beta*C.at(col_A,col_B); }
+ }
+ }
+ }
+ #endif
+ }
+ else
+ {
+ for(uword col_A=0; col_A < A_n_cols; ++col_A)
+ {
+ // col_A is interpreted as row_A when storing the results in matrix C
+
+ const in_eT1* A_coldata = A.colptr(col_A);
+
+ for(uword col_B=0; col_B < B_n_cols; ++col_B)
+ {
+ const in_eT2* B_coldata = B.colptr(col_B);
+
+ out_eT acc = out_eT(0);
+ for(uword i=0; i < B_n_rows; ++i)
+ {
+ acc += upgrade_val<in_eT1,in_eT2>::apply(A_coldata[i]) * upgrade_val<in_eT1,in_eT2>::apply(B_coldata[i]);
+ }
+
+ if( (use_alpha == false) && (use_beta == false) ) { C.at(col_A,col_B) = acc; }
+ else if( (use_alpha == true ) && (use_beta == false) ) { C.at(col_A,col_B) = alpha*acc; }
+ else if( (use_alpha == false) && (use_beta == true ) ) { C.at(col_A,col_B) = acc + beta*C.at(col_A,col_B); }
+ else if( (use_alpha == true ) && (use_beta == true ) ) { C.at(col_A,col_B) = alpha*acc + beta*C.at(col_A,col_B); }
+ }
+ }
+ }
+ }
+ else
+ if( (do_trans_A == false) && (do_trans_B == true) )
+ {
+ Mat<in_eT2> B_tmp;
+
+ op_strans::apply_mat_noalias(B_tmp, B);
+
+ gemm_mixed_large<false, false, use_alpha, use_beta>::apply(C, A, B_tmp, alpha, beta);
+ }
+ else
+ if( (do_trans_A == true) && (do_trans_B == true) )
+ {
+ // mat B_tmp = trans(B);
+ // dgemm_arma<true, false, use_alpha, use_beta>::apply(C, A, B_tmp, alpha, beta);
+
+
+ // By using the trans(A)*trans(B) = trans(B*A) equivalency,
+ // transpose operations are not needed
+
+ podarray<in_eT2> tmp(B_n_cols);
+ in_eT2* B_rowdata = tmp.memptr();
+
+ for(uword row_B=0; row_B < B_n_rows; ++row_B)
+ {
+ tmp.copy_row(B, row_B);
+
+ for(uword col_A=0; col_A < A_n_cols; ++col_A)
+ {
+ const in_eT1* A_coldata = A.colptr(col_A);
+
+ out_eT acc = out_eT(0);
+ for(uword i=0; i < A_n_rows; ++i)
+ {
+ acc += upgrade_val<in_eT1,in_eT2>::apply(B_rowdata[i]) * upgrade_val<in_eT1,in_eT2>::apply(A_coldata[i]);
+ }
+
+ if( (use_alpha == false) && (use_beta == false) ) { C.at(col_A,row_B) = acc; }
+ else if( (use_alpha == true ) && (use_beta == false) ) { C.at(col_A,row_B) = alpha*acc; }
+ else if( (use_alpha == false) && (use_beta == true ) ) { C.at(col_A,row_B) = acc + beta*C.at(col_A,row_B); }
+ else if( (use_alpha == true ) && (use_beta == true ) ) { C.at(col_A,row_B) = alpha*acc + beta*C.at(col_A,row_B); }
+ }
+ }
+
+ }
+ }
+
+ };
+
+
+
+//! \brief
+//! Matrix multplication where the matrices have differing element types.
+
+template<const bool do_trans_A=false, const bool do_trans_B=false, const bool use_alpha=false, const bool use_beta=false>
+class gemm_mixed
+ {
+ public:
+
+ //! immediate multiplication of matrices A and B, storing the result in C
+ template<typename out_eT, typename in_eT1, typename in_eT2>
+ inline
+ static
+ void
+ apply
+ (
+ Mat<out_eT>& C,
+ const Mat<in_eT1>& A,
+ const Mat<in_eT2>& B,
+ const out_eT alpha = out_eT(1),
+ const out_eT beta = out_eT(0)
+ )
+ {
+ arma_extra_debug_sigprint();
+
+ if((is_cx<in_eT1>::yes && do_trans_A) || (is_cx<in_eT2>::yes && do_trans_B))
+ {
+ // better-than-nothing handling of hermitian transpose
+
+ Mat<in_eT1> tmp_A;
+ Mat<in_eT2> tmp_B;
+
+ const bool predo_trans_A = ( (do_trans_A == true) && (is_cx<in_eT1>::yes) );
+ const bool predo_trans_B = ( (do_trans_B == true) && (is_cx<in_eT2>::yes) );
+
+ if(predo_trans_A) { op_htrans::apply_mat_noalias(tmp_A, A); }
+ if(predo_trans_B) { op_htrans::apply_mat_noalias(tmp_B, B); }
+
+ const Mat<in_eT1>& AA = (predo_trans_A == false) ? A : tmp_A;
+ const Mat<in_eT2>& BB = (predo_trans_B == false) ? B : tmp_B;
+
+ gemm_mixed_large<((predo_trans_A) ? false : do_trans_A), ((predo_trans_B) ? false : do_trans_B), use_alpha, use_beta>::apply(C, AA, BB, alpha, beta);
+ }
+ else
+ {
+ gemm_mixed_large<do_trans_A, do_trans_B, use_alpha, use_beta>::apply(C, A, B, alpha, beta);
+ }
+ }
+
+
+ };
+
+
+
+//! @}
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