Static Public Member Functions

gemm_mixed_simple< do_trans_A, do_trans_B, use_alpha, use_beta > Class Template Reference
[Gemm_mixed]

Matrix multplication where the matrices have different element types. //! Simple version (no caching). //! Matrix 'C' is assumed to have been set to the correct size (i.e. taking into account transposes). More...

#include <gemm_mixed.hpp>

List of all members.

Static Public Member Functions

template<typename out_eT , typename in_eT1 , typename in_eT2 >
static arma_hot 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))

Detailed Description

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_simple< do_trans_A, do_trans_B, use_alpha, use_beta >

Matrix multplication where the matrices have different element types. //! Simple version (no caching). //! Matrix 'C' is assumed to have been set to the correct size (i.e. taking into account transposes).

Definition at line 213 of file gemm_mixed.hpp.


Member Function Documentation

template<const bool do_trans_A = false, const bool do_trans_B = false, const bool use_alpha = false, const bool use_beta = false>
template<typename out_eT , typename in_eT1 , typename in_eT2 >
static arma_hot void gemm_mixed_simple< do_trans_A, do_trans_B, use_alpha, use_beta >::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) 
) [inline, static]

Definition at line 223 of file gemm_mixed.hpp.

References Mat< eT >::at(), Mat< eT >::colptr(), Mat< eT >::n_cols, and Mat< eT >::n_rows.

    {
    arma_extra_debug_sigprint();
    
    const u32 A_n_rows = A.n_rows;
    const u32 A_n_cols = A.n_cols;
    
    const u32 B_n_rows = B.n_rows;
    const u32 B_n_cols = B.n_cols;
    
    if( (do_trans_A == false) && (do_trans_B == false) )
      {
      for(u32 row_A = 0; row_A < A_n_rows; ++row_A)
        {
        for(u32 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(u32 i = 0; i < B_n_rows; ++i)
            {
            const out_eT val1 = upgrade_val<in_eT1,in_eT2>::apply(A.at(row_A,i));
            const out_eT val2 = upgrade_val<in_eT1,in_eT2>::apply(B_coldata[i]);
            acc += val1 * val2;
            //acc += upgrade_val<in_eT1,in_eT2>::apply(A.at(row_A,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) )
      {
      for(u32 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(u32 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(u32 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) )
      {
      for(u32 row_A = 0; row_A < A_n_rows; ++row_A)
        {
        for(u32 row_B = 0; row_B < B_n_rows; ++row_B)
          {
          out_eT acc = out_eT(0);
          for(u32 i = 0; i < B_n_cols; ++i)
            {
            acc += upgrade_val<in_eT1,in_eT2>::apply(A.at(row_A,i)) * upgrade_val<in_eT1,in_eT2>::apply(B.at(row_B,i));
            }
          
          if( (use_alpha == false) && (use_beta == false) )
            {
            C.at(row_A,row_B) = acc;
            }
          else
          if( (use_alpha == true) && (use_beta == false) )
            {
            C.at(row_A,row_B) = alpha * acc;
            }
          else
          if( (use_alpha == false) && (use_beta == true) )
            {
            C.at(row_A,row_B) = acc + beta*C.at(row_A,row_B);
            }
          else
          if( (use_alpha == true) && (use_beta == true) )
            {
            C.at(row_A,row_B) = alpha*acc + beta*C.at(row_A,row_B);
            }
          }
        }
      }
    else
    if( (do_trans_A == true) && (do_trans_B == true) )
      {
      for(u32 row_B=0; row_B < B_n_rows; ++row_B)
        {
        
        for(u32 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(u32 i=0; i < A_n_rows; ++i)
            {
            acc += upgrade_val<in_eT1,in_eT2>::apply(B.at(row_B,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);
            }
          
          }
        }
      
      }
    }