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matrix_operations_row.hpp
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#ifndef VIENNACL_LINALG_CUDA_MATRIX_OPERATIONS_ROW_HPP_
#define VIENNACL_LINALG_CUDA_MATRIX_OPERATIONS_ROW_HPP_
/* =========================================================================
Copyright (c) 2010-2016, Institute for Microelectronics,
Institute for Analysis and Scientific Computing,
TU Wien.
Portions of this software are copyright by UChicago Argonne, LLC.
-----------------
ViennaCL - The Vienna Computing Library
-----------------
Project Head: Karl Rupp rupp@iue.tuwien.ac.at
(A list of authors and contributors can be found in the manual)
License: MIT (X11), see file LICENSE in the base directory
============================================================================= */
namespace viennacl
{
namespace linalg
{
namespace cuda
{
template<typename DestNumericT, typename SrcNumericT>
__global__ void convert_row_kernel(
DestNumericT * A,
unsigned int A_start1, unsigned int A_start2,
unsigned int A_inc1, unsigned int A_inc2,
unsigned int A_size1, unsigned int A_size2,
unsigned int A_internal_size1, unsigned int A_internal_size2,
const SrcNumericT * B,
unsigned int B_start1, unsigned int B_start2,
unsigned int B_inc1, unsigned int B_inc2,
unsigned int B_internal_size1, unsigned int B_internal_size2)
{
unsigned int row_gid = (blockIdx.x * blockDim.x + threadIdx.x) / blockDim.x;
unsigned int col_gid = (blockIdx.x * blockDim.x + threadIdx.x) % blockDim.x;
for (unsigned int row = row_gid; row < A_size1; row += gridDim.x)
for (unsigned int col = col_gid; col < A_size2; col += blockDim.x)
A[(row * A_inc1 + A_start1) * A_internal_size2 + col * A_inc2 + A_start2] = B[(row * B_inc1 + B_start1) * B_internal_size2 + col * B_inc2 + B_start2];
}
//Matrix transpose kernel
template<typename NumericT>
__global__ void trans_kernel(
const NumericT * A,
unsigned int A_start1, unsigned int A_start2,
unsigned int A_internal_size1, unsigned int A_internal_size2,
unsigned int A_size1, unsigned int A_size2,
unsigned int A_stride1, unsigned int A_stride2,
NumericT * B,
unsigned int B_start1, unsigned int B_start2,
unsigned int B_internal_size1, unsigned int B_internal_size2,
unsigned int B_stride1, unsigned int B_stride2,
bool data_major)
{
for(unsigned int row = blockIdx.x; row<A_size1; row+=gridDim.x)
{
for(unsigned int col = threadIdx.x; col<A_size2; col+=blockDim.x)
{
if(data_major)
B[(B_start1 + B_stride1 * col) * B_internal_size2 + (B_start2 + B_stride2 * row)] = A[(A_start1 + A_stride1 * row) * A_internal_size2 + (A_start2 + A_stride2 * col)];
else
B[(B_start1 + B_stride1 * col) + (B_start2 + B_stride2 * row) * B_internal_size1] = A[(A_start1 + A_stride1 * row) + (A_start2 + A_stride2 * col) * A_internal_size1];
}
}
}
//
// am
//
// alpha on CPU
template<typename NumericT>
__global__ void am_row_kernel(
NumericT * A,
unsigned int A_start1, unsigned int A_start2,
unsigned int A_inc1, unsigned int A_inc2,
unsigned int A_size1, unsigned int A_size2,
unsigned int A_internal_size1, unsigned int A_internal_size2,
NumericT fac2,
unsigned int options2,
const NumericT * B,
unsigned int B_start1, unsigned int B_start2,
unsigned int B_inc1, unsigned int B_inc2,
unsigned int B_internal_size1, unsigned int B_internal_size2)
{
NumericT alpha = fac2;
if (options2 & (1 << 0))
alpha = -alpha;
unsigned int row_gid = (blockIdx.x * blockDim.x + threadIdx.x) / blockDim.x;
unsigned int col_gid = (blockIdx.x * blockDim.x + threadIdx.x) % blockDim.x;
if (options2 & (1 << 1))
{
for (unsigned int row = row_gid; row < A_size1; row += gridDim.x)
for (unsigned int col = col_gid; col < A_size2; col += blockDim.x)
A[(row * A_inc1 + A_start1) * A_internal_size2 + col * A_inc2 + A_start2] = B[(row * B_inc1 + B_start1) * B_internal_size2 + col * B_inc2 + B_start2] / alpha;
}
else
{
for (unsigned int row = row_gid; row < A_size1; row += gridDim.x)
for (unsigned int col = col_gid; col < A_size2; col += blockDim.x)
A[(row * A_inc1 + A_start1) * A_internal_size2 + col * A_inc2 + A_start2] = B[(row * B_inc1 + B_start1) * B_internal_size2 + col * B_inc2 + B_start2] * alpha;
}
}
// alpha on GPU
template<typename NumericT>
__global__ void am_row_kernel(
NumericT * A,
unsigned int A_start1, unsigned int A_start2,
unsigned int A_inc1, unsigned int A_inc2,
unsigned int A_size1, unsigned int A_size2,
unsigned int A_internal_size1, unsigned int A_internal_size2,
const NumericT * fac2,
unsigned int options2,
const NumericT * B,
unsigned int B_start1, unsigned int B_start2,
unsigned int B_inc1, unsigned int B_inc2,
unsigned int B_internal_size1, unsigned int B_internal_size2)
{
NumericT alpha = *fac2;
if (options2 & (1 << 0))
alpha = -alpha;
unsigned int row_gid = (blockIdx.x * blockDim.x + threadIdx.x) / blockDim.x;
unsigned int col_gid = (blockIdx.x * blockDim.x + threadIdx.x) % blockDim.x;
if (options2 & (1 << 1))
{
for (unsigned int row = row_gid; row < A_size1; row += gridDim.x)
for (unsigned int col = col_gid; col < A_size2; col += blockDim.x)
A[(row * A_inc1 + A_start1) * A_internal_size2 + col * A_inc2 + A_start2] = B[(row * B_inc1 + B_start1) * B_internal_size2 + col * B_inc2 + B_start2] / alpha;
}
else
{
for (unsigned int row = row_gid; row < A_size1; row += gridDim.x)
for (unsigned int col = col_gid; col < A_size2; col += blockDim.x)
A[(row * A_inc1 + A_start1) * A_internal_size2 + col * A_inc2 + A_start2] = B[(row * B_inc1 + B_start1) * B_internal_size2 + col * B_inc2 + B_start2] * alpha;
}
}
//
// ambm
//
// alpha and beta on CPU
template<typename NumericT>
__global__ void ambm_row_kernel(
NumericT * A,
unsigned int A_start1, unsigned int A_start2,
unsigned int A_inc1, unsigned int A_inc2,
unsigned int A_size1, unsigned int A_size2,
unsigned int A_internal_size1, unsigned int A_internal_size2,
NumericT fac2,
unsigned int options2,
const NumericT * B,
unsigned int B_start1, unsigned int B_start2,
unsigned int B_inc1, unsigned int B_inc2,
unsigned int B_internal_size1, unsigned int B_internal_size2,
NumericT fac3,
unsigned int options3,
const NumericT * C,
unsigned int C_start1, unsigned int C_start2,
unsigned int C_inc1, unsigned int C_inc2,
unsigned int C_internal_size1, unsigned int C_internal_size2)
{
NumericT alpha = fac2;
if (options2 & (1 << 0))
alpha = -alpha;
NumericT beta = fac3;
if (options3 & (1 << 0))
beta = -beta;
unsigned int row_gid = (blockIdx.x * blockDim.x + threadIdx.x) / blockDim.x;
unsigned int col_gid = (blockIdx.x * blockDim.x + threadIdx.x) % blockDim.x;
if (options2 & (1 << 1))
{
if (options3 & (1 << 1))
{
for (unsigned int row = row_gid; row < A_size1; row += gridDim.x)
for (unsigned int col = col_gid; col < A_size2; col += blockDim.x)
A[(row * A_inc1 + A_start1) * A_internal_size2 + col * A_inc2 + A_start2]
= B[(row * B_inc1 + B_start1) * B_internal_size2 + col * B_inc2 + B_start2] / alpha
+ C[(row * C_inc1 + C_start1) * C_internal_size2 + col * C_inc2 + C_start2] / beta;
}
else
{
for (unsigned int row = row_gid; row < A_size1; row += gridDim.x)
for (unsigned int col = col_gid; col < A_size2; col += blockDim.x)
A[(row * A_inc1 + A_start1) * A_internal_size2 + col * A_inc2 + A_start2]
= B[(row * B_inc1 + B_start1) * B_internal_size2 + col * B_inc2 + B_start2] / alpha
+ C[(row * C_inc1 + C_start1) * C_internal_size2 + col * C_inc2 + C_start2] * beta;
}
}
else
{
if (options3 & (1 << 1))
{
for (unsigned int row = row_gid; row < A_size1; row += gridDim.x)
for (unsigned int col = col_gid; col < A_size2; col += blockDim.x)
A[(row * A_inc1 + A_start1) * A_internal_size2 + col * A_inc2 + A_start2]
= B[(row * B_inc1 + B_start1) * B_internal_size2 + col * B_inc2 + B_start2] * alpha
+ C[(row * C_inc1 + C_start1) * C_internal_size2 + col * C_inc2 + C_start2] / beta;
}
else
{
for (unsigned int row = row_gid; row < A_size1; row += gridDim.x)
for (unsigned int col = col_gid; col < A_size2; col += blockDim.x)
A[(row * A_inc1 + A_start1) * A_internal_size2 + col * A_inc2 + A_start2]
= B[(row * B_inc1 + B_start1) * B_internal_size2 + col * B_inc2 + B_start2] * alpha
+ C[(row * C_inc1 + C_start1) * C_internal_size2 + col * C_inc2 + C_start2] * beta;
}
}
}
// alpha on CPU, beta on GPU
template<typename NumericT>
__global__ void ambm_row_kernel(
NumericT * A,
unsigned int A_start1, unsigned int A_start2,
unsigned int A_inc1, unsigned int A_inc2,
unsigned int A_size1, unsigned int A_size2,
unsigned int A_internal_size1, unsigned int A_internal_size2,
NumericT fac2,
unsigned int options2,
const NumericT * B,
unsigned int B_start1, unsigned int B_start2,
unsigned int B_inc1, unsigned int B_inc2,
unsigned int B_internal_size1, unsigned int B_internal_size2,
const NumericT * fac3,
unsigned int options3,
const NumericT * C,
unsigned int C_start1, unsigned int C_start2,
unsigned int C_inc1, unsigned int C_inc2,
unsigned int C_internal_size1, unsigned int C_internal_size2)
{
NumericT alpha = fac2;
if (options2 & (1 << 0))
alpha = -alpha;
NumericT beta = *fac3;
if (options3 & (1 << 0))
beta = -beta;
unsigned int row_gid = (blockIdx.x * blockDim.x + threadIdx.x) / blockDim.x;
unsigned int col_gid = (blockIdx.x * blockDim.x + threadIdx.x) % blockDim.x;
if (options2 & (1 << 1))
{
if (options3 & (1 << 1))
{
for (unsigned int row = row_gid; row < A_size1; row += gridDim.x)
for (unsigned int col = col_gid; col < A_size2; col += blockDim.x)
A[(row * A_inc1 + A_start1) * A_internal_size2 + col * A_inc2 + A_start2]
= B[(row * B_inc1 + B_start1) * B_internal_size2 + col * B_inc2 + B_start2] / alpha
+ C[(row * C_inc1 + C_start1) * C_internal_size2 + col * C_inc2 + C_start2] / beta;
}
else
{
for (unsigned int row = row_gid; row < A_size1; row += gridDim.x)
for (unsigned int col = col_gid; col < A_size2; col += blockDim.x)
A[(row * A_inc1 + A_start1) * A_internal_size2 + col * A_inc2 + A_start2]
= B[(row * B_inc1 + B_start1) * B_internal_size2 + col * B_inc2 + B_start2] / alpha
+ C[(row * C_inc1 + C_start1) * C_internal_size2 + col * C_inc2 + C_start2] * beta;
}
}
else
{
if (options3 & (1 << 1))
{
for (unsigned int row = row_gid; row < A_size1; row += gridDim.x)
for (unsigned int col = col_gid; col < A_size2; col += blockDim.x)
A[(row * A_inc1 + A_start1) * A_internal_size2 + col * A_inc2 + A_start2]
= B[(row * B_inc1 + B_start1) * B_internal_size2 + col * B_inc2 + B_start2] * alpha
+ C[(row * C_inc1 + C_start1) * C_internal_size2 + col * C_inc2 + C_start2] / beta;
}
else
{
for (unsigned int row = row_gid; row < A_size1; row += gridDim.x)
for (unsigned int col = col_gid; col < A_size2; col += blockDim.x)
A[(row * A_inc1 + A_start1) * A_internal_size2 + col * A_inc2 + A_start2]
= B[(row * B_inc1 + B_start1) * B_internal_size2 + col * B_inc2 + B_start2] * alpha
+ C[(row * C_inc1 + C_start1) * C_internal_size2 + col * C_inc2 + C_start2] * beta;
}
}
}
// alpha on GPU, beta on CPU
template<typename NumericT>
__global__ void ambm_row_kernel(
NumericT * A,
unsigned int A_start1, unsigned int A_start2,
unsigned int A_inc1, unsigned int A_inc2,
unsigned int A_size1, unsigned int A_size2,
unsigned int A_internal_size1, unsigned int A_internal_size2,
const NumericT * fac2,
unsigned int options2,
const NumericT * B,
unsigned int B_start1, unsigned int B_start2,
unsigned int B_inc1, unsigned int B_inc2,
unsigned int B_internal_size1, unsigned int B_internal_size2,
NumericT fac3,
unsigned int options3,
const NumericT * C,
unsigned int C_start1, unsigned int C_start2,
unsigned int C_inc1, unsigned int C_inc2,
unsigned int C_internal_size1, unsigned int C_internal_size2)
{
NumericT alpha = *fac2;
if (options2 & (1 << 0))
alpha = -alpha;
NumericT beta = fac3;
if (options3 & (1 << 0))
beta = -beta;
unsigned int row_gid = (blockIdx.x * blockDim.x + threadIdx.x) / blockDim.x;
unsigned int col_gid = (blockIdx.x * blockDim.x + threadIdx.x) % blockDim.x;
if (options2 & (1 << 1))
{
if (options3 & (1 << 1))
{
for (unsigned int row = row_gid; row < A_size1; row += gridDim.x)
for (unsigned int col = col_gid; col < A_size2; col += blockDim.x)
A[(row * A_inc1 + A_start1) * A_internal_size2 + col * A_inc2 + A_start2]
= B[(row * B_inc1 + B_start1) * B_internal_size2 + col * B_inc2 + B_start2] / alpha
+ C[(row * C_inc1 + C_start1) * C_internal_size2 + col * C_inc2 + C_start2] / beta;
}
else
{
for (unsigned int row = row_gid; row < A_size1; row += gridDim.x)
for (unsigned int col = col_gid; col < A_size2; col += blockDim.x)
A[(row * A_inc1 + A_start1) * A_internal_size2 + col * A_inc2 + A_start2]
= B[(row * B_inc1 + B_start1) * B_internal_size2 + col * B_inc2 + B_start2] / alpha
+ C[(row * C_inc1 + C_start1) * C_internal_size2 + col * C_inc2 + C_start2] * beta;
}
}
else
{
if (options3 & (1 << 1))
{
for (unsigned int row = row_gid; row < A_size1; row += gridDim.x)
for (unsigned int col = col_gid; col < A_size2; col += blockDim.x)
A[(row * A_inc1 + A_start1) * A_internal_size2 + col * A_inc2 + A_start2]
= B[(row * B_inc1 + B_start1) * B_internal_size2 + col * B_inc2 + B_start2] * alpha
+ C[(row * C_inc1 + C_start1) * C_internal_size2 + col * C_inc2 + C_start2] / beta;
}
else
{
for (unsigned int row = row_gid; row < A_size1; row += gridDim.x)
for (unsigned int col = col_gid; col < A_size2; col += blockDim.x)
A[(row * A_inc1 + A_start1) * A_internal_size2 + col * A_inc2 + A_start2]
= B[(row * B_inc1 + B_start1) * B_internal_size2 + col * B_inc2 + B_start2] * alpha
+ C[(row * C_inc1 + C_start1) * C_internal_size2 + col * C_inc2 + C_start2] * beta;
}
}
}
// alpha and beta on GPU
template<typename NumericT>
__global__ void ambm_row_kernel(
NumericT * A,
unsigned int A_start1, unsigned int A_start2,
unsigned int A_inc1, unsigned int A_inc2,
unsigned int A_size1, unsigned int A_size2,
unsigned int A_internal_size1, unsigned int A_internal_size2,
const NumericT * fac2,
unsigned int options2,
const NumericT * B,
unsigned int B_start1, unsigned int B_start2,
unsigned int B_inc1, unsigned int B_inc2,
unsigned int B_internal_size1, unsigned int B_internal_size2,
const NumericT * fac3,
unsigned int options3,
const NumericT * C,
unsigned int C_start1, unsigned int C_start2,
unsigned int C_inc1, unsigned int C_inc2,
unsigned int C_internal_size1, unsigned int C_internal_size2)
{
NumericT alpha = *fac2;
if (options2 & (1 << 0))
alpha = -alpha;
NumericT beta = *fac3;
if (options3 & (1 << 0))
beta = -beta;
unsigned int row_gid = (blockIdx.x * blockDim.x + threadIdx.x) / blockDim.x;
unsigned int col_gid = (blockIdx.x * blockDim.x + threadIdx.x) % blockDim.x;
if (options2 & (1 << 1))
{
if (options3 & (1 << 1))
{
for (unsigned int row = row_gid; row < A_size1; row += gridDim.x)
for (unsigned int col = col_gid; col < A_size2; col += blockDim.x)
A[(row * A_inc1 + A_start1) * A_internal_size2 + col * A_inc2 + A_start2]
= B[(row * B_inc1 + B_start1) * B_internal_size2 + col * B_inc2 + B_start2] / alpha
+ C[(row * C_inc1 + C_start1) * C_internal_size2 + col * C_inc2 + C_start2] / beta;
}
else
{
for (unsigned int row = row_gid; row < A_size1; row += gridDim.x)
for (unsigned int col = col_gid; col < A_size2; col += blockDim.x)
A[(row * A_inc1 + A_start1) * A_internal_size2 + col * A_inc2 + A_start2]
= B[(row * B_inc1 + B_start1) * B_internal_size2 + col * B_inc2 + B_start2] / alpha
+ C[(row * C_inc1 + C_start1) * C_internal_size2 + col * C_inc2 + C_start2] * beta;
}
}
else
{
if (options3 & (1 << 1))
{
for (unsigned int row = row_gid; row < A_size1; row += gridDim.x)
for (unsigned int col = col_gid; col < A_size2; col += blockDim.x)
A[(row * A_inc1 + A_start1) * A_internal_size2 + col * A_inc2 + A_start2]
= B[(row * B_inc1 + B_start1) * B_internal_size2 + col * B_inc2 + B_start2] * alpha
+ C[(row * C_inc1 + C_start1) * C_internal_size2 + col * C_inc2 + C_start2] / beta;
}
else
{
for (unsigned int row = row_gid; row < A_size1; row += gridDim.x)
for (unsigned int col = col_gid; col < A_size2; col += blockDim.x)
A[(row * A_inc1 + A_start1) * A_internal_size2 + col * A_inc2 + A_start2]
= B[(row * B_inc1 + B_start1) * B_internal_size2 + col * B_inc2 + B_start2] * alpha
+ C[(row * C_inc1 + C_start1) * C_internal_size2 + col * C_inc2 + C_start2] * beta;
}
}
}
//
// ambm_m
//
// alpha and beta on CPU
template<typename NumericT>
__global__ void ambm_m_row_kernel(
NumericT * A,
unsigned int A_start1, unsigned int A_start2,
unsigned int A_inc1, unsigned int A_inc2,
unsigned int A_size1, unsigned int A_size2,
unsigned int A_internal_size1, unsigned int A_internal_size2,
NumericT fac2,
unsigned int options2,
const NumericT * B,
unsigned int B_start1, unsigned int B_start2,
unsigned int B_inc1, unsigned int B_inc2,
unsigned int B_internal_size1, unsigned int B_internal_size2,
NumericT fac3,
unsigned int options3,
const NumericT * C,
unsigned int C_start1, unsigned int C_start2,
unsigned int C_inc1, unsigned int C_inc2,
unsigned int C_internal_size1, unsigned int C_internal_size2)
{
NumericT alpha = fac2;
if (options2 & (1 << 0))
alpha = -alpha;
NumericT beta = fac3;
if (options3 & (1 << 0))
beta = -beta;
unsigned int row_gid = (blockIdx.x * blockDim.x + threadIdx.x) / blockDim.x;
unsigned int col_gid = (blockIdx.x * blockDim.x + threadIdx.x) % blockDim.x;
if (options2 & (1 << 1))
{
if (options3 & (1 << 1))
{
for (unsigned int row = row_gid; row < A_size1; row += gridDim.x)
for (unsigned int col = col_gid; col < A_size2; col += blockDim.x)
A[(row * A_inc1 + A_start1) * A_internal_size2 + col * A_inc2 + A_start2]
+= B[(row * B_inc1 + B_start1) * B_internal_size2 + col * B_inc2 + B_start2] / alpha
+ C[(row * C_inc1 + C_start1) * C_internal_size2 + col * C_inc2 + C_start2] / beta;
}
else
{
for (unsigned int row = row_gid; row < A_size1; row += gridDim.x)
for (unsigned int col = col_gid; col < A_size2; col += blockDim.x)
A[(row * A_inc1 + A_start1) * A_internal_size2 + col * A_inc2 + A_start2]
+= B[(row * B_inc1 + B_start1) * B_internal_size2 + col * B_inc2 + B_start2] / alpha
+ C[(row * C_inc1 + C_start1) * C_internal_size2 + col * C_inc2 + C_start2] * beta;
}
}
else
{
if (options3 & (1 << 1))
{
for (unsigned int row = row_gid; row < A_size1; row += gridDim.x)
for (unsigned int col = col_gid; col < A_size2; col += blockDim.x)
A[(row * A_inc1 + A_start1) * A_internal_size2 + col * A_inc2 + A_start2]
+= B[(row * B_inc1 + B_start1) * B_internal_size2 + col * B_inc2 + B_start2] * alpha
+ C[(row * C_inc1 + C_start1) * C_internal_size2 + col * C_inc2 + C_start2] / beta;
}
else
{
for (unsigned int row = row_gid; row < A_size1; row += gridDim.x)
for (unsigned int col = col_gid; col < A_size2; col += blockDim.x)
A[(row * A_inc1 + A_start1) * A_internal_size2 + col * A_inc2 + A_start2]
+= B[(row * B_inc1 + B_start1) * B_internal_size2 + col * B_inc2 + B_start2] * alpha
+ C[(row * C_inc1 + C_start1) * C_internal_size2 + col * C_inc2 + C_start2] * beta;
}
}
}
// alpha on CPU, beta on GPU
template<typename NumericT>
__global__ void ambm_m_row_kernel(
NumericT * A,
unsigned int A_start1, unsigned int A_start2,
unsigned int A_inc1, unsigned int A_inc2,
unsigned int A_size1, unsigned int A_size2,
unsigned int A_internal_size1, unsigned int A_internal_size2,
NumericT fac2,
unsigned int options2,
const NumericT * B,
unsigned int B_start1, unsigned int B_start2,
unsigned int B_inc1, unsigned int B_inc2,
unsigned int B_internal_size1, unsigned int B_internal_size2,
const NumericT * fac3,
unsigned int options3,
const NumericT * C,
unsigned int C_start1, unsigned int C_start2,
unsigned int C_inc1, unsigned int C_inc2,
unsigned int C_internal_size1, unsigned int C_internal_size2)
{
NumericT alpha = fac2;
if (options2 & (1 << 0))
alpha = -alpha;
NumericT beta = *fac3;
if (options3 & (1 << 0))
beta = -beta;
unsigned int row_gid = (blockIdx.x * blockDim.x + threadIdx.x) / blockDim.x;
unsigned int col_gid = (blockIdx.x * blockDim.x + threadIdx.x) % blockDim.x;
if (options2 & (1 << 1))
{
if (options3 & (1 << 1))
{
for (unsigned int row = row_gid; row < A_size1; row += gridDim.x)
for (unsigned int col = col_gid; col < A_size2; col += blockDim.x)
A[(row * A_inc1 + A_start1) * A_internal_size2 + col * A_inc2 + A_start2]
+= B[(row * B_inc1 + B_start1) * B_internal_size2 + col * B_inc2 + B_start2] / alpha
+ C[(row * C_inc1 + C_start1) * C_internal_size2 + col * C_inc2 + C_start2] / beta;
}
else
{
for (unsigned int row = row_gid; row < A_size1; row += gridDim.x)
for (unsigned int col = col_gid; col < A_size2; col += blockDim.x)
A[(row * A_inc1 + A_start1) * A_internal_size2 + col * A_inc2 + A_start2]
+= B[(row * B_inc1 + B_start1) * B_internal_size2 + col * B_inc2 + B_start2] / alpha
+ C[(row * C_inc1 + C_start1) * C_internal_size2 + col * C_inc2 + C_start2] * beta;
}
}
else
{
if (options3 & (1 << 1))
{
for (unsigned int row = row_gid; row < A_size1; row += gridDim.x)
for (unsigned int col = col_gid; col < A_size2; col += blockDim.x)
A[(row * A_inc1 + A_start1) * A_internal_size2 + col * A_inc2 + A_start2]
+= B[(row * B_inc1 + B_start1) * B_internal_size2 + col * B_inc2 + B_start2] * alpha
+ C[(row * C_inc1 + C_start1) * C_internal_size2 + col * C_inc2 + C_start2] / beta;
}
else
{
for (unsigned int row = row_gid; row < A_size1; row += gridDim.x)
for (unsigned int col = col_gid; col < A_size2; col += blockDim.x)
A[(row * A_inc1 + A_start1) * A_internal_size2 + col * A_inc2 + A_start2]
+= B[(row * B_inc1 + B_start1) * B_internal_size2 + col * B_inc2 + B_start2] * alpha
+ C[(row * C_inc1 + C_start1) * C_internal_size2 + col * C_inc2 + C_start2] * beta;
}
}
}
// alpha on GPU, beta on CPU
template<typename NumericT>
__global__ void ambm_m_row_kernel(
NumericT * A,
unsigned int A_start1, unsigned int A_start2,
unsigned int A_inc1, unsigned int A_inc2,
unsigned int A_size1, unsigned int A_size2,
unsigned int A_internal_size1, unsigned int A_internal_size2,
const NumericT * fac2,
unsigned int options2,
const NumericT * B,
unsigned int B_start1, unsigned int B_start2,
unsigned int B_inc1, unsigned int B_inc2,
unsigned int B_internal_size1, unsigned int B_internal_size2,
NumericT fac3,
unsigned int options3,
const NumericT * C,
unsigned int C_start1, unsigned int C_start2,
unsigned int C_inc1, unsigned int C_inc2,
unsigned int C_internal_size1, unsigned int C_internal_size2)
{
NumericT alpha = *fac2;
if (options2 & (1 << 0))
alpha = -alpha;
NumericT beta = fac3;
if (options3 & (1 << 0))
beta = -beta;
unsigned int row_gid = (blockIdx.x * blockDim.x + threadIdx.x) / blockDim.x;
unsigned int col_gid = (blockIdx.x * blockDim.x + threadIdx.x) % blockDim.x;
if (options2 & (1 << 1))
{
if (options3 & (1 << 1))
{
for (unsigned int row = row_gid; row < A_size1; row += gridDim.x)
for (unsigned int col = col_gid; col < A_size2; col += blockDim.x)
A[(row * A_inc1 + A_start1) * A_internal_size2 + col * A_inc2 + A_start2]
+= B[(row * B_inc1 + B_start1) * B_internal_size2 + col * B_inc2 + B_start2] / alpha
+ C[(row * C_inc1 + C_start1) * C_internal_size2 + col * C_inc2 + C_start2] / beta;
}
else
{
for (unsigned int row = row_gid; row < A_size1; row += gridDim.x)
for (unsigned int col = col_gid; col < A_size2; col += blockDim.x)
A[(row * A_inc1 + A_start1) * A_internal_size2 + col * A_inc2 + A_start2]
+= B[(row * B_inc1 + B_start1) * B_internal_size2 + col * B_inc2 + B_start2] / alpha
+ C[(row * C_inc1 + C_start1) * C_internal_size2 + col * C_inc2 + C_start2] * beta;
}
}
else
{
if (options3 & (1 << 1))
{
for (unsigned int row = row_gid; row < A_size1; row += gridDim.x)
for (unsigned int col = col_gid; col < A_size2; col += blockDim.x)
A[(row * A_inc1 + A_start1) * A_internal_size2 + col * A_inc2 + A_start2]
+= B[(row * B_inc1 + B_start1) * B_internal_size2 + col * B_inc2 + B_start2] * alpha
+ C[(row * C_inc1 + C_start1) * C_internal_size2 + col * C_inc2 + C_start2] / beta;
}
else
{
for (unsigned int row = row_gid; row < A_size1; row += gridDim.x)
for (unsigned int col = col_gid; col < A_size2; col += blockDim.x)
A[(row * A_inc1 + A_start1) * A_internal_size2 + col * A_inc2 + A_start2]
+= B[(row * B_inc1 + B_start1) * B_internal_size2 + col * B_inc2 + B_start2] * alpha
+ C[(row * C_inc1 + C_start1) * C_internal_size2 + col * C_inc2 + C_start2] * beta;
}
}
}
// alpha and beta on GPU
template<typename NumericT>
__global__ void ambm_m_row_kernel(
NumericT * A,
unsigned int A_start1, unsigned int A_start2,
unsigned int A_inc1, unsigned int A_inc2,
unsigned int A_size1, unsigned int A_size2,
unsigned int A_internal_size1, unsigned int A_internal_size2,
const NumericT * fac2,
unsigned int options2,
const NumericT * B,
unsigned int B_start1, unsigned int B_start2,
unsigned int B_inc1, unsigned int B_inc2,
unsigned int B_internal_size1, unsigned int B_internal_size2,
const NumericT * fac3,
unsigned int options3,
const NumericT * C,
unsigned int C_start1, unsigned int C_start2,
unsigned int C_inc1, unsigned int C_inc2,
unsigned int C_internal_size1, unsigned int C_internal_size2)
{
NumericT alpha = *fac2;
if (options2 & (1 << 0))
alpha = -alpha;
NumericT beta = *fac3;
if (options3 & (1 << 0))
beta = -beta;
unsigned int row_gid = (blockIdx.x * blockDim.x + threadIdx.x) / blockDim.x;
unsigned int col_gid = (blockIdx.x * blockDim.x + threadIdx.x) % blockDim.x;
if (options2 & (1 << 1))
{
if (options3 & (1 << 1))
{
for (unsigned int row = row_gid; row < A_size1; row += gridDim.x)
for (unsigned int col = col_gid; col < A_size2; col += blockDim.x)
A[(row * A_inc1 + A_start1) * A_internal_size2 + col * A_inc2 + A_start2]
+= B[(row * B_inc1 + B_start1) * B_internal_size2 + col * B_inc2 + B_start2] / alpha
+ C[(row * C_inc1 + C_start1) * C_internal_size2 + col * C_inc2 + C_start2] / beta;
}
else
{
for (unsigned int row = row_gid; row < A_size1; row += gridDim.x)
for (unsigned int col = col_gid; col < A_size2; col += blockDim.x)
A[(row * A_inc1 + A_start1) * A_internal_size2 + col * A_inc2 + A_start2]
+= B[(row * B_inc1 + B_start1) * B_internal_size2 + col * B_inc2 + B_start2] / alpha
+ C[(row * C_inc1 + C_start1) * C_internal_size2 + col * C_inc2 + C_start2] * beta;
}
}
else
{
if (options3 & (1 << 1))
{
for (unsigned int row = row_gid; row < A_size1; row += gridDim.x)
for (unsigned int col = col_gid; col < A_size2; col += blockDim.x)
A[(row * A_inc1 + A_start1) * A_internal_size2 + col * A_inc2 + A_start2]
+= B[(row * B_inc1 + B_start1) * B_internal_size2 + col * B_inc2 + B_start2] * alpha
+ C[(row * C_inc1 + C_start1) * C_internal_size2 + col * C_inc2 + C_start2] / beta;
}
else
{
for (unsigned int row = row_gid; row < A_size1; row += gridDim.x)
for (unsigned int col = col_gid; col < A_size2; col += blockDim.x)
A[(row * A_inc1 + A_start1) * A_internal_size2 + col * A_inc2 + A_start2]
+= B[(row * B_inc1 + B_start1) * B_internal_size2 + col * B_inc2 + B_start2] * alpha
+ C[(row * C_inc1 + C_start1) * C_internal_size2 + col * C_inc2 + C_start2] * beta;
}
}
}
//
// assignments
//
template<typename NumericT>
__global__ void matrix_row_assign_kernel(
NumericT * A,
unsigned int A_start1, unsigned int A_start2,
unsigned int A_inc1, unsigned int A_inc2,
unsigned int A_size1, unsigned int A_size2,
unsigned int A_internal_size1, unsigned int A_internal_size2,
NumericT alpha)
{
unsigned int row_gid = (blockIdx.x * blockDim.x + threadIdx.x) / blockDim.x;
unsigned int col_gid = (blockIdx.x * blockDim.x + threadIdx.x) % blockDim.x;
for (unsigned int row = row_gid; row < A_size1; row += gridDim.x)
for (unsigned int col = col_gid; col < A_size2; col += blockDim.x)
A[(row * A_inc1 + A_start1) * A_internal_size2 + col * A_inc2 + A_start2] = alpha;
}
template<typename NumericT>
__global__ void matrix_row_diagonal_assign_kernel(
NumericT * A,
unsigned int A_start1, unsigned int A_start2,
unsigned int A_inc1, unsigned int A_inc2,
unsigned int A_size1, unsigned int A_size2,
unsigned int A_internal_size1, unsigned int A_internal_size2,
NumericT alpha)
{
unsigned int gid = (blockIdx.x * blockDim.x + threadIdx.x);
for (unsigned int row = gid; row < A_size1; row += blockDim.x * gridDim.x)
A[(row * A_inc1 + A_start1) * A_internal_size2 + row * A_inc2 + A_start2] = alpha;
}
//
// binary element-wise operations
//
template<typename NumericT>
__global__ void element_op_row_kernel(
NumericT * A,
unsigned int A_start1, unsigned int A_start2,
unsigned int A_inc1, unsigned int A_inc2,
unsigned int A_size1, unsigned int A_size2,
unsigned int A_internal_size1, unsigned int A_internal_size2,
const NumericT * B,
unsigned int B_start1, unsigned int B_start2,
unsigned int B_inc1, unsigned int B_inc2,
unsigned int B_internal_size1, unsigned int B_internal_size2,
const NumericT * C,
unsigned int C_start1, unsigned int C_start2,
unsigned int C_inc1, unsigned int C_inc2,
unsigned int C_internal_size1, unsigned int C_internal_size2,
unsigned int op_type) //0: product, 1: division, 2: pow
{
unsigned int row_gid = (blockIdx.x * blockDim.x + threadIdx.x) / blockDim.x;
unsigned int col_gid = (blockIdx.x * blockDim.x + threadIdx.x) % blockDim.x;
if (op_type == 2)
{
for (unsigned int row = row_gid; row < A_size1; row += gridDim.x)
for (unsigned int col = col_gid; col < A_size2; col += blockDim.x)
A[(row * A_inc1 + A_start1) * A_internal_size2 + col * A_inc2 + A_start2]
= pow(B[(row * B_inc1 + B_start1) * B_internal_size2 + col * B_inc2 + B_start2],
C[(row * C_inc1 + C_start1) * C_internal_size2 + col * C_inc2 + C_start2]);
}
else if (op_type == 1)
{
for (unsigned int row = row_gid; row < A_size1; row += gridDim.x)
for (unsigned int col = col_gid; col < A_size2; col += blockDim.x)
A[(row * A_inc1 + A_start1) * A_internal_size2 + col * A_inc2 + A_start2]
= B[(row * B_inc1 + B_start1) * B_internal_size2 + col * B_inc2 + B_start2]
/ C[(row * C_inc1 + C_start1) * C_internal_size2 + col * C_inc2 + C_start2];
}
else if (op_type == 0)
{
for (unsigned int row = row_gid; row < A_size1; row += gridDim.x)
for (unsigned int col = col_gid; col < A_size2; col += blockDim.x)
A[(row * A_inc1 + A_start1) * A_internal_size2 + col * A_inc2 + A_start2]
= B[(row * B_inc1 + B_start1) * B_internal_size2 + col * B_inc2 + B_start2]
* C[(row * C_inc1 + C_start1) * C_internal_size2 + col * C_inc2 + C_start2];
}
}
template<typename NumericT>
__global__ void element_op_int_row_kernel(
NumericT * A,
unsigned int A_start1, unsigned int A_start2,
unsigned int A_inc1, unsigned int A_inc2,
unsigned int A_size1, unsigned int A_size2,
unsigned int A_internal_size1, unsigned int A_internal_size2,
const NumericT * B,
unsigned int B_start1, unsigned int B_start2,
unsigned int B_inc1, unsigned int B_inc2,
unsigned int B_internal_size1, unsigned int B_internal_size2,
const NumericT * C,
unsigned int C_start1, unsigned int C_start2,
unsigned int C_inc1, unsigned int C_inc2,
unsigned int C_internal_size1, unsigned int C_internal_size2,
unsigned int op_type) //0: product, 1: division, 2: pow
{
unsigned int row_gid = (blockIdx.x * blockDim.x + threadIdx.x) / blockDim.x;
unsigned int col_gid = (blockIdx.x * blockDim.x + threadIdx.x) % blockDim.x;
if (op_type == 1)
{
for (unsigned int row = row_gid; row < A_size1; row += gridDim.x)
for (unsigned int col = col_gid; col < A_size2; col += blockDim.x)
A[(row * A_inc1 + A_start1) * A_internal_size2 + col * A_inc2 + A_start2]
= B[(row * B_inc1 + B_start1) * B_internal_size2 + col * B_inc2 + B_start2]
/ C[(row * C_inc1 + C_start1) * C_internal_size2 + col * C_inc2 + C_start2];
}
else if (op_type == 0)
{
for (unsigned int row = row_gid; row < A_size1; row += gridDim.x)
for (unsigned int col = col_gid; col < A_size2; col += blockDim.x)
A[(row * A_inc1 + A_start1) * A_internal_size2 + col * A_inc2 + A_start2]
= B[(row * B_inc1 + B_start1) * B_internal_size2 + col * B_inc2 + B_start2]
* C[(row * C_inc1 + C_start1) * C_internal_size2 + col * C_inc2 + C_start2];
}
}
//
// unary element-wise operations
//
// abs
template<typename NumericT>
__global__ void matrix_row_element_abs_kernel(
NumericT * A,
unsigned int A_start1, unsigned int A_start2,
unsigned int A_inc1, unsigned int A_inc2,
unsigned int A_size1, unsigned int A_size2,
unsigned int A_internal_size1, unsigned int A_internal_size2,
const NumericT * B,
unsigned int B_start1, unsigned int B_start2,
unsigned int B_inc1, unsigned int B_inc2,
unsigned int B_internal_size1, unsigned int B_internal_size2)
{
unsigned int row_gid = (blockIdx.x * blockDim.x + threadIdx.x) / blockDim.x;
unsigned int col_gid = (blockIdx.x * blockDim.x + threadIdx.x) % blockDim.x;
for (unsigned int row = row_gid; row < A_size1; row += gridDim.x)
for (unsigned int col = col_gid; col < A_size2; col += blockDim.x)
A[(row * A_inc1 + A_start1) * A_internal_size2 + col * A_inc2 + A_start2] = abs(B[(row * B_inc1 + B_start1) * B_internal_size2 + col * B_inc2 + B_start2]);
}
// acos
template<typename NumericT>
__global__ void matrix_row_element_acos_kernel(
NumericT * A,
unsigned int A_start1, unsigned int A_start2,
unsigned int A_inc1, unsigned int A_inc2,
unsigned int A_size1, unsigned int A_size2,
unsigned int A_internal_size1, unsigned int A_internal_size2,
const NumericT * B,
unsigned int B_start1, unsigned int B_start2,
unsigned int B_inc1, unsigned int B_inc2,
unsigned int B_internal_size1, unsigned int B_internal_size2)
{
unsigned int row_gid = (blockIdx.x * blockDim.x + threadIdx.x) / blockDim.x;
unsigned int col_gid = (blockIdx.x * blockDim.x + threadIdx.x) % blockDim.x;
for (unsigned int row = row_gid; row < A_size1; row += gridDim.x)
for (unsigned int col = col_gid; col < A_size2; col += blockDim.x)
A[(row * A_inc1 + A_start1) * A_internal_size2 + col * A_inc2 + A_start2] = acos(B[(row * B_inc1 + B_start1) * B_internal_size2 + col * B_inc2 + B_start2]);
}
// asin
template<typename NumericT>
__global__ void matrix_row_element_asin_kernel(
NumericT * A,
unsigned int A_start1, unsigned int A_start2,
unsigned int A_inc1, unsigned int A_inc2,
unsigned int A_size1, unsigned int A_size2,
unsigned int A_internal_size1, unsigned int A_internal_size2,
const NumericT * B,
unsigned int B_start1, unsigned int B_start2,
unsigned int B_inc1, unsigned int B_inc2,
unsigned int B_internal_size1, unsigned int B_internal_size2)
{
unsigned int row_gid = (blockIdx.x * blockDim.x + threadIdx.x) / blockDim.x;
unsigned int col_gid = (blockIdx.x * blockDim.x + threadIdx.x) % blockDim.x;
for (unsigned int row = row_gid; row < A_size1; row += gridDim.x)
for (unsigned int col = col_gid; col < A_size2; col += blockDim.x)
A[(row * A_inc1 + A_start1) * A_internal_size2 + col * A_inc2 + A_start2] = asin(B[(row * B_inc1 + B_start1) * B_internal_size2 + col * B_inc2 + B_start2]);
}
// atan
template<typename NumericT>
__global__ void matrix_row_element_atan_kernel(
NumericT * A,
unsigned int A_start1, unsigned int A_start2,
unsigned int A_inc1, unsigned int A_inc2,
unsigned int A_size1, unsigned int A_size2,
unsigned int A_internal_size1, unsigned int A_internal_size2,
const NumericT * B,
unsigned int B_start1, unsigned int B_start2,
unsigned int B_inc1, unsigned int B_inc2,
unsigned int B_internal_size1, unsigned int B_internal_size2)
{
unsigned int row_gid = (blockIdx.x * blockDim.x + threadIdx.x) / blockDim.x;
unsigned int col_gid = (blockIdx.x * blockDim.x + threadIdx.x) % blockDim.x;
for (unsigned int row = row_gid; row < A_size1; row += gridDim.x)
for (unsigned int col = col_gid; col < A_size2; col += blockDim.x)
A[(row * A_inc1 + A_start1) * A_internal_size2 + col * A_inc2 + A_start2] = atan(B[(row * B_inc1 + B_start1) * B_internal_size2 + col * B_inc2 + B_start2]);
}
// ceil
template<typename NumericT>
__global__ void matrix_row_element_ceil_kernel(
NumericT * A,
unsigned int A_start1, unsigned int A_start2,
unsigned int A_inc1, unsigned int A_inc2,
unsigned int A_size1, unsigned int A_size2,
unsigned int A_internal_size1, unsigned int A_internal_size2,
const NumericT * B,
unsigned int B_start1, unsigned int B_start2,
unsigned int B_inc1, unsigned int B_inc2,
unsigned int B_internal_size1, unsigned int B_internal_size2)
{
unsigned int row_gid = (blockIdx.x * blockDim.x + threadIdx.x) / blockDim.x;
unsigned int col_gid = (blockIdx.x * blockDim.x + threadIdx.x) % blockDim.x;
for (unsigned int row = row_gid; row < A_size1; row += gridDim.x)
for (unsigned int col = col_gid; col < A_size2; col += blockDim.x)
A[(row * A_inc1 + A_start1) * A_internal_size2 + col * A_inc2 + A_start2] = ceil(B[(row * B_inc1 + B_start1) * B_internal_size2 + col * B_inc2 + B_start2]);
}
// cos
template<typename NumericT>
__global__ void matrix_row_element_cos_kernel(
NumericT * A,
unsigned int A_start1, unsigned int A_start2,
unsigned int A_inc1, unsigned int A_inc2,
unsigned int A_size1, unsigned int A_size2,
unsigned int A_internal_size1, unsigned int A_internal_size2,
const NumericT * B,
unsigned int B_start1, unsigned int B_start2,
unsigned int B_inc1, unsigned int B_inc2,
unsigned int B_internal_size1, unsigned int B_internal_size2)
{
unsigned int row_gid = (blockIdx.x * blockDim.x + threadIdx.x) / blockDim.x;
unsigned int col_gid = (blockIdx.x * blockDim.x + threadIdx.x) % blockDim.x;
for (unsigned int row = row_gid; row < A_size1; row += gridDim.x)
for (unsigned int col = col_gid; col < A_size2; col += blockDim.x)
A[(row * A_inc1 + A_start1) * A_internal_size2 + col * A_inc2 + A_start2] = cos(B[(row * B_inc1 + B_start1) * B_internal_size2 + col * B_inc2 + B_start2]);
}
// cosh
template<typename NumericT>
__global__ void matrix_row_element_cosh_kernel(
NumericT * A,
unsigned int A_start1, unsigned int A_start2,
unsigned int A_inc1, unsigned int A_inc2,
unsigned int A_size1, unsigned int A_size2,
unsigned int A_internal_size1, unsigned int A_internal_size2,
const NumericT * B,
unsigned int B_start1, unsigned int B_start2,
unsigned int B_inc1, unsigned int B_inc2,
unsigned int B_internal_size1, unsigned int B_internal_size2)
{
unsigned int row_gid = (blockIdx.x * blockDim.x + threadIdx.x) / blockDim.x;
unsigned int col_gid = (blockIdx.x * blockDim.x + threadIdx.x) % blockDim.x;
for (unsigned int row = row_gid; row < A_size1; row += gridDim.x)
for (unsigned int col = col_gid; col < A_size2; col += blockDim.x)
A[(row * A_inc1 + A_start1) * A_internal_size2 + col * A_inc2 + A_start2] = cosh(B[(row * B_inc1 + B_start1) * B_internal_size2 + col * B_inc2 + B_start2]);
}
// exp
template<typename NumericT>
__global__ void matrix_row_element_exp_kernel(
NumericT * A,
unsigned int A_start1, unsigned int A_start2,
unsigned int A_inc1, unsigned int A_inc2,
unsigned int A_size1, unsigned int A_size2,
unsigned int A_internal_size1, unsigned int A_internal_size2,
const NumericT * B,
unsigned int B_start1, unsigned int B_start2,
unsigned int B_inc1, unsigned int B_inc2,
unsigned int B_internal_size1, unsigned int B_internal_size2)
{
unsigned int row_gid = (blockIdx.x * blockDim.x + threadIdx.x) / blockDim.x;
unsigned int col_gid = (blockIdx.x * blockDim.x + threadIdx.x) % blockDim.x;
for (unsigned int row = row_gid; row < A_size1; row += gridDim.x)
for (unsigned int col = col_gid; col < A_size2; col += blockDim.x)
A[(row * A_inc1 + A_start1) * A_internal_size2 + col * A_inc2 + A_start2] = exp(B[(row * B_inc1 + B_start1) * B_internal_size2 + col * B_inc2 + B_start2]);
}
// fabs
template<typename NumericT>
__global__ void matrix_row_element_fabs_kernel(
NumericT * A,
unsigned int A_start1, unsigned int A_start2,
unsigned int A_inc1, unsigned int A_inc2,
unsigned int A_size1, unsigned int A_size2,
unsigned int A_internal_size1, unsigned int A_internal_size2,
const NumericT * B,
unsigned int B_start1, unsigned int B_start2,
unsigned int B_inc1, unsigned int B_inc2,
unsigned int B_internal_size1, unsigned int B_internal_size2)
{
unsigned int row_gid = (blockIdx.x * blockDim.x + threadIdx.x) / blockDim.x;
unsigned int col_gid = (blockIdx.x * blockDim.x + threadIdx.x) % blockDim.x;
for (unsigned int row = row_gid; row < A_size1; row += gridDim.x)
for (unsigned int col = col_gid; col < A_size2; col += blockDim.x)
A[(row * A_inc1 + A_start1) * A_internal_size2 + col * A_inc2 + A_start2] = fabs(B[(row * B_inc1 + B_start1) * B_internal_size2 + col * B_inc2 + B_start2]);
}
// floor
template<typename NumericT>
__global__ void matrix_row_element_floor_kernel(
NumericT * A,
unsigned int A_start1, unsigned int A_start2,
unsigned int A_inc1, unsigned int A_inc2,
unsigned int A_size1, unsigned int A_size2,
unsigned int A_internal_size1, unsigned int A_internal_size2,
const NumericT * B,
unsigned int B_start1, unsigned int B_start2,
unsigned int B_inc1, unsigned int B_inc2,
unsigned int B_internal_size1, unsigned int B_internal_size2)
{
unsigned int row_gid = (blockIdx.x * blockDim.x + threadIdx.x) / blockDim.x;
unsigned int col_gid = (blockIdx.x * blockDim.x + threadIdx.x) % blockDim.x;
for (unsigned int row = row_gid; row < A_size1; row += gridDim.x)
for (unsigned int col = col_gid; col < A_size2; col += blockDim.x)
A[(row * A_inc1 + A_start1) * A_internal_size2 + col * A_inc2 + A_start2] = floor(B[(row * B_inc1 + B_start1) * B_internal_size2 + col * B_inc2 + B_start2]);
}
// log
template<typename NumericT>
__global__ void matrix_row_element_log_kernel(
NumericT * A,
unsigned int A_start1, unsigned int A_start2,
unsigned int A_inc1, unsigned int A_inc2,
unsigned int A_size1, unsigned int A_size2,
unsigned int A_internal_size1, unsigned int A_internal_size2,
const NumericT * B,
unsigned int B_start1, unsigned int B_start2,
unsigned int B_inc1, unsigned int B_inc2,
unsigned int B_internal_size1, unsigned int B_internal_size2)
{
unsigned int row_gid = (blockIdx.x * blockDim.x + threadIdx.x) / blockDim.x;
unsigned int col_gid = (blockIdx.x * blockDim.x + threadIdx.x) % blockDim.x;
for (unsigned int row = row_gid; row < A_size1; row += gridDim.x)
for (unsigned int col = col_gid; col < A_size2; col += blockDim.x)
A[(row * A_inc1 + A_start1) * A_internal_size2 + col * A_inc2 + A_start2] = log(B[(row * B_inc1 + B_start1) * B_internal_size2 + col * B_inc2 + B_start2]);
}
// log10
template<typename NumericT>
__global__ void matrix_row_element_log10_kernel(
NumericT * A,
unsigned int A_start1, unsigned int A_start2,
unsigned int A_inc1, unsigned int A_inc2,
unsigned int A_size1, unsigned int A_size2,
unsigned int A_internal_size1, unsigned int A_internal_size2,
const NumericT * B,
unsigned int B_start1, unsigned int B_start2,
unsigned int B_inc1, unsigned int B_inc2,
unsigned int B_internal_size1, unsigned int B_internal_size2)
{
unsigned int row_gid = (blockIdx.x * blockDim.x + threadIdx.x) / blockDim.x;
unsigned int col_gid = (blockIdx.x * blockDim.x + threadIdx.x) % blockDim.x;
for (unsigned int row = row_gid; row < A_size1; row += gridDim.x)
for (unsigned int col = col_gid; col < A_size2; col += blockDim.x)
A[(row * A_inc1 + A_start1) * A_internal_size2 + col * A_inc2 + A_start2] = log10(B[(row * B_inc1 + B_start1) * B_internal_size2 + col * B_inc2 + B_start2]);
}
// sin
template<typename NumericT>
__global__ void matrix_row_element_sin_kernel(
NumericT * A,
unsigned int A_start1, unsigned int A_start2,
unsigned int A_inc1, unsigned int A_inc2,
unsigned int A_size1, unsigned int A_size2,
unsigned int A_internal_size1, unsigned int A_internal_size2,
const NumericT * B,
unsigned int B_start1, unsigned int B_start2,
unsigned int B_inc1, unsigned int B_inc2,
unsigned int B_internal_size1, unsigned int B_internal_size2)
{
unsigned int row_gid = (blockIdx.x * blockDim.x + threadIdx.x) / blockDim.x;
unsigned int col_gid = (blockIdx.x * blockDim.x + threadIdx.x) % blockDim.x;
for (unsigned int row = row_gid; row < A_size1; row += gridDim.x)
for (unsigned int col = col_gid; col < A_size2; col += blockDim.x)
A[(row * A_inc1 + A_start1) * A_internal_size2 + col * A_inc2 + A_start2] = sin(B[(row * B_inc1 + B_start1) * B_internal_size2 + col * B_inc2 + B_start2]);
}
// sinh
template<typename NumericT>
__global__ void matrix_row_element_sinh_kernel(
NumericT * A,
unsigned int A_start1, unsigned int A_start2,
unsigned int A_inc1, unsigned int A_inc2,
unsigned int A_size1, unsigned int A_size2,
unsigned int A_internal_size1, unsigned int A_internal_size2,
const NumericT * B,
unsigned int B_start1, unsigned int B_start2,
unsigned int B_inc1, unsigned int B_inc2,
unsigned int B_internal_size1, unsigned int B_internal_size2)
{
unsigned int row_gid = (blockIdx.x * blockDim.x + threadIdx.x) / blockDim.x;
unsigned int col_gid = (blockIdx.x * blockDim.x + threadIdx.x) % blockDim.x;
for (unsigned int row = row_gid; row < A_size1; row += gridDim.x)
for (unsigned int col = col_gid; col < A_size2; col += blockDim.x)
A[(row * A_inc1 + A_start1) * A_internal_size2 + col * A_inc2 + A_start2] = sinh(B[(row * B_inc1 + B_start1) * B_internal_size2 + col * B_inc2 + B_start2]);
}
// sqrt
template<typename NumericT>
__global__ void matrix_row_element_sqrt_kernel(
NumericT * A,
unsigned int A_start1, unsigned int A_start2,
unsigned int A_inc1, unsigned int A_inc2,
unsigned int A_size1, unsigned int A_size2,
unsigned int A_internal_size1, unsigned int A_internal_size2,
const NumericT * B,
unsigned int B_start1, unsigned int B_start2,
unsigned int B_inc1, unsigned int B_inc2,
unsigned int B_internal_size1, unsigned int B_internal_size2)
{
unsigned int row_gid = (blockIdx.x * blockDim.x + threadIdx.x) / blockDim.x;
unsigned int col_gid = (blockIdx.x * blockDim.x + threadIdx.x) % blockDim.x;
for (unsigned int row = row_gid; row < A_size1; row += gridDim.x)
for (unsigned int col = col_gid; col < A_size2; col += blockDim.x)
A[(row * A_inc1 + A_start1) * A_internal_size2 + col * A_inc2 + A_start2] = sqrt(B[(row * B_inc1 + B_start1) * B_internal_size2 + col * B_inc2 + B_start2]);
}
// tan
template<typename NumericT>
__global__ void matrix_row_element_tan_kernel(
NumericT * A,
unsigned int A_start1, unsigned int A_start2,
unsigned int A_inc1, unsigned int A_inc2,
unsigned int A_size1, unsigned int A_size2,
unsigned int A_internal_size1, unsigned int A_internal_size2,
const NumericT * B,
unsigned int B_start1, unsigned int B_start2,
unsigned int B_inc1, unsigned int B_inc2,
unsigned int B_internal_size1, unsigned int B_internal_size2)
{
unsigned int row_gid = (blockIdx.x * blockDim.x + threadIdx.x) / blockDim.x;
unsigned int col_gid = (blockIdx.x * blockDim.x + threadIdx.x) % blockDim.x;
for (unsigned int row = row_gid; row < A_size1; row += gridDim.x)
for (unsigned int col = col_gid; col < A_size2; col += blockDim.x)
A[(row * A_inc1 + A_start1) * A_internal_size2 + col * A_inc2 + A_start2] = tan(B[(row * B_inc1 + B_start1) * B_internal_size2 + col * B_inc2 + B_start2]);
}
// tanh
template<typename NumericT>
__global__ void matrix_row_element_tanh_kernel(
NumericT * A,
unsigned int A_start1, unsigned int A_start2,
unsigned int A_inc1, unsigned int A_inc2,
unsigned int A_size1, unsigned int A_size2,
unsigned int A_internal_size1, unsigned int A_internal_size2,
const NumericT * B,
unsigned int B_start1, unsigned int B_start2,
unsigned int B_inc1, unsigned int B_inc2,
unsigned int B_internal_size1, unsigned int B_internal_size2)
{
unsigned int row_gid = (blockIdx.x * blockDim.x + threadIdx.x) / blockDim.x;
unsigned int col_gid = (blockIdx.x * blockDim.x + threadIdx.x) % blockDim.x;
for (unsigned int row = row_gid; row < A_size1; row += gridDim.x)
for (unsigned int col = col_gid; col < A_size2; col += blockDim.x)
A[(row * A_inc1 + A_start1) * A_internal_size2 + col * A_inc2 + A_start2] = tanh(B[(row * B_inc1 + B_start1) * B_internal_size2 + col * B_inc2 + B_start2]);
}
//
// matrix-vector product
//
template<typename NumericT>
__global__ void vec_mul_row_kernel(
const NumericT * A,
unsigned int A_row_start,
unsigned int A_col_start,
unsigned int A_row_inc,
unsigned int A_col_inc,
unsigned int A_row_size,
unsigned int A_col_size,
unsigned int A_internal_rows,
unsigned int A_internal_cols,
const NumericT * v,
unsigned int v_start,
unsigned int v_inc,
unsigned int v_size,
NumericT * result,
unsigned int result_start,
unsigned int result_inc,
unsigned int result_size)
{
__shared__ NumericT work[128];
unsigned int row_gid = (blockIdx.x * blockDim.x + threadIdx.x) / blockDim.x;
unsigned int col_gid = (blockIdx.x * blockDim.x + threadIdx.x) % blockDim.x;
unsigned int lid = threadIdx.x;
for (unsigned int row = row_gid; row < A_row_size; row += gridDim.x)
{
NumericT dot_prod = 0;
for (unsigned int col = col_gid; col < A_col_size; col += blockDim.x)
dot_prod += A[(row * A_row_inc + A_row_start) * A_internal_cols + col * A_col_inc + A_col_start] * v[v_start + v_inc * col];
work[lid] = dot_prod;
for (unsigned int stride = blockDim.x/2; stride>0; stride>>=1){
__syncthreads();
if (lid < stride)
work[lid] += work[lid+stride];
}
if (lid == 0)
result[row * result_inc + result_start] = work[0];
}
}
template<typename NumericT>
__global__ void trans_vec_mul_row_kernel(
const NumericT * A,
unsigned int A_row_start,
unsigned int A_col_start,
unsigned int A_row_inc,
unsigned int A_col_inc,
unsigned int A_row_size,
unsigned int A_col_size,
unsigned int A_internal_rows,
unsigned int A_internal_cols,
const NumericT * v,
unsigned int v_start,
unsigned int v_inc,
unsigned int v_size,
NumericT * result,
unsigned int result_start,
unsigned int result_inc,
unsigned int result_size)
{
for (unsigned int row = blockIdx.x * blockDim.x + threadIdx.x; row < A_col_size; row += gridDim.x * blockDim.x)
{
NumericT dot_prod = 0;
for (unsigned int col = 0; col < A_row_size; ++col)
dot_prod += A[(row * A_col_inc + A_col_start) + (col * A_row_inc + A_row_start) * A_internal_cols] * v[v_start + v_inc * col];
result[row * result_inc + result_start] = dot_prod;
}
}
//
// matrix-matrix products
//
//
// scaled rank-1-update
//
// alpha on CPU
template<typename NumericT>
__global__ void scaled_rank1_update_row_kernel(
NumericT * A,
unsigned int A_start1, unsigned int A_start2,
unsigned int A_inc1, unsigned int A_inc2,
unsigned int A_size1, unsigned int A_size2,
unsigned int A_internal_size1, unsigned int A_internal_size2,
NumericT val,
unsigned int options2,
const NumericT * vec1,
unsigned int start1,
unsigned int inc1,
unsigned int size1,
const NumericT * vec2,
unsigned int start2,
unsigned int inc2,
unsigned int size2)
{
NumericT alpha = val;
if (options2 & (1 << 0))
alpha = -alpha;
if (options2 & (1 << 1))
alpha = NumericT(1) / alpha;
unsigned int row_gid = (blockIdx.x * blockDim.x + threadIdx.x) / blockDim.x;
unsigned int col_gid = (blockIdx.x * blockDim.x + threadIdx.x) % blockDim.x;
for (unsigned int row = row_gid; row < A_size1; row += gridDim.x)
{
NumericT tmp = alpha * vec1[row * inc1 + start1];
for (unsigned int col = col_gid; col < A_size2; col += blockDim.x)
A[(row * A_inc1 + A_start1) * A_internal_size2 + col * A_inc2 + A_start2] += tmp * vec2[col * inc2 + start2];
}
}
// alpha on GPU
template<typename NumericT>
__global__ void scaled_rank1_update_row_kernel(
NumericT * A,
unsigned int A_start1, unsigned int A_start2,
unsigned int A_inc1, unsigned int A_inc2,
unsigned int A_size1, unsigned int A_size2,
unsigned int A_internal_size1, unsigned int A_internal_size2,
const NumericT * val,
unsigned int options2,
const NumericT * vec1,
unsigned int start1,
unsigned int inc1,
unsigned int size1,
const NumericT * vec2,
unsigned int start2,
unsigned int inc2,
unsigned int size2)
{
NumericT alpha = *val;
if (options2 & (1 << 0))
alpha = -alpha;
if (options2 & (1 << 1))
alpha = NumericT(1) / alpha;
unsigned int row_gid = (blockIdx.x * blockDim.x + threadIdx.x) / blockDim.x;
unsigned int col_gid = (blockIdx.x * blockDim.x + threadIdx.x) % blockDim.x;
for (unsigned int row = row_gid; row < A_size1; row += gridDim.x)
{
NumericT tmp = alpha * vec1[row * inc1 + start1];
for (unsigned int col = col_gid; col < A_size2; col += blockDim.x)
A[(row * A_inc1 + A_start1) * A_internal_size2 + col * A_inc2 + A_start2] += tmp * vec2[col * inc2 + start2];
}
}
} // namespace cuda
} //namespace linalg
} //namespace viennacl
#endif
viennacl::linalg::cuda::element_op_int_row_kernel
__global__ void element_op_int_row_kernel(NumericT *A, unsigned int A_start1, unsigned int A_start2, unsigned int A_inc1, unsigned int A_inc2, unsigned int A_size1, unsigned int A_size2, unsigned int A_internal_size1, unsigned int A_internal_size2, const NumericT *B, unsigned int B_start1, unsigned int B_start2, unsigned int B_inc1, unsigned int B_inc2, unsigned int B_internal_size1, unsigned int B_internal_size2, const NumericT *C, unsigned int C_start1, unsigned int C_start2, unsigned int C_inc1, unsigned int C_inc2, unsigned int C_internal_size1, unsigned int C_internal_size2, unsigned int op_type)
Definition: matrix_operations_row.hpp:856
viennacl::linalg::cuda::matrix_row_element_exp_kernel
__global__ void matrix_row_element_exp_kernel(NumericT *A, unsigned int A_start1, unsigned int A_start2, unsigned int A_inc1, unsigned int A_inc2, unsigned int A_size1, unsigned int A_size2, unsigned int A_internal_size1, unsigned int A_internal_size2, const NumericT *B, unsigned int B_start1, unsigned int B_start2, unsigned int B_inc1, unsigned int B_inc2, unsigned int B_internal_size1, unsigned int B_internal_size2)
Definition: matrix_operations_row.hpp:1063
viennacl::linalg::cuda::matrix_row_element_acos_kernel
__global__ void matrix_row_element_acos_kernel(NumericT *A, unsigned int A_start1, unsigned int A_start2, unsigned int A_inc1, unsigned int A_inc2, unsigned int A_size1, unsigned int A_size2, unsigned int A_internal_size1, unsigned int A_internal_size2, const NumericT *B, unsigned int B_start1, unsigned int B_start2, unsigned int B_inc1, unsigned int B_inc2, unsigned int B_internal_size1, unsigned int B_internal_size2)
Definition: matrix_operations_row.hpp:925
viennacl::linalg::cuda::matrix_row_element_cosh_kernel
__global__ void matrix_row_element_cosh_kernel(NumericT *A, unsigned int A_start1, unsigned int A_start2, unsigned int A_inc1, unsigned int A_inc2, unsigned int A_size1, unsigned int A_size2, unsigned int A_internal_size1, unsigned int A_internal_size2, const NumericT *B, unsigned int B_start1, unsigned int B_start2, unsigned int B_inc1, unsigned int B_inc2, unsigned int B_internal_size1, unsigned int B_internal_size2)
Definition: matrix_operations_row.hpp:1040
viennacl::linalg::cuda::matrix_row_element_floor_kernel
__global__ void matrix_row_element_floor_kernel(NumericT *A, unsigned int A_start1, unsigned int A_start2, unsigned int A_inc1, unsigned int A_inc2, unsigned int A_size1, unsigned int A_size2, unsigned int A_internal_size1, unsigned int A_internal_size2, const NumericT *B, unsigned int B_start1, unsigned int B_start2, unsigned int B_inc1, unsigned int B_inc2, unsigned int B_internal_size1, unsigned int B_internal_size2)
Definition: matrix_operations_row.hpp:1109
viennacl::linalg::cuda::am_row_kernel
__global__ void am_row_kernel(NumericT *A, unsigned int A_start1, unsigned int A_start2, unsigned int A_inc1, unsigned int A_inc2, unsigned int A_size1, unsigned int A_size2, unsigned int A_internal_size1, unsigned int A_internal_size2, NumericT fac2, unsigned int options2, const NumericT *B, unsigned int B_start1, unsigned int B_start2, unsigned int B_inc1, unsigned int B_inc2, unsigned int B_internal_size1, unsigned int B_internal_size2)
Definition: matrix_operations_row.hpp:87
viennacl::linalg::cuda::matrix_row_element_abs_kernel
__global__ void matrix_row_element_abs_kernel(NumericT *A, unsigned int A_start1, unsigned int A_start2, unsigned int A_inc1, unsigned int A_inc2, unsigned int A_size1, unsigned int A_size2, unsigned int A_internal_size1, unsigned int A_internal_size2, const NumericT *B, unsigned int B_start1, unsigned int B_start2, unsigned int B_inc1, unsigned int B_inc2, unsigned int B_internal_size1, unsigned int B_internal_size2)
Definition: matrix_operations_row.hpp:902
viennacl::linalg::cuda::matrix_row_element_tanh_kernel
__global__ void matrix_row_element_tanh_kernel(NumericT *A, unsigned int A_start1, unsigned int A_start2, unsigned int A_inc1, unsigned int A_inc2, unsigned int A_size1, unsigned int A_size2, unsigned int A_internal_size1, unsigned int A_internal_size2, const NumericT *B, unsigned int B_start1, unsigned int B_start2, unsigned int B_inc1, unsigned int B_inc2, unsigned int B_internal_size1, unsigned int B_internal_size2)
Definition: matrix_operations_row.hpp:1270
viennacl::linalg::cuda::matrix_row_element_fabs_kernel
__global__ void matrix_row_element_fabs_kernel(NumericT *A, unsigned int A_start1, unsigned int A_start2, unsigned int A_inc1, unsigned int A_inc2, unsigned int A_size1, unsigned int A_size2, unsigned int A_internal_size1, unsigned int A_internal_size2, const NumericT *B, unsigned int B_start1, unsigned int B_start2, unsigned int B_inc1, unsigned int B_inc2, unsigned int B_internal_size1, unsigned int B_internal_size2)
Definition: matrix_operations_row.hpp:1086
viennacl::traits::size1
vcl_size_t size1(MatrixType const &mat)
Generic routine for obtaining the number of rows of a matrix (ViennaCL, uBLAS, etc.)
Definition: size.hpp:163
viennacl::linalg::cuda::matrix_row_element_asin_kernel
__global__ void matrix_row_element_asin_kernel(NumericT *A, unsigned int A_start1, unsigned int A_start2, unsigned int A_inc1, unsigned int A_inc2, unsigned int A_size1, unsigned int A_size2, unsigned int A_internal_size1, unsigned int A_internal_size2, const NumericT *B, unsigned int B_start1, unsigned int B_start2, unsigned int B_inc1, unsigned int B_inc2, unsigned int B_internal_size1, unsigned int B_internal_size2)
Definition: matrix_operations_row.hpp:948
viennacl::traits::stride
result_of::size_type< viennacl::vector_base< T > >::type stride(viennacl::vector_base< T > const &s)
Definition: stride.hpp:45
viennacl::traits::start1
result_of::size_type< T >::type start1(T const &obj)
Definition: start.hpp:65
viennacl::linalg::cuda::ambm_m_row_kernel
__global__ void ambm_m_row_kernel(NumericT *A, unsigned int A_start1, unsigned int A_start2, unsigned int A_inc1, unsigned int A_inc2, unsigned int A_size1, unsigned int A_size2, unsigned int A_internal_size1, unsigned int A_internal_size2, NumericT fac2, unsigned int options2, const NumericT *B, unsigned int B_start1, unsigned int B_start2, unsigned int B_inc1, unsigned int B_inc2, unsigned int B_internal_size1, unsigned int B_internal_size2, NumericT fac3, unsigned int options3, const NumericT *C, unsigned int C_start1, unsigned int C_start2, unsigned int C_inc1, unsigned int C_inc2, unsigned int C_internal_size1, unsigned int C_internal_size2)
Definition: matrix_operations_row.hpp:469
viennacl::linalg::detail::spai::dot_prod
void dot_prod(MatrixT const &A, unsigned int beg_ind, NumericT &res)
Dot prod of particular column of martix A with it's self starting at a certain index beg_ind...
Definition: qr.hpp:182
viennacl::linalg::cuda::matrix_row_element_sqrt_kernel
__global__ void matrix_row_element_sqrt_kernel(NumericT *A, unsigned int A_start1, unsigned int A_start2, unsigned int A_inc1, unsigned int A_inc2, unsigned int A_size1, unsigned int A_size2, unsigned int A_internal_size1, unsigned int A_internal_size2, const NumericT *B, unsigned int B_start1, unsigned int B_start2, unsigned int B_inc1, unsigned int B_inc2, unsigned int B_internal_size1, unsigned int B_internal_size2)
Definition: matrix_operations_row.hpp:1224
viennacl::traits::size2
result_of::size_type< MatrixType >::type size2(MatrixType const &mat)
Generic routine for obtaining the number of columns of a matrix (ViennaCL, uBLAS, etc...
Definition: size.hpp:201
NumericT
float NumericT
Definition: bisect.cpp:40
viennacl::linalg::cuda::trans_vec_mul_row_kernel
__global__ void trans_vec_mul_row_kernel(const NumericT *A, unsigned int A_row_start, unsigned int A_col_start, unsigned int A_row_inc, unsigned int A_col_inc, unsigned int A_row_size, unsigned int A_col_size, unsigned int A_internal_rows, unsigned int A_internal_cols, const NumericT *v, unsigned int v_start, unsigned int v_inc, unsigned int v_size, NumericT *result, unsigned int result_start, unsigned int result_inc, unsigned int result_size)
Definition: matrix_operations_row.hpp:1342
viennacl::traits::start2
result_of::size_type< T >::type start2(T const &obj)
Definition: start.hpp:84
viennacl::linalg::cuda::element_op_row_kernel
__global__ void element_op_row_kernel(NumericT *A, unsigned int A_start1, unsigned int A_start2, unsigned int A_inc1, unsigned int A_inc2, unsigned int A_size1, unsigned int A_size2, unsigned int A_internal_size1, unsigned int A_internal_size2, const NumericT *B, unsigned int B_start1, unsigned int B_start2, unsigned int B_inc1, unsigned int B_inc2, unsigned int B_internal_size1, unsigned int B_internal_size2, const NumericT *C, unsigned int C_start1, unsigned int C_start2, unsigned int C_inc1, unsigned int C_inc2, unsigned int C_internal_size1, unsigned int C_internal_size2, unsigned int op_type)
Definition: matrix_operations_row.hpp:807
viennacl::linalg::cuda::matrix_row_element_log10_kernel
__global__ void matrix_row_element_log10_kernel(NumericT *A, unsigned int A_start1, unsigned int A_start2, unsigned int A_inc1, unsigned int A_inc2, unsigned int A_size1, unsigned int A_size2, unsigned int A_internal_size1, unsigned int A_internal_size2, const NumericT *B, unsigned int B_start1, unsigned int B_start2, unsigned int B_inc1, unsigned int B_inc2, unsigned int B_internal_size1, unsigned int B_internal_size2)
Definition: matrix_operations_row.hpp:1155
viennacl::linalg::cuda::matrix_row_element_ceil_kernel
__global__ void matrix_row_element_ceil_kernel(NumericT *A, unsigned int A_start1, unsigned int A_start2, unsigned int A_inc1, unsigned int A_inc2, unsigned int A_size1, unsigned int A_size2, unsigned int A_internal_size1, unsigned int A_internal_size2, const NumericT *B, unsigned int B_start1, unsigned int B_start2, unsigned int B_inc1, unsigned int B_inc2, unsigned int B_internal_size1, unsigned int B_internal_size2)
Definition: matrix_operations_row.hpp:994
viennacl::linalg::cuda::matrix_row_diagonal_assign_kernel
__global__ void matrix_row_diagonal_assign_kernel(NumericT *A, unsigned int A_start1, unsigned int A_start2, unsigned int A_inc1, unsigned int A_inc2, unsigned int A_size1, unsigned int A_size2, unsigned int A_internal_size1, unsigned int A_internal_size2, NumericT alpha)
Definition: matrix_operations_row.hpp:788
viennacl::linalg::cuda::convert_row_kernel
__global__ void convert_row_kernel(DestNumericT *A, unsigned int A_start1, unsigned int A_start2, unsigned int A_inc1, unsigned int A_inc2, unsigned int A_size1, unsigned int A_size2, unsigned int A_internal_size1, unsigned int A_internal_size2, const SrcNumericT *B, unsigned int B_start1, unsigned int B_start2, unsigned int B_inc1, unsigned int B_inc2, unsigned int B_internal_size1, unsigned int B_internal_size2)
Definition: matrix_operations_row.hpp:34
viennacl::linalg::cuda::matrix_row_element_cos_kernel
__global__ void matrix_row_element_cos_kernel(NumericT *A, unsigned int A_start1, unsigned int A_start2, unsigned int A_inc1, unsigned int A_inc2, unsigned int A_size1, unsigned int A_size2, unsigned int A_internal_size1, unsigned int A_internal_size2, const NumericT *B, unsigned int B_start1, unsigned int B_start2, unsigned int B_inc1, unsigned int B_inc2, unsigned int B_internal_size1, unsigned int B_internal_size2)
Definition: matrix_operations_row.hpp:1017
viennacl::linalg::cuda::vec_mul_row_kernel
__global__ void vec_mul_row_kernel(const NumericT *A, unsigned int A_row_start, unsigned int A_col_start, unsigned int A_row_inc, unsigned int A_col_inc, unsigned int A_row_size, unsigned int A_col_size, unsigned int A_internal_rows, unsigned int A_internal_cols, const NumericT *v, unsigned int v_start, unsigned int v_inc, unsigned int v_size, NumericT *result, unsigned int result_start, unsigned int result_inc, unsigned int result_size)
Definition: matrix_operations_row.hpp:1297
viennacl::row
vector_expression< const matrix_base< NumericT, F >, const unsigned int, op_row > row(const matrix_base< NumericT, F > &A, unsigned int i)
Definition: matrix.hpp:910
viennacl::linalg::cuda::scaled_rank1_update_row_kernel
__global__ void scaled_rank1_update_row_kernel(NumericT *A, unsigned int A_start1, unsigned int A_start2, unsigned int A_inc1, unsigned int A_inc2, unsigned int A_size1, unsigned int A_size2, unsigned int A_internal_size1, unsigned int A_internal_size2, NumericT val, unsigned int options2, const NumericT *vec1, unsigned int start1, unsigned int inc1, unsigned int size1, const NumericT *vec2, unsigned int start2, unsigned int inc2, unsigned int size2)
Definition: matrix_operations_row.hpp:1384
viennacl::linalg::cuda::trans_kernel
__global__ void trans_kernel(const NumericT *A, unsigned int A_start1, unsigned int A_start2, unsigned int A_internal_size1, unsigned int A_internal_size2, unsigned int A_size1, unsigned int A_size2, unsigned int A_stride1, unsigned int A_stride2, NumericT *B, unsigned int B_start1, unsigned int B_start2, unsigned int B_internal_size1, unsigned int B_internal_size2, unsigned int B_stride1, unsigned int B_stride2, bool data_major)
Definition: matrix_operations_row.hpp:56
viennacl::linalg::cuda::matrix_row_element_atan_kernel
__global__ void matrix_row_element_atan_kernel(NumericT *A, unsigned int A_start1, unsigned int A_start2, unsigned int A_inc1, unsigned int A_inc2, unsigned int A_size1, unsigned int A_size2, unsigned int A_internal_size1, unsigned int A_internal_size2, const NumericT *B, unsigned int B_start1, unsigned int B_start2, unsigned int B_inc1, unsigned int B_inc2, unsigned int B_internal_size1, unsigned int B_internal_size2)
Definition: matrix_operations_row.hpp:971
viennacl::linalg::cuda::matrix_row_element_tan_kernel
__global__ void matrix_row_element_tan_kernel(NumericT *A, unsigned int A_start1, unsigned int A_start2, unsigned int A_inc1, unsigned int A_inc2, unsigned int A_size1, unsigned int A_size2, unsigned int A_internal_size1, unsigned int A_internal_size2, const NumericT *B, unsigned int B_start1, unsigned int B_start2, unsigned int B_inc1, unsigned int B_inc2, unsigned int B_internal_size1, unsigned int B_internal_size2)
Definition: matrix_operations_row.hpp:1247
viennacl::linalg::cuda::ambm_row_kernel
__global__ void ambm_row_kernel(NumericT *A, unsigned int A_start1, unsigned int A_start2, unsigned int A_inc1, unsigned int A_inc2, unsigned int A_size1, unsigned int A_size2, unsigned int A_internal_size1, unsigned int A_internal_size2, NumericT fac2, unsigned int options2, const NumericT *B, unsigned int B_start1, unsigned int B_start2, unsigned int B_inc1, unsigned int B_inc2, unsigned int B_internal_size1, unsigned int B_internal_size2, NumericT fac3, unsigned int options3, const NumericT *C, unsigned int C_start1, unsigned int C_start2, unsigned int C_inc1, unsigned int C_inc2, unsigned int C_internal_size1, unsigned int C_internal_size2)
Definition: matrix_operations_row.hpp:166
viennacl::linalg::cuda::matrix_row_element_sin_kernel
__global__ void matrix_row_element_sin_kernel(NumericT *A, unsigned int A_start1, unsigned int A_start2, unsigned int A_inc1, unsigned int A_inc2, unsigned int A_size1, unsigned int A_size2, unsigned int A_internal_size1, unsigned int A_internal_size2, const NumericT *B, unsigned int B_start1, unsigned int B_start2, unsigned int B_inc1, unsigned int B_inc2, unsigned int B_internal_size1, unsigned int B_internal_size2)
Definition: matrix_operations_row.hpp:1178
viennacl::linalg::cuda::matrix_row_assign_kernel
__global__ void matrix_row_assign_kernel(NumericT *A, unsigned int A_start1, unsigned int A_start2, unsigned int A_inc1, unsigned int A_inc2, unsigned int A_size1, unsigned int A_size2, unsigned int A_internal_size1, unsigned int A_internal_size2, NumericT alpha)
Definition: matrix_operations_row.hpp:770
viennacl::linalg::cuda::matrix_row_element_sinh_kernel
__global__ void matrix_row_element_sinh_kernel(NumericT *A, unsigned int A_start1, unsigned int A_start2, unsigned int A_inc1, unsigned int A_inc2, unsigned int A_size1, unsigned int A_size2, unsigned int A_internal_size1, unsigned int A_internal_size2, const NumericT *B, unsigned int B_start1, unsigned int B_start2, unsigned int B_inc1, unsigned int B_inc2, unsigned int B_internal_size1, unsigned int B_internal_size2)
Definition: matrix_operations_row.hpp:1201
viennacl::linalg::cuda::matrix_row_element_log_kernel
__global__ void matrix_row_element_log_kernel(NumericT *A, unsigned int A_start1, unsigned int A_start2, unsigned int A_inc1, unsigned int A_inc2, unsigned int A_size1, unsigned int A_size2, unsigned int A_internal_size1, unsigned int A_internal_size2, const NumericT *B, unsigned int B_start1, unsigned int B_start2, unsigned int B_inc1, unsigned int B_inc2, unsigned int B_internal_size1, unsigned int B_internal_size2)
Definition: matrix_operations_row.hpp:1132