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/*
* Copyright 2014-2015 The University of Queensland
* http://www.uq.edu.au
*
* 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.
*/
#pragma once
#include <thrust/functional.h>
#include <cusp/detail/functional.h>
#ifndef DIA_CHUNKSIZE
#define DIA_CHUNKSIZE 1024
#endif
namespace cusp
{
namespace detail
{
namespace host
{
/////////////////////////
// DIA transposed SpMV //
/////////////////////////
template <typename Matrix,
typename Vector1,
typename Vector2,
typename UnaryFunction,
typename BinaryFunction1,
typename BinaryFunction2>
void transposed_spmv_dia(const Matrix& A,
const Vector1& x,
Vector2& y,
UnaryFunction initialize,
BinaryFunction1 combine,
BinaryFunction2 reduce)
{
typedef typename Matrix::index_type IndexType;
//typedef typename Vector2::value_type ValueType;
const size_t num_diagonals = A.values.num_cols;
#pragma omp parallel for
for (size_t ch = 0; ch < A.num_cols; ch += DIA_CHUNKSIZE) {
// initialize chunk
for (size_t row = ch; row < std::min(ch+DIA_CHUNKSIZE,A.num_cols); row++)
{
y[row] = initialize(y[row]);
}
// for each diagonal
for (size_t d = 0; d < num_diagonals; d++)
{
for (IndexType row=ch; row<std::min(ch+DIA_CHUNKSIZE,A.num_cols); row++)
{
const IndexType col = row - A.diagonal_offsets[d];
if (col >= 0 && col < A.num_rows)
{
y[row] = reduce(y[row], combine(A.values(col, d), x[col]));
}
}
}
}
}
template <typename Matrix,
typename Vector1,
typename Vector2>
void transposed_spmv_dia(const Matrix& A,
const Vector1& x,
Vector2& y)
{
typedef typename Vector2::value_type ValueType;
transposed_spmv_dia(A, x, y,
cusp::detail::zero_function<ValueType>(),
thrust::multiplies<ValueType>(),
thrust::plus<ValueType>());
}
template <typename Matrix,
typename Vector1,
typename Vector2,
typename UnaryFunction,
typename BinaryFunction1,
typename BinaryFunction2>
void transposed_spmv_cds(const Matrix& A,
const Vector1& x,
Vector2& y,
UnaryFunction initialize,
BinaryFunction1 combine,
BinaryFunction2 reduce)
{
typedef typename Matrix::index_type IndexType;
typedef typename Vector2::value_type ValueType;
const IndexType num_diagonals = A.diagonal_offsets.size();
const IndexType block_size = (IndexType)A.block_size;
const IndexType num_cols = (IndexType)A.num_cols;
// make chunksize a multiple of block_size
const IndexType chunksize = block_size*(DIA_CHUNKSIZE/block_size);
// optimisation for special case
if (block_size == 2) {
#pragma omp parallel for
for (IndexType ch = 0; ch < num_cols; ch += chunksize) {
for (IndexType row = ch; row < std::min(ch+chunksize,num_cols); row+=2)
{
ValueType sum1 = initialize(y[row]);
ValueType sum2 = initialize(y[row+1]);
// for each diagonal block
for (IndexType d = 0; d < num_diagonals; d++)
{
const IndexType col = row - A.diagonal_offsets[d]*2;
if (col >= 0 && col < A.num_rows)
{
sum1 = reduce(sum1, combine(A.values(col, 2*d), x[col]));
sum2 = reduce(sum2, combine(A.values(col, 2*d+1),x[col]));
sum1 = reduce(sum1, combine(A.values(col+1, 2*d), x[col+1]));
sum2 = reduce(sum2, combine(A.values(col+1, 2*d+1),x[col+1]));
}
}
y[row] = sum1;
y[row+1] = sum2;
}
}
} else { // block_size!=2
#pragma omp parallel for
for (IndexType ch = 0; ch < num_cols; ch += chunksize) {
for (IndexType row = ch; row < std::min(ch+chunksize,num_cols); row++)
{
y[row] = initialize(y[row]);
// for each diagonal block
for (IndexType d = 0; d < num_diagonals; d++)
{
const IndexType k = A.diagonal_offsets[d]*block_size;
const IndexType col = block_size*(row/block_size) - k;
if (col >= 0 && col <= A.num_rows-block_size)
{
// for each column in block
for (IndexType i = 0; i < block_size; i++)
{
const ValueType& Aij = A.values(col+i, d*block_size+row%block_size);
const ValueType& xj = x[col + i];
y[row] = reduce(y[row], combine(Aij, xj));
}
}
} // diagonals
} // rows
} // chunks
} // block_size
}
template <typename Matrix,
typename Vector1,
typename Vector2>
void transposed_spmv_cds(const Matrix& A,
const Vector1& x,
Vector2& y)
{
typedef typename Vector2::value_type ValueType;
if (A.block_size == 1) {
transposed_spmv_dia(A, x, y,
cusp::detail::zero_function<ValueType>(),
thrust::multiplies<ValueType>(),
thrust::plus<ValueType>());
} else {
transposed_spmv_cds(A, x, y,
cusp::detail::zero_function<ValueType>(),
thrust::multiplies<ValueType>(),
thrust::plus<ValueType>());
}
}
} // end namespace host
} // end namespace detail
} // end namespace cusp
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