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/*
* Copyright 2008-2009 NVIDIA Corporation
*
* 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.
*/
#ifndef __DENSE_H__
#define __DENSE_H__
// Simplified BLAS routines and other dense linear algebra functions
/*
* Level 1
*/
// y += a*x
template <class I, class T>
void axpy(const I n, const T a, const T * x, T * y){
for(I i = 0; i < n; i++){
y[i] += a * x[i];
}
}
// scale a vector in-place
template <class I, class T>
void scal(const I n, const T a, T * x){
for(I i = 0; i < n; i++){
x[i] *= a;
}
}
// dot product
template <class I, class T>
void dot(const I n, const T * x, const T * y){
T dp = 0;
for(I i = 0; i < n; i++){
dp += x[i] * y[i];
}
return dp;
}
// vectorize a binary operation
template<class I, class T, class binary_operator>
void vector_binop(const I n, const T * x, const T * y, T * z,
const binary_operator& op)
{
for(I i = 0; i < n; i++){
z[i] = op(x[i],y[i]);
}
}
//template<class I, class T>
//void vector_multiply(const I n, const T * x, const T * y, T * z){
//{
// vector_binop(n,x,y,z, std::multiplies<T>() );
//}
// Level 2
template <class I, class T>
void gemv(const I m, const I n, const T * A, const T * x, T * y){
for(I i = 0; i < m; i++){
T dot = y[i];
for(I j = 0; j < n; j++){
dot += A[n * i + j] * x[j];
}
y[i] = dot;
}
}
// Level 3
template <class I, class T>
void gemm(const I m, const I n, const I k, const T * A, const T * B, T * C){
for(I i = 0; i < m; i++){
for(I j = 0; j < n; j++){
T dot = C[n * i + j];
for(I _d = 0; _d < k; _d++){
dot += A[k * i + _d] * B[n * _d + j];
}
C[n * i + j] = dot;
}
}
}
#endif
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