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CudaVector.cu
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246 lines (193 loc) · 5.75 KB
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#pragma once
#include <cuda.h>
#include <cuda_runtime.h>
#include <cuda_runtime_api.h>
#include "CudaVector.h"
/**
* Kernel Functions
*/
template <class T>
__global__ void add(T* a, T* b, T* c, unsigned long n) {
unsigned long index = threadIdx.x + blockIdx.x * blockDim.x;
if (index < n) c[index] = a[index] + b[index];
}
template <class T>
__global__ void subtract(T* a, T* b, T* c, unsigned long n) {
unsigned long index = threadIdx.x + blockIdx.x * blockDim.x;
if (index < n) c[index] = a[index] - b[index];
}
template <class T>
__global__ void dotProduct(T* a, T* b, T* c, unsigned long n) {
unsigned long index = threadIdx.x + blockIdx.x * blockDim.x;
if (index < n) c[index] = a[index] * b[index];
}
template <class T>
__global__ void constantMultiply(T* a, double b, T* c, unsigned long n) {
unsigned long index = threadIdx.x + blockIdx.x * blockDim.x;
if (index < n) c[index] = a[index] * b;
}
template <class T>
__global__ void contantDivide(T* a, double b, T* c, unsigned long n) {
unsigned long index = threadIdx.x + blockIdx.x * blockDim.x;
if (index < n) c[index] = a[index] / b;
}
/** =================
* Class definitions
* =================
*/
/**
* Creates CudaVector object and sets the size
*/
template <class T>
CudaVector<T>::CudaVector(unsigned long size) {
this->_array = new T[size];
this->_size = size;
}
/**
* Free up memory
*/
template <class T>
CudaVector<T>::~CudaVector() {
delete[] _array;
}
/**
* Adds vector in GPU
*
* Returns CudaVector object
*/
template <class T>
CudaVector<T> CudaVector<T>::operator+(const CudaVector<T>& a) {
if (this->_size != a._size)
throw CudaVectorException("Vector size not same!");
// create result array
CudaVector<T> result(this->_size);
T *d_a, *d_b, *d_c;
const size_t size = this->_size * sizeof(T);
// allocate memory
cudaMalloc((void**)&d_a, size);
cudaMalloc((void**)&d_b, size);
cudaMalloc((void**)&d_c, size);
// copy memory to device
cudaMemcpy(d_a, this->_array, size, cudaMemcpyHostToDevice);
cudaMemcpy(d_b, a._array, size, cudaMemcpyHostToDevice);
add<<<NUM_BLOCKS, NUM_THREADS_PER_BLOCK>>>(d_a, d_b, d_c, this->_size);
// copy to host
cudaMemcpy(result._array, d_c, size, cudaMemcpyDeviceToHost);
return result;
}
/**
* Subtract vector in GPU
*
* Returns CudaVector object
*/
template <class T>
CudaVector<T> CudaVector<T>::operator-(const CudaVector<T>& a) {
if (this->_size != a._size)
throw CudaVectorException("Vector size not same!");
// create result array
CudaVector<T> result(this->_size);
T *d_a, *d_b, *d_c;
const size_t size = this->_size * sizeof(T);
// allocate memory
cudaMalloc((void**)&d_a, size);
cudaMalloc((void**)&d_b, size);
cudaMalloc((void**)&d_c, size);
// copy memory to device
cudaMemcpy(d_a, this->_array, size, cudaMemcpyHostToDevice);
cudaMemcpy(d_b, a._array, size, cudaMemcpyHostToDevice);
subtract<<<NUM_BLOCKS, NUM_THREADS_PER_BLOCK>>>(d_a, d_b, d_c, this->_size);
// copy to host
cudaMemcpy(result._array, d_c, size, cudaMemcpyDeviceToHost);
return result;
}
/**
* Dot Product vector in GPU
*
* Returns CudaVector object
*/
template <class T>
CudaVector<T> CudaVector<T>::operator*(const CudaVector<T>& a) {
if (this->_size != a._size)
throw CudaVectorException("Vector size not same!");
// create result array
CudaVector<T> result(this->_size);
T *d_a, *d_b, *d_c;
const size_t size = this->_size * sizeof(T);
// allocate memory
cudaMalloc((void**)&d_a, size);
cudaMalloc((void**)&d_b, size);
cudaMalloc((void**)&d_c, size);
// copy memory to device
cudaMemcpy(d_a, this->_array, size, cudaMemcpyHostToDevice);
cudaMemcpy(d_b, a._array, size, cudaMemcpyHostToDevice);
dotProduct<<<NUM_BLOCKS, NUM_THREADS_PER_BLOCK>>>(d_a, d_b, d_c, this->_size);
// copy to host
cudaMemcpy(result._array, d_c, size, cudaMemcpyDeviceToHost);
return result;
}
/**
* Constant Multiplication of vector in GPU
*
* Returns CudaVector object
*/
template <class T>
CudaVector<T> CudaVector<T>::operator*(const double& a) {
// create result array
CudaVector<T> result(this->_size);
T *d_a, *d_c;
const size_t size = this->_size * sizeof(T);
// allocate memory
cudaMalloc((void**)&d_a, size);
cudaMalloc((void**)&d_c, size);
// copy memory to device
cudaMemcpy(d_a, this->_array, size, cudaMemcpyHostToDevice);
constantMultiply<<<NUM_BLOCKS, NUM_THREADS_PER_BLOCK>>>(d_a, a, d_c,
this->_size);
// copy to host
cudaMemcpy(result._array, d_c, size, cudaMemcpyDeviceToHost);
return result;
}
/**
* Constant Division of vector in GPU
*
* Returns CudaVector object
*/
template <class T>
CudaVector<T> CudaVector<T>::operator/(const double& a) {
// create result array
CudaVector<T> result(this->_size);
T *d_a, *d_c;
const size_t size = this->_size * sizeof(T);
// allocate memory
cudaMalloc((void**)&d_a, size);
cudaMalloc((void**)&d_c, size);
// copy memory to device
cudaMemcpy(d_a, this->_array, size, cudaMemcpyHostToDevice);
contantDivide<<<NUM_BLOCKS, NUM_THREADS_PER_BLOCK>>>(d_a, a, d_c,
this->_size);
// copy to host
cudaMemcpy(result._array, d_c, size, cudaMemcpyDeviceToHost);
return result;
}
/**
* Subscript operator overloading
*
* Returns CudaVector object
*/
template <class T>
T& CudaVector<T>::operator[](unsigned long i) {
if (i > this->_size || i < 0)
throw CudaVectorException("Index out of bounds!");
return this->_array[i];
}
template <class T>
unsigned long CudaVector<T>::size() {
return this->_size;
}
/**
* Exception Class definition
*/
template <class T>
CudaVector<T>::CudaVectorException::CudaVectorException(
const std::string& message)
: message_(message) {}