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41a1a62
Proj1 finished
DiracSea3921 Sep 21, 2014
e627f06
Performence Anlysis Update
DiracSea3921 Sep 21, 2014
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14 changes: 14 additions & 0 deletions Part1/PROJ_WIN/CIS565_PROJ_1.sln
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Expand Up @@ -3,16 +3,30 @@ Microsoft Visual Studio Solution File, Format Version 11.00
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4 changes: 2 additions & 2 deletions Part1/PROJ_WIN/CIS565_PROJ_1/CIS565_PROJ_1.vcxproj
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Expand Up @@ -30,7 +30,7 @@
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Expand Down Expand Up @@ -114,6 +114,6 @@
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156 changes: 156 additions & 0 deletions Part1/PROJ_WIN/Matrix/Matrix.vcxproj
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158 changes: 158 additions & 0 deletions Part1/PROJ_WIN/Matrix/kernel.cu
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#include "cuda_runtime.h"
#include "device_launch_parameters.h"

#include <stdio.h>


__global__ void mat_add(const float *m1, const float *m2, float *m3)
{
int i = threadIdx.x;
m3[i] = m2[i] + m1[i];
}

__global__ void mat_sub(const float *m1, const float *m2, float *m3)
{
int i = threadIdx.x;
m3[i] = m1[i] - m2[i];
}

__global__ void mat_mult(const float *m1, const float *m2, float *m3, int matrix_size)
{
int i = threadIdx.x;
int row = i / matrix_size;
int column = i - (i / matrix_size) * matrix_size;

m3[i] = 0;
for(int j=0; j<matrix_size; j++)
{
m3[i] += m1[row * matrix_size + j] * m2[j * matrix_size + column];
}

}

void mat_add_serial(const float *m1, const float *m2, float *m3, int matrix_size)
{
for(int i=0; i< matrix_size * matrix_size; i++)
m3[i] = m2[i] + m1[i];
}

void mat_sub_serial(const float *m1, const float *m2, float *m3, int matrix_size)
{
for(int i=0; i< matrix_size * matrix_size; i++)
m3[i] = m1[i] - m2[i];
}

void mat_mult_serial(const float *m1, const float *m2, float *m3, int matrix_size)
{
for(int i=0; i< matrix_size * matrix_size; i++){
int row = i / matrix_size;
int column = i - (i / matrix_size) * matrix_size;

m3[i] = 0;
for(int j=0; j<matrix_size; j++)
{
m3[i] += m1[row * matrix_size + j] * m2[j * matrix_size + column];
}
}
}

int main()
{
const int matrix_width = 5;
const int matrix_height = 5;
const float m1[matrix_width * matrix_height] = {0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24};
const float m2[matrix_width * matrix_height] = {0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24};
float m3[matrix_width * matrix_height] = {0};

cudaError_t cudaStatus;
cudaStatus = cudaSetDevice(0);
if (cudaStatus != cudaSuccess) {
fprintf(stderr, "cudaSetDevice failed! Do you have a CUDA-capable GPU installed?");
}

float *dev_m1 = 0;
float *dev_m2 = 0;
float *dev_m3 = 0;
// Allocate GPU buffers for three vectors (two input, one output) .
cudaStatus = cudaMalloc((void**)&dev_m1, matrix_width * matrix_height * sizeof(float));
if (cudaStatus != cudaSuccess) {
fprintf(stderr, "cudaMalloc failed!");
}

cudaStatus = cudaMalloc((void**)&dev_m2, matrix_width * matrix_height * sizeof(float));
if (cudaStatus != cudaSuccess) {
fprintf(stderr, "cudaMalloc failed!");
}

cudaStatus = cudaMalloc((void**)&dev_m3, matrix_width * matrix_height * sizeof(float));
if (cudaStatus != cudaSuccess) {
fprintf(stderr, "cudaMalloc failed!");
}

// Copy input vectors from host memory to GPU buffers.
cudaStatus = cudaMemcpy(dev_m1, m1, matrix_width * matrix_height * sizeof(float), cudaMemcpyHostToDevice);
if (cudaStatus != cudaSuccess) {
fprintf(stderr, "cudaMemcpy failed!");
}

cudaStatus = cudaMemcpy(dev_m2, m2, matrix_width * matrix_height * sizeof(float), cudaMemcpyHostToDevice);
if (cudaStatus != cudaSuccess) {
fprintf(stderr, "cudaMemcpy failed!");
}

// add
mat_add<<<1, matrix_width * matrix_height>>>(dev_m1, dev_m2, dev_m3);
cudaDeviceSynchronize();
cudaMemcpy(m3, dev_m3, matrix_width * matrix_height * sizeof(float), cudaMemcpyDeviceToHost);

for(int i=0;i<matrix_height;i++)
printf("{%.0f,%.0f,%.0f,%.0f,%.0f}\n",m3[i*matrix_width], m3[i*matrix_width+1], m3[i*matrix_width+2], m3[i*matrix_width+3], m3[i*matrix_width+4]);
printf("\n");

// sub
mat_sub<<<1, matrix_width * matrix_height>>>(dev_m1, dev_m2, dev_m3);
cudaDeviceSynchronize();
cudaMemcpy(m3, dev_m3, matrix_width * matrix_height * sizeof(float), cudaMemcpyDeviceToHost);

for(int i=0;i<matrix_height;i++)
printf("{%.0f,%.0f,%.0f,%.0f,%.0f}\n",m3[i*matrix_width], m3[i*matrix_width+1], m3[i*matrix_width+2], m3[i*matrix_width+3], m3[i*matrix_width+4]);
printf("\n");

//mult
mat_mult<<<1, matrix_width * matrix_height>>>(dev_m1, dev_m2, dev_m3,matrix_width);
cudaDeviceSynchronize();
cudaStatus = cudaMemcpy(m3, dev_m3, matrix_width * matrix_height * sizeof(float), cudaMemcpyDeviceToHost);

for(int i=0;i<matrix_height;i++)
printf("{%.0f,%.0f,%.0f,%.0f,%.0f}\n",m3[i*matrix_width], m3[i*matrix_width+1], m3[i*matrix_width+2], m3[i*matrix_width+3], m3[i*matrix_width+4]);
printf("\n");

// Check for any errors launching the kernel
cudaStatus = cudaGetLastError();
if (cudaStatus != cudaSuccess) {
fprintf(stderr, "addKernel launch failed: %s\n", cudaGetErrorString(cudaStatus));
}



cudaFree(dev_m1);
cudaFree(dev_m2);
cudaFree(dev_m3);

// Add vectors in parallel.
if (cudaStatus != cudaSuccess) {
fprintf(stderr, "addWithCuda failed!");
return 1;
}

// cudaDeviceReset must be called before exiting in order for profiling and
// tracing tools such as Nsight and Visual Profiler to show complete traces.
cudaStatus = cudaDeviceReset();
if (cudaStatus != cudaSuccess) {
fprintf(stderr, "cudaDeviceReset failed!");
return 1;
}

return 0;
}
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