-
Notifications
You must be signed in to change notification settings - Fork 0
/
mp2.cu
99 lines (84 loc) · 4.16 KB
/
mp2.cu
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
#include <wb.h>
#define wbCheck(stmt) \
do { \
cudaError_t err = stmt; \
if (err != cudaSuccess) { \
wbLog(ERROR, "Failed to run stmt ", #stmt); \
wbLog(ERROR, "Got CUDA error ... ", cudaGetErrorString(err)); \
return -1; \
} \
} while (0)
#define TILE_WIDTH 16
// Compute C = A * B
__global__ void matrixMultiply(float *A, float *B, float *C, int numARows,
int numAColumns, int numBRows, int numBColumns,
int numCRows, int numCColumns) {
//@@ Insert code to implement matrix multiplication here
int r = blockIdx.y * blockDim.y + threadIdx.y, c = blockIdx.x * blockDim.x + threadIdx.x;
if(r >= numCRows || c >= numCColumns) return;
for(int i = 0; i < numAColumns; i++)
C[r * numCColumns + c] += A[r * numAColumns + i] * B[i * numBColumns + c];
}
int main(int argc, char **argv) {
wbArg_t args;
float *hostA; // The A matrix
float *hostB; // The B matrix
float *hostC; // The output C matrix
float *deviceA;
float *deviceB;
float *deviceC;
int numARows; // number of rows in the matrix A
int numAColumns; // number of columns in the matrix A
int numBRows; // number of rows in the matrix B
int numBColumns; // number of columns in the matrix B
int numCRows; // number of rows in the matrix C (you have to set this)
int numCColumns; // number of columns in the matrix C (you have to set this)
args = wbArg_read(argc, argv);
wbTime_start(Generic, "Importing data and creating memory on host");
hostA =
( float * )wbImport(wbArg_getInputFile(args, 0), &numARows, &numAColumns);
hostB =
( float * )wbImport(wbArg_getInputFile(args, 1), &numBRows, &numBColumns);
//@@ Set numCRows and numCColumns
numCRows = numARows;
numCColumns = numBColumns;
//@@ Allocate the hostC matrix
int aSize = numARows * numAColumns * sizeof(float), bSize = numBRows * numBColumns * sizeof(float), cSize = numCRows * numCColumns * sizeof(float);
hostC = ( float * )malloc(cSize);
wbTime_stop(Generic, "Importing data and creating memory on host");
wbLog(TRACE, "The dimensions of A are ", numARows, " x ", numAColumns);
wbLog(TRACE, "The dimensions of B are ", numBRows, " x ", numBColumns);
wbLog(TRACE, "The dimensions of C are ", numCRows, " x ", numCColumns);
wbTime_start(GPU, "Allocating GPU memory.");
//@@ Allocate GPU memory here
cudaMalloc((void **) &deviceA, aSize);
cudaMalloc((void **) &deviceB, bSize);
cudaMalloc((void **) &deviceC, cSize);
wbTime_stop(GPU, "Allocating GPU memory.");
wbTime_start(GPU, "Copying input memory to the GPU.");
//@@ Copy memory to the GPU here
cudaMemcpy(deviceA, hostA, aSize, cudaMemcpyHostToDevice);
cudaMemcpy(deviceB, hostB, bSize, cudaMemcpyHostToDevice);
wbTime_stop(GPU, "Copying input memory to the GPU.");
//@@ Initialize the grid and block dimensions here
dim3 dimGrid((numCColumns - 1) / TILE_WIDTH + 1, (numCRows - 1) / TILE_WIDTH + 1, 1);
dim3 dimBlock(TILE_WIDTH, TILE_WIDTH, 1);
wbTime_start(Compute, "Performing CUDA computation");
//@@ Launch the GPU Kernel here
matrixMultiply<<<dimGrid, dimBlock>>>(deviceA, deviceB, deviceC, numARows, numAColumns, numBRows, numBColumns, numCRows, numCColumns);
cudaDeviceSynchronize();
wbTime_stop(Compute, "Performing CUDA computation");
wbTime_start(Copy, "Copying output memory to the CPU");
//@@ Copy the GPU memory back to the CPU here
cudaMemcpy(hostC, deviceC, cSize, cudaMemcpyDeviceToHost);
wbTime_stop(Copy, "Copying output memory to the CPU");
wbTime_start(GPU, "Freeing GPU Memory");
//@@ Free the GPU memory here
cudaFree(deviceA); cudaFree(deviceB); cudaFree(deviceC);
wbTime_stop(GPU, "Freeing GPU Memory");
wbSolution(args, hostC, numCRows, numCColumns);
free(hostA);
free(hostB);
free(hostC);
return 0;
}