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Apply .clangformat to all repo source files

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Change-Id: I7e79c6058f0303f9a98911e3b7dd2e8596079344
Esse commit está contido em:
Maneesh Gupta
2018-03-12 11:29:03 +05:30
pai 18e70b1e6b
commit 1ba06f63c4
293 arquivos alterados com 43980 adições e 45830 exclusões
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samples/2_Cookbook/3_shared_memory/sharedMemory.cpp
+69 -82
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@@ -20,28 +20,24 @@ OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
THE SOFTWARE.
*/
#include<iostream>
#include <iostream>
// hip header file
#include "hip/hip_runtime.h"
#define WIDTH 64
#define WIDTH 64
#define NUM (WIDTH*WIDTH)
#define NUM (WIDTH * WIDTH)
#define THREADS_PER_BLOCK_X 4
#define THREADS_PER_BLOCK_Y 4
#define THREADS_PER_BLOCK_Z 1
#define THREADS_PER_BLOCK_X 4
#define THREADS_PER_BLOCK_Y 4
#define THREADS_PER_BLOCK_Z 1
// Device (Kernel) function, it must be void
// hipLaunchParm provides the execution configuration
__global__ void matrixTranspose(hipLaunchParm lp,
float *out,
float *in,
const int width)
{
__shared__ float sharedMem[WIDTH*WIDTH];
__global__ void matrixTranspose(hipLaunchParm lp, float* out, float* in, const int width) {
__shared__ float sharedMem[WIDTH * WIDTH];
int x = hipBlockDim_x * hipBlockIdx_x + hipThreadIdx_x;
int y = hipBlockDim_y * hipBlockIdx_y + hipThreadIdx_y;
@@ -54,89 +50,80 @@ __global__ void matrixTranspose(hipLaunchParm lp,
}
// CPU implementation of matrix transpose
void matrixTransposeCPUReference(
float * output,
float * input,
const unsigned int width)
{
for(unsigned int j=0; j < width; j++)
{
for(unsigned int i=0; i < width; i++)
{
output[i*width + j] = input[j*width + i];
void matrixTransposeCPUReference(float* output, float* input, const unsigned int width) {
for (unsigned int j = 0; j < width; j++) {
for (unsigned int i = 0; i < width; i++) {
output[i * width + j] = input[j * width + i];
}
}
}
int main() {
float* Matrix;
float* TransposeMatrix;
float* cpuTransposeMatrix;
float* Matrix;
float* TransposeMatrix;
float* cpuTransposeMatrix;
float* gpuMatrix;
float* gpuTransposeMatrix;
float* gpuMatrix;
float* gpuTransposeMatrix;
hipDeviceProp_t devProp;
hipGetDeviceProperties(&devProp, 0);
hipDeviceProp_t devProp;
hipGetDeviceProperties(&devProp, 0);
std::cout << "Device name " << devProp.name << std::endl;
std::cout << "Device name " << devProp.name << std::endl;
int i;
int errors;
int i;
int errors;
Matrix = (float*)malloc(NUM * sizeof(float));
TransposeMatrix = (float*)malloc(NUM * sizeof(float));
cpuTransposeMatrix = (float*)malloc(NUM * sizeof(float));
Matrix = (float*)malloc(NUM * sizeof(float));
TransposeMatrix = (float*)malloc(NUM * sizeof(float));
cpuTransposeMatrix = (float*)malloc(NUM * sizeof(float));
// initialize the input data
for (i = 0; i < NUM; i++) {
Matrix[i] = (float)i*10.0f;
}
// allocate the memory on the device side
hipMalloc((void**)&gpuMatrix, NUM * sizeof(float));
hipMalloc((void**)&gpuTransposeMatrix, NUM * sizeof(float));
// Memory transfer from host to device
hipMemcpy(gpuMatrix, Matrix, NUM*sizeof(float), hipMemcpyHostToDevice);
// Lauching kernel from host
hipLaunchKernel(matrixTranspose,
dim3(WIDTH/THREADS_PER_BLOCK_X, WIDTH/THREADS_PER_BLOCK_Y),
dim3(THREADS_PER_BLOCK_X, THREADS_PER_BLOCK_Y),
0, 0,
gpuTransposeMatrix , gpuMatrix, WIDTH);
// Memory transfer from device to host
hipMemcpy(TransposeMatrix, gpuTransposeMatrix, NUM*sizeof(float), hipMemcpyDeviceToHost);
// CPU MatrixTranspose computation
matrixTransposeCPUReference(cpuTransposeMatrix, Matrix, WIDTH);
// verify the results
errors = 0;
double eps = 1.0E-6;
for (i = 0; i < NUM; i++) {
if (std::abs(TransposeMatrix[i] - cpuTransposeMatrix[i]) > eps ) {
printf("%d cpu: %f gpu %f\n",i,cpuTransposeMatrix[i],TransposeMatrix[i]);
errors++;
// initialize the input data
for (i = 0; i < NUM; i++) {
Matrix[i] = (float)i * 10.0f;
}
}
if (errors!=0) {
printf("FAILED: %d errors\n",errors);
} else {
printf ("PASSED!\n");
}
//free the resources on device side
hipFree(gpuMatrix);
hipFree(gpuTransposeMatrix);
// allocate the memory on the device side
hipMalloc((void**)&gpuMatrix, NUM * sizeof(float));
hipMalloc((void**)&gpuTransposeMatrix, NUM * sizeof(float));
//free the resources on host side
free(Matrix);
free(TransposeMatrix);
free(cpuTransposeMatrix);
// Memory transfer from host to device
hipMemcpy(gpuMatrix, Matrix, NUM * sizeof(float), hipMemcpyHostToDevice);
return errors;
// Lauching kernel from host
hipLaunchKernel(matrixTranspose, dim3(WIDTH / THREADS_PER_BLOCK_X, WIDTH / THREADS_PER_BLOCK_Y),
dim3(THREADS_PER_BLOCK_X, THREADS_PER_BLOCK_Y), 0, 0, gpuTransposeMatrix,
gpuMatrix, WIDTH);
// Memory transfer from device to host
hipMemcpy(TransposeMatrix, gpuTransposeMatrix, NUM * sizeof(float), hipMemcpyDeviceToHost);
// CPU MatrixTranspose computation
matrixTransposeCPUReference(cpuTransposeMatrix, Matrix, WIDTH);
// verify the results
errors = 0;
double eps = 1.0E-6;
for (i = 0; i < NUM; i++) {
if (std::abs(TransposeMatrix[i] - cpuTransposeMatrix[i]) > eps) {
printf("%d cpu: %f gpu %f\n", i, cpuTransposeMatrix[i], TransposeMatrix[i]);
errors++;
}
}
if (errors != 0) {
printf("FAILED: %d errors\n", errors);
} else {
printf("PASSED!\n");
}
// free the resources on device side
hipFree(gpuMatrix);
hipFree(gpuTransposeMatrix);
// free the resources on host side
free(Matrix);
free(TransposeMatrix);
free(cpuTransposeMatrix);
return errors;
}