NASP/cuda-samples
35
0
Fork 0
mirror of https://github.com/NVIDIA/cuda-samples.git synced 2024-11-24 17:29:18 +08:00
Code Issues Packages Projects Releases Wiki Activity

conjugateGradientCudaGraphs: Add cusparseScsrmv & cublasSdot instead of

Browse Source 
gpuSpMV & gpuDotProduct as they are graph compliant
This commit is contained in:
Mahesh Doijade 2019-08-19 15:47:24 +05:30
parent c8483e0798
commit 489d9f7b1f
1 changed files with 5 additions and 75 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

80
Samples/conjugateGradientCudaGraphs/conjugateGradientCudaGraphs.cu
View File

@ -98,62 +98,6 @@ __global__ void initVectors(float *rhs, float *x, int N) {
}
}
__global__ void gpuDotProduct(float *vecA, float *vecB, float *result,
int size) {
cg::thread_block cta = cg::this_thread_block();
int gid = blockIdx.x * blockDim.x + threadIdx.x;
extern __shared__ double tmp[];
double temp_sum = 0.0;
for (int i = gid; i < size; i += gridDim.x * blockDim.x) {
temp_sum += (double)(vecA[i] * vecB[i]);
}
tmp[cta.thread_rank()] = temp_sum;
cg::sync(cta);
cg::thread_block_tile<32> tile32 = cg::tiled_partition<32>(cta);
double beta = temp_sum;
double temp;
for (int i = tile32.size() / 2; i > 0; i >>= 1) {
if (tile32.thread_rank() < i) {
temp = tmp[cta.thread_rank() + i];
beta += temp;
tmp[cta.thread_rank()] = beta;
}
cg::sync(tile32);
}
cg::sync(cta);
if (cta.thread_rank() == 0) {
beta = 0.0;
for (int i = 0; i < cta.size(); i += tile32.size()) {
beta += tmp[i];
}
atomicAdd(result, (float)beta);
}
}
__global__ void gpuSpMV(int *I, int *J, float *val, int nnz, int num_rows,
float alpha, float *inputVecX, float *outputVecY) {
size_t gid = blockIdx.x * blockDim.x + threadIdx.x;
for (size_t i = gid; i < num_rows; i += blockDim.x * gridDim.x) {
int row_elem = I[i];
int next_row_elem = I[i + 1];
int num_elems_this_row = next_row_elem - row_elem;
float output = 0.0;
for (int j = 0; j < num_elems_this_row; j++) {
output += alpha * val[row_elem + j] * inputVecX[J[row_elem + j]];
}
outputVecY[i] = output;
}
}
__global__ void r1_div_x(float *r1, float *r0, float *b) {
int gid = blockIdx.x * blockDim.x + threadIdx.x;
if (gid == 0) {
@ -255,7 +199,7 @@ int main(int argc, char **argv) {
checkCudaErrors(cusparseSetMatType(descr, CUSPARSE_MATRIX_TYPE_GENERAL));
checkCudaErrors(cusparseSetMatIndexBase(descr, CUSPARSE_INDEX_BASE_ZERO));
int numBlocks = 0, blockSize = 0, numBlocks2 = 0, blockSize2 = 0;
int numBlocks = 0, blockSize = 0;
checkCudaErrors(
cudaOccupancyMaxPotentialBlockSize(&numBlocks, &blockSize, initVectors));
@ -268,11 +212,6 @@ int main(int argc, char **argv) {
initVectors<<<numBlocks, blockSize, 0, stream1>>>(d_r, d_x, N);
checkCudaErrors(cudaOccupancyMaxPotentialBlockSize(&numBlocks2, &blockSize2,
gpuSpMV));
checkCudaErrors(cudaOccupancyMaxPotentialBlockSize(&numBlocks, &blockSize,
gpuDotProduct));
alpha = 1.0;
alpham1 = -1.0;
beta = 0.0;
@ -332,22 +271,14 @@ int main(int argc, char **argv) {
checkCudaErrors(cublasSaxpy(cublasHandle, N, &alpha, d_r, 1, d_p, 1));
cublasSetPointerMode(cublasHandle, CUBLAS_POINTER_MODE_DEVICE);
#if 0 // Use cusparseScsrmv API when it is cuda graph compliant
checkCudaErrors(
cusparseSetPointerMode(cusparseHandle, CUSPARSE_POINTER_MODE_HOST));
checkCudaErrors(
cusparseScsrmv(cusparseHandle, CUSPARSE_OPERATION_NON_TRANSPOSE, N, N, nz,
&alpha, descr, d_val, d_row, d_col, d_p, &beta, d_Ax));
#else
gpuSpMV<<<numBlocks2, blockSize2, 0, stream1>>>(d_row, d_col, d_val, nz,
N, alpha, d_p, d_Ax);
#endif
checkCudaErrors(cudaMemsetAsync(d_dot, 0, sizeof(float), stream1));
// Use cublasSdot API when it is cuda graph compliant.
// checkCudaErrors(cublasSdot(cublasHandle, N, d_p, 1, d_Ax, 1, d_dot));
gpuDotProduct<<<numBlocks, blockSize, blockSize * sizeof(double), stream1>>>(
d_p, d_Ax, d_dot, N);
checkCudaErrors(cublasSdot(cublasHandle, N, d_p, 1, d_Ax, 1, d_dot));
r1_div_x<<<1, 1, 0, stream1>>>(d_r1, d_dot, d_a);
@ -360,10 +291,9 @@ int main(int argc, char **argv) {
checkCudaErrors(cudaMemcpyAsync(d_r0, d_r1, sizeof(float),
cudaMemcpyDeviceToDevice, stream1));
checkCudaErrors(cudaMemsetAsync(d_r1, 0, sizeof(float), stream1));
// Use cublasSdot API when it is cuda graph compliant.
// checkCudaErrors(cublasSdot(cublasHandle, N, d_r, 1, d_r, 1, d_r1));
gpuDotProduct<<<numBlocks, blockSize, blockSize * sizeof(double), stream1>>>(
d_r, d_r, d_r1, N);
checkCudaErrors(cublasSdot(cublasHandle, N, d_r, 1, d_r, 1, d_r1));
checkCudaErrors(cudaMemcpyAsync((float *)&r1, d_r1, sizeof(float),
cudaMemcpyDeviceToHost, stream1));