mirror of
https://github.com/NVIDIA/cuda-samples.git
synced 2026-10-25 22:28:17 +08:00
Apply consistent code formatting across the repo. Add clang-format and pre-commit hooks.
This commit is contained in:
Rob Armstrong
@@ -29,9 +29,9 @@
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* This is a simple test showing performance and usability
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* improvements with large kernel parameters introduced in CUDA 12.1
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*/
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#include <cassert>
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#include <chrono>
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#include <iostream>
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#include <cassert>
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// Utility includes
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#include <helper_cuda.h>
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@@ -40,134 +40,141 @@ using namespace std;
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using namespace std::chrono;
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#define TEST_ITERATIONS (1000)
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#define TOTAL_PARAMS (8000) // ints
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#define KERNEL_PARAM_LIMIT (1024) // ints
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#define TOTAL_PARAMS (8000) // ints
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#define KERNEL_PARAM_LIMIT (1024) // ints
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#define CONST_COPIED_PARAMS (TOTAL_PARAMS - KERNEL_PARAM_LIMIT)
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__constant__ int excess_params[CONST_COPIED_PARAMS];
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typedef struct {
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int param[KERNEL_PARAM_LIMIT];
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typedef struct
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{
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int param[KERNEL_PARAM_LIMIT];
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} param_t;
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typedef struct {
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int param[TOTAL_PARAMS];
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typedef struct
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{
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int param[TOTAL_PARAMS];
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} param_large_t;
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// Kernel with 4KB kernel parameter limit
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__global__ void kernelDefault(__grid_constant__ const param_t p, int *result) {
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int tmp = 0;
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__global__ void kernelDefault(__grid_constant__ const param_t p, int *result)
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{
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int tmp = 0;
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// accumulate kernel parameters
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for (int i = 0; i < KERNEL_PARAM_LIMIT; ++i) {
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tmp += p.param[i];
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}
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// accumulate kernel parameters
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for (int i = 0; i < KERNEL_PARAM_LIMIT; ++i) {
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tmp += p.param[i];
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}
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// accumulate excess values passed via const memory
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for (int i = 0; i < CONST_COPIED_PARAMS; ++i) {
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tmp += excess_params[i];
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}
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// accumulate excess values passed via const memory
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for (int i = 0; i < CONST_COPIED_PARAMS; ++i) {
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tmp += excess_params[i];
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}
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*result = tmp;
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*result = tmp;
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}
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// Kernel with 32,764 byte kernel parameter limit
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__global__ void kernelLargeParam(__grid_constant__ const param_large_t p, int *result) {
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int tmp = 0;
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__global__ void kernelLargeParam(__grid_constant__ const param_large_t p, int *result)
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{
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int tmp = 0;
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// accumulate kernel parameters
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for (int i = 0; i < TOTAL_PARAMS; ++i) {
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tmp += p.param[i];
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}
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// accumulate kernel parameters
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for (int i = 0; i < TOTAL_PARAMS; ++i) {
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tmp += p.param[i];
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}
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*result = tmp;
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*result = tmp;
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}
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static void report_time(std::chrono::time_point<std::chrono::steady_clock> start,
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std::chrono::time_point<std::chrono::steady_clock> end,
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int iters) {
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auto usecs = duration_cast<duration<float,
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microseconds::period>>(end - start);
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cout << usecs.count() / iters << endl;
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int iters)
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{
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auto usecs = duration_cast<duration<float, microseconds::period>>(end - start);
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cout << usecs.count() / iters << endl;
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}
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int main() {
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int rc;
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cudaFree(0);
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int main()
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{
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int rc;
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cudaFree(0);
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param_t p;
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param_large_t p_large;
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param_t p;
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param_large_t p_large;
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// pageable host memory that holds excess constants passed via constant memory
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int *copied_params = (int *)malloc(CONST_COPIED_PARAMS * sizeof(int));
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assert(copied_params);
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// pageable host memory that holds excess constants passed via constant memory
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int *copied_params = (int *)malloc(CONST_COPIED_PARAMS * sizeof(int));
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assert(copied_params);
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// storage for computed result
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int *d_result;
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int h_result;
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checkCudaErrors(cudaMalloc(&d_result, sizeof(int)));
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// storage for computed result
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int *d_result;
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int h_result;
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checkCudaErrors(cudaMalloc(&d_result, sizeof(int)));
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int expected_result = 0;
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int expected_result = 0;
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// fill in data for validation
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for (int i = 0; i < KERNEL_PARAM_LIMIT; ++i) {
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p.param[i] = (i & 0xFF);
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}
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for (int i = KERNEL_PARAM_LIMIT; i < TOTAL_PARAMS; ++i) {
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copied_params[i - KERNEL_PARAM_LIMIT] = (i & 0xFF);
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}
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for (int i = 0; i < TOTAL_PARAMS; ++i) {
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p_large.param[i] = (i & 0xFF);
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expected_result += (i & 0xFF);
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}
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// warmup, verify correctness
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checkCudaErrors(cudaMemcpyToSymbol(excess_params, copied_params, CONST_COPIED_PARAMS * sizeof(int), 0, cudaMemcpyHostToDevice));
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kernelDefault<<<1,1>>>(p, d_result);
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checkCudaErrors(cudaMemcpy(&h_result, d_result, sizeof(int), cudaMemcpyDeviceToHost));
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checkCudaErrors(cudaDeviceSynchronize());
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if(h_result != expected_result) {
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std::cout << "Test failed" << std::endl;
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rc=-1;
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goto Exit;
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}
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kernelLargeParam<<<1,1>>>(p_large, d_result);
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checkCudaErrors(cudaMemcpy(&h_result, d_result, sizeof(int), cudaMemcpyDeviceToHost));
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checkCudaErrors(cudaDeviceSynchronize());
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if(h_result != expected_result) {
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std::cout << "Test failed" << std::endl;
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rc=-1;
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goto Exit;
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}
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// benchmark default kernel parameter limit
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{
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auto start = steady_clock::now();
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for (int i = 0; i < TEST_ITERATIONS; ++i) {
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checkCudaErrors(cudaMemcpyToSymbol(excess_params, copied_params, CONST_COPIED_PARAMS * sizeof(int), 0, cudaMemcpyHostToDevice));
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kernelDefault<<<1, 1>>>(p, d_result);
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// fill in data for validation
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for (int i = 0; i < KERNEL_PARAM_LIMIT; ++i) {
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p.param[i] = (i & 0xFF);
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}
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for (int i = KERNEL_PARAM_LIMIT; i < TOTAL_PARAMS; ++i) {
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copied_params[i - KERNEL_PARAM_LIMIT] = (i & 0xFF);
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}
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for (int i = 0; i < TOTAL_PARAMS; ++i) {
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p_large.param[i] = (i & 0xFF);
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expected_result += (i & 0xFF);
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}
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checkCudaErrors(cudaDeviceSynchronize());
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auto end = steady_clock::now();
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std::cout << "Kernel 4KB parameter limit - time (us):";
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report_time(start, end, TEST_ITERATIONS);
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// benchmark large kernel parameter limit
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start = steady_clock::now();
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for (int i = 0; i < TEST_ITERATIONS; ++i) {
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kernelLargeParam<<<1, 1>>>(p_large, d_result);
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}
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// warmup, verify correctness
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checkCudaErrors(
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cudaMemcpyToSymbol(excess_params, copied_params, CONST_COPIED_PARAMS * sizeof(int), 0, cudaMemcpyHostToDevice));
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kernelDefault<<<1, 1>>>(p, d_result);
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checkCudaErrors(cudaMemcpy(&h_result, d_result, sizeof(int), cudaMemcpyDeviceToHost));
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checkCudaErrors(cudaDeviceSynchronize());
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end = steady_clock::now();
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std::cout << "Kernel 32,764 byte parameter limit - time (us):";
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report_time(start, end, TEST_ITERATIONS);
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}
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std::cout << "Test passed!" << std::endl;
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rc=0;
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if (h_result != expected_result) {
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std::cout << "Test failed" << std::endl;
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rc = -1;
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goto Exit;
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}
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kernelLargeParam<<<1, 1>>>(p_large, d_result);
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checkCudaErrors(cudaMemcpy(&h_result, d_result, sizeof(int), cudaMemcpyDeviceToHost));
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checkCudaErrors(cudaDeviceSynchronize());
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if (h_result != expected_result) {
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std::cout << "Test failed" << std::endl;
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rc = -1;
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goto Exit;
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}
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// benchmark default kernel parameter limit
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{
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auto start = steady_clock::now();
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for (int i = 0; i < TEST_ITERATIONS; ++i) {
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checkCudaErrors(cudaMemcpyToSymbol(
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excess_params, copied_params, CONST_COPIED_PARAMS * sizeof(int), 0, cudaMemcpyHostToDevice));
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kernelDefault<<<1, 1>>>(p, d_result);
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}
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checkCudaErrors(cudaDeviceSynchronize());
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auto end = steady_clock::now();
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std::cout << "Kernel 4KB parameter limit - time (us):";
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report_time(start, end, TEST_ITERATIONS);
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// benchmark large kernel parameter limit
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start = steady_clock::now();
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for (int i = 0; i < TEST_ITERATIONS; ++i) {
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kernelLargeParam<<<1, 1>>>(p_large, d_result);
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}
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checkCudaErrors(cudaDeviceSynchronize());
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end = steady_clock::now();
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std::cout << "Kernel 32,764 byte parameter limit - time (us):";
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report_time(start, end, TEST_ITERATIONS);
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}
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std::cout << "Test passed!" << std::endl;
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rc = 0;
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Exit:
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// cleanup
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cudaFree(d_result);
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free(copied_params);
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return rc;
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// cleanup
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cudaFree(d_result);
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free(copied_params);
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return rc;
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}
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