Istvan Kiss
197f73dac9
* Add examples to tools folder * Correct P2P memory access section * Sync poriting guide * Add HIP Graph tutorial * Add hint about using amdgpu-dkms for IPC API * Add a few more env variables
111 рядки
3.2 KiB
Plaintext
111 рядки
3.2 KiB
Plaintext
// MIT License
|
|
//
|
|
// Copyright (c) 2025 Advanced Micro Devices, Inc. All rights reserved.
|
|
//
|
|
// Permission is hereby granted, free of charge, to any person obtaining a copy
|
|
// of this software and associated documentation files (the "Software"), to deal
|
|
// in the Software without restriction, including without limitation the rights
|
|
// to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
|
|
// copies of the Software, and to permit persons to whom the Software is
|
|
// furnished to do so, subject to the following conditions:
|
|
//
|
|
// The above copyright notice and this permission notice shall be included in all
|
|
// copies or substantial portions of the Software.
|
|
//
|
|
// THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
|
|
// IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
|
|
// FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
|
|
// AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
|
|
// LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
|
|
// OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
|
|
// SOFTWARE.
|
|
|
|
// [sphinx-start]
|
|
#include <cuda_runtime.h>
|
|
|
|
#include <iostream>
|
|
#include <vector>
|
|
|
|
__global__ void block_reduction(const float* input, float* output, int num_elements)
|
|
{
|
|
extern __shared__ float s_data[];
|
|
|
|
int tid = threadIdx.x;
|
|
int global_id = blockDim.x * blockIdx.x + tid;
|
|
|
|
if (global_id < num_elements)
|
|
{
|
|
s_data[tid] = input[global_id];
|
|
}
|
|
else
|
|
{
|
|
s_data[tid] = 0.0f;
|
|
}
|
|
__syncthreads();
|
|
|
|
for (int stride = blockDim.x / 2; stride > 0; stride >>= 1)
|
|
{
|
|
if (tid < stride)
|
|
{
|
|
s_data[tid] += s_data[tid + stride];
|
|
}
|
|
__syncthreads();
|
|
}
|
|
|
|
if (tid == 0)
|
|
{
|
|
output[blockIdx.x] = s_data[0];
|
|
}
|
|
}
|
|
|
|
int main()
|
|
{
|
|
int threads = 256;
|
|
const int num_elements = 50000;
|
|
|
|
std::vector<float> h_a(num_elements);
|
|
std::vector<float> h_b((num_elements + threads - 1) / threads);
|
|
|
|
for (int i = 0; i < num_elements; ++i)
|
|
{
|
|
h_a[i] = rand() / static_cast<float>(RAND_MAX);
|
|
}
|
|
|
|
float *d_a, *d_b;
|
|
cudaMalloc(&d_a, h_a.size() * sizeof(float));
|
|
cudaMalloc(&d_b, h_b.size() * sizeof(float));
|
|
|
|
cudaStream_t stream;
|
|
cudaStreamCreateWithFlags(&stream, cudaStreamNonBlocking);
|
|
|
|
cudaEvent_t start_event, stop_event;
|
|
cudaEventCreate(&start_event);
|
|
cudaEventCreate(&stop_event);
|
|
|
|
cudaMemcpyAsync(d_a, h_a.data(), h_a.size() * sizeof(float), cudaMemcpyHostToDevice, stream);
|
|
|
|
cudaEventRecord(start_event, stream);
|
|
|
|
int blocks = (num_elements + threads - 1) / threads;
|
|
block_reduction<<<blocks, threads, threads * sizeof(float), stream>>>(d_a, d_b, num_elements);
|
|
|
|
cudaMemcpyAsync(h_b.data(), d_b, h_b.size() * sizeof(float), cudaMemcpyDeviceToHost, stream);
|
|
|
|
cudaEventRecord(stop_event, stream);
|
|
cudaEventSynchronize(stop_event);
|
|
|
|
float milliseconds = 0.f;
|
|
cudaEventElapsedTime(&milliseconds, start_event, stop_event);
|
|
std::cout << "Kernel execution time: " << milliseconds << " ms\n";
|
|
|
|
cudaFree(d_a);
|
|
cudaFree(d_b);
|
|
|
|
cudaEventDestroy(start_event);
|
|
cudaEventDestroy(stop_event);
|
|
cudaStreamDestroy(stream);
|
|
|
|
return 0;
|
|
}
|
|
// [sphinx-end]
|