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[sample] Add hipDispatchEnqueueRateMT (ROCm#1869)
* [sample] Add hipDispatchEnqueueRateMT
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samples/1_Utils/hipDispatchLatency/hipDispatchEnqueueRateMT.cpp
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/* | ||
Copyright (c) 2020-present 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. | ||
*/ | ||
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#include <stdio.h> | ||
#include "hip/hip_runtime.h" | ||
#ifdef __HIP_PLATFORM_HCC__ | ||
#include "hip/hip_ext.h" | ||
#endif | ||
#include <iostream> | ||
#include <chrono> | ||
#include <algorithm> | ||
#include <atomic> | ||
#include <thread> | ||
#include <future> | ||
#include <functional> | ||
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#define NUM_GROUPS 1 | ||
#define GROUP_SIZE 1 | ||
#define WARMUP_RUN_COUNT 10 | ||
#define TIMING_RUN_COUNT 100 | ||
#define TOTAL_RUN_COUNT WARMUP_RUN_COUNT + TIMING_RUN_COUNT | ||
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__global__ void EmptyKernel() {} | ||
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// Helper to print various timing metrics | ||
void print_timing(std::string test, std::array<float, TOTAL_RUN_COUNT> &results, int batch = 1) | ||
{ | ||
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float total_us = 0.0f, mean_us = 0.0f, stddev_us = 0.0f; | ||
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// remove top outliers due to nature of variability across large number of multi-threaded runs | ||
std::sort(results.begin(), results.end(), std::greater<float>()); | ||
auto start_iter = std::next(results.begin(), WARMUP_RUN_COUNT); | ||
auto end_iter = results.end(); | ||
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// mean | ||
std::for_each(start_iter, end_iter, [&](const float &run_ms) { | ||
total_us += (run_ms * 1000) / batch; | ||
}); | ||
mean_us = total_us / TIMING_RUN_COUNT; | ||
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// stddev | ||
total_us = 0; | ||
std::for_each(start_iter, end_iter, [&](const float &run_ms) { | ||
float dev_us = ((run_ms * 1000) / batch) - mean_us; | ||
total_us += dev_us * dev_us; | ||
}); | ||
stddev_us = sqrt(total_us / TIMING_RUN_COUNT); | ||
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printf("\n %s: %.1f us, std: %.1f us\n", test.c_str(), mean_us, stddev_us); | ||
} | ||
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// Measure time taken to enqueue a kernel on the GPU using hipModuleLaunchKernel | ||
void hipModuleLaunchKernel_enqueue_rate(std::atomic_int* shared, int max_threads) | ||
{ | ||
//resources necessary for this thread | ||
hipStream_t stream; | ||
hipStreamCreate(&stream); | ||
hipModule_t module; | ||
hipFunction_t function; | ||
hipModuleLoad(&module, "test_kernel.code"); | ||
hipModuleGetFunction(&function, module, "test"); | ||
void* kernel_params = nullptr; | ||
std::array<float, TOTAL_RUN_COUNT> results; | ||
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//synchronize all threads, before running | ||
int tid = shared->fetch_add(1, std::memory_order_release); | ||
while (max_threads != shared->load(std::memory_order_acquire)) {} | ||
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for (auto i = 0; i < TOTAL_RUN_COUNT; ++i) { | ||
auto start = std::chrono::high_resolution_clock::now(); | ||
hipModuleLaunchKernel(function, 1, 1, 1, 1, 1, 1, 0, stream, &kernel_params, nullptr); | ||
auto stop = std::chrono::high_resolution_clock::now(); | ||
results[i] = std::chrono::duration<double, std::milli>(stop - start).count(); | ||
} | ||
print_timing("Thread ID : " + std::to_string(tid) + " , " + "hipModuleLaunchKernel enqueue rate", results); | ||
} | ||
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// Measure time taken to enqueue a kernel on the GPU using hipLaunchKernelGGL | ||
void hipLaunchKernelGGL_enqueue_rate(std::atomic_int* shared, int max_threads) | ||
{ | ||
//resources necessary for this thread | ||
hipStream_t stream; | ||
hipStreamCreate(&stream); | ||
std::array<float, TOTAL_RUN_COUNT> results; | ||
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//synchronize all threads, before running | ||
int tid = shared->fetch_add(1, std::memory_order_release); | ||
while (max_threads != shared->load(std::memory_order_acquire)) {} | ||
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for (auto i = 0; i < TOTAL_RUN_COUNT; ++i) { | ||
auto start = std::chrono::high_resolution_clock::now(); | ||
hipLaunchKernelGGL((EmptyKernel), dim3(NUM_GROUPS), dim3(GROUP_SIZE), 0, stream); | ||
auto stop = std::chrono::high_resolution_clock::now(); | ||
results[i] = std::chrono::duration<double, std::milli>(stop - start).count(); | ||
} | ||
print_timing("Thread ID : " + std::to_string(tid) + " , " + "hipLaunchKernelGGL enqueue rate", results); | ||
} | ||
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// Simple thread pool | ||
struct thread_pool { | ||
thread_pool(int total_threads) : max_threads(total_threads) {} | ||
void start(std::function<void(std::atomic_int*, int)> f) { | ||
for (int i = 0; i < max_threads; ++i) { | ||
threads.push_back(std::async(std::launch::async, f, &shared, max_threads)); | ||
} | ||
} | ||
void finish() { | ||
for (auto&&thread : threads) { | ||
thread.get(); | ||
} | ||
threads.clear(); | ||
shared = {0}; | ||
} | ||
~thread_pool() { | ||
finish(); | ||
} | ||
private: | ||
std::atomic_int shared {0}; | ||
std::vector<std::future<void>> threads; | ||
int max_threads = 1; | ||
}; | ||
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int main(int argc, char* argv[]) | ||
{ | ||
if (argc != 3) { | ||
std::cerr << "Run test as 'hipDispatchEnqueueRateMT <num_threads> <0-hipModuleLaunchKernel /1-hipLaunchKernelGGL>'\n"; | ||
return -1; | ||
} | ||
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int max_threads = atoi(argv[1]); | ||
int run_module_test = atoi(argv[2]); | ||
if(max_threads < 1 || run_module_test < 0 || run_module_test > 1) { | ||
std::cerr << "Invalid Input.\n"; | ||
std::cerr << "Run test as 'hipDispatchEnqueueRateMT <num_threads> <0-hipModuleLaunchKernel /1-hipLaunchKernelGGL>'\n"; | ||
return -1; | ||
} | ||
thread_pool task(max_threads); | ||
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if(run_module_test == 0) { | ||
task.start(hipModuleLaunchKernel_enqueue_rate); | ||
task.finish(); | ||
} else { | ||
task.start(hipLaunchKernelGGL_enqueue_rate); | ||
task.finish(); | ||
} | ||
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return 0; | ||
} | ||
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