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
@@ -29,115 +29,124 @@
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#if defined(WIN32) || defined(_WIN32) || defined(WIN64) || defined(_WIN64)
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// Create thread
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CUTThread cutStartThread(CUT_THREADROUTINE func, void *data) {
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return CreateThread(NULL, 0, (LPTHREAD_START_ROUTINE)func, data, 0, NULL);
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CUTThread cutStartThread(CUT_THREADROUTINE func, void *data)
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{
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return CreateThread(NULL, 0, (LPTHREAD_START_ROUTINE)func, data, 0, NULL);
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}
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// Wait for thread to finish
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void cutEndThread(CUTThread thread) {
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WaitForSingleObject(thread, INFINITE);
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CloseHandle(thread);
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void cutEndThread(CUTThread thread)
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{
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WaitForSingleObject(thread, INFINITE);
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CloseHandle(thread);
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}
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// Wait for multiple threads
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void cutWaitForThreads(const CUTThread *threads, int num) {
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WaitForMultipleObjects(num, threads, true, INFINITE);
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void cutWaitForThreads(const CUTThread *threads, int num)
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{
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WaitForMultipleObjects(num, threads, true, INFINITE);
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for (int i = 0; i < num; i++) {
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CloseHandle(threads[i]);
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}
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for (int i = 0; i < num; i++) {
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CloseHandle(threads[i]);
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}
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}
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// Create barrier.
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CUTBarrier cutCreateBarrier(int releaseCount) {
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CUTBarrier barrier;
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CUTBarrier cutCreateBarrier(int releaseCount)
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{
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CUTBarrier barrier;
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InitializeCriticalSection(&barrier.criticalSection);
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barrier.barrierEvent = CreateEvent(NULL, TRUE, FALSE, TEXT("BarrierEvent"));
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barrier.count = 0;
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barrier.releaseCount = releaseCount;
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InitializeCriticalSection(&barrier.criticalSection);
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barrier.barrierEvent = CreateEvent(NULL, TRUE, FALSE, TEXT("BarrierEvent"));
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barrier.count = 0;
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barrier.releaseCount = releaseCount;
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return barrier;
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return barrier;
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}
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// Increment barrier. (execution continues)
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void cutIncrementBarrier(CUTBarrier *barrier) {
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int myBarrierCount;
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EnterCriticalSection(&barrier->criticalSection);
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myBarrierCount = ++barrier->count;
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LeaveCriticalSection(&barrier->criticalSection);
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void cutIncrementBarrier(CUTBarrier *barrier)
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{
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int myBarrierCount;
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EnterCriticalSection(&barrier->criticalSection);
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myBarrierCount = ++barrier->count;
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LeaveCriticalSection(&barrier->criticalSection);
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if (myBarrierCount >= barrier->releaseCount) {
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SetEvent(barrier->barrierEvent);
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}
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if (myBarrierCount >= barrier->releaseCount) {
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SetEvent(barrier->barrierEvent);
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}
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}
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// Wait for barrier release.
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void cutWaitForBarrier(CUTBarrier *barrier) {
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WaitForSingleObject(barrier->barrierEvent, INFINITE);
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}
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void cutWaitForBarrier(CUTBarrier *barrier) { WaitForSingleObject(barrier->barrierEvent, INFINITE); }
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// Destroy barrier
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void cutDestroyBarrier(CUTBarrier *barrier) {}
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#else
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// Create thread
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CUTThread cutStartThread(CUT_THREADROUTINE func, void *data) {
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pthread_t thread;
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pthread_create(&thread, NULL, func, data);
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return thread;
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CUTThread cutStartThread(CUT_THREADROUTINE func, void *data)
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{
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pthread_t thread;
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pthread_create(&thread, NULL, func, data);
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return thread;
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}
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// Wait for thread to finish
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void cutEndThread(CUTThread thread) { pthread_join(thread, NULL); }
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// Wait for multiple threads
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void cutWaitForThreads(const CUTThread *threads, int num) {
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for (int i = 0; i < num; i++) {
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cutEndThread(threads[i]);
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}
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void cutWaitForThreads(const CUTThread *threads, int num)
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{
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for (int i = 0; i < num; i++) {
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cutEndThread(threads[i]);
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}
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}
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// Create barrier.
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CUTBarrier cutCreateBarrier(int releaseCount) {
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CUTBarrier barrier;
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CUTBarrier cutCreateBarrier(int releaseCount)
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{
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CUTBarrier barrier;
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barrier.count = 0;
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barrier.releaseCount = releaseCount;
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barrier.count = 0;
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barrier.releaseCount = releaseCount;
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pthread_mutex_init(&barrier.mutex, 0);
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pthread_cond_init(&barrier.conditionVariable, 0);
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pthread_mutex_init(&barrier.mutex, 0);
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pthread_cond_init(&barrier.conditionVariable, 0);
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return barrier;
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return barrier;
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}
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// Increment barrier. (execution continues)
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void cutIncrementBarrier(CUTBarrier *barrier) {
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int myBarrierCount;
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pthread_mutex_lock(&barrier->mutex);
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myBarrierCount = ++barrier->count;
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pthread_mutex_unlock(&barrier->mutex);
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void cutIncrementBarrier(CUTBarrier *barrier)
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{
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int myBarrierCount;
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pthread_mutex_lock(&barrier->mutex);
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myBarrierCount = ++barrier->count;
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pthread_mutex_unlock(&barrier->mutex);
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if (myBarrierCount >= barrier->releaseCount) {
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pthread_cond_signal(&barrier->conditionVariable);
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}
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if (myBarrierCount >= barrier->releaseCount) {
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pthread_cond_signal(&barrier->conditionVariable);
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}
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}
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// Wait for barrier release.
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void cutWaitForBarrier(CUTBarrier *barrier) {
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pthread_mutex_lock(&barrier->mutex);
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void cutWaitForBarrier(CUTBarrier *barrier)
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{
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pthread_mutex_lock(&barrier->mutex);
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while (barrier->count < barrier->releaseCount) {
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pthread_cond_wait(&barrier->conditionVariable, &barrier->mutex);
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}
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while (barrier->count < barrier->releaseCount) {
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pthread_cond_wait(&barrier->conditionVariable, &barrier->mutex);
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}
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pthread_mutex_unlock(&barrier->mutex);
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pthread_mutex_unlock(&barrier->mutex);
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}
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// Destroy barrier
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void cutDestroyBarrier(CUTBarrier *barrier) {
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pthread_mutex_destroy(&barrier->mutex);
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pthread_cond_destroy(&barrier->conditionVariable);
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void cutDestroyBarrier(CUTBarrier *barrier)
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{
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pthread_mutex_destroy(&barrier->mutex);
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pthread_cond_destroy(&barrier->conditionVariable);
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}
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#endif
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@@ -37,15 +37,16 @@
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typedef HANDLE CUTThread;
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typedef unsigned(WINAPI *CUT_THREADROUTINE)(void *);
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struct CUTBarrier {
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CRITICAL_SECTION criticalSection;
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HANDLE barrierEvent;
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int releaseCount;
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int count;
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struct CUTBarrier
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{
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CRITICAL_SECTION criticalSection;
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HANDLE barrierEvent;
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int releaseCount;
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int count;
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};
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#define CUT_THREADPROC unsigned WINAPI
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#define CUT_THREADEND return 0
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#define CUT_THREADEND return 0
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#else
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// POSIX threads.
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@@ -55,44 +56,46 @@ typedef pthread_t CUTThread;
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typedef void *(*CUT_THREADROUTINE)(void *);
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#define CUT_THREADPROC void *
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#define CUT_THREADEND return 0
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#define CUT_THREADEND return 0
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struct CUTBarrier {
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pthread_mutex_t mutex;
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pthread_cond_t conditionVariable;
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int releaseCount;
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int count;
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struct CUTBarrier
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{
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pthread_mutex_t mutex;
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pthread_cond_t conditionVariable;
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int releaseCount;
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int count;
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};
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#endif
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#ifdef __cplusplus
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extern "C" {
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extern "C"
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{
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#endif
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// Create thread.
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CUTThread cutStartThread(CUT_THREADROUTINE, void *data);
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// Create thread.
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CUTThread cutStartThread(CUT_THREADROUTINE, void *data);
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// Wait for thread to finish.
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void cutEndThread(CUTThread thread);
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// Wait for thread to finish.
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void cutEndThread(CUTThread thread);
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// Wait for multiple threads.
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void cutWaitForThreads(const CUTThread *threads, int num);
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// Wait for multiple threads.
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void cutWaitForThreads(const CUTThread *threads, int num);
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// Create barrier.
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CUTBarrier cutCreateBarrier(int releaseCount);
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// Create barrier.
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CUTBarrier cutCreateBarrier(int releaseCount);
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// Increment barrier. (execution continues)
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void cutIncrementBarrier(CUTBarrier *barrier);
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// Increment barrier. (execution continues)
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void cutIncrementBarrier(CUTBarrier *barrier);
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// Wait for barrier release.
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void cutWaitForBarrier(CUTBarrier *barrier);
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// Wait for barrier release.
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void cutWaitForBarrier(CUTBarrier *barrier);
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// Destroy barrier
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void cutDestroyBarrier(CUTBarrier *barrier);
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// Destroy barrier
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void cutDestroyBarrier(CUTBarrier *barrier);
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#ifdef __cplusplus
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} // extern "C"
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} // extern "C"
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#endif
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#endif // MULTITHREADING_H
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#endif // MULTITHREADING_H
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@@ -43,172 +43,173 @@
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#include <stdio.h>
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// helper functions and utilities to work with CUDA
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#include <helper_functions.h>
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#include <helper_cuda.h>
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#include <helper_functions.h>
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#include "multithreading.h"
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const int N_workloads = 8;
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const int N_workloads = 8;
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const int N_elements_per_workload = 100000;
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CUTBarrier thread_barrier;
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void CUDART_CB myStreamCallback(cudaStream_t event, cudaError_t status,
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void *data);
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void CUDART_CB myStreamCallback(cudaStream_t event, cudaError_t status, void *data);
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struct heterogeneous_workload {
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int id;
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int cudaDeviceID;
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struct heterogeneous_workload
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{
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int id;
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int cudaDeviceID;
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int *h_data;
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int *d_data;
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cudaStream_t stream;
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int *h_data;
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int *d_data;
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cudaStream_t stream;
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bool success;
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bool success;
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};
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__global__ void incKernel(int *data, int N) {
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int i = blockIdx.x * blockDim.x + threadIdx.x;
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__global__ void incKernel(int *data, int N)
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{
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int i = blockIdx.x * blockDim.x + threadIdx.x;
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if (i < N) data[i]++;
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if (i < N)
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data[i]++;
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}
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CUT_THREADPROC launch(void *void_arg) {
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heterogeneous_workload *workload = (heterogeneous_workload *)void_arg;
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CUT_THREADPROC launch(void *void_arg)
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{
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heterogeneous_workload *workload = (heterogeneous_workload *)void_arg;
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// Select GPU for this CPU thread
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checkCudaErrors(cudaSetDevice(workload->cudaDeviceID));
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// Select GPU for this CPU thread
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checkCudaErrors(cudaSetDevice(workload->cudaDeviceID));
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// Allocate Resources
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checkCudaErrors(cudaStreamCreate(&workload->stream));
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checkCudaErrors(
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cudaMalloc(&workload->d_data, N_elements_per_workload * sizeof(int)));
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checkCudaErrors(cudaHostAlloc(&workload->h_data,
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N_elements_per_workload * sizeof(int),
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cudaHostAllocPortable));
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// Allocate Resources
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checkCudaErrors(cudaStreamCreate(&workload->stream));
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checkCudaErrors(cudaMalloc(&workload->d_data, N_elements_per_workload * sizeof(int)));
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checkCudaErrors(cudaHostAlloc(&workload->h_data, N_elements_per_workload * sizeof(int), cudaHostAllocPortable));
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// CPU thread generates data
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for (int i = 0; i < N_elements_per_workload; ++i) {
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workload->h_data[i] = workload->id + i;
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}
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// Schedule work for GPU in CUDA stream without blocking the CPU thread
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// Note: Dedicated streams enable concurrent execution of workloads on the GPU
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dim3 block(512);
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dim3 grid((N_elements_per_workload + block.x - 1) / block.x);
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checkCudaErrors(cudaMemcpyAsync(workload->d_data, workload->h_data,
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N_elements_per_workload * sizeof(int),
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cudaMemcpyHostToDevice, workload->stream));
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incKernel<<<grid, block, 0, workload->stream>>>(workload->d_data,
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N_elements_per_workload);
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checkCudaErrors(cudaMemcpyAsync(workload->h_data, workload->d_data,
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N_elements_per_workload * sizeof(int),
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cudaMemcpyDeviceToHost, workload->stream));
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// New in CUDA 5.0: Add a CPU callback which is called once all currently
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// pending operations in the CUDA stream have finished
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checkCudaErrors(
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cudaStreamAddCallback(workload->stream, myStreamCallback, workload, 0));
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CUT_THREADEND;
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// CPU thread end of life, GPU continues to process data...
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}
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CUT_THREADPROC postprocess(void *void_arg) {
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heterogeneous_workload *workload = (heterogeneous_workload *)void_arg;
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// ... GPU is done with processing, continue on new CPU thread...
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// Select GPU for this CPU thread
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checkCudaErrors(cudaSetDevice(workload->cudaDeviceID));
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// CPU thread consumes results from GPU
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workload->success = true;
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for (int i = 0; i < N_workloads; ++i) {
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workload->success &= workload->h_data[i] == i + workload->id + 1;
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}
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// Free Resources
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checkCudaErrors(cudaFree(workload->d_data));
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checkCudaErrors(cudaFreeHost(workload->h_data));
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checkCudaErrors(cudaStreamDestroy(workload->stream));
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// Signal the end of the heterogeneous workload to main thread
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cutIncrementBarrier(&thread_barrier);
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CUT_THREADEND;
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}
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|
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void CUDART_CB myStreamCallback(cudaStream_t stream, cudaError_t status,
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void *data) {
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// Check status of GPU after stream operations are done
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checkCudaErrors(status);
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// Spawn new CPU worker thread and continue processing on the CPU
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cutStartThread(postprocess, data);
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}
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int main(int argc, char **argv) {
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int N_gpus, max_gpus = 0;
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int gpuInfo[32]; // assume a maximum of 32 GPUs in a system configuration
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printf("Starting simpleCallback\n");
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checkCudaErrors(cudaGetDeviceCount(&N_gpus));
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printf("Found %d CUDA capable GPUs\n", N_gpus);
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if (N_gpus > 32) {
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printf("simpleCallback only supports 32 GPU(s)\n");
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}
|
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|
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for (int devid = 0; devid < N_gpus; devid++) {
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int SMversion;
|
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cudaDeviceProp deviceProp;
|
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cudaSetDevice(devid);
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cudaGetDeviceProperties(&deviceProp, devid);
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SMversion = deviceProp.major << 4 + deviceProp.minor;
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printf("GPU[%d] %s supports SM %d.%d", devid, deviceProp.name,
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deviceProp.major, deviceProp.minor);
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printf(", %s GPU Callback Functions\n",
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(SMversion >= 0x11) ? "capable" : "NOT capable");
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if (SMversion >= 0x11) {
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gpuInfo[max_gpus++] = devid;
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// CPU thread generates data
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||||
for (int i = 0; i < N_elements_per_workload; ++i) {
|
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workload->h_data[i] = workload->id + i;
|
||||
}
|
||||
}
|
||||
|
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printf("%d GPUs available to run Callback Functions\n", max_gpus);
|
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// Schedule work for GPU in CUDA stream without blocking the CPU thread
|
||||
// Note: Dedicated streams enable concurrent execution of workloads on the GPU
|
||||
dim3 block(512);
|
||||
dim3 grid((N_elements_per_workload + block.x - 1) / block.x);
|
||||
|
||||
heterogeneous_workload *workloads;
|
||||
workloads = (heterogeneous_workload *)malloc(N_workloads *
|
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sizeof(heterogeneous_workload));
|
||||
;
|
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thread_barrier = cutCreateBarrier(N_workloads);
|
||||
checkCudaErrors(cudaMemcpyAsync(workload->d_data,
|
||||
workload->h_data,
|
||||
N_elements_per_workload * sizeof(int),
|
||||
cudaMemcpyHostToDevice,
|
||||
workload->stream));
|
||||
incKernel<<<grid, block, 0, workload->stream>>>(workload->d_data, N_elements_per_workload);
|
||||
checkCudaErrors(cudaMemcpyAsync(workload->h_data,
|
||||
workload->d_data,
|
||||
N_elements_per_workload * sizeof(int),
|
||||
cudaMemcpyDeviceToHost,
|
||||
workload->stream));
|
||||
|
||||
// Main thread spawns a CPU worker thread for each heterogeneous workload
|
||||
printf("Starting %d heterogeneous computing workloads\n", N_workloads);
|
||||
// New in CUDA 5.0: Add a CPU callback which is called once all currently
|
||||
// pending operations in the CUDA stream have finished
|
||||
checkCudaErrors(cudaStreamAddCallback(workload->stream, myStreamCallback, workload, 0));
|
||||
|
||||
for (int i = 0; i < N_workloads; ++i) {
|
||||
workloads[i].id = i;
|
||||
workloads[i].cudaDeviceID = gpuInfo[i % max_gpus]; // i % N_gpus;
|
||||
|
||||
cutStartThread(launch, &workloads[i]);
|
||||
}
|
||||
|
||||
// Sleep until all workloads have finished
|
||||
cutWaitForBarrier(&thread_barrier);
|
||||
printf("Total of %d workloads finished:\n", N_workloads);
|
||||
|
||||
bool success = true;
|
||||
|
||||
for (int i = 0; i < N_workloads; ++i) {
|
||||
success &= workloads[i].success;
|
||||
}
|
||||
|
||||
printf("%s\n", success ? "Success" : "Failure");
|
||||
|
||||
free(workloads);
|
||||
|
||||
exit(success ? EXIT_SUCCESS : EXIT_FAILURE);
|
||||
CUT_THREADEND;
|
||||
// CPU thread end of life, GPU continues to process data...
|
||||
}
|
||||
|
||||
CUT_THREADPROC postprocess(void *void_arg)
|
||||
{
|
||||
heterogeneous_workload *workload = (heterogeneous_workload *)void_arg;
|
||||
// ... GPU is done with processing, continue on new CPU thread...
|
||||
|
||||
// Select GPU for this CPU thread
|
||||
checkCudaErrors(cudaSetDevice(workload->cudaDeviceID));
|
||||
|
||||
// CPU thread consumes results from GPU
|
||||
workload->success = true;
|
||||
|
||||
for (int i = 0; i < N_workloads; ++i) {
|
||||
workload->success &= workload->h_data[i] == i + workload->id + 1;
|
||||
}
|
||||
|
||||
// Free Resources
|
||||
checkCudaErrors(cudaFree(workload->d_data));
|
||||
checkCudaErrors(cudaFreeHost(workload->h_data));
|
||||
checkCudaErrors(cudaStreamDestroy(workload->stream));
|
||||
|
||||
// Signal the end of the heterogeneous workload to main thread
|
||||
cutIncrementBarrier(&thread_barrier);
|
||||
|
||||
CUT_THREADEND;
|
||||
}
|
||||
|
||||
void CUDART_CB myStreamCallback(cudaStream_t stream, cudaError_t status, void *data)
|
||||
{
|
||||
// Check status of GPU after stream operations are done
|
||||
checkCudaErrors(status);
|
||||
|
||||
// Spawn new CPU worker thread and continue processing on the CPU
|
||||
cutStartThread(postprocess, data);
|
||||
}
|
||||
|
||||
int main(int argc, char **argv)
|
||||
{
|
||||
int N_gpus, max_gpus = 0;
|
||||
int gpuInfo[32]; // assume a maximum of 32 GPUs in a system configuration
|
||||
|
||||
printf("Starting simpleCallback\n");
|
||||
|
||||
checkCudaErrors(cudaGetDeviceCount(&N_gpus));
|
||||
printf("Found %d CUDA capable GPUs\n", N_gpus);
|
||||
|
||||
if (N_gpus > 32) {
|
||||
printf("simpleCallback only supports 32 GPU(s)\n");
|
||||
}
|
||||
|
||||
for (int devid = 0; devid < N_gpus; devid++) {
|
||||
int SMversion;
|
||||
cudaDeviceProp deviceProp;
|
||||
cudaSetDevice(devid);
|
||||
cudaGetDeviceProperties(&deviceProp, devid);
|
||||
SMversion = deviceProp.major << 4 + deviceProp.minor;
|
||||
printf("GPU[%d] %s supports SM %d.%d", devid, deviceProp.name, deviceProp.major, deviceProp.minor);
|
||||
printf(", %s GPU Callback Functions\n", (SMversion >= 0x11) ? "capable" : "NOT capable");
|
||||
|
||||
if (SMversion >= 0x11) {
|
||||
gpuInfo[max_gpus++] = devid;
|
||||
}
|
||||
}
|
||||
|
||||
printf("%d GPUs available to run Callback Functions\n", max_gpus);
|
||||
|
||||
heterogeneous_workload *workloads;
|
||||
workloads = (heterogeneous_workload *)malloc(N_workloads * sizeof(heterogeneous_workload));
|
||||
;
|
||||
thread_barrier = cutCreateBarrier(N_workloads);
|
||||
|
||||
// Main thread spawns a CPU worker thread for each heterogeneous workload
|
||||
printf("Starting %d heterogeneous computing workloads\n", N_workloads);
|
||||
|
||||
for (int i = 0; i < N_workloads; ++i) {
|
||||
workloads[i].id = i;
|
||||
workloads[i].cudaDeviceID = gpuInfo[i % max_gpus]; // i % N_gpus;
|
||||
|
||||
cutStartThread(launch, &workloads[i]);
|
||||
}
|
||||
|
||||
// Sleep until all workloads have finished
|
||||
cutWaitForBarrier(&thread_barrier);
|
||||
printf("Total of %d workloads finished:\n", N_workloads);
|
||||
|
||||
bool success = true;
|
||||
|
||||
for (int i = 0; i < N_workloads; ++i) {
|
||||
success &= workloads[i].success;
|
||||
}
|
||||
|
||||
printf("%s\n", success ? "Success" : "Failure");
|
||||
|
||||
free(workloads);
|
||||
|
||||
exit(success ? EXIT_SUCCESS : EXIT_FAILURE);
|
||||
}
|
||||
|
||||
Reference in New Issue
Block a user