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/* Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
*
* Redistribution and use in source and binary forms, with or without
* modification, are permitted provided that the following conditions
* are met:
* * Redistributions of source code must retain the above copyright
* notice, this list of conditions and the following disclaimer.
* * Redistributions in binary form must reproduce the above copyright
* notice, this list of conditions and the following disclaimer in the
* documentation and/or other materials provided with the distribution.
* * Neither the name of NVIDIA CORPORATION nor the names of its
* contributors may be used to endorse or promote products derived
* from this software without specific prior written permission.
*
* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS ``AS IS'' AND ANY
* EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
* IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
* PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR
* CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
* EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
* PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
* PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY
* OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
* (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
* OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
*/
/******************************************************************************
*
* Module: threadMigration.cpp
*
* Description:
* Simple sample demonstrating multi-GPU/multithread functionality using
* the CUDA Context Management API. This API allows the a CUDA context to
* be associated with a CPU process. A host thread may have only one device
* context current at a time.
*
* Refer to the CUDA programming guide 4.5.3.3 on Context Management
*
******************************************************************************/
#define MAXTHREADS 256
#define NUM_INTS 32
#if defined(WIN32) || defined(_WIN32) || defined(WIN64) || defined(_WIN64)
// Windows threads use different data structures
#include <windows.h>
DWORD rgdwThreadIds[MAXTHREADS];
HANDLE rghThreads[MAXTHREADS];
CRITICAL_SECTION g_cs;
#define ENTERCRITICALSECTION EnterCriticalSection(&g_cs);
#define LEAVECRITICALSECTION LeaveCriticalSection(&g_cs);
#define STRICMP stricmp
#else
// Includes POSIX thread headers for Linux thread support
#include <pthread.h>
#include <stdint.h>
pthread_t rghThreads[MAXTHREADS];
pthread_mutex_t g_mutex;
#define ENTERCRITICALSECTION pthread_mutex_lock(&g_mutex);
#define LEAVECRITICALSECTION pthread_mutex_unlock(&g_mutex);
#define STRICMP strcasecmp
#endif
#include <stdlib.h>
#include <stdio.h>
#include <cuda.h>
#include <cuda_runtime_api.h>
#include <helper_cuda_drvapi.h>
#include <iostream>
#include <cstring>
using namespace std;
int NumThreads;
int ThreadLaunchCount;
typedef struct _CUDAContext_st {
CUcontext hcuContext;
CUmodule hcuModule;
CUfunction hcuFunction;
CUdeviceptr dptr;
int deviceID;
int threadNum;
} CUDAContext;
CUDAContext g_ThreadParams[MAXTHREADS];
// define input fatbin file
#ifndef FATBIN_FILE
#define FATBIN_FILE "threadMigration_kernel64.fatbin"
#endif
bool gbAutoQuit = false;
////////////////////////////////////////////////////////////////////////////////
// declaration, forward
bool runTest(int argc, char **argv);
#define CLEANUP_ON_ERROR(dptr, hcuModule, hcuContext, status) \
if (dptr) cuMemFree(dptr); \
if (hcuModule) cuModuleUnload(hcuModule); \
if (hcuContext) cuCtxDestroy(hcuContext); \
return status;
#define THREAD_QUIT \
printf("Error\n"); \
return 0;
// This sample uses the Driver API interface. The CUDA context needs
// to be setup and the CUDA module (CUBIN) is built by NVCC
static CUresult InitCUDAContext(CUDAContext *pContext, CUdevice hcuDevice,
int deviceID, char **argv) {
CUcontext hcuContext = 0;
CUmodule hcuModule = 0;
CUfunction hcuFunction = 0;
CUdeviceptr dptr = 0;
// cuCtxCreate: Function works on floating contexts and current context
CUresult status = cuCtxCreate(&hcuContext, 0, hcuDevice);
if (CUDA_SUCCESS != status) {
fprintf(stderr, "cuCtxCreate for <deviceID=%d> failed %d\n", deviceID,
status);
CLEANUP_ON_ERROR(dptr, hcuModule, hcuContext, status);
}
status = CUDA_ERROR_INVALID_IMAGE;
string module_path, ptx_source;
std::ostringstream fatbin;
if (!findFatbinPath(FATBIN_FILE, module_path, argv, fatbin)) {
exit(EXIT_FAILURE);
} else {
printf("> initCUDA loading module: <%s>\n", module_path.c_str());
}
if (!fatbin.str().size()) {
printf("fatbin file empty. exiting..\n");
exit(EXIT_FAILURE);
}
// Create module from binary file (FATBIN)
checkCudaErrors(cuModuleLoadData(&hcuModule, fatbin.str().c_str()));
status = cuModuleGetFunction(&hcuFunction, hcuModule, "kernelFunction");
if (CUDA_SUCCESS != status) {
fprintf(stderr, "cuModuleGetFunction failed %d\n", status);
CLEANUP_ON_ERROR(dptr, hcuModule, hcuContext, status);
}
// Here we must release the CUDA context from the thread context
status = cuCtxPopCurrent(NULL);
if (CUDA_SUCCESS != status) {
fprintf(stderr, "cuCtxPopCurrent failed %d\n", status);
CLEANUP_ON_ERROR(dptr, hcuModule, hcuContext, status);
}
pContext->hcuContext = hcuContext;
pContext->hcuModule = hcuModule;
pContext->hcuFunction = hcuFunction;
pContext->deviceID = deviceID;
return CUDA_SUCCESS;
}
// ThreadProc launches the CUDA kernel on a CUDA context.
// We have more than one thread that talks to a CUDA context
#if defined(WIN32) || defined(_WIN32) || defined(WIN64) || defined(_WIN64)
DWORD WINAPI ThreadProc(CUDAContext *pParams)
#else
void *ThreadProc(CUDAContext *pParams)
#endif
{
int wrong = 0;
int *pInt = 0;
printf("<CUDA Device=%d, Context=%p, Thread=%d> - ThreadProc() Launched...\n",
pParams->deviceID, pParams->hcuContext, pParams->threadNum);
// cuCtxPushCurrent: Attach the caller CUDA context to the thread context.
CUresult status = cuCtxPushCurrent(pParams->hcuContext);
if (CUDA_SUCCESS != status) {
THREAD_QUIT;
}
checkCudaErrors(cuMemAlloc(&pParams->dptr, NUM_INTS * sizeof(int)));
// There are two ways to launch CUDA kernels via the Driver API.
// In this CUDA Sample, we illustrate both ways to pass parameters
// and specify parameters. By default we use the simpler method.
if (1) {
// This is the new CUDA 4.0 API for Kernel Parameter passing and Kernel
// Launching (simpler method)
void *args[5] = {&pParams->dptr};
// new CUDA 4.0 Driver API Kernel launch call
status = cuLaunchKernel(pParams->hcuFunction, 1, 1, 1, 32, 1, 1, 0, NULL,
args, NULL);
if (CUDA_SUCCESS != status) {
fprintf(stderr, "cuLaunch failed %d\n", status);
THREAD_QUIT;
}
} else {
// This is the new CUDA 4.0 API for Kernel Parameter passing and Kernel
// Launching (advanced method)
int offset = 0;
char argBuffer[256];
// pass in launch parameters (not actually de-referencing CUdeviceptr).
// CUdeviceptr is storing the value of the parameters
*((CUdeviceptr *)&argBuffer[offset]) = pParams->dptr;
offset += sizeof(CUdeviceptr);
void *kernel_launch_config[5] = {CU_LAUNCH_PARAM_BUFFER_POINTER, argBuffer,
CU_LAUNCH_PARAM_BUFFER_SIZE, &offset,
CU_LAUNCH_PARAM_END};
// new CUDA 4.0 Driver API Kernel launch call
status = cuLaunchKernel(pParams->hcuFunction, 1, 1, 1, 32, 1, 1, 0, 0, NULL,
(void **)&kernel_launch_config);
if (CUDA_SUCCESS != status) {
fprintf(stderr, "cuLaunch failed %d\n", status);
THREAD_QUIT;
}
}
pInt = (int *)malloc(NUM_INTS * sizeof(int));
if (!pInt) return 0;
if (CUDA_SUCCESS ==
cuMemcpyDtoH(pInt, pParams->dptr, NUM_INTS * sizeof(int))) {
for (int i = 0; i < NUM_INTS; i++) {
if (pInt[i] != 32 - i) {
printf("<CUDA Device=%d, Context=%p, Thread=%d> error [%d]=%d!\n",
pParams->deviceID, pParams->hcuContext, pParams->threadNum, i,
pInt[i]);
wrong++;
}
}
ENTERCRITICALSECTION
if (!wrong) ThreadLaunchCount += 1;
LEAVECRITICALSECTION
}
free(pInt);
fflush(stdout);
checkCudaErrors(cuMemFree(pParams->dptr));
// cuCtxPopCurrent: Detach the current CUDA context from the calling thread.
checkCudaErrors(cuCtxPopCurrent(NULL));
printf("<CUDA Device=%d, Context=%p, Thread=%d> - ThreadProc() Finished!\n\n",
pParams->deviceID, pParams->hcuContext, pParams->threadNum);
return 0;
}
bool FinalErrorCheck(CUDAContext *pContext, int NumThreads, int deviceCount) {
if (ThreadLaunchCount != NumThreads * deviceCount) {
printf("<Expected=%d, Actual=%d> ThreadLaunchCounts(s)\n",
NumThreads * deviceCount, ThreadLaunchCount);
return false;
} else {
for (int iDevice = 0; iDevice < deviceCount; iDevice++) {
// cuCtxDestroy called on current context or a floating context
if (CUDA_SUCCESS != cuCtxDestroy(pContext[iDevice].hcuContext))
return false;
}
return true;
}
}
int main(int argc, char **argv) {
printf("Starting threadMigration\n");
bool bTestResult = runTest(argc, argv);
exit(bTestResult ? EXIT_SUCCESS : EXIT_FAILURE);
}
bool runTest(int argc, char **argv) {
printf("[ threadMigration ] API test...\n");
#if defined(WIN32) || defined(_WIN32) || defined(WIN64) || defined(_WIN64)
InitializeCriticalSection(&g_cs);
#else
pthread_mutex_init(&g_mutex, NULL);
#endif
// By default, we will launch 2 CUDA threads for each device
NumThreads = 2;
if (argc > 1) {
// If we are doing the QAtest or automated testing, we quit without
// prompting
if (checkCmdLineFlag(argc, (const char **)argv, "qatest") ||
checkCmdLineFlag(argc, (const char **)argv, "noprompt")) {
gbAutoQuit = true;
}
if (checkCmdLineFlag(argc, (const char **)argv, "numthreads")) {
NumThreads =
getCmdLineArgumentInt(argc, (const char **)argv, "numthreads");
if (NumThreads < 1 || NumThreads > 15) {
printf(
"Usage: \"threadMigration -n=<threads>\", <threads> ranges 1-15\n");
return 1;
}
}
}
int deviceCount;
int hcuDevice = 0;
CUresult status;
status = cuInit(0);
if (CUDA_SUCCESS != status) return false;
status = cuDeviceGetCount(&deviceCount);
if (CUDA_SUCCESS != status) return false;
printf("> %d CUDA device(s), %d Thread(s)/device to launched\n\n",
deviceCount, NumThreads);
if (deviceCount == 0) {
return false;
}
int ihThread = 0;
int ThreadIndex = 0;
CUDAContext *pContext =
(CUDAContext *)malloc(sizeof(CUDAContext) * deviceCount);
for (int iDevice = 0; iDevice < deviceCount; iDevice++) {
char szName[256];
status = cuDeviceGet(&hcuDevice, iDevice);
if (CUDA_SUCCESS != status) return false;
status = cuDeviceGetName(szName, 256, hcuDevice);
if (CUDA_SUCCESS != status) return false;
{
int major = 0, minor = 0;
checkCudaErrors(cuDeviceGetAttribute(
&major, CU_DEVICE_ATTRIBUTE_COMPUTE_CAPABILITY_MAJOR, hcuDevice));
checkCudaErrors(cuDeviceGetAttribute(
&minor, CU_DEVICE_ATTRIBUTE_COMPUTE_CAPABILITY_MINOR, hcuDevice));
int sharedMemPerBlock;
checkCudaErrors(cuDeviceGetAttribute(
&sharedMemPerBlock, CU_DEVICE_ATTRIBUTE_MAX_SHARED_MEMORY_PER_BLOCK,
hcuDevice));
int totalConstantMemory;
checkCudaErrors(cuDeviceGetAttribute(
&totalConstantMemory, CU_DEVICE_ATTRIBUTE_TOTAL_CONSTANT_MEMORY,
hcuDevice));
int regsPerBlock;
checkCudaErrors(cuDeviceGetAttribute(
®sPerBlock, CU_DEVICE_ATTRIBUTE_MAX_REGISTERS_PER_BLOCK,
hcuDevice));
int clockRate;
checkCudaErrors(cuDeviceGetAttribute(
&clockRate, CU_DEVICE_ATTRIBUTE_CLOCK_RATE, hcuDevice));
printf("Device %d: \"%s\" (Compute %d.%d)\n", iDevice, szName, major,
minor);
printf("\tsharedMemPerBlock: %d\n", sharedMemPerBlock);
printf("\tconstantMemory : %d\n", totalConstantMemory);
printf("\tregsPerBlock : %d\n", regsPerBlock);
printf("\tclockRate : %d\n", clockRate);
printf("\n");
}
if (CUDA_SUCCESS !=
InitCUDAContext(&pContext[iDevice], hcuDevice, iDevice, argv)) {
return FinalErrorCheck(pContext, NumThreads, deviceCount);
} else {
for (int iThread = 0; iThread < NumThreads; iThread++, ihThread++) {
g_ThreadParams[ThreadIndex].hcuContext = pContext[iDevice].hcuContext;
g_ThreadParams[ThreadIndex].hcuModule = pContext[iDevice].hcuModule;
g_ThreadParams[ThreadIndex].hcuFunction = pContext[iDevice].hcuFunction;
g_ThreadParams[ThreadIndex].deviceID = pContext[iDevice].deviceID;
g_ThreadParams[ThreadIndex].threadNum = iThread;
// Launch (NumThreads) for each CUDA context
#if defined(WIN32) || defined(_WIN32) || defined(WIN64) || defined(_WIN64)
rghThreads[ThreadIndex] = CreateThread(
NULL, 0, (LPTHREAD_START_ROUTINE)ThreadProc,
&g_ThreadParams[ThreadIndex], 0, &rgdwThreadIds[ThreadIndex]);
#else // Assume we are running linux
pthread_create(&rghThreads[ThreadIndex], NULL,
(void *(*)(void *))ThreadProc,
&g_ThreadParams[ThreadIndex]);
#endif
ThreadIndex += 1;
}
}
}
// Wait until all workers are done
#if defined(WIN32) || defined(_WIN32) || defined(WIN64) || defined(_WIN64)
WaitForMultipleObjects(ThreadIndex, rghThreads, TRUE, INFINITE);
#else
for (int i = 0; i < ThreadIndex; i++) {
pthread_join(rghThreads[i], NULL);
}
#endif
bool ret_status = FinalErrorCheck(pContext, NumThreads, deviceCount);
free(pContext);
return ret_status;
}
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