bool load_kernels(bool experimental)
{
/* check if cuda init succeeded */
if(cuContext == 0)
return false;
/* check if GPU is supported with current feature set */
if(!support_device(experimental))
return false;
/* get kernel */
string cubin = compile_kernel();
if(cubin == "")
return false;
/* open module */
cuda_push_context();
CUresult result = cuModuleLoad(&cuModule, cubin.c_str());
if(cuda_error_(result, "cuModuleLoad"))
cuda_error_message(string_printf("Failed loading CUDA kernel %s.", cubin.c_str()));
cuda_pop_context();
return (result == CUDA_SUCCESS);
}
CUresult cuda_driver_api_init(CUcontext *pctx, CUmodule *pmod, const char *f)
{
CUresult res;
CUdevice dev;
res = cuInit(0);
if (res != CUDA_SUCCESS) {
printf("cuInit failed: res = %lu\n", (unsigned long)res);
return res;
}
res = cuDeviceGet(&dev, 0);
if (res != CUDA_SUCCESS) {
printf("cuDeviceGet failed: res = %lu\n", (unsigned long)res);
return res;
}
res = cuCtxCreate(pctx, 0, dev);
if (res != CUDA_SUCCESS) {
printf("cuCtxCreate failed: res = %lu\n", (unsigned long)res);
return res;
}
res = cuModuleLoad(pmod, f);
if (res != CUDA_SUCCESS) {
printf("cuModuleLoad() failed\n");
cuCtxDestroy(*pctx);
return res;
}
return CUDA_SUCCESS;
}
Object cuda_over_map(Object self, int nparts, int *argcv,
Object *argv, int flags) {
CUresult error;
cuInit(0);
int deviceCount = 0;
error = cuDeviceGetCount(&deviceCount);
if (deviceCount == 0) {
raiseError("No CUDA devices found");
}
CUdevice cuDevice;
CUcontext cuContext;
CUmodule cuModule;
CUfunction cuFunc;
error = cuDeviceGet(&cuDevice, 0);
error = cuCtxCreate(&cuContext, 0, cuDevice);
CUdeviceptr d_A;
CUdeviceptr d_B;
CUdeviceptr d_res;
errcheck(cuModuleLoad(&cuModule, grcstring(argv[argcv[0]])));
CUdeviceptr dps[argcv[0]];
void *args[argcv[0]+2];
int size = INT_MAX;
for (int i=0; i<argcv[0]; i++) {
struct CudaFloatArray *a = (struct CudaFloatArray *)argv[i];
if (a->size < size)
size = a->size;
errcheck(cuMemAlloc(&dps[i], size * sizeof(float)));
errcheck(cuMemcpyHtoD(dps[i], &a->data, size * sizeof(float)));
args[i+1] = &dps[i];
}
struct CudaFloatArray *r =
(struct CudaFloatArray *)(alloc_CudaFloatArray(size));
int fsize = sizeof(float) * size;
errcheck(cuMemAlloc(&d_res, fsize));
errcheck(cuMemcpyHtoD(d_res, &r->data, fsize));
args[0] = &d_res;
args[argcv[0]+1] = &size;
int threadsPerBlock = 256;
int blocksPerGrid = (size + threadsPerBlock - 1) / threadsPerBlock;
char name[256];
strcpy(name, "block");
strcat(name, grcstring(argv[argcv[0]]) + strlen("_cuda/"));
for (int i=0; name[i] != 0; i++)
if (name[i] == '.') {
name[i] = 0;
break;
}
errcheck(cuModuleGetFunction(&cuFunc, cuModule, name));
errcheck(cuLaunchKernel(cuFunc, blocksPerGrid, 1, 1,
threadsPerBlock, 1, 1,
0,
NULL, args, NULL));
errcheck(cuMemcpyDtoH(&r->data, d_res, fsize));
cuMemFree(d_res);
for (int i=0; i<argcv[0]; i++)
cuMemFree(dps[i]);
return (Object)r;
}
CUresult loadCUDAModules()
{
CUmodule cuModule_;
checkCudaErrors(cuModuleLoad(&cuModule_, "videoPP64.ptx"));
checkCudaErrors(cuModuleGetFunction(&g_kernelNV12toARGB, cuModule_, "NV12ToARGBdrvapi"));
checkCudaErrors(cuModuleGetFunction(&g_kernelARGBtoNV12, cuModule_, "ARGBToNv12drvapi"));
checkCudaErrors(cuModuleGetFunction(&g_kernelARGBpostprocess, cuModule_, "ARGBpostprocess"));
}
static CUresult
initCuda(CUcontext _cuContext, char* executablePath, CUfunction *mathop,
int argc, char** argv, const char* cubin_name, const char* kernel_name)
{
CUdevice cuDevice;
CUT_DEVICE_INIT_DRV(cuDevice, argc, argv);
print_GetProperties(cuDevice);
CUresult status = cuCtxCreate( &_cuContext, 0, cuDevice );
if ( CUDA_SUCCESS != status ) {
Error(_cuContext, status);
}
else printf("(1) context creation successful\n");
char* module_path = cutFindFilePath(cubin_name, executablePath);
printf ("\t cubin:%s, path:%s, mmp_ptr:%lu\n", cubin_name, executablePath, module_path);
if(module_path != NULL)
printf ("\t cubin:%s, path:%s, module_path:%c%c%c%c\n", cubin_name, executablePath, *module_path, *(module_path+1), *(module_path+2), *(module_path+3));
char* data_path = "./data/";
size_t len_path = strlen(data_path);
size_t len_fn = strlen(cubin_name);
// printf ("Sizes: data:%lu, cubinname:%lu\n", len_path, len_fn);
char* module_path_new = (char*)malloc(sizeof(char) * (len_path + len_fn));
strcpy(module_path_new, data_path);
strcat(module_path_new, cubin_name);
strcat(module_path_new, "\0");
if (module_path_new == 0) {
status = CUDA_ERROR_NOT_FOUND;
Error(_cuContext, status);
}
FILE *fp = fopen(module_path_new,"r");
if( fp ) {
printf("(2) cubin_File found in modulepath:%s\n", module_path_new);
fclose(fp);
} else {
printf("(2) cubin file not exist: %s\n", module_path_new);
}
CUmodule cuModule;
status = cuModuleLoad(&cuModule, module_path_new);
cutFree(module_path_new);
if ( CUDA_SUCCESS != status ) {
Error(_cuContext, status);
}
else printf ("(3) module Load successful\n");
CUfunction cuFunction = 0;
status = cuModuleGetFunction(&cuFunction, cuModule, kernel_name);
if ( CUDA_SUCCESS != status) {
Error(_cuContext, status);
}
else printf ("(4) getFunction successful w/cuFunction\n");
*mathop = cuFunction;
return CUDA_SUCCESS;
}
/*
* Class: edu_syr_pcpratts_rootbeer_runtime2_cuda_CudaRuntime2
* Method: loadFunction
* Signature: ()V
*/
JNIEXPORT void JNICALL Java_edu_syr_pcpratts_rootbeer_runtime2_cuda_CudaRuntime2_loadFunction
(JNIEnv *env, jobject this_obj, jlong heap_end_ptr, jstring filename, jint num_blocks){
void * cubin_file;
int offset;
CUresult status;
char * native_filename;
heapEndPtr = heap_end_ptr;
native_filename = (*env)->GetStringUTFChars(env, filename, 0);
status = cuModuleLoad(&cuModule, native_filename);
CHECK_STATUS(env, "error in cuModuleLoad", status);
(*env)->ReleaseStringUTFChars(env, filename, native_filename);
status = cuModuleGetFunction(&cuFunction, cuModule, "_Z5entryPcS_PiPxS1_S0_S0_i");
CHECK_STATUS(env,"error in cuModuleGetFunction",status)
status = cuFuncSetCacheConfig(cuFunction, CU_FUNC_CACHE_PREFER_L1);
CHECK_STATUS(env,"error in cuFuncSetCacheConfig",status)
status = cuParamSetSize(cuFunction, (7 * sizeof(CUdeviceptr) + sizeof(int)));
CHECK_STATUS(env,"error in cuParamSetSize",status)
offset = 0;
status = cuParamSetv(cuFunction, offset, (void *) &gcInfoSpace, sizeof(CUdeviceptr));
CHECK_STATUS(env,"error in cuParamSetv gcInfoSpace",status)
offset += sizeof(CUdeviceptr);
status = cuParamSetv(cuFunction, offset, (void *) &gpuToSpace, sizeof(CUdeviceptr));
CHECK_STATUS(env,"error in cuParamSetv gpuToSpace",status)
offset += sizeof(CUdeviceptr);
status = cuParamSetv(cuFunction, offset, (void *) &gpuHandlesMemory, sizeof(CUdeviceptr));
CHECK_STATUS(env,"error in cuParamSetv gpuHandlesMemory %",status)
offset += sizeof(CUdeviceptr);
status = cuParamSetv(cuFunction, offset, (void *) &gpuHeapEndPtr, sizeof(CUdeviceptr));
CHECK_STATUS(env,"error in cuParamSetv gpuHeapEndPtr",status)
offset += sizeof(CUdeviceptr);
status = cuParamSetv(cuFunction, offset, (void *) &gpuBufferSize, sizeof(CUdeviceptr));
CHECK_STATUS(env,"error in cuParamSetv gpuBufferSize",status)
offset += sizeof(CUdeviceptr);
status = cuParamSetv(cuFunction, offset, (void *) &gpuExceptionsMemory, sizeof(CUdeviceptr));
CHECK_STATUS(env,"error in cuParamSetv gpuExceptionsMemory",status)
offset += sizeof(CUdeviceptr);
status = cuParamSetv(cuFunction, offset, (void *) &gpuClassMemory, sizeof(CUdeviceptr));
CHECK_STATUS(env,"error in cuParamSetv gpuClassMemory",status)
offset += sizeof(CUdeviceptr);
status = cuParamSeti(cuFunction, offset, num_blocks);
CHECK_STATUS(env,"error in cuParamSetv num_blocks",status)
offset += sizeof(int);
}
CUresult CuContext::LoadModuleFilename(const std::string& filename,
ModulePtr* ppModule) {
ModulePtr module(new CuModule);
CUresult result = cuModuleLoad(&module->_module, filename.c_str());
HANDLE_RESULT();
module->_context = this;
ppModule->swap(module);
return CUDA_SUCCESS;
}
/*
* Initializaiton in order to use kernel program
*/
void
init_cuda(void){
thread_num = (N <= 16) ? N : 16 ;
block_num = N / (thread_num*thread_num);
if(N % (thread_num*thread_num) != 0) block_num++;
res = cuInit(0);
if(res != CUDA_SUCCESS){
printf("cuInit failed: res = %s\n", conv(res));
exit(1);
}
res = cuDeviceGet(&dev, 0);
if(res != CUDA_SUCCESS){
printf("cuDeviceGet failed: res = %s\n", conv(res));
exit(1);
}
res = cuCtxCreate(&ctx, 0, dev);
if(res != CUDA_SUCCESS){
printf("cuCtxCreate failed: res = %s\n", conv(res));
exit(1);
}
res = cuModuleLoad(&module, "./cuda_main.cubin");
if(res != CUDA_SUCCESS){
printf("cuModuleLoad() failed: res = %s\n", conv(res));
exit(1);
}
res = cuModuleGetFunction(&function, module, "cuda_main");
if(res != CUDA_SUCCESS){
printf("cuModuleGetFunction() failed: res = %s\n", conv(res));
exit(1);
}
/*
* preparation for launch kernel
*/
res = cuFuncSetSharedSize(function, 0x40); /* just random */
if(res != CUDA_SUCCESS){
printf("cuFuncSetSharedSize() failed: res = %s\n", conv(res));
exit(1);
}
res = cuFuncSetBlockShape(function, thread_num, thread_num, 1);
if(res != CUDA_SUCCESS){
printf("cuFuncSetBlockShape() failed: res = %s\n", conv(res));
exit(1);
}
}
SEXP
R_auto_cuModuleLoad(SEXP r_fname)
{
SEXP r_ans = R_NilValue;
CUmodule module;
const char * fname = CHAR(STRING_ELT(r_fname, 0));
CUresult ans;
ans = cuModuleLoad(& module, fname);
if(ans)
return(R_cudaErrorInfo(ans));
r_ans = R_createRef(module, "CUmodule") ;
return(r_ans);
}
kernel_t<CUDA>* kernel_t<CUDA>::buildFromBinary(const std::string &filename,
const std::string &functionName_){
OCCA_EXTRACT_DATA(CUDA, Kernel);
functionName = functionName_;
OCCA_CUDA_CHECK("Kernel (" + functionName + ") : Loading Module",
cuModuleLoad(&data_.module, filename.c_str()));
OCCA_CUDA_CHECK("Kernel (" + functionName + ") : Loading Function",
cuModuleGetFunction(&data_.function, data_.module, functionName.c_str()));
return this;
}
int
main()
{
CUresult result;
result = cuInit(0);
CUdevice device;
result = cuDeviceGet(&device, 0);
CUcontext ctx;
result = cuCtxCreate(&ctx, 0, device);
CUmodule module;
result = cuModuleLoad(&module, "cuda-shift-throughput.cubin");
CUfunction kernel;
result = cuModuleGetFunction(&kernel, module, "kernel");
int block;
result = cuFuncGetAttribute(&block,
CU_FUNC_ATTRIBUTE_MAX_THREADS_PER_BLOCK,
kernel);
int grid = 1024 * 1024;
CUevent event[2];
for (ptrdiff_t i = 0; i < 2; ++i) {
result = cuEventCreate(&event[i], 0);
}
result = cuEventRecord(event[0], 0);
result = cuLaunchKernel(kernel, grid, 1, 1, block, 1, 1, 0, 0, 0, 0);
result = cuEventRecord(event[1], 0);
result = cuEventSynchronize(event[1]);
float time;
result = cuEventElapsedTime(&time, event[0], event[1]);
int gpuclock;
result =
cuDeviceGetAttribute(&gpuclock, CU_DEVICE_ATTRIBUTE_CLOCK_RATE, device);
int gpump;
result =
cuDeviceGetAttribute(&gpump, CU_DEVICE_ATTRIBUTE_MULTIPROCESSOR_COUNT,
device);
std::printf("Clock: %d KHz, # of MPs: %d\n", gpuclock, gpump);
std::printf("Elapsed Time: %f milliseconds\n", time);
std::printf("# of Threads: %d, # of SHLs : %lld\n", block,
1024ll * block * grid);
std::printf("Throughput: %f\n",
1024.0 * block * grid / ((double) gpump * gpuclock * time));
for (ptrdiff_t i = 0; i < 2; ++i) {
result = cuEventDestroy(event[i]);
}
result = cuModuleUnload(module);
result = cuCtxDestroy(ctx);
return 0;
}
CUresult initialize(int device, CUcontext *phContext, CUdevice *phDevice, CUmodule *phModule, CUstream *phStream)
{
// Initialize the device and create the context
cuInit(0);
cuDeviceGet(phDevice, device);
CUresult status = cuCtxCreate(phContext, 0, *phDevice);
if (status != CUDA_SUCCESS)
{std::cout << "ERROR: could not create context\n"; exit(0);}
status = cuModuleLoad(phModule, "PTXTestFunctions.o.ptx");
if (status != CUDA_SUCCESS)
{std::cout << "ERROR: could not load .ptx module: " << status << "\n"; exit(0);}
// Create stream
status = cuStreamCreate(phStream, 0);
if (status != CUDA_SUCCESS)
{printf("ERROR: during stream creation\n"); exit(0);}
return status;
}
int main(int argc, char ** argv)
{
int dev_count = 0;
CUdevice device;
CUcontext context;
CUmodule module;
CUfunction function;
cuInit(0);
cuDeviceGetCount(&dev_count);
if (dev_count < 1) return -1;
cuDeviceGet( &device, 0 );
cuCtxCreate( &context, 0, device );
cuModuleLoad( &module, "hello.cuda_runtime.ptx" );
cuModuleGetFunction( &function, module, "_Z6kernelPf" );
int N = 512;
CUdeviceptr pData;
cuMemAlloc( &pData, N * sizeof(float) );
cuFuncSetBlockShape( function, N, 1, 1 );
cuParamSeti( function, 0, pData );
cuParamSetSize( function, 4 );
cuLaunchGrid( function, 1, 1 );
float * pHostData = new float[N];
cuMemcpyDtoH( pHostData, pData, N * sizeof( float) );
cuMemFree( pData );
delete [] pHostData;
return 0;
}
int madd_gpu_init(struct device_info *device_info)
{
char fname[256];
CUresult res;
/* printf("madd_gpu_init called.\n"); */
/* Initialization */
if ((res = cuInit(0)) != CUDA_SUCCESS) {
printf("cuInit failed: res = %lu\n", (unsigned long)res);
return -1;
}
if ((res = cuDeviceGet(&device_info->dev, 0)) != CUDA_SUCCESS) {
printf("cuDeviceGet failed: res = %lu\n", (unsigned long)res);
return -1;
}
if ((res = cuCtxCreate(&device_info->context, 0, device_info->dev)) !=
CUDA_SUCCESS) {
printf("cuCtxCreate failed: res = %lu\n", (unsigned long)res);
return -1;
}
/* binary files are located in the same directory as the source code */
if ((res = cuModuleLoad(&device_info->module, MODULE_FILE_NAME)) !=
CUDA_SUCCESS) {
printf("cuModuleLoad() failed\n");
return -1;
}
if ((res = cuModuleGetFunction(&device_info->kernel,
device_info->module, KERNEL_NAME)) != CUDA_SUCCESS) {
printf("cuModuleGetFunction() failed\n");
return -1;
}
return 0;
}
kernel_t<CUDA>* kernel_t<CUDA>::buildFromSource(const std::string &filename,
const std::string &functionName_,
const kernelInfo &info_){
OCCA_EXTRACT_DATA(CUDA, Kernel);
functionName = functionName_;
kernelInfo info = info_;
std::string cachedBinary = getCachedBinaryName(filename, info);
struct stat buffer;
const bool fileExists = (stat(cachedBinary.c_str(), &buffer) == 0);
if(fileExists){
std::cout << "Found cached binary of [" << filename << "] in [" << cachedBinary << "]\n";
return buildFromBinary(cachedBinary, functionName);
}
if(!haveFile(cachedBinary)){
waitForFile(cachedBinary);
return buildFromBinary(cachedBinary, functionName);
}
std::string iCachedBinary = createIntermediateSource(filename,
cachedBinary,
info);
std::string libPath, soname;
getFilePrefixAndName(cachedBinary, libPath, soname);
std::string oCachedBinary = libPath + "o_" + soname + ".o";
std::string archSM = "";
if(dev->dHandle->compilerFlags.find("-arch=sm_") == std::string::npos){
std::stringstream archSM_;
int major, minor;
OCCA_CUDA_CHECK("Kernel (" + functionName + ") : Getting CUDA Device Arch",
cuDeviceComputeCapability(&major, &minor, data_.device) );
archSM_ << " -arch=sm_" << major << minor << ' ';
archSM = archSM_.str();
}
std::stringstream command;
//---[ PTX Check Command ]----------
if(dev->dHandle->compilerEnvScript.size())
command << dev->dHandle->compilerEnvScript << " && ";
command << dev->dHandle->compiler
<< ' ' << dev->dHandle->compilerFlags
<< archSM
<< " -Xptxas -v,-dlcm=cg,-abi=no"
<< ' ' << info.flags
<< " -x cu -c " << iCachedBinary
<< " -o " << oCachedBinary;
const std::string &ptxCommand = command.str();
std::cout << "Compiling [" << functionName << "]\n" << ptxCommand << "\n";
#if (OCCA_OS == LINUX_OS) || (OCCA_OS == OSX_OS)
const int ptxError = system(ptxCommand.c_str());
#else
const int ptxError = system(("\"" + ptxCommand + "\"").c_str());
#endif
// Not needed here I guess
// if(ptxError){
// releaseFile(cachedBinary);
// throw 1;
// }
//---[ Compiling Command ]----------
command.str("");
command << dev->dHandle->compiler
<< " -o " << cachedBinary
<< " -ptx -I."
<< ' ' << dev->dHandle->compilerFlags
<< archSM
<< ' ' << info.flags
<< " -x cu " << iCachedBinary;
const std::string &sCommand = command.str();
std::cout << sCommand << '\n';
const int compileError = system(sCommand.c_str());
if(compileError){
releaseFile(cachedBinary);
throw 1;
}
const CUresult moduleLoadError = cuModuleLoad(&data_.module,
cachedBinary.c_str());
if(moduleLoadError)
releaseFile(cachedBinary);
OCCA_CUDA_CHECK("Kernel (" + functionName + ") : Loading Module",
moduleLoadError);
const CUresult moduleGetFunctionError = cuModuleGetFunction(&data_.function,
data_.module,
functionName.c_str());
if(moduleGetFunctionError)
releaseFile(cachedBinary);
OCCA_CUDA_CHECK("Kernel (" + functionName + ") : Loading Function",
moduleGetFunctionError);
releaseFile(cachedBinary);
return this;
}
Object cuda_using_do_blockWidth_blockHeight_gridWidth_gridHeight(Object self, int nparts, int *argcv,
Object *argv, int flags) {
CUresult error;
cuInit(0);
int deviceCount = 0;
error = cuDeviceGetCount(&deviceCount);
if (deviceCount == 0) {
raiseError("No CUDA devices found");
}
CUdevice cuDevice;
CUcontext cuContext;
CUmodule cuModule;
CUfunction cuFunc;
error = cuDeviceGet(&cuDevice, 0);
error = cuCtxCreate(&cuContext, 0, cuDevice);
// do through gridWidth only have one argument each
int argOffset = argcv[0] + 1;
int blockDimX = integerfromAny(argv[argOffset++]);
int blockDimY = integerfromAny(argv[argOffset++]);
int gridDimX = integerfromAny(argv[argOffset++]);
int gridDimY = integerfromAny(argv[argOffset++]);
char *tmp = grcstring(argv[argcv[0]]);
char argStr[strlen(tmp) + 1];
strcpy(argStr, tmp);
char *tmp2 = strtok(argStr, " ");
char blockname[128];
strcpy(blockname, tmp2);
errcheck(cuModuleLoad(&cuModule, blockname));
CUdeviceptr dps[argcv[0]];
float floats[argcv[0]];
void *args[argcv[0]];
int ints[argcv[0]];
argStr[strlen(blockname)] = ' ';
strtok(argStr, " ");
for (int i=0; i<argcv[0]; i++) {
char *argType = strtok(NULL, " ");
if (argType[0] == 'f' && argType[1] == '*') {
struct CudaFloatArray *a = (struct CudaFloatArray *)argv[i];
errcheck(cuMemAlloc(&dps[i], a->size * sizeof(float)));
errcheck(cuMemcpyHtoD(dps[i], &a->data, a->size * sizeof(float)));
args[i] = &dps[i];
} else if (argType[0] == 'f') {
floats[i] = (float)*((double *)(argv[i]->data));
args[i] = &floats[i];
} else if (argType[0] == 'i') {
ints[i] = integerfromAny(argv[i]);
args[i] = &ints[i];
} else {
// Fail
char buf[256];
sprintf(buf, "CUDA argument cannot be coerced. This shouldn't happen. Argument string: %s\n", argType);
raiseError(buf);
}
}
char name[256];
strcpy(name, "block");
strcat(name, blockname + strlen("_cuda/"));
for (int i=0; name[i] != 0; i++)
if (name[i] == '.') {
name[i] = 0;
break;
}
errcheck(cuModuleGetFunction(&cuFunc, cuModule, name));
errcheck(cuLaunchKernel(cuFunc, gridDimX, gridDimY, 1,
blockDimX, blockDimY, 1,
0,
NULL, args, NULL));
for (int i=0; i<argcv[0]; i++) {
struct CudaFloatArray *a = (struct CudaFloatArray *)argv[i];
errcheck(cuMemcpyDtoH(&a->data, dps[i], a->size * sizeof(float)));
cuMemFree(dps[i]);
}
return alloc_none();
}
void test_tasks(unsigned int size, int nr_tasks)
{
int i;
pid_t pid;
int status;
CUresult res;
CUdevice dev;
CUcontext ctx;
CUdeviceptr data_addr;
CUmodule module;
CUfunction function;
unsigned int *in, *out;
unsigned int n = size / 4;
res = cuInit(0);
if (res != CUDA_SUCCESS) {
printf("cuInit failed: res = %u\n", res);
exit(-1);
}
res = cuDeviceGet(&dev, 0);
if (res != CUDA_SUCCESS) {
printf("cuDeviceGet failed: res = %u\n", res);
exit(-1);
}
res = cuCtxCreate(&ctx, 0, dev);
if (res != CUDA_SUCCESS) {
printf("cuCtxCreate failed: res = %u\n", res);
exit(-1);
}
res = cuMemAlloc(&data_addr, size);
if (res != CUDA_SUCCESS) {
printf("cuMemAlloc failed: res = %u\n", res);
exit(-1);
}
in = (unsigned int *) malloc(size);
out = (unsigned int *) malloc(size);
res = cuMemcpyHtoD(data_addr, in, size);
if (res != CUDA_SUCCESS) {
printf("cuMemcpyHtoD failed: res = %u\n", res);
exit(-1);
}
#if 1
res = cuModuleLoad(&module, "./loop_gpu.cubin");
if (res != CUDA_SUCCESS) {
printf("cuModuleLoad() failed\n");
exit(-1);
}
res = cuModuleGetFunction(&function, module, "_Z4loopPjjj");
if (res != CUDA_SUCCESS) {
printf("cuModuleGetFunction() failed\n");
exit(-1);
}
void *param1[] = {&data_addr, &size, &n};
//res = cuLaunchKernel(function, 1, 1, 1, 1, 1, 1, 0, 0, (void**)param1, 0);
if (res != CUDA_SUCCESS) {
printf("cuLaunchKernel failed: res = %u\n", res);
exit(-1);
}
//cuCtxSynchronize();
#endif
if (--nr_tasks) {
pid = fork();
if (pid == 0) { /* child */
test_tasks(size, nr_tasks);
printf("Child finished\n");
exit(0);
}
else { /* parent */
waitpid(pid, &status, 0);
}
}
#if 0
res = cuModuleLoad(&module, "./loop_gpu.cubin");
if (res != CUDA_SUCCESS) {
printf("cuModuleLoad() failed\n");
exit(-1);
}
res = cuModuleGetFunction(&function, module, "_Z4loopPjjj");
if (res != CUDA_SUCCESS) {
printf("cuModuleGetFunction() failed\n");
exit(-1);
}
void *param1[] = {&data_addr, &size, &n};
res = cuLaunchKernel(function, 1, 1, 1, 1, 1, 1, 0, 0, (void**)param1, 0);
if (res != CUDA_SUCCESS) {
printf("cuLaunchKernel failed: res = %u\n", res);
exit(-1);
}
#endif
res = cuMemcpyDtoH(out, data_addr, size);
if (res != CUDA_SUCCESS) {
printf("cuMemcpyDtoH failed: res = %u\n", res);
exit(-1);
}
res = cuModuleUnload(module);
if (res != CUDA_SUCCESS) {
printf("cuModuleUnload failed: res = %lu\n", res);
exit(-1);
}
res = cuMemFree(data_addr);
if (res != CUDA_SUCCESS) {
printf("cuMemFree failed: res = %u\n", res);
exit(-1);
}
res = cuCtxDestroy(ctx);
if (res != CUDA_SUCCESS) {
printf("cuCtxDestroy failed: res = %u\n", (unsigned int)res);
exit(-1);
}
free(in);
free(out);
}
int main() {
CU_ERROR_CHECK(cuInit(0));
int count;
CU_ERROR_CHECK(cuDeviceGetCount(&count));
count = (count > 2) ? 2 : count;
CUdevice devices[count];
for (int i = 0; i < count; i++)
CU_ERROR_CHECK(cuDeviceGet(&devices[i], i));
// Question 1: Can you create multiple contexts on the same device?
{
fprintf(stderr, "Attempting to create multiple contexts on each device...\n");
CUcontext contexts[count * N];
size_t j = 0;
for (int i = 0; i < count; i++) {
CUresult error = CUDA_SUCCESS;
size_t k;
for (k = 0; k < N && error == CUDA_SUCCESS; k++) {
error = cuCtxCreate(&contexts[j], CU_CTX_SCHED_AUTO, devices[i]);
if (error == CUDA_SUCCESS)
CU_ERROR_CHECK(cuCtxPopCurrent(&contexts[j++]));
}
fprintf(stderr, " created %zu contexts on device %d before cuCtxCreate returned \"%s\"\n", (k - 1), i, cuGetErrorString(error));
}
CUresult error = CUDA_SUCCESS;
size_t k;
for (k = 0; k < j && error == CUDA_SUCCESS; k++)
error = cuCtxPushCurrent(contexts[k]);
if (error == CUDA_SUCCESS)
fprintf(stderr, " successfully pushed %zu contexts with cuCtxPushCurrent\n", k);
else
fprintf(stderr, " pushed %zu contexts before cuCtxPushCurrent returned \"%s\"\n", (k - 1), cuGetErrorString(error));
for (size_t k = 0; k < j; k++)
CU_ERROR_CHECK(cuCtxDestroy(contexts[k]));
fprintf(stderr, "\n");
}
CUcontext contexts[count][2];
for (int i = 0; i < count; i++) {
for (size_t j = 0; j < 2; j++) {
CU_ERROR_CHECK(cuCtxCreate(&contexts[i][j], CU_CTX_SCHED_AUTO, devices[i]));
CU_ERROR_CHECK(cuCtxPopCurrent(&contexts[i][j]));
}
}
// Question 2: Can you access a host pointer in a different context from
// which it was created?
// Question 3: Can you free a host pointer in a different context from which
// it was created?
{
void * hPtr;
CU_ERROR_CHECK(cuCtxPushCurrent(contexts[0][0]));
CU_ERROR_CHECK(cuMemAllocHost(&hPtr, 1024));
CU_ERROR_CHECK(cuCtxPopCurrent(&contexts[0][0]));
CUdeviceptr dPtr[count];
CU_ERROR_CHECK(cuCtxPushCurrent(contexts[0][1]));
CU_ERROR_CHECK(cuMemAlloc(&dPtr[0], 1024)); // Different context, same device
fprintf(stderr, "Accessing a host pointer from a different context to which it was allocated (on the same device) returns \"%s\"\n", cuGetErrorString(cuMemcpyHtoD(dPtr[0], hPtr, 1024)));
CU_ERROR_CHECK(cuMemFree(dPtr[0]));
CU_ERROR_CHECK(cuCtxPopCurrent(&contexts[0][1]));
if (count > 1) {
CU_ERROR_CHECK(cuCtxPushCurrent(contexts[1][0]));
CU_ERROR_CHECK(cuMemAlloc(&dPtr[1], 1024)); // Different context, different device
fprintf(stderr, "Accessing a host pointer from a different context to which it was allocated (on a different device) returns \"%s\"\n", cuGetErrorString(cuMemcpyHtoD(dPtr[1], hPtr, 1024)));
CU_ERROR_CHECK(cuMemFree(dPtr[1]));
CU_ERROR_CHECK(cuCtxPopCurrent(&contexts[1][0]));
}
fprintf(stderr, "\n");
CUresult error = CUDA_ERROR_UNKNOWN;
if (count > 1) {
CU_ERROR_CHECK(cuCtxPushCurrent(contexts[1][0]));
error = cuMemFreeHost(hPtr);
fprintf(stderr, "Freeing a host pointer from a different context to which it was allocated (on a different device) returns \"%s\"\n", cuGetErrorString(error));
CU_ERROR_CHECK(cuCtxPopCurrent(&contexts[1][0]));
}
if (error != CUDA_SUCCESS) {
CU_ERROR_CHECK(cuCtxPushCurrent(contexts[0][1]));
error = cuMemFreeHost(hPtr);
fprintf(stderr, "Freeing a host pointer from a different context to which it was allocated (on the same device) returns \"%s\"\n", cuGetErrorString(error));
CU_ERROR_CHECK(cuCtxPopCurrent(&contexts[0][1]));
}
if (error != CUDA_SUCCESS) {
CU_ERROR_CHECK(cuCtxPushCurrent(contexts[0][0]));
error = cuMemFreeHost(hPtr);
fprintf(stderr, "Freeing a host pointer from the same context to which it was allocated returns \"%s\"\n", cuGetErrorString(error));
CU_ERROR_CHECK(cuCtxPopCurrent(&contexts[0][0]));
}
fprintf(stderr, "\n");
}
// Question 4: Can you access a device pointer in a different context from
// which it was created?
// Question 5: Can you free a device pointer in a different context from which
// it was created?
{
CUdeviceptr dPtr[count][2];
CU_ERROR_CHECK(cuCtxPushCurrent(contexts[0][0]));
CU_ERROR_CHECK(cuMemAlloc(&dPtr[0][0], 1024));
CU_ERROR_CHECK(cuCtxPopCurrent(&contexts[0][0]));
CU_ERROR_CHECK(cuCtxPushCurrent(contexts[0][1]));
CU_ERROR_CHECK(cuMemAlloc(&dPtr[0][1], 1024));
CU_ERROR_CHECK(cuCtxPopCurrent(&contexts[0][1]));
CU_ERROR_CHECK(cuCtxPushCurrent(contexts[0][1]));
fprintf(stderr, "Accessing a device pointer from a different context to which it was allocated (on the same device) returns \"%s\"\n", cuGetErrorString(cuMemcpyDtoD(dPtr[0][0], dPtr[0][1], 1024)));
CU_ERROR_CHECK(cuMemFree(dPtr[0][1]));
CU_ERROR_CHECK(cuCtxPopCurrent(&contexts[0][1]));
if (count > 1) {
CU_ERROR_CHECK(cuCtxPushCurrent(contexts[1][0]));
CU_ERROR_CHECK(cuMemAlloc(&dPtr[1][0], 1024)); // Different context, different device
fprintf(stderr, "Accessing a device pointer from a different context to which it was allocated (on a different device) returns \"%s\"\n", cuGetErrorString(cuMemcpyDtoD(dPtr[0][0], dPtr[1][0], 1024)));
CU_ERROR_CHECK(cuMemFree(dPtr[1][0]));
CU_ERROR_CHECK(cuCtxPopCurrent(&contexts[1][0]));
}
fprintf(stderr, "\n");
CUresult error = CUDA_ERROR_UNKNOWN;
if (count > 1) {
CU_ERROR_CHECK(cuCtxPushCurrent(contexts[1][0]));
error = cuMemFree(dPtr[0][0]);
fprintf(stderr, "Freeing a device pointer from a different context to which it was allocated (on a different device) returns \"%s\"\n", cuGetErrorString(error));
CU_ERROR_CHECK(cuCtxPopCurrent(&contexts[1][0]));
}
if (error != CUDA_SUCCESS) {
CU_ERROR_CHECK(cuCtxPushCurrent(contexts[0][1]));
error = cuMemFree(dPtr[0][0]);
fprintf(stderr, "Freeing a device pointer from a different context to which it was allocated (on the same device) returns \"%s\"\n", cuGetErrorString(error));
CU_ERROR_CHECK(cuCtxPopCurrent(&contexts[0][1]));
}
if (error != CUDA_SUCCESS) {
CU_ERROR_CHECK(cuCtxPushCurrent(contexts[0][0]));
error = cuMemFree(dPtr[0][0]);
fprintf(stderr, "Freeing a device pointer from the same context to which it was allocated returns \"%s\"\n", cuGetErrorString(error));
CU_ERROR_CHECK(cuCtxPopCurrent(&contexts[0][0]));
}
fprintf(stderr, "\n");
}
// Question 6: Can you access a module in a different context from which it
// was loaded?
// Question 7: Can you unload a module in a different context from which it
// was loaded?
{
CUmodule module;
CUdeviceptr ptr;
CU_ERROR_CHECK(cuCtxPushCurrent(contexts[0][0]));
CU_ERROR_CHECK(cuModuleLoad(&module, "kernel-test.ptx"));
CU_ERROR_CHECK(cuMemAlloc(&ptr, sizeof(float)));
CU_ERROR_CHECK(cuCtxPopCurrent(&contexts[0][0]));
CUfunction function = 0;
if (count > 0) {
CU_ERROR_CHECK(cuCtxPushCurrent(contexts[1][0]));
fprintf(stderr, "Getting a function pointer from a different context to which it was loaded (on a different device) returns \"%s\"\n", cuGetErrorString(cuModuleGetFunction(&function, module, "kernel")));
CU_ERROR_CHECK(cuCtxPopCurrent(&contexts[1][0]));
}
if (function == 0) {
CU_ERROR_CHECK(cuCtxPushCurrent(contexts[0][1]));
fprintf(stderr, "Getting a function pointer from a different context to which it was loaded (on the same device) returns \"%s\"\n", cuGetErrorString(cuModuleGetFunction(&function, module, "kernel")));
CU_ERROR_CHECK(cuCtxPopCurrent(&contexts[0][1]));
}
if (function == 0) {
CU_ERROR_CHECK(cuCtxPushCurrent(contexts[0][0]));
fprintf(stderr, "Getting a function pointer from the same context to which it was loaded returns \"%s\"\n", cuGetErrorString(cuModuleGetFunction(&function, module, "kernel")));
CU_ERROR_CHECK(cuCtxPopCurrent(&contexts[0][0]));
}
fprintf(stderr, "\n");
CUdeviceptr a, b;
CU_ERROR_CHECK(cuCtxPushCurrent(contexts[0][0]));
CU_ERROR_CHECK(cuMemAlloc(&a, sizeof(float)));
CU_ERROR_CHECK(cuMemAlloc(&b, sizeof(float)));
CU_ERROR_CHECK(cuCtxPopCurrent(&contexts[0][0]));
void * params[] = { &a, & b };
CUresult error = CUDA_ERROR_UNKNOWN;
if (count > 0) {
CU_ERROR_CHECK(cuCtxPushCurrent(contexts[1][0]));
fprintf(stderr, "Launching a function from a different context to which it was loaded (on a different device) returns \"%s\"\n", cuGetErrorString(error = cuLaunchKernel(function, 1, 1, 1, 1, 1, 1, 0, 0, params, NULL)));
CU_ERROR_CHECK(cuCtxPopCurrent(&contexts[1][0]));
}
if (error != CUDA_SUCCESS) {
CU_ERROR_CHECK(cuCtxPushCurrent(contexts[0][1]));
fprintf(stderr, "Launching a function from a different context to which it was loaded (on the same device) returns \"%s\"\n", cuGetErrorString(error = cuLaunchKernel(function, 1, 1, 1, 1, 1, 1, 0, 0, params, NULL)));
CU_ERROR_CHECK(cuCtxPopCurrent(&contexts[0][1]));
}
if (error != CUDA_SUCCESS) {
CU_ERROR_CHECK(cuCtxPushCurrent(contexts[0][0]));
fprintf(stderr, "Launching a function from the same context to which it was loaded returns \"%s\"\n", cuGetErrorString(error = cuLaunchKernel(function, 1, 1, 1, 1, 1, 1, 0, 0, params, NULL)));
CU_ERROR_CHECK(cuCtxPopCurrent(&contexts[0][0]));
}
fprintf(stderr, "\n");
error = CUDA_ERROR_UNKNOWN;
if (count > 0) {
CU_ERROR_CHECK(cuCtxPushCurrent(contexts[1][0]));
fprintf(stderr, "Unloading a module from a different context to which it was loaded (on a different device) returns \"%s\"\n", cuGetErrorString(error = cuModuleUnload(module)));
CU_ERROR_CHECK(cuCtxPopCurrent(&contexts[1][0]));
}
if (error != CUDA_SUCCESS) {
CU_ERROR_CHECK(cuCtxPushCurrent(contexts[0][1]));
fprintf(stderr, "Unloading a module from a different context to which it was loaded (on the same device) returns \"%s\"\n", cuGetErrorString(error = cuModuleUnload(module)));
CU_ERROR_CHECK(cuCtxPopCurrent(&contexts[0][1]));
}
if (error != CUDA_SUCCESS) {
CU_ERROR_CHECK(cuCtxPushCurrent(contexts[0][0]));
fprintf(stderr, "Unloading a module from the same context to which it was loaded returns \"%s\"\n", cuGetErrorString(error = cuModuleUnload(module)));
CU_ERROR_CHECK(cuCtxPopCurrent(&contexts[0][0]));
}
CU_ERROR_CHECK(cuCtxPushCurrent(contexts[0][0]));
CU_ERROR_CHECK(cuMemFree(a));
CU_ERROR_CHECK(cuMemFree(b));
CU_ERROR_CHECK(cuCtxPopCurrent(&contexts[0][0]));
}
for (int i = 0; i < count; i++) {
for (size_t j = 0; j < 2; j++)
CU_ERROR_CHECK(cuCtxDestroy(contexts[i][j]));
}
return 0;
}
int cuda_test_madd_vmmap_hybrid(unsigned int n, char *path)
{
int i, j, idx;
CUresult res;
CUdevice dev;
CUcontext ctx;
CUfunction function;
CUmodule module;
CUdeviceptr a_dev, b_dev, c_dev;
unsigned int *a_buf, *b_buf, *c_buf;
unsigned long long int a_phys, b_phys, c_phys;
unsigned int *c = (unsigned int *) malloc (n*n * sizeof(unsigned int));
int block_x, block_y, grid_x, grid_y;
char fname[256];
int ret = 0;
struct timeval tv;
struct timeval tv_total_start, tv_total_end;
float total;
struct timeval tv_h2d_start, tv_h2d_end;
float h2d;
struct timeval tv_d2h_start, tv_d2h_end;
float d2h;
struct timeval tv_exec_start, tv_exec_end;
struct timeval tv_mem_alloc_start;
struct timeval tv_data_init_start;
float data_init;
struct timeval tv_conf_kern_start;
struct timeval tv_close_start;
float mem_alloc;
float exec;
float init_gpu;
float configure_kernel;
float close_gpu;
float data_read;
unsigned int dummy_b, dummy_c;
/* block_x * block_y should not exceed 512. */
block_x = n < 16 ? n : 16;
block_y = n < 16 ? n : 16;
grid_x = n / block_x;
if (n % block_x != 0)
grid_x++;
grid_y = n / block_y;
if (n % block_y != 0)
grid_y++;
gettimeofday(&tv_total_start, NULL);
res = cuInit(0);
if (res != CUDA_SUCCESS) {
printf("cuInit failed: res = %lu\n", (unsigned long)res);
return -1;
}
res = cuDeviceGet(&dev, 0);
if (res != CUDA_SUCCESS) {
printf("cuDeviceGet failed: res = %lu\n", (unsigned long)res);
return -1;
}
res = cuCtxCreate(&ctx, 0, dev);
if (res != CUDA_SUCCESS) {
printf("cuCtxCreate failed: res = %lu\n", (unsigned long)res);
return -1;
}
sprintf(fname, "%s/madd_gpu.cubin", path);
res = cuModuleLoad(&module, fname);
if (res != CUDA_SUCCESS) {
printf("cuModuleLoad() failed\n");
return -1;
}
res = cuModuleGetFunction(&function, module, "_Z3addPjS_S_j");
if (res != CUDA_SUCCESS) {
printf("cuModuleGetFunction() failed\n");
return -1;
}
res = cuFuncSetBlockShape(function, block_x, block_y, 1);
if (res != CUDA_SUCCESS) {
printf("cuFuncSetBlockShape() failed\n");
return -1;
}
gettimeofday(&tv_mem_alloc_start, NULL);
/* a[] */
res = cuMemAlloc(&a_dev, n*n * sizeof(unsigned int));
if (res != CUDA_SUCCESS) {
printf("cuMemAlloc (a) failed\n");
return -1;
}
res = cuMemMap((void**)&a_buf, a_dev, n*n * sizeof(unsigned int));
if (res != CUDA_SUCCESS) {
printf("cuMemMap (a) failed\n");
return -1;
}
res = cuMemGetPhysAddr(&a_phys, (void*)a_buf);
if (res != CUDA_SUCCESS) {
printf("cuMemGetPhysAddress (a) failed\n");
return -1;
}
/*printf("a[]: Physical Address 0x%llx\n", a_phys);*/
/* b[] */
res = cuMemAlloc(&b_dev, n*n * sizeof(unsigned int));
if (res != CUDA_SUCCESS) {
printf("cuMemAlloc (b) failed\n");
return -1;
}
res = cuMemMap((void**)&b_buf, b_dev, n*n * sizeof(unsigned int));
if (res != CUDA_SUCCESS) {
printf("cuMemMap (b) failed\n");
return -1;
}
res = cuMemGetPhysAddr(&b_phys, (void*)b_buf);
if (res != CUDA_SUCCESS) {
printf("cuMemGetPhysAddress (b) failed\n");
return -1;
}
/*printf("b[]: Physical Address 0x%llx\n", b_phys);*/
/* c[] */
res = cuMemAlloc(&c_dev, n*n * sizeof(unsigned int));
if (res != CUDA_SUCCESS) {
printf("cuMemAlloc (c) failed\n");
return -1;
}
res = cuMemMap((void**)&c_buf, c_dev, n*n * sizeof(unsigned int));
if (res != CUDA_SUCCESS) {
printf("cuMemMap (c) failed\n");
return -1;
}
res = cuMemGetPhysAddr(&c_phys, (void*)c_buf);
if (res != CUDA_SUCCESS) {
printf("cuMemGetPhysAddress (c) failed\n");
return -1;
}
/*printf("c[]: Physical Address 0x%llx\n", c_phys);*/
gettimeofday(&tv_data_init_start, NULL);
/* initialize A[] & B[] */
for (i = 0; i < n; i++) {
idx = i*n;
for(j = 0; j < n; j++) {
a_buf[idx++] = i;
}
}
for (i = 0; i < n; i++) {
idx = i*n;
for(j = 0; j < n; j++) {
b_buf[idx++] = i;
}
}
gettimeofday(&tv_h2d_start, NULL);
gettimeofday(&tv_h2d_end, NULL);
gettimeofday(&tv_conf_kern_start, NULL);
/* set kernel parameters */
res = cuParamSeti(function, 0, a_dev);
if (res != CUDA_SUCCESS) {
printf("cuParamSeti (a) failed: res = %lu\n", (unsigned long)res);
return -1;
}
res = cuParamSeti(function, 4, a_dev >> 32);
if (res != CUDA_SUCCESS) {
printf("cuParamSeti (a) failed: res = %lu\n", (unsigned long)res);
return -1;
}
res = cuParamSeti(function, 8, b_dev);
if (res != CUDA_SUCCESS) {
printf("cuParamSeti (b) failed: res = %lu\n", (unsigned long)res);
return -1;
}
res = cuParamSeti(function, 12, b_dev >> 32);
if (res != CUDA_SUCCESS) {
printf("cuParamSeti (b) failed: res = %lu\n", (unsigned long)res);
return -1;
}
res = cuParamSeti(function, 16, c_dev);
if (res != CUDA_SUCCESS) {
printf("cuParamSeti (c) failed: res = %lu\n", (unsigned long)res);
return -1;
}
res = cuParamSeti(function, 20, c_dev >> 32);
if (res != CUDA_SUCCESS) {
printf("cuParamSeti (c) failed: res = %lu\n", (unsigned long)res);
return -1;
}
res = cuParamSeti(function, 24, n);
if (res != CUDA_SUCCESS) {
printf("cuParamSeti (c) failed: res = %lu\n", (unsigned long)res);
return -1;
}
res = cuParamSetSize(function, 28);
if (res != CUDA_SUCCESS) {
printf("cuParamSetSize failed: res = %lu\n", (unsigned long)res);
return -1;
}
gettimeofday(&tv_exec_start, NULL);
/* launch the kernel */
res = cuLaunchGrid(function, grid_x, grid_y);
if (res != CUDA_SUCCESS) {
printf("cuLaunchGrid failed: res = %lu\n", (unsigned long)res);
return -1;
}
cuCtxSynchronize();
gettimeofday(&tv_exec_end, NULL);
gettimeofday(&tv_d2h_start, NULL);
/* download c[] */
memcpy(c, c_buf, n*n*sizeof(unsigned int));
gettimeofday(&tv_d2h_end, NULL);
/* Read back */
for (i = 0; i < n; i++) {
idx = i*n;
for(j = 0; j < n; j++) {
dummy_c = c[idx++];
}
}
gettimeofday(&tv_close_start, NULL);
res = cuMemUnmap((void*)a_buf);
if (res != CUDA_SUCCESS) {
printf("cuMemUnmap (a) failed: res = %lu\n", (unsigned long)res);
return -1;
}
res = cuMemFree(a_dev);
if (res != CUDA_SUCCESS) {
printf("cuMemFree (a) failed: res = %lu\n", (unsigned long)res);
return -1;
}
res = cuMemUnmap((void*)b_buf);
if (res != CUDA_SUCCESS) {
printf("cuMemUnmap (b) failed: res = %lu\n", (unsigned long)res);
return -1;
}
res = cuMemFree(b_dev);
if (res != CUDA_SUCCESS) {
printf("cuMemFree (b) failed: res = %lu\n", (unsigned long)res);
return -1;
}
res = cuMemUnmap((void*)c_buf);
if (res != CUDA_SUCCESS) {
printf("cuMemUnmap (c) failed: res = %lu\n", (unsigned long)res);
return -1;
}
res = cuMemFree(c_dev);
if (res != CUDA_SUCCESS) {
printf("cuMemFree (c) failed: res = %lu\n", (unsigned long)res);
return -1;
}
res = cuModuleUnload(module);
if (res != CUDA_SUCCESS) {
printf("cuModuleUnload failed: res = %lu\n", (unsigned long)res);
return -1;
}
res = cuCtxDestroy(ctx);
if (res != CUDA_SUCCESS) {
printf("cuCtxDestroy failed: res = %lu\n", (unsigned long)res);
return -1;
}
gettimeofday(&tv_total_end, NULL);
tvsub(&tv_mem_alloc_start, &tv_total_start, &tv);
init_gpu = tv.tv_sec * 1000.0 + (float) tv.tv_usec / 1000.0;
tvsub(&tv_data_init_start, &tv_mem_alloc_start, &tv);
mem_alloc = tv.tv_sec * 1000.0 + (float) tv.tv_usec / 1000.0;
tvsub(&tv_h2d_start, &tv_data_init_start, &tv);
data_init = tv.tv_sec * 1000.0 + (float) tv.tv_usec / 1000.0;
tvsub(&tv_h2d_end, &tv_h2d_start, &tv);
h2d = tv.tv_sec * 1000.0 + (float) tv.tv_usec / 1000.0;
tvsub(&tv_exec_start, &tv_conf_kern_start, &tv);
configure_kernel = tv.tv_sec * 1000.0 + (float) tv.tv_usec / 1000.0;
tvsub(&tv_exec_end, &tv_exec_start, &tv);
exec = tv.tv_sec * 1000.0 + (float) tv.tv_usec / 1000.0;
tvsub(&tv_d2h_end, &tv_d2h_start, &tv);
d2h = tv.tv_sec * 1000.0 + (float) tv.tv_usec / 1000.0;
tvsub(&tv_close_start, &tv_d2h_end, &tv);
data_read = tv.tv_sec * 1000.0 + (float) tv.tv_usec / 1000.0;
tvsub(&tv_total_end, &tv_close_start, &tv);
close_gpu = tv.tv_sec * 1000.0 + (float) tv.tv_usec / 1000.0;
tvsub(&tv_total_end, &tv_total_start, &tv);
total = tv.tv_sec * 1000.0 + (float) tv.tv_usec / 1000.0;
printf("Init: %f\n", init_gpu);
printf("MemAlloc: %f\n", mem_alloc);
printf("DataInit: %f\n", data_init);
printf("HtoD: %f\n", h2d);
printf("KernConf: %f\n", configure_kernel);
printf("Exec: %f\n", exec);
printf("DtoH: %f\n", d2h);
printf("DataRead: %f\n", data_read);
printf("Close: %f\n", close_gpu);
printf("Total: %f\n", total);
return ret;
}
int
main (int argc, char **argv)
{
CUdevice dev;
CUfunction delay;
CUmodule module;
CUresult r;
CUstream stream;
unsigned long *a, *d_a, dticks;
int nbytes;
float dtime;
void *kargs[2];
int clkrate;
int devnum, nprocs;
acc_init (acc_device_nvidia);
devnum = acc_get_device_num (acc_device_nvidia);
r = cuDeviceGet (&dev, devnum);
if (r != CUDA_SUCCESS)
{
fprintf (stderr, "cuDeviceGet failed: %d\n", r);
abort ();
}
r =
cuDeviceGetAttribute (&nprocs, CU_DEVICE_ATTRIBUTE_MULTIPROCESSOR_COUNT,
dev);
if (r != CUDA_SUCCESS)
{
fprintf (stderr, "cuDeviceGetAttribute failed: %d\n", r);
abort ();
}
r = cuDeviceGetAttribute (&clkrate, CU_DEVICE_ATTRIBUTE_CLOCK_RATE, dev);
if (r != CUDA_SUCCESS)
{
fprintf (stderr, "cuDeviceGetAttribute failed: %d\n", r);
abort ();
}
r = cuModuleLoad (&module, "subr.ptx");
if (r != CUDA_SUCCESS)
{
fprintf (stderr, "cuModuleLoad failed: %d\n", r);
abort ();
}
r = cuModuleGetFunction (&delay, module, "delay");
if (r != CUDA_SUCCESS)
{
fprintf (stderr, "cuModuleGetFunction failed: %d\n", r);
abort ();
}
nbytes = nprocs * sizeof (unsigned long);
dtime = 200.0;
dticks = (unsigned long) (dtime * clkrate);
a = (unsigned long *) malloc (nbytes);
d_a = (unsigned long *) acc_malloc (nbytes);
acc_map_data (a, d_a, nbytes);
kargs[0] = (void *) &d_a;
kargs[1] = (void *) &dticks;
r = cuStreamCreate (&stream, CU_STREAM_DEFAULT);
if (r != CUDA_SUCCESS)
{
fprintf (stderr, "cuStreamCreate failed: %d\n", r);
abort ();
}
if (!acc_set_cuda_stream (0, stream))
abort ();
r = cuLaunchKernel (delay, 1, 1, 1, 1, 1, 1, 0, stream, kargs, 0);
if (r != CUDA_SUCCESS)
{
fprintf (stderr, "cuLaunchKernel failed: %d\n", r);
abort ();
}
if (acc_async_test_all () != 0)
{
fprintf (stderr, "asynchronous operation not running\n");
abort ();
}
sleep ((int) (dtime / 1000.f) + 1);
if (acc_async_test_all () != 1)
{
fprintf (stderr, "found asynchronous operation still running\n");
abort ();
}
acc_unmap_data (a);
free (a);
acc_free (d_a);
acc_shutdown (acc_device_nvidia);
exit (0);
}
CudaModule::CudaModule(const std::string& cubinFile)
{
staticInit();
checkError("cuModuleLoad", cuModuleLoad(&m_module, cubinFile.c_str()));
}
int main( int argc, char **argv )
{
CUdevice main_device = 0;
CUcontext main_context = nullptr;
CUmodule mod_vectorAdd = nullptr;
CUfunction fun_vectorAdd = nullptr;
std::string path_vectorAdd( "D:/devel/vectoradd-cuda-driverAPI/vectorAdd.cu" );
std::string ptx_vectorAdd ( "D:/devel/vectoradd-cuda-driverAPI/vectorAdd.ptx" );
CUdeviceptr input_data = 0u;
CUdeviceptr output_data = 0u;
std::size_t problem_size = 1024;
try
{
//Initialize the driver API
check_error( cuInit( 0u ) );
{
int device_count = 0u;
check_error( cuDeviceGetCount( &device_count ) );
if( ! device_count )
{
std::cerr << "No CUDA devices available" << std::endl;
throw CUDA_ERROR_NO_DEVICE;
}
}
check_error( cuDeviceGet( &main_device, 0 ) );
check_error( cuCtxCreate( &main_context, 0, main_device ) );
//Try to manually compile the source file
{
std::stringstream build_command;
build_command <<
"nvcc "
"-ptx "
"-o " << ptx_vectorAdd << " " <<
path_vectorAdd;
if( int build_status = system( build_command.str( ).c_str( ) ) )
{
std::cerr << "Failed to compile source cuda file into a ptx assembly" << std::endl;
throw CUDA_ERROR_UNKNOWN;
}
//Find module entry with assembly
std::string str_assembly;
{
std::ifstream fassembly( ptx_vectorAdd );
if( !fassembly.is_open( ) )
{
std::cerr << "'Vector Add' assembly unavailable" << std::endl;
throw CUDA_ERROR_FILE_NOT_FOUND;
}
fassembly.seekg (0, std::ios::end);
str_assembly.resize( std::string::size_type( fassembly.tellg() ) );
fassembly.seekg (0, std::ios::beg);
fassembly.read( &str_assembly[0], str_assembly.size( ) );
fassembly.close( );
}
auto entry_pos = str_assembly.find( ".entry" );
if( entry_pos == std::string::npos )
{
std::cerr << "No entry point in 'Vector Add'" << std::endl;
throw CUDA_ERROR_INVALID_SOURCE;
}
entry_pos += 6u; //".entry".size( )
auto search_limit = str_assembly.find_first_of( " (", entry_pos );
if( search_limit == std::string::npos )
{
std::cerr << "No entry point in 'Vector Add'" << std::endl;
throw CUDA_ERROR_INVALID_SOURCE;
}
std::string funcName( str_assembly.substr( entry_pos, search_limit ) );
check_error( cuModuleLoad ( &mod_vectorAdd, ptx_vectorAdd.c_str( ) ) );
check_error( cuModuleGetFunction ( &fun_vectorAdd, mod_vectorAdd, funcName.c_str( ) ) );
}
//Play with buffer
cuMemAlloc( &input_data, problem_size * sizeof( float ) );
cuMemAlloc( &output_data, problem_size * sizeof( float ) );
{
int threadsPerBlock = 256;
int blocksPerGrid = (problem_size + threadsPerBlock - 1) / threadsPerBlock;
void* args[] = { &input_data, &output_data, &problem_size };
cuLaunchKernel(
fun_vectorAdd,
blocksPerGrid, 1, 1,
threadsPerBlock, 1, 1,
0,
0,
args,
nullptr);
}
float* result = new float[problem_size];
cuMemcpyDtoH( result, output_data, problem_size * sizeof( float ) );
std::copy(
result, result + problem_size,
std::ostream_iterator<float>(std::cout, ", ") );
delete[] result;
if( output_data ) cuMemFree ( output_data );
if( input_data ) cuMemFree ( input_data );
if( mod_vectorAdd ) cuModuleUnload ( mod_vectorAdd );
if( main_context ) cuCtxDestroy ( main_context );
}
catch( int return_code )
{
if( output_data ) cuMemFree ( output_data );
if( input_data ) cuMemFree ( input_data );
if( mod_vectorAdd ) cuModuleUnload ( mod_vectorAdd );
if( main_context ) cuCtxDestroy ( main_context );
system("PAUSE");
return return_code;
int cuda_test_fmadd(unsigned int n, char *path)
{
int i, j, idx;
CUresult res;
CUdevice dev;
CUcontext ctx;
CUfunction function;
CUmodule module;
CUdeviceptr a_dev, b_dev, c_dev;
float *a = (float *) malloc (n*n * sizeof(float));
float *b = (float *) malloc (n*n * sizeof(float));
float *c = (float *) malloc (n*n * sizeof(float));
int block_x, block_y, grid_x, grid_y;
int offset;
char fname[256];
struct timeval tv;
struct timeval tv_total_start, tv_total_end;
float total;
struct timeval tv_h2d_start, tv_h2d_end;
float h2d;
struct timeval tv_d2h_start, tv_d2h_end;
float d2h;
struct timeval tv_exec_start, tv_exec_end;
float exec;
/* initialize A[] & B[] */
for (i = 0; i < n; i++) {
for(j = 0; j < n; j++) {
idx = i * n + j;
a[idx] = i + 0.1;
b[idx] = i + 0.1;
}
}
/* block_x * block_y should not exceed 512. */
block_x = n < 16 ? n : 16;
block_y = n < 16 ? n : 16;
grid_x = n / block_x;
if (n % block_x != 0)
grid_x++;
grid_y = n / block_y;
if (n % block_y != 0)
grid_y++;
printf("block = (%d, %d)\n", block_x, block_y);
printf("grid = (%d, %d)\n", grid_x, grid_y);
gettimeofday(&tv_total_start, NULL);
res = cuInit(0);
if (res != CUDA_SUCCESS) {
printf("cuInit failed: res = %lu\n", (unsigned long)res);
return -1;
}
res = cuDeviceGet(&dev, 0);
if (res != CUDA_SUCCESS) {
printf("cuDeviceGet failed: res = %lu\n", (unsigned long)res);
return -1;
}
res = cuCtxCreate(&ctx, 0, dev);
if (res != CUDA_SUCCESS) {
printf("cuCtxCreate failed: res = %lu\n", (unsigned long)res);
return -1;
}
sprintf(fname, "%s/fmadd_gpu.cubin", path);
res = cuModuleLoad(&module, fname);
if (res != CUDA_SUCCESS) {
printf("cuModuleLoad() failed\n");
return -1;
}
res = cuModuleGetFunction(&function, module, "_Z3addPfS_S_i");
if (res != CUDA_SUCCESS) {
printf("cuModuleGetFunction() failed\n");
return -1;
}
res = cuFuncSetSharedSize(function, 0x40); /* just random */
if (res != CUDA_SUCCESS) {
printf("cuFuncSetSharedSize() failed\n");
return -1;
}
res = cuFuncSetBlockShape(function, block_x, block_y, 1);
if (res != CUDA_SUCCESS) {
printf("cuFuncSetBlockShape() failed\n");
return -1;
}
/* a[] */
res = cuMemAlloc(&a_dev, n*n * sizeof(float));
if (res != CUDA_SUCCESS) {
printf("cuMemAlloc (a) failed\n");
return -1;
}
/* b[] */
res = cuMemAlloc(&b_dev, n*n * sizeof(float));
if (res != CUDA_SUCCESS) {
printf("cuMemAlloc (b) failed\n");
return -1;
}
/* c[] */
res = cuMemAlloc(&c_dev, n*n * sizeof(float));
if (res != CUDA_SUCCESS) {
printf("cuMemAlloc (c) failed\n");
return -1;
}
gettimeofday(&tv_h2d_start, NULL);
/* upload a[] and b[] */
res = cuMemcpyHtoD(a_dev, a, n*n * sizeof(float));
if (res != CUDA_SUCCESS) {
printf("cuMemcpyHtoD (a) failed: res = %lu\n", (unsigned long)res);
return -1;
}
res = cuMemcpyHtoD(b_dev, b, n*n * sizeof(float));
if (res != CUDA_SUCCESS) {
printf("cuMemcpyHtoD (b) failed: res = %lu\n", (unsigned long)res);
return -1;
}
gettimeofday(&tv_h2d_end, NULL);
/* set kernel parameters */
offset = 0;
res = cuParamSetv(function, offset, &a_dev, sizeof(a_dev));
if (res != CUDA_SUCCESS) {
printf("cuParamSeti (a) failed: res = %lu\n", (unsigned long)res);
return -1;
}
offset += sizeof(a_dev);
res = cuParamSetv(function, offset, &b_dev, sizeof(b_dev));
if (res != CUDA_SUCCESS) {
printf("cuParamSeti (b) failed: res = %lu\n", (unsigned long)res);
return -1;
}
offset += sizeof(b_dev);
res = cuParamSetv(function, offset, &c_dev, sizeof(c_dev));
if (res != CUDA_SUCCESS) {
printf("cuParamSeti (c) failed: res = %lu\n", (unsigned long)res);
return -1;
}
offset += sizeof(c_dev);
res = cuParamSetv(function, offset, &n, sizeof(n));
if (res != CUDA_SUCCESS) {
printf("cuParamSeti (c) failed: res = %lu\n", (unsigned long)res);
return -1;
}
offset += sizeof(n);
res = cuParamSetSize(function, offset);
if (res != CUDA_SUCCESS) {
printf("cuParamSetSize failed: res = %lu\n", (unsigned long)res);
return -1;
}
gettimeofday(&tv_exec_start, NULL);
/* launch the kernel */
res = cuLaunchGrid(function, grid_x, grid_y);
if (res != CUDA_SUCCESS) {
printf("cuLaunchGrid failed: res = %lu\n", (unsigned long)res);
return -1;
}
cuCtxSynchronize();
gettimeofday(&tv_exec_end, NULL);
gettimeofday(&tv_d2h_start, NULL);
/* download c[] */
res = cuMemcpyDtoH(c, c_dev, n*n * sizeof(float));
if (res != CUDA_SUCCESS) {
printf("cuMemcpyDtoH (c) failed: res = %lu\n", (unsigned long)res);
return -1;
}
gettimeofday(&tv_d2h_end, NULL);
res = cuMemFree(a_dev);
if (res != CUDA_SUCCESS) {
printf("cuMemFree (a) failed: res = %lu\n", (unsigned long)res);
return -1;
}
res = cuMemFree(b_dev);
if (res != CUDA_SUCCESS) {
printf("cuMemFree (b) failed: res = %lu\n", (unsigned long)res);
return -1;
}
res = cuMemFree(c_dev);
if (res != CUDA_SUCCESS) {
printf("cuMemFree (c) failed: res = %lu\n", (unsigned long)res);
return -1;
}
res = cuModuleUnload(module);
if (res != CUDA_SUCCESS) {
printf("cuModuleUnload failed: res = %lu\n", (unsigned long)res);
return -1;
}
res = cuCtxDestroy(ctx);
if (res != CUDA_SUCCESS) {
printf("cuCtxDestroy failed: res = %lu\n", (unsigned long)res);
return -1;
}
gettimeofday(&tv_total_end, NULL);
/* check the results */
i = j = idx = 0;
while (i < n) {
while (j < n) {
idx = i * n + j;
if (c[idx] != a[idx] + b[idx]) {
printf("c[%d] = %f\n", idx, c[idx]);
printf("a[%d]+b[%d] = %f\n", idx, idx, a[idx]+b[idx]);
return -1;
}
j++;
}
i++;
}
free(a);
free(b);
free(c);
tvsub(&tv_h2d_end, &tv_h2d_start, &tv);
h2d = tv.tv_sec * 1000.0 + (float) tv.tv_usec / 1000.0;
tvsub(&tv_d2h_end, &tv_d2h_start, &tv);
d2h = tv.tv_sec * 1000.0 + (float) tv.tv_usec / 1000.0;
tvsub(&tv_exec_end, &tv_exec_start, &tv);
exec = tv.tv_sec * 1000.0 + (float) tv.tv_usec / 1000.0;
tvsub(&tv_total_end, &tv_total_start, &tv);
total = tv.tv_sec * 1000.0 + (float) tv.tv_usec / 1000.0;
printf("HtoD: %f\n", h2d);
printf("DtoH: %f\n", d2h);
printf("Exec: %f\n", exec);
printf("Time (Memcpy + Launch): %f\n", h2d + d2h + exec);
printf("Total: %f\n", total);
return 0;
}
int main( int argc, char** argv)
{
uint num_threads;
uint num_blocks, block_size;
uint length;
uint nBytes;
int *list;
int status, verbose, c, i, j, logBlocks;
int read_stdin;
struct timeval start_time, end_time;
unsigned long total_time;
CUdevice hDevice;
CUcontext hContext;
CUmodule hModule;
CUfunction bitonicBlockFn;
CUfunction mergeBlocksFn;
CUdeviceptr pDeviceArrayA;
CUdeviceptr pDeviceArrayB;
status = SUCCESS;
verbose = 0;
read_stdin = FALSE;
length = 0;
while ((c = getopt (argc, argv, "dip:vO")) != -1) {
switch (c) {
case 'd':
verbose |= GROSS_DEBUG;
break;
case 'i':
read_stdin = TRUE;
case 'O':
verbose |= OUTPUT;
break;
case 'p':
length = 1 << atoi(optarg);
break;
case 'v':
verbose |= DEBUG;
break;
case '?':
default:
print_usage();
return FAILURE;
}
}
if ( read_stdin == TRUE ) {
/* Read sequence of integers from stdin */
list = (int*) malloc (INIT_INPUT_SIZE * sizeof(int) );
length = readIntegers(list, INIT_INPUT_SIZE);
} else if ( length > 0 ) {
list = (int*) malloc (length * sizeof(int) );
randomInts(list, length);
} else if (optind >= argc) { /* No size was given */
print_usage();
return FAILURE;
} else {
/* Generate our own integers */
length = atoi(argv[optind]);
list = (int*) malloc (length * sizeof(int) );
randomInts(list, length);
}
/*
* Phase 1:
* There will be one thread for each element to be sorted. Each
* block will perform bitonic sort on MAX_THREADS_PER_BLOCK elements.
*/
/* Initialize sizes */
num_threads = _min(length, MAX_THREADS_PER_BLOCK );
num_blocks = (length-1) / MAX_THREADS_PER_BLOCK + 1;
nBytes = length * sizeof(int);
if (verbose & DEBUG) printf("Initializing GPU.\n");
/* Start timing */
gettimeofday(&start_time, NULL);
/* Initialize GPU */
cutilDrvSafeCall( cuInit(0) );
cutilDrvSafeCall( cuDeviceGet(&hDevice, 0) );
cutilDrvSafeCall( cuCtxCreate(&hContext, 0, hDevice) );
cutilDrvSafeCall( cuModuleLoad(&hModule, MODULE_FILE) );
cutilDrvSafeCall( cuModuleGetFunction(&bitonicBlockFn, hModule, BITONIC_BLOCK_FN) );
/* Allocate memory on the device */
cutilDrvSafeCall( cuMemAlloc(&pDeviceArrayA, nBytes) );
cutilDrvSafeCall( cuMemAlloc(&pDeviceArrayB, nBytes) );
cutilDrvSafeCall( cuMemcpyHtoD(pDeviceArrayA, list, nBytes) );
cutilDrvSafeCall( cuFuncSetBlockShape(bitonicBlockFn, num_threads, 1, 1));
cutilDrvSafeCall( cuParamSeti(bitonicBlockFn, 0, pDeviceArrayA) );
cutilDrvSafeCall( cuParamSetSize(bitonicBlockFn, 4) );
/* Execute the kernel on the GPU */
if ( verbose & DEBUG ) printf("Launching bitonic sort kernel with %d blocks and %d threads per block.\n", num_blocks, num_threads);
cutilDrvSafeCall( cuLaunchGrid(bitonicBlockFn, num_blocks, 1) );
/*
* Phase 2:
* At this point each block is a sorted list. Now it's time to merge them.
*/
/* TODO This should go away after development */
if ( verbose & GROSS_DEBUG ) {
cuMemcpyDtoH(list, pDeviceArrayA, nBytes);
for (i=0; i<num_blocks; ++i) {
printf("### Block %d:\n", i);
for (j=0; j<num_threads; ++j) {
printf("%d\n", list[i*num_threads + j]);
}
}
}
i=0;
/* Do we need to merge blocks? */
if ( num_blocks > 1 ) {
/* There will be Log_2(num_blocks) merge steps. */
logBlocks = 0;
for (i=1; i<num_blocks; i *= 2) ++logBlocks;
if ( verbose & DEBUG ) printf("There will be %d merge steps.\n", logBlocks);
block_size = num_threads; /* How big the blocks were in the last grid launch. */
num_threads = num_blocks >> 1; /* Start with blocks/2 threads */
num_blocks = (num_threads-1) / MAX_THREADS_PER_BLOCK + 1;
cutilDrvSafeCall( cuModuleGetFunction(&mergeBlocksFn, hModule, MERGE_BLOCKS_FN) );
cuParamSeti(mergeBlocksFn, 4, block_size);
cuParamSetSize(mergeBlocksFn, 16);
for (i=0; i < logBlocks; ++i) {
cuFuncSetBlockShape(mergeBlocksFn, num_threads, 1, 1);
cuParamSeti(mergeBlocksFn, 0, i); /* set merge level */
/* Merging uses a source array and destination array, the gpu has 2 arrays allocated
* so we swap which is the source and which is the destination for each iteration. */
if ( i%2 == 0 ) {
cuParamSeti(mergeBlocksFn, 8, pDeviceArrayA);
cuParamSeti(mergeBlocksFn, 12, pDeviceArrayB);
} else {
cuParamSeti(mergeBlocksFn, 8, pDeviceArrayB);
cuParamSeti(mergeBlocksFn, 12, pDeviceArrayA);
}
if ( verbose & DEBUG ) {
printf("Launching block merge kernel with %d blocks and %d threads per block\n",
num_blocks, num_threads/num_blocks);
}
cutilDrvSafeCall( cuLaunchGrid(mergeBlocksFn, num_blocks, 1) );
num_threads = num_threads >> 1;
num_blocks = (num_threads-1) / MAX_THREADS_PER_BLOCK + 1;
}
}
// Host code
int main()
{
int N = 3;
size_t size = N * sizeof(float);
float* h_A = (float*)malloc(size);
float* h_B = (float*)malloc(size);
float* h_C = (float*)malloc(size);
// Set up vectors.
for (int i = 0; i < N; ++i)
{
h_A[i] = i * 1.0;
h_B[i] = i * 1.0 + 1;
h_C[i] = 0;
printf("i %d A %f B %f C %f\n", i, h_A[i], h_B[i], h_C[i]);
}
// Initialize
if (cuInit(0) != CUDA_SUCCESS)
exit (0);
// Get number of devices supporting CUDA
int deviceCount = 0;
cuDeviceGetCount(&deviceCount);
if (deviceCount == 0)
{
printf("There is no device supporting CUDA.\n");
exit (0);
}
// Get handle for device 0
CUdevice cuDevice = 0;
CUresult r1 = cuDeviceGet(&cuDevice, 0);
// Create context
CUcontext cuContext;
cuCtxCreate(&cuContext, 0, cuDevice);
// Create module from binary file
CUmodule cuModule;
CUresult r2 = cuModuleLoad(&cuModule, "VecAdd.ptx");
// Get function handle from module
CUfunction vecAdd;
CUresult r3 = cuModuleGetFunction(&vecAdd, cuModule, "VecAdd");
// Allocate vectors in device memory
CUdeviceptr d_A;
CUresult r4 = cuMemAlloc(&d_A, size);
CUdeviceptr d_B;
CUresult r5 = cuMemAlloc(&d_B, size);
CUdeviceptr d_C;
CUresult r6 = cuMemAlloc(&d_C, size);
// Copy vectors from host memory to device memory
// h_A and h_B are input vectors stored in host memory
CUresult r7 = cuMemcpyHtoD(d_A, h_A, size);
CUresult r8 = cuMemcpyHtoD(d_B, h_B, size);
// Invoke kernel
#define ALIGN_UP(offset, alignment) (offset) = ((offset) + (alignment) - 1) & ~((alignment) - 1)
int offset = 0;
void* ptr;
ptr = (void*)(size_t)d_A;
ALIGN_UP(offset, __alignof(ptr));
CUresult r9 = cuParamSetv(vecAdd, offset, &ptr, sizeof(ptr));
offset += sizeof(ptr);
ptr = (void*)(size_t)d_B;
ALIGN_UP(offset, __alignof(ptr));
CUresult r10 = cuParamSetv(vecAdd, offset, &ptr, sizeof(ptr));
offset += sizeof(ptr);
ptr = (void*)(size_t)d_C;
ALIGN_UP(offset, __alignof(ptr));
CUresult r11 = cuParamSetv(vecAdd, offset, &ptr, sizeof(ptr));
offset += sizeof(ptr);
ptr = (void*)(int)N;
ALIGN_UP(offset, __alignof(ptr));
CUresult r11a = cuParamSetv(vecAdd, offset, &ptr, sizeof(ptr));
offset += sizeof(ptr);
CUresult r12 = cuParamSetSize(vecAdd, offset);
int threadsPerBlock = 256;
int blocksPerGrid = (N + threadsPerBlock - 1) / threadsPerBlock;
CUresult r13 = cuFuncSetBlockShape(vecAdd, threadsPerBlock, 1, 1);
CUresult r14 = cuLaunchGrid(vecAdd, blocksPerGrid, 1);
// Copy result from device memory to host memory
// h_C contains the result in host memory
CUresult r15 = cuMemcpyDtoH(h_C, d_C, size);
for (int i = 0; i < N; ++i)
{
printf("i %d A %f B %f C %f\n", i, h_A[i], h_B[i], h_C[i]);
}
// Free device memory
cuMemFree(d_A);
cuMemFree(d_B);
cuMemFree(d_C);
}
CUDARunner::CUDARunner():GPURunner<unsigned long,int>(TYPE_CUDA)
{
m_in=0;
m_devin=0;
m_out=0;
m_devout=0;
CUresult rval;
int major=0;
int minor=0;
std::string cuda_module_path("bitcoinminercuda.ptx");
rval=cuInit(0);
if(rval==CUDA_SUCCESS)
{
rval=cuDeviceGetCount(&m_devicecount);
printf("%d CUDA GPU devices found\n",m_devicecount);
if(m_devicecount>0)
{
if(m_deviceindex>=0 && m_deviceindex<m_devicecount)
{
printf("Setting CUDA device to device %d\n",m_deviceindex);
rval=cuDeviceGet(&m_device,m_deviceindex);
if(rval!=CUDA_SUCCESS)
{
exit(0);
}
}
else
{
m_deviceindex=0;
printf("Setting CUDA device to first device found\n");
rval=cuDeviceGet(&m_device,0);
if(rval!=CUDA_SUCCESS)
{
exit(0);
}
}
cuDeviceComputeCapability(&major, &minor, m_device);
rval=cuCtxCreate(&m_context,CU_CTX_BLOCKING_SYNC,m_device);
if(rval!=CUDA_SUCCESS)
{
printf("Unable to create CUDA context\n");
exit(0);
}
printf("Loading module %s\n",cuda_module_path.c_str());
rval=cuModuleLoad(&m_module,cuda_module_path.c_str());
if(rval!=CUDA_SUCCESS)
{
printf("Unable to load CUDA module: %i\n", rval);
cuCtxDestroy(m_context);
exit(0);
}
rval=cuModuleGetFunction(&m_function,m_module,"cuda_process");
if(rval!=CUDA_SUCCESS)
{
printf("Unable to get function cuda_process %d\n",rval);
cuModuleUnload(m_module);
cuCtxDestroy(m_context);
exit(0);
}
printf("CUDA initialized\n");
}
else
{
printf("No CUDA capable devices found\n");
exit(0);
}
}
else
{
printf("Unable to initialize CUDA\n");
exit(0);
}
}
double CUDAImpl::Build(std::string * err)
{
_StartTimer();
if(!_UnloadModule(err)) {
return GPUIP_ERROR;
}
const char * file_helper_math_h = ".helper_math.h";
const char * file_temp_cu = ".temp.cu";
const char * file_temp_ptx = ".temp.ptx";
// Includes vector float operations such as mult, add etc
std::ofstream out_helper(file_helper_math_h);
out_helper << get_cuda_helper_math();
out_helper.close();
// Create temporary file to compile
std::ofstream out(file_temp_cu);
out << "#include \"" << file_helper_math_h << "\"\n";
out << "extern \"C\" { \n"; // To avoid function name mangling
for(size_t i = 0; i < _kernels.size(); ++i) {
out << _kernels[i]->code << "\n";
}
out << "}"; // End the extern C bracket
out.close();
std::stringstream ss;
const char * cuda_bin_path = getenv("CUDA_BIN_PATH");
if (cuda_bin_path != NULL) {
ss << cuda_bin_path << "/nvcc";
} else {
ss << "nvcc";
}
ss << " -ptx " << file_temp_cu << " -o " << file_temp_ptx
<< " --Wno-deprecated-gpu-targets"
<< " -include " << file_helper_math_h;
if(sizeof(void *) == 4) {
ss << " -m32";
} else {
ss << " -m64";
}
#ifdef _WIN32
const char * cl_bin_path = getenv("CL_BIN_PATH");
if (cl_bin_path != NULL) {
ss << " -ccbin \"" << cl_bin_path << "\"";
}
#endif
ss << " 2>&1" << std::endl; // get both standard output and error
std::string pipe_err;
int nvcc_exit_status = _execPipe(ss.str().c_str(), &pipe_err);
// Cleanup temp text file
_removeFile(file_helper_math_h);
_removeFile(file_temp_cu);
if (nvcc_exit_status) {
(*err) = "Cuda error: Could not compile kernels:\n";
(*err) += pipe_err;
return GPUIP_ERROR;
}
// Load cuda ptx from file
CUresult c_err = cuModuleLoad(&_cudaModule, ".temp.ptx");
_removeFile(file_temp_ptx);
if (_cudaErrorLoadModule(c_err, err)) {
return GPUIP_ERROR;
}
_cudaKernels.resize(_kernels.size());
for(size_t i = 0; i < _kernels.size(); ++i) {
c_err = cuModuleGetFunction(&_cudaKernels[i], _cudaModule,
_kernels[i]->name.c_str());
if (_cudaErrorGetFunction(c_err, err, _kernels[i]->name)) {
return GPUIP_ERROR;
}
}
_cudaBuild = true;
return _StopTimer();
}
int main(int argc, char *argv[])
{
argc--; argv++;
// Instruction-level test of PTX assembly language and emulator.
// This test should work natively and under emulation. Many of the
// instructions tested here stress many poorly documented features
// of the PTX assembly language. If the emulator passes these
// tests, then it can surely pass code that is generated by the
// nvcc compiler.
test(cuInit(0), "cuInit");
int deviceCount = 0;
test(cuDeviceGetCount(&deviceCount), "cuDeviceGetCount");
int device = 0;
if (argc)
device = atoi(*argv);
CUdevice cuDevice = 0;
test(cuDeviceGet(&cuDevice, device), "cuDeviceGet");
CUcontext cuContext;
int xxx = cuCtxCreate(&cuContext, 0, cuDevice);
CUmodule cuModule;
test(cuModuleLoad(&cuModule, "inst.ptx"), "cuModuleLoad");
// Do basic test. No sense continuing if we cannot complete this
// test.
try
{
CUfunction proc;
test(cuModuleGetFunction(&proc, cuModule, "InstBasic"), "cuModuleGetFunction");
bool * h_R = (bool*)malloc(sizeof(bool));
memset(h_R, 0, sizeof(bool));
CUdeviceptr d_R;
test(cuMemAlloc(&d_R, sizeof(bool)), "cuMemAlloc");
test(cuMemcpyHtoD(d_R, h_R, sizeof(bool)), "cuMemcpyHtoD");
int offset = 0;
void* ptr;
ptr = (void*)(size_t)d_R;
ALIGN_UP(offset, __alignof(ptr));
test(cuParamSetv(proc, offset, &ptr, sizeof(ptr)), "cuParamSetv");
offset += sizeof(ptr);
test(cuParamSetSize(proc, offset), "cuParamSetSize");
int threadsPerBlock = 1;
int blocksPerGrid = 1;
test(cuFuncSetBlockShape(proc, threadsPerBlock, 1, 1), "cuFuncSetBlockShape");
test(cuLaunchGrid(proc, blocksPerGrid, 1), "cuLaunchGrid");
test(cuMemcpyDtoH(h_R, d_R, sizeof(bool)), "cuMemcpyDtoH");
test(cuMemFree(d_R), "cuMemFree");
if (h_R[0] == 1)
std::cout << "Basic test passed.\n";
else {
std::cout << "Basic test failed.\n";
exit(1);
}
} catch (...)
{
test(1, "test crashed.");
}
// Do LD, ST, MOV test.
load_and_test(cuModule, "InstLSMC");
// Do ADD, SUB test.
load_and_test(cuModule, "InstAddSub");
return 0;
}
int
main (int argc, char **argv)
{
CUdevice dev;
CUfunction delay;
CUmodule module;
CUresult r;
CUstream stream;
unsigned long *a, *d_a, dticks;
int nbytes;
float atime, dtime;
void *kargs[2];
int clkrate;
int devnum, nprocs;
acc_init (acc_device_nvidia);
devnum = acc_get_device_num (acc_device_nvidia);
r = cuDeviceGet (&dev, devnum);
if (r != CUDA_SUCCESS)
{
fprintf (stderr, "cuDeviceGet failed: %d\n", r);
abort ();
}
r =
cuDeviceGetAttribute (&nprocs, CU_DEVICE_ATTRIBUTE_MULTIPROCESSOR_COUNT,
dev);
if (r != CUDA_SUCCESS)
{
fprintf (stderr, "cuDeviceGetAttribute failed: %d\n", r);
abort ();
}
r = cuDeviceGetAttribute (&clkrate, CU_DEVICE_ATTRIBUTE_CLOCK_RATE, dev);
if (r != CUDA_SUCCESS)
{
fprintf (stderr, "cuDeviceGetAttribute failed: %d\n", r);
abort ();
}
r = cuModuleLoad (&module, "subr.ptx");
if (r != CUDA_SUCCESS)
{
fprintf (stderr, "cuModuleLoad failed: %d\n", r);
abort ();
}
r = cuModuleGetFunction (&delay, module, "delay");
if (r != CUDA_SUCCESS)
{
fprintf (stderr, "cuModuleGetFunction failed: %d\n", r);
abort ();
}
nbytes = nprocs * sizeof (unsigned long);
dtime = 200.0;
dticks = (unsigned long) (dtime * clkrate);
a = (unsigned long *) malloc (nbytes);
d_a = (unsigned long *) acc_malloc (nbytes);
acc_map_data (a, d_a, nbytes);
kargs[0] = (void *) &d_a;
kargs[1] = (void *) &dticks;
r = cuStreamCreate (&stream, CU_STREAM_DEFAULT);
if (r != CUDA_SUCCESS)
{
fprintf (stderr, "cuStreamCreate failed: %d\n", r);
abort ();
}
acc_set_cuda_stream (0, stream);
init_timers (1);
start_timer (0);
r = cuLaunchKernel (delay, 1, 1, 1, 1, 1, 1, 0, stream, kargs, 0);
if (r != CUDA_SUCCESS)
{
fprintf (stderr, "cuLaunchKernel failed: %d\n", r);
abort ();
}
acc_wait (1);
atime = stop_timer (0);
if (atime < dtime)
{
fprintf (stderr, "actual time < delay time\n");
abort ();
}
start_timer (0);
acc_wait (1);
atime = stop_timer (0);
if (0.010 < atime)
{
fprintf (stderr, "actual time < delay time\n");
abort ();
}
acc_unmap_data (a);
fini_timers ();
free (a);
acc_free (d_a);
acc_shutdown (acc_device_nvidia);
return 0;
}
void test_driver_api()
{
CUdevice cuDevice;
CUcontext cuContext;
CUmodule cuModule;
size_t totalGlobalMem;
CUfunction matrixMult = 0;
// cuda driver api intialization
{
int major = 0, minor = 0;
char deviceName[100];
cuda::Check::CUDAError(cuInit(0), "Error intializing cuda");
int deviceCount;
cuda::Check::CUDAError(cuDeviceGetCount(&deviceCount), "Error getting the number of devices");
if (deviceCount <= 0)
{
std::cerr << "No devices found" << std::endl;
return;
}
cuDeviceGet(&cuDevice, 0);
// get compute capabilities and the devicename
cuda::Check::CUDAError(cuDeviceComputeCapability(&major, &minor, cuDevice), "Error getting Device compute capability");
cuda::Check::CUDAError(cuDeviceGetName(deviceName, 256, cuDevice), "Error getting device name");
std::cout << "> GPU Device has SM " << major << "." << minor << " compute capability" << std::endl;
cuda::Check::CUDAError(cuDeviceTotalMem(&totalGlobalMem, cuDevice), "Error getting totat global memory");
std::cout << " Total amount of global memory: " << (unsigned long long)totalGlobalMem << " bytes" << std::endl;
std::string tmp = (totalGlobalMem > (unsigned long long)4 * 1024 * 1024 * 1024L) ? "YES" : "NO";
std::cout << " 64-bit Memory Address: " << tmp << std::endl;
cuda::Check::CUDAError(cuCtxCreate(&cuContext, 0, cuDevice), "Error creating the context");
}
// Compile and get the function
{
std::string module_path = "MatrixMult.cubin";
std::cout << "> initCUDA loading module: " << module_path << std::endl;
cuda::Check::CUDAError(cuModuleLoad(&cuModule, module_path.c_str()), "Error loading module");
cuda::Check::CUDAError(cuModuleGetFunction(&matrixMult, cuModule, "MatrixMultKernelSimpleDriverAPI"), "Error retrieving the function");
}
// Call the kernel
{
int WIDTH = BLOCK_SIZE;
int HEIGHT = BLOCK_SIZE;
std::stringstream text;
text << "CUDA Matrix Multiplication (" << WIDTH << "x" << WIDTH << ") Simple method Multiplication time";
HostMatrix<float> M(WIDTH, HEIGHT); M.fillWithRandomData(); //M.print(std::cout);
HostMatrix<float> N(WIDTH, HEIGHT); N.fill_diagonal(2); //N.print(std::cout);
HostMatrix<float> C(WIDTH, HEIGHT);
{
ScopedTimer t(text.str());
// allocate device memory
CUdeviceptr d_M;
cuda::Check::CUDAError(cuMemAlloc(&d_M, M.sizeInBytes()), "Error allocating memory");
CUdeviceptr d_N;
cuda::Check::CUDAError(cuMemAlloc(&d_N, N.sizeInBytes()), "Error allocating memory");
// copy host memory to device
cuda::Check::CUDAError(cuMemcpyHtoD(d_M, M, M.sizeInBytes()), "Error uploading memory to device");
cuda::Check::CUDAError(cuMemcpyHtoD(d_N, N, N.sizeInBytes()), "Error uploading memory to device");
// allocate device memory for result
CUdeviceptr d_C;
cuda::Check::CUDAError(cuMemAlloc(&d_C, C.sizeInBytes()), "Error allocating memory");
dim3 block(BLOCK_SIZE, BLOCK_SIZE, 1);
dim3 grid(C.width_ / BLOCK_SIZE, C.height_ / BLOCK_SIZE, 1);
void *args[6] = { &d_M, &d_N, &d_C, &WIDTH, &WIDTH, &WIDTH};
// new CUDA 4.0 Driver API Kernel launch call
cuda::Check::CUDAError(cuLaunchKernel(
matrixMult, // Selected kernel function
grid.x, grid.y, grid.z, // grid config
block.x, block.y, block.z, // block config
2 * BLOCK_SIZE*BLOCK_SIZE*sizeof(float),
NULL, args, NULL), "Error executing Kernel");
cuda::Check::CUDAError(cuMemcpyDtoH((void *)C, d_C, C.sizeInBytes()),"Error downloading memory to host");
}
C.print(std::cout);
}
cuCtxDestroy(cuContext);
}
