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
@@ -30,4 +30,3 @@ cudaStreamCreateWithFlags, cudaStreamDestroy, cudaFree, cudaGetErrorName, cudaSe
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Download and install the [CUDA Toolkit 12.5](https://developer.nvidia.com/cuda-downloads) for your corresponding platform.
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## References (for more details)
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@@ -25,407 +25,399 @@
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* OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
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*/
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#include "cudla.h"
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#include "cuda_runtime.h"
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#include <cstdio>
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#include <cstdlib>
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#include <cstring>
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#include <sys/stat.h>
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#include <fstream>
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#include <sstream>
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#include <sys/stat.h>
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#include "cuda_runtime.h"
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#include "cudla.h"
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#define DPRINTF(...) printf(__VA_ARGS__)
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static void printTensorDesc(cudlaModuleTensorDescriptor* tensorDesc) {
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DPRINTF("\tTENSOR NAME : %s\n", tensorDesc->name);
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DPRINTF("\tsize: %lu\n", tensorDesc->size);
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static void printTensorDesc(cudlaModuleTensorDescriptor *tensorDesc)
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{
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DPRINTF("\tTENSOR NAME : %s\n", tensorDesc->name);
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DPRINTF("\tsize: %lu\n", tensorDesc->size);
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DPRINTF("\tdims: [%lu, %lu, %lu, %lu]\n", tensorDesc->n, tensorDesc->c,
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tensorDesc->h, tensorDesc->w);
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DPRINTF("\tdims: [%lu, %lu, %lu, %lu]\n", tensorDesc->n, tensorDesc->c, tensorDesc->h, tensorDesc->w);
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DPRINTF("\tdata fmt: %d\n", tensorDesc->dataFormat);
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DPRINTF("\tdata type: %d\n", tensorDesc->dataType);
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DPRINTF("\tdata category: %d\n", tensorDesc->dataCategory);
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DPRINTF("\tpixel fmt: %d\n", tensorDesc->pixelFormat);
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DPRINTF("\tpixel mapping: %d\n", tensorDesc->pixelMapping);
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DPRINTF("\tstride[0]: %d\n", tensorDesc->stride[0]);
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DPRINTF("\tstride[1]: %d\n", tensorDesc->stride[1]);
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DPRINTF("\tstride[2]: %d\n", tensorDesc->stride[2]);
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DPRINTF("\tstride[3]: %d\n", tensorDesc->stride[3]);
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DPRINTF("\tdata fmt: %d\n", tensorDesc->dataFormat);
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DPRINTF("\tdata type: %d\n", tensorDesc->dataType);
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DPRINTF("\tdata category: %d\n", tensorDesc->dataCategory);
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DPRINTF("\tpixel fmt: %d\n", tensorDesc->pixelFormat);
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DPRINTF("\tpixel mapping: %d\n", tensorDesc->pixelMapping);
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DPRINTF("\tstride[0]: %d\n", tensorDesc->stride[0]);
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DPRINTF("\tstride[1]: %d\n", tensorDesc->stride[1]);
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DPRINTF("\tstride[2]: %d\n", tensorDesc->stride[2]);
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DPRINTF("\tstride[3]: %d\n", tensorDesc->stride[3]);
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}
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typedef struct {
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cudlaDevHandle devHandle;
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cudlaModule moduleHandle;
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unsigned char* loadableData;
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cudaStream_t stream;
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unsigned char* inputBuffer;
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unsigned char* outputBuffer;
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void* inputBufferGPU;
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void* outputBufferGPU;
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cudlaModuleTensorDescriptor* inputTensorDesc;
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cudlaModuleTensorDescriptor* outputTensorDesc;
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typedef struct
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{
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cudlaDevHandle devHandle;
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cudlaModule moduleHandle;
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unsigned char *loadableData;
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cudaStream_t stream;
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unsigned char *inputBuffer;
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unsigned char *outputBuffer;
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void *inputBufferGPU;
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void *outputBufferGPU;
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cudlaModuleTensorDescriptor *inputTensorDesc;
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cudlaModuleTensorDescriptor *outputTensorDesc;
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} ResourceList;
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void cleanUp(ResourceList* resourceList);
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void cleanUp(ResourceList *resourceList);
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void cleanUp(ResourceList* resourceList) {
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if (resourceList->inputTensorDesc != NULL) {
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free(resourceList->inputTensorDesc);
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resourceList->inputTensorDesc = NULL;
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}
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if (resourceList->outputTensorDesc != NULL) {
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free(resourceList->outputTensorDesc);
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resourceList->outputTensorDesc = NULL;
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}
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void cleanUp(ResourceList *resourceList)
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{
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if (resourceList->inputTensorDesc != NULL) {
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free(resourceList->inputTensorDesc);
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resourceList->inputTensorDesc = NULL;
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}
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if (resourceList->outputTensorDesc != NULL) {
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free(resourceList->outputTensorDesc);
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resourceList->outputTensorDesc = NULL;
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}
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if (resourceList->loadableData != NULL) {
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free(resourceList->loadableData);
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resourceList->loadableData = NULL;
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}
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if (resourceList->loadableData != NULL) {
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free(resourceList->loadableData);
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resourceList->loadableData = NULL;
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}
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if (resourceList->moduleHandle != NULL) {
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cudlaModuleUnload(resourceList->moduleHandle, 0);
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resourceList->moduleHandle = NULL;
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}
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if (resourceList->moduleHandle != NULL) {
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cudlaModuleUnload(resourceList->moduleHandle, 0);
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resourceList->moduleHandle = NULL;
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}
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if (resourceList->devHandle != NULL) {
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cudlaDestroyDevice(resourceList->devHandle);
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resourceList->devHandle = NULL;
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}
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if (resourceList->devHandle != NULL) {
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cudlaDestroyDevice(resourceList->devHandle);
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resourceList->devHandle = NULL;
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}
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if (resourceList->inputBufferGPU != 0) {
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cudaFree(resourceList->inputBufferGPU);
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resourceList->inputBufferGPU = 0;
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}
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if (resourceList->outputBufferGPU != 0) {
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cudaFree(resourceList->outputBufferGPU);
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resourceList->outputBufferGPU = 0;
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}
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if (resourceList->inputBufferGPU != 0) {
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cudaFree(resourceList->inputBufferGPU);
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resourceList->inputBufferGPU = 0;
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}
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if (resourceList->outputBufferGPU != 0) {
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cudaFree(resourceList->outputBufferGPU);
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resourceList->outputBufferGPU = 0;
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}
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if (resourceList->inputBuffer != NULL) {
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free(resourceList->inputBuffer);
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resourceList->inputBuffer = NULL;
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}
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if (resourceList->outputBuffer != NULL) {
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free(resourceList->outputBuffer);
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resourceList->outputBuffer = NULL;
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}
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if (resourceList->inputBuffer != NULL) {
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free(resourceList->inputBuffer);
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resourceList->inputBuffer = NULL;
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}
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if (resourceList->outputBuffer != NULL) {
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free(resourceList->outputBuffer);
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resourceList->outputBuffer = NULL;
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}
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if (resourceList->stream != NULL) {
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cudaStreamDestroy(resourceList->stream);
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resourceList->stream = NULL;
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}
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if (resourceList->stream != NULL) {
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cudaStreamDestroy(resourceList->stream);
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resourceList->stream = NULL;
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}
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}
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int main(int argc, char** argv) {
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cudlaDevHandle devHandle;
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cudlaModule moduleHandle;
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cudlaStatus err;
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FILE* fp = NULL;
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struct stat st;
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size_t file_size;
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size_t actually_read = 0;
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unsigned char* loadableData = NULL;
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int main(int argc, char **argv)
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{
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cudlaDevHandle devHandle;
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cudlaModule moduleHandle;
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cudlaStatus err;
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FILE *fp = NULL;
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struct stat st;
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size_t file_size;
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size_t actually_read = 0;
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unsigned char *loadableData = NULL;
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cudaStream_t stream;
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cudaError_t result;
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const char* errPtr = NULL;
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cudaStream_t stream;
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cudaError_t result;
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const char *errPtr = NULL;
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ResourceList resourceList;
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ResourceList resourceList;
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memset(&resourceList, 0x00, sizeof(ResourceList));
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memset(&resourceList, 0x00, sizeof(ResourceList));
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if (argc != 2) {
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DPRINTF("Usage : ./cuDLAErrorReporting <loadable>\n");
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return 1;
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}
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// Read loadable into buffer.
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fp = fopen(argv[1], "rb");
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if (fp == NULL) {
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DPRINTF("Cannot open file %s\n", argv[1]);
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return 1;
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}
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if (stat(argv[1], &st) != 0) {
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DPRINTF("Cannot stat file\n");
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return 1;
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}
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file_size = st.st_size;
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DPRINTF("The file size = %ld\n", file_size);
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loadableData = (unsigned char*)malloc(file_size);
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if (loadableData == NULL) {
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DPRINTF("Cannot Allocate memory for loadable\n");
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return 1;
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}
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actually_read = fread(loadableData, 1, file_size, fp);
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if (actually_read != file_size) {
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free(loadableData);
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DPRINTF("Read wrong size\n");
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return 1;
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}
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fclose(fp);
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resourceList.loadableData = loadableData;
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// Initialize CUDA.
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result = cudaFree(0);
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if (result != cudaSuccess) {
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errPtr = cudaGetErrorName(result);
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DPRINTF("Error in creating cudaFree = %s\n", errPtr);
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cleanUp(&resourceList);
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return 1;
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}
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result = cudaSetDevice(0);
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if (result != cudaSuccess) {
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errPtr = cudaGetErrorName(result);
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DPRINTF("Error in creating cudaSetDevice = %s\n", errPtr);
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cleanUp(&resourceList);
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return 1;
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}
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err = cudlaCreateDevice(0, &devHandle, CUDLA_CUDA_DLA);
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if (err != cudlaSuccess) {
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DPRINTF("Error in cuDLA create device = %d\n", err);
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cleanUp(&resourceList);
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return 1;
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}
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DPRINTF("Device created successfully\n");
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resourceList.devHandle = devHandle;
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err = cudlaModuleLoadFromMemory(devHandle, loadableData, file_size,
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&moduleHandle, 0);
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if (err != cudlaSuccess) {
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DPRINTF("Error in cudlaModuleLoadFromMemory = %d\n", err);
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cleanUp(&resourceList);
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return 1;
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} else {
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DPRINTF("Successfully loaded module\n");
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}
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resourceList.moduleHandle = moduleHandle;
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// Create CUDA stream.
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result = cudaStreamCreateWithFlags(&stream, cudaStreamNonBlocking);
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if (result != cudaSuccess) {
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errPtr = cudaGetErrorName(result);
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DPRINTF("Error in creating cuda stream = %s\n", errPtr);
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cleanUp(&resourceList);
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return 1;
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}
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resourceList.stream = stream;
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// Get tensor attributes.
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uint32_t numInputTensors = 0;
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uint32_t numOutputTensors = 0;
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cudlaModuleAttribute attribute;
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err = cudlaModuleGetAttributes(moduleHandle, CUDLA_NUM_INPUT_TENSORS,
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&attribute);
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if (err != cudlaSuccess) {
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DPRINTF("Error in getting numInputTensors = %d\n", err);
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cleanUp(&resourceList);
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return 1;
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}
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numInputTensors = attribute.numInputTensors;
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DPRINTF("numInputTensors = %d\n", numInputTensors);
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err = cudlaModuleGetAttributes(moduleHandle, CUDLA_NUM_OUTPUT_TENSORS,
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&attribute);
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if (err != cudlaSuccess) {
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DPRINTF("Error in getting numOutputTensors = %d\n", err);
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cleanUp(&resourceList);
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return 1;
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}
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numOutputTensors = attribute.numOutputTensors;
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DPRINTF("numOutputTensors = %d\n", numOutputTensors);
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|
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cudlaModuleTensorDescriptor* inputTensorDesc =
|
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(cudlaModuleTensorDescriptor*)malloc(sizeof(cudlaModuleTensorDescriptor) *
|
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numInputTensors);
|
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cudlaModuleTensorDescriptor* outputTensorDesc =
|
||||
(cudlaModuleTensorDescriptor*)malloc(sizeof(cudlaModuleTensorDescriptor) *
|
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numOutputTensors);
|
||||
|
||||
if ((inputTensorDesc == NULL) || (outputTensorDesc == NULL)) {
|
||||
if (inputTensorDesc != NULL) {
|
||||
free(inputTensorDesc);
|
||||
inputTensorDesc = NULL;
|
||||
if (argc != 2) {
|
||||
DPRINTF("Usage : ./cuDLAErrorReporting <loadable>\n");
|
||||
return 1;
|
||||
}
|
||||
|
||||
if (outputTensorDesc != NULL) {
|
||||
free(outputTensorDesc);
|
||||
outputTensorDesc = NULL;
|
||||
// Read loadable into buffer.
|
||||
fp = fopen(argv[1], "rb");
|
||||
if (fp == NULL) {
|
||||
DPRINTF("Cannot open file %s\n", argv[1]);
|
||||
return 1;
|
||||
}
|
||||
|
||||
if (stat(argv[1], &st) != 0) {
|
||||
DPRINTF("Cannot stat file\n");
|
||||
return 1;
|
||||
}
|
||||
|
||||
file_size = st.st_size;
|
||||
DPRINTF("The file size = %ld\n", file_size);
|
||||
|
||||
loadableData = (unsigned char *)malloc(file_size);
|
||||
if (loadableData == NULL) {
|
||||
DPRINTF("Cannot Allocate memory for loadable\n");
|
||||
return 1;
|
||||
}
|
||||
|
||||
actually_read = fread(loadableData, 1, file_size, fp);
|
||||
if (actually_read != file_size) {
|
||||
free(loadableData);
|
||||
DPRINTF("Read wrong size\n");
|
||||
return 1;
|
||||
}
|
||||
fclose(fp);
|
||||
|
||||
resourceList.loadableData = loadableData;
|
||||
|
||||
// Initialize CUDA.
|
||||
result = cudaFree(0);
|
||||
if (result != cudaSuccess) {
|
||||
errPtr = cudaGetErrorName(result);
|
||||
DPRINTF("Error in creating cudaFree = %s\n", errPtr);
|
||||
cleanUp(&resourceList);
|
||||
return 1;
|
||||
}
|
||||
result = cudaSetDevice(0);
|
||||
if (result != cudaSuccess) {
|
||||
errPtr = cudaGetErrorName(result);
|
||||
DPRINTF("Error in creating cudaSetDevice = %s\n", errPtr);
|
||||
cleanUp(&resourceList);
|
||||
return 1;
|
||||
}
|
||||
|
||||
err = cudlaCreateDevice(0, &devHandle, CUDLA_CUDA_DLA);
|
||||
if (err != cudlaSuccess) {
|
||||
DPRINTF("Error in cuDLA create device = %d\n", err);
|
||||
cleanUp(&resourceList);
|
||||
return 1;
|
||||
}
|
||||
|
||||
DPRINTF("Device created successfully\n");
|
||||
resourceList.devHandle = devHandle;
|
||||
|
||||
err = cudlaModuleLoadFromMemory(devHandle, loadableData, file_size, &moduleHandle, 0);
|
||||
if (err != cudlaSuccess) {
|
||||
DPRINTF("Error in cudlaModuleLoadFromMemory = %d\n", err);
|
||||
cleanUp(&resourceList);
|
||||
return 1;
|
||||
}
|
||||
else {
|
||||
DPRINTF("Successfully loaded module\n");
|
||||
}
|
||||
|
||||
resourceList.moduleHandle = moduleHandle;
|
||||
|
||||
// Create CUDA stream.
|
||||
result = cudaStreamCreateWithFlags(&stream, cudaStreamNonBlocking);
|
||||
|
||||
if (result != cudaSuccess) {
|
||||
errPtr = cudaGetErrorName(result);
|
||||
DPRINTF("Error in creating cuda stream = %s\n", errPtr);
|
||||
cleanUp(&resourceList);
|
||||
return 1;
|
||||
}
|
||||
|
||||
resourceList.stream = stream;
|
||||
|
||||
// Get tensor attributes.
|
||||
uint32_t numInputTensors = 0;
|
||||
uint32_t numOutputTensors = 0;
|
||||
cudlaModuleAttribute attribute;
|
||||
|
||||
err = cudlaModuleGetAttributes(moduleHandle, CUDLA_NUM_INPUT_TENSORS, &attribute);
|
||||
if (err != cudlaSuccess) {
|
||||
DPRINTF("Error in getting numInputTensors = %d\n", err);
|
||||
cleanUp(&resourceList);
|
||||
return 1;
|
||||
}
|
||||
numInputTensors = attribute.numInputTensors;
|
||||
DPRINTF("numInputTensors = %d\n", numInputTensors);
|
||||
|
||||
err = cudlaModuleGetAttributes(moduleHandle, CUDLA_NUM_OUTPUT_TENSORS, &attribute);
|
||||
if (err != cudlaSuccess) {
|
||||
DPRINTF("Error in getting numOutputTensors = %d\n", err);
|
||||
cleanUp(&resourceList);
|
||||
return 1;
|
||||
}
|
||||
numOutputTensors = attribute.numOutputTensors;
|
||||
DPRINTF("numOutputTensors = %d\n", numOutputTensors);
|
||||
|
||||
cudlaModuleTensorDescriptor *inputTensorDesc =
|
||||
(cudlaModuleTensorDescriptor *)malloc(sizeof(cudlaModuleTensorDescriptor) * numInputTensors);
|
||||
cudlaModuleTensorDescriptor *outputTensorDesc =
|
||||
(cudlaModuleTensorDescriptor *)malloc(sizeof(cudlaModuleTensorDescriptor) * numOutputTensors);
|
||||
|
||||
if ((inputTensorDesc == NULL) || (outputTensorDesc == NULL)) {
|
||||
if (inputTensorDesc != NULL) {
|
||||
free(inputTensorDesc);
|
||||
inputTensorDesc = NULL;
|
||||
}
|
||||
|
||||
if (outputTensorDesc != NULL) {
|
||||
free(outputTensorDesc);
|
||||
outputTensorDesc = NULL;
|
||||
}
|
||||
|
||||
cleanUp(&resourceList);
|
||||
return 1;
|
||||
}
|
||||
|
||||
resourceList.inputTensorDesc = inputTensorDesc;
|
||||
resourceList.outputTensorDesc = outputTensorDesc;
|
||||
|
||||
attribute.inputTensorDesc = inputTensorDesc;
|
||||
err = cudlaModuleGetAttributes(moduleHandle, CUDLA_INPUT_TENSOR_DESCRIPTORS, &attribute);
|
||||
if (err != cudlaSuccess) {
|
||||
DPRINTF("Error in getting input tensor descriptor = %d\n", err);
|
||||
cleanUp(&resourceList);
|
||||
return 1;
|
||||
}
|
||||
DPRINTF("Printing input tensor descriptor\n");
|
||||
printTensorDesc(inputTensorDesc);
|
||||
|
||||
attribute.outputTensorDesc = outputTensorDesc;
|
||||
err = cudlaModuleGetAttributes(moduleHandle, CUDLA_OUTPUT_TENSOR_DESCRIPTORS, &attribute);
|
||||
if (err != cudlaSuccess) {
|
||||
DPRINTF("Error in getting output tensor descriptor = %d\n", err);
|
||||
cleanUp(&resourceList);
|
||||
return 1;
|
||||
}
|
||||
DPRINTF("Printing output tensor descriptor\n");
|
||||
printTensorDesc(outputTensorDesc);
|
||||
|
||||
// Setup the input and output buffers which will be used as an input to CUDA.
|
||||
unsigned char *inputBuffer = (unsigned char *)malloc(inputTensorDesc[0].size);
|
||||
if (inputBuffer == NULL) {
|
||||
DPRINTF("Error in allocating input memory\n");
|
||||
cleanUp(&resourceList);
|
||||
return 1;
|
||||
}
|
||||
|
||||
resourceList.inputBuffer = inputBuffer;
|
||||
|
||||
unsigned char *outputBuffer = (unsigned char *)malloc(outputTensorDesc[0].size);
|
||||
if (outputBuffer == NULL) {
|
||||
DPRINTF("Error in allocating output memory\n");
|
||||
cleanUp(&resourceList);
|
||||
return 1;
|
||||
}
|
||||
|
||||
resourceList.outputBuffer = outputBuffer;
|
||||
|
||||
memset(inputBuffer, 0x01, inputTensorDesc[0].size);
|
||||
memset(outputBuffer, 0x00, outputTensorDesc[0].size);
|
||||
|
||||
// Allocate memory on GPU.
|
||||
void *inputBufferGPU;
|
||||
void *outputBufferGPU;
|
||||
result = cudaMalloc(&inputBufferGPU, inputTensorDesc[0].size);
|
||||
if (result != cudaSuccess) {
|
||||
DPRINTF("Error in allocating input memory on GPU\n");
|
||||
cleanUp(&resourceList);
|
||||
return 1;
|
||||
}
|
||||
|
||||
resourceList.inputBufferGPU = inputBufferGPU;
|
||||
|
||||
result = cudaMalloc(&outputBufferGPU, outputTensorDesc[0].size);
|
||||
if (result != cudaSuccess) {
|
||||
DPRINTF("Error in allocating output memory on GPU\n");
|
||||
cleanUp(&resourceList);
|
||||
return 1;
|
||||
}
|
||||
|
||||
resourceList.outputBufferGPU = outputBufferGPU;
|
||||
|
||||
// Register the CUDA-allocated buffers.
|
||||
uint64_t *inputBufferRegisteredPtr = NULL;
|
||||
uint64_t *outputBufferRegisteredPtr = NULL;
|
||||
|
||||
err =
|
||||
cudlaMemRegister(devHandle, (uint64_t *)inputBufferGPU, inputTensorDesc[0].size, &inputBufferRegisteredPtr, 0);
|
||||
if (err != cudlaSuccess) {
|
||||
DPRINTF("Error in registering input memory = %d\n", err);
|
||||
cleanUp(&resourceList);
|
||||
return 1;
|
||||
}
|
||||
|
||||
err = cudlaMemRegister(
|
||||
devHandle, (uint64_t *)outputBufferGPU, outputTensorDesc[0].size, &outputBufferRegisteredPtr, 0);
|
||||
if (err != cudlaSuccess) {
|
||||
DPRINTF("Error in registering output memory = %d\n", err);
|
||||
cleanUp(&resourceList);
|
||||
return 1;
|
||||
}
|
||||
DPRINTF("ALL MEMORY REGISTERED SUCCESSFULLY\n");
|
||||
|
||||
// Copy data from CPU buffers to GPU buffers.
|
||||
result = cudaMemcpyAsync(inputBufferGPU, inputBuffer, inputTensorDesc[0].size, cudaMemcpyHostToDevice, stream);
|
||||
if (result != cudaSuccess) {
|
||||
DPRINTF("Error in enqueueing memcpy for input\n");
|
||||
cleanUp(&resourceList);
|
||||
return 1;
|
||||
}
|
||||
result = cudaMemsetAsync(outputBufferGPU, 0, outputTensorDesc[0].size, stream);
|
||||
if (result != cudaSuccess) {
|
||||
DPRINTF("Error in enqueueing memset for output\n");
|
||||
cleanUp(&resourceList);
|
||||
return 1;
|
||||
}
|
||||
|
||||
// Enqueue a cuDLA task.
|
||||
cudlaTask task;
|
||||
task.moduleHandle = moduleHandle;
|
||||
task.outputTensor = &outputBufferRegisteredPtr;
|
||||
task.numOutputTensors = 1;
|
||||
task.numInputTensors = 1;
|
||||
task.inputTensor = &inputBufferRegisteredPtr;
|
||||
task.waitEvents = NULL;
|
||||
task.signalEvents = NULL;
|
||||
err = cudlaSubmitTask(devHandle, &task, 1, stream, 0);
|
||||
if (err != cudlaSuccess) {
|
||||
DPRINTF("Error in submitting task\n");
|
||||
cleanUp(&resourceList);
|
||||
return 1;
|
||||
}
|
||||
DPRINTF("SUBMIT IS DONE !!!\n");
|
||||
|
||||
// Wait for stream operations to finish and bring output buffer to CPU.
|
||||
result = cudaMemcpyAsync(outputBuffer, outputBufferGPU, outputTensorDesc[0].size, cudaMemcpyDeviceToHost, stream);
|
||||
if (result != cudaSuccess) {
|
||||
if (result != cudaErrorExternalDevice) {
|
||||
DPRINTF("Error in bringing result back to CPU\n");
|
||||
cleanUp(&resourceList);
|
||||
return 1;
|
||||
}
|
||||
else {
|
||||
cudlaStatus hwStatus = cudlaGetLastError(devHandle);
|
||||
if (hwStatus != cudlaSuccess) {
|
||||
DPRINTF("Asynchronous error in HW = %u\n", hwStatus);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
result = cudaStreamSynchronize(stream);
|
||||
if (result != cudaSuccess) {
|
||||
DPRINTF("Error in synchronizing stream = %s\n", cudaGetErrorName(result));
|
||||
|
||||
if (result == cudaErrorExternalDevice) {
|
||||
cudlaStatus hwStatus = cudlaGetLastError(devHandle);
|
||||
if (hwStatus != cudlaSuccess) {
|
||||
DPRINTF("Asynchronous error in HW = %u\n", hwStatus);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
cleanUp(&resourceList);
|
||||
return 1;
|
||||
}
|
||||
|
||||
resourceList.inputTensorDesc = inputTensorDesc;
|
||||
resourceList.outputTensorDesc = outputTensorDesc;
|
||||
DPRINTF("cuDLAErrorReporting DONE !!!\n");
|
||||
|
||||
attribute.inputTensorDesc = inputTensorDesc;
|
||||
err = cudlaModuleGetAttributes(moduleHandle, CUDLA_INPUT_TENSOR_DESCRIPTORS,
|
||||
&attribute);
|
||||
if (err != cudlaSuccess) {
|
||||
DPRINTF("Error in getting input tensor descriptor = %d\n", err);
|
||||
cleanUp(&resourceList);
|
||||
return 1;
|
||||
}
|
||||
DPRINTF("Printing input tensor descriptor\n");
|
||||
printTensorDesc(inputTensorDesc);
|
||||
|
||||
attribute.outputTensorDesc = outputTensorDesc;
|
||||
err = cudlaModuleGetAttributes(moduleHandle, CUDLA_OUTPUT_TENSOR_DESCRIPTORS,
|
||||
&attribute);
|
||||
if (err != cudlaSuccess) {
|
||||
DPRINTF("Error in getting output tensor descriptor = %d\n", err);
|
||||
cleanUp(&resourceList);
|
||||
return 1;
|
||||
}
|
||||
DPRINTF("Printing output tensor descriptor\n");
|
||||
printTensorDesc(outputTensorDesc);
|
||||
|
||||
// Setup the input and output buffers which will be used as an input to CUDA.
|
||||
unsigned char* inputBuffer = (unsigned char*)malloc(inputTensorDesc[0].size);
|
||||
if (inputBuffer == NULL) {
|
||||
DPRINTF("Error in allocating input memory\n");
|
||||
cleanUp(&resourceList);
|
||||
return 1;
|
||||
}
|
||||
|
||||
resourceList.inputBuffer = inputBuffer;
|
||||
|
||||
unsigned char* outputBuffer =
|
||||
(unsigned char*)malloc(outputTensorDesc[0].size);
|
||||
if (outputBuffer == NULL) {
|
||||
DPRINTF("Error in allocating output memory\n");
|
||||
cleanUp(&resourceList);
|
||||
return 1;
|
||||
}
|
||||
|
||||
resourceList.outputBuffer = outputBuffer;
|
||||
|
||||
memset(inputBuffer, 0x01, inputTensorDesc[0].size);
|
||||
memset(outputBuffer, 0x00, outputTensorDesc[0].size);
|
||||
|
||||
// Allocate memory on GPU.
|
||||
void* inputBufferGPU;
|
||||
void* outputBufferGPU;
|
||||
result = cudaMalloc(&inputBufferGPU, inputTensorDesc[0].size);
|
||||
if (result != cudaSuccess) {
|
||||
DPRINTF("Error in allocating input memory on GPU\n");
|
||||
cleanUp(&resourceList);
|
||||
return 1;
|
||||
}
|
||||
|
||||
resourceList.inputBufferGPU = inputBufferGPU;
|
||||
|
||||
result = cudaMalloc(&outputBufferGPU, outputTensorDesc[0].size);
|
||||
if (result != cudaSuccess) {
|
||||
DPRINTF("Error in allocating output memory on GPU\n");
|
||||
cleanUp(&resourceList);
|
||||
return 1;
|
||||
}
|
||||
|
||||
resourceList.outputBufferGPU = outputBufferGPU;
|
||||
|
||||
// Register the CUDA-allocated buffers.
|
||||
uint64_t* inputBufferRegisteredPtr = NULL;
|
||||
uint64_t* outputBufferRegisteredPtr = NULL;
|
||||
|
||||
err = cudlaMemRegister(devHandle, (uint64_t*)inputBufferGPU,
|
||||
inputTensorDesc[0].size, &inputBufferRegisteredPtr, 0);
|
||||
if (err != cudlaSuccess) {
|
||||
DPRINTF("Error in registering input memory = %d\n", err);
|
||||
cleanUp(&resourceList);
|
||||
return 1;
|
||||
}
|
||||
|
||||
err =
|
||||
cudlaMemRegister(devHandle, (uint64_t*)outputBufferGPU,
|
||||
outputTensorDesc[0].size, &outputBufferRegisteredPtr, 0);
|
||||
if (err != cudlaSuccess) {
|
||||
DPRINTF("Error in registering output memory = %d\n", err);
|
||||
cleanUp(&resourceList);
|
||||
return 1;
|
||||
}
|
||||
DPRINTF("ALL MEMORY REGISTERED SUCCESSFULLY\n");
|
||||
|
||||
// Copy data from CPU buffers to GPU buffers.
|
||||
result = cudaMemcpyAsync(inputBufferGPU, inputBuffer, inputTensorDesc[0].size,
|
||||
cudaMemcpyHostToDevice, stream);
|
||||
if (result != cudaSuccess) {
|
||||
DPRINTF("Error in enqueueing memcpy for input\n");
|
||||
cleanUp(&resourceList);
|
||||
return 1;
|
||||
}
|
||||
result =
|
||||
cudaMemsetAsync(outputBufferGPU, 0, outputTensorDesc[0].size, stream);
|
||||
if (result != cudaSuccess) {
|
||||
DPRINTF("Error in enqueueing memset for output\n");
|
||||
cleanUp(&resourceList);
|
||||
return 1;
|
||||
}
|
||||
|
||||
// Enqueue a cuDLA task.
|
||||
cudlaTask task;
|
||||
task.moduleHandle = moduleHandle;
|
||||
task.outputTensor = &outputBufferRegisteredPtr;
|
||||
task.numOutputTensors = 1;
|
||||
task.numInputTensors = 1;
|
||||
task.inputTensor = &inputBufferRegisteredPtr;
|
||||
task.waitEvents = NULL;
|
||||
task.signalEvents = NULL;
|
||||
err = cudlaSubmitTask(devHandle, &task, 1, stream, 0);
|
||||
if (err != cudlaSuccess) {
|
||||
DPRINTF("Error in submitting task\n");
|
||||
cleanUp(&resourceList);
|
||||
return 1;
|
||||
}
|
||||
DPRINTF("SUBMIT IS DONE !!!\n");
|
||||
|
||||
// Wait for stream operations to finish and bring output buffer to CPU.
|
||||
result =
|
||||
cudaMemcpyAsync(outputBuffer, outputBufferGPU, outputTensorDesc[0].size,
|
||||
cudaMemcpyDeviceToHost, stream);
|
||||
if (result != cudaSuccess) {
|
||||
if (result != cudaErrorExternalDevice) {
|
||||
DPRINTF("Error in bringing result back to CPU\n");
|
||||
cleanUp(&resourceList);
|
||||
return 1;
|
||||
} else {
|
||||
cudlaStatus hwStatus = cudlaGetLastError(devHandle);
|
||||
if (hwStatus != cudlaSuccess) {
|
||||
DPRINTF("Asynchronous error in HW = %u\n", hwStatus);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
result = cudaStreamSynchronize(stream);
|
||||
if (result != cudaSuccess) {
|
||||
DPRINTF("Error in synchronizing stream = %s\n", cudaGetErrorName(result));
|
||||
|
||||
if (result == cudaErrorExternalDevice) {
|
||||
cudlaStatus hwStatus = cudlaGetLastError(devHandle);
|
||||
if (hwStatus != cudlaSuccess) {
|
||||
DPRINTF("Asynchronous error in HW = %u\n", hwStatus);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
cleanUp(&resourceList);
|
||||
|
||||
DPRINTF("cuDLAErrorReporting DONE !!!\n");
|
||||
|
||||
return 0;
|
||||
return 0;
|
||||
}
|
||||
|
||||
Reference in New Issue
Block a user