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aad-assignment-1/aad_cuda_utilities.h

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//
// Tomás Oliveira e Silva, September 2025
//
// Arquiteturas de Alto Desempenho 2025/2026
//
// CUDA driver API stuff
//
#ifndef AAD_CUDA_UTILITIES
#define AAD_CUDA_UTILITIES
#include <cuda.h>
//
// data type used to store all CUDA related stuff
//
#define MAX_N_ARGUMENTS 4
typedef struct
{
// input data
int device_number; // number of the device to initialize
char *cubin_file_name; // name of the cubin file to load (NULL if not needed)
char *kernel_name; // name of the CUDA kernel to load (NULL if not needed)
u32_t data_size[2]; // the number of bytes of the two data arrays to allocate on the host and on the device (0 if not needed)
// persistent data
CUdevice cu_device; // the device yhandle
char device_name[256]; // the device name
CUcontext cu_context; // the device context
CUmodule cu_module; // the loaded cubin file contents
CUfunction cu_kernel; // the pointer to the CUDA kernel
CUstream cu_stream; // the command stream
void *host_data[2]; // the pointers to the host data
CUdeviceptr device_data[2]; // the pointers to the device data
// launch kernel data
unsigned int grid_dim_x; // the number of grid blocks (in the X dimension, the only one we will use here)
unsigned int block_dim_x; // the number of threads in a block (in the X dimension, the only one we will use here, should be equal to RECOMMENDED_CUDA_BLOCK_SIZE)
int n_kernel_arguments; // number of kernel arguments
void *arg[MAX_N_ARGUMENTS]; // pointers to the kernel argument data
}
cuda_data_t;
//
// CU_CALL --- macro that should be used to call a CUDA driver API function and to test its return value
//
// it should be used to test the return value of calls such as
// cuInit(device_number);
// cuDeviceGet(&cu_device,device_number);
//
// in these cases, f_name is, respectively, cuInit and cuDeviceGet, and args is, respectively,
// (device_number) and (&cu_device,device_number)
//
#define CU_CALL(f_name,args) \
do \
{ \
CUresult e = f_name args; \
if(e != CUDA_SUCCESS) \
{ /* the call failed, terminate the program */ \
fprintf(stderr,"" # f_name "() returned %s (file %s, line %d)\n",cu_error_string(e),__FILE__,__LINE__); \
exit(1); \
} \
} \
while(0)
//
// terse description of the CUDA error codes (replacement of the error code number by its name)
//
static const char *cu_error_string(CUresult e)
{
static char error_string[64];
# define CASE(error_code) case error_code: return "" # error_code;
switch((int)e)
{ // list of error codes extracted from cuda.h (TODO: /usr/local/cuda-10.2/targets/x86_64-linux/include/CL)
default: sprintf(error_string,"unknown error code (%d)",(int)e); return(error_string);
CASE(CUDA_SUCCESS );
CASE(CUDA_ERROR_INVALID_VALUE );
CASE(CUDA_ERROR_OUT_OF_MEMORY );
CASE(CUDA_ERROR_NOT_INITIALIZED );
CASE(CUDA_ERROR_DEINITIALIZED );
CASE(CUDA_ERROR_PROFILER_DISABLED );
CASE(CUDA_ERROR_PROFILER_NOT_INITIALIZED );
CASE(CUDA_ERROR_PROFILER_ALREADY_STARTED );
CASE(CUDA_ERROR_PROFILER_ALREADY_STOPPED );
CASE(CUDA_ERROR_NO_DEVICE );
CASE(CUDA_ERROR_INVALID_DEVICE );
CASE(CUDA_ERROR_INVALID_IMAGE );
CASE(CUDA_ERROR_INVALID_CONTEXT );
CASE(CUDA_ERROR_CONTEXT_ALREADY_CURRENT );
CASE(CUDA_ERROR_MAP_FAILED );
CASE(CUDA_ERROR_UNMAP_FAILED );
CASE(CUDA_ERROR_ARRAY_IS_MAPPED );
CASE(CUDA_ERROR_ALREADY_MAPPED );
CASE(CUDA_ERROR_NO_BINARY_FOR_GPU );
CASE(CUDA_ERROR_ALREADY_ACQUIRED );
CASE(CUDA_ERROR_NOT_MAPPED );
CASE(CUDA_ERROR_NOT_MAPPED_AS_ARRAY );
CASE(CUDA_ERROR_NOT_MAPPED_AS_POINTER );
CASE(CUDA_ERROR_ECC_UNCORRECTABLE );
CASE(CUDA_ERROR_UNSUPPORTED_LIMIT );
CASE(CUDA_ERROR_CONTEXT_ALREADY_IN_USE );
CASE(CUDA_ERROR_PEER_ACCESS_UNSUPPORTED );
CASE(CUDA_ERROR_INVALID_PTX );
CASE(CUDA_ERROR_INVALID_GRAPHICS_CONTEXT );
CASE(CUDA_ERROR_NVLINK_UNCORRECTABLE );
CASE(CUDA_ERROR_INVALID_SOURCE );
CASE(CUDA_ERROR_FILE_NOT_FOUND );
CASE(CUDA_ERROR_SHARED_OBJECT_SYMBOL_NOT_FOUND);
CASE(CUDA_ERROR_SHARED_OBJECT_INIT_FAILED );
CASE(CUDA_ERROR_OPERATING_SYSTEM );
CASE(CUDA_ERROR_INVALID_HANDLE );
CASE(CUDA_ERROR_NOT_FOUND );
CASE(CUDA_ERROR_NOT_READY );
CASE(CUDA_ERROR_ILLEGAL_ADDRESS );
CASE(CUDA_ERROR_LAUNCH_OUT_OF_RESOURCES );
CASE(CUDA_ERROR_LAUNCH_TIMEOUT );
CASE(CUDA_ERROR_LAUNCH_INCOMPATIBLE_TEXTURING );
CASE(CUDA_ERROR_PEER_ACCESS_ALREADY_ENABLED );
CASE(CUDA_ERROR_PEER_ACCESS_NOT_ENABLED );
CASE(CUDA_ERROR_PRIMARY_CONTEXT_ACTIVE );
CASE(CUDA_ERROR_CONTEXT_IS_DESTROYED );
CASE(CUDA_ERROR_ASSERT );
CASE(CUDA_ERROR_TOO_MANY_PEERS );
CASE(CUDA_ERROR_HOST_MEMORY_ALREADY_REGISTERED);
CASE(CUDA_ERROR_HOST_MEMORY_NOT_REGISTERED );
CASE(CUDA_ERROR_HARDWARE_STACK_ERROR );
CASE(CUDA_ERROR_ILLEGAL_INSTRUCTION );
CASE(CUDA_ERROR_MISALIGNED_ADDRESS );
CASE(CUDA_ERROR_INVALID_ADDRESS_SPACE );
CASE(CUDA_ERROR_INVALID_PC );
CASE(CUDA_ERROR_LAUNCH_FAILED );
CASE(CUDA_ERROR_NOT_PERMITTED );
CASE(CUDA_ERROR_NOT_SUPPORTED );
CASE(CUDA_ERROR_UNKNOWN );
};
# undef CASE
}
//
// synchonize the stream command buffer
//
static void synchronize_cuda(cuda_data_t *cd)
{
CU_CALL( cuStreamSynchronize , (cd->cu_stream) );
}
//
// initialize the CUDA driver API interface
//
// load a single cubin file, with a single CUDA kernel
// allocate up to two storage areas both on the host and on the device
//
static void initialize_cuda(cuda_data_t *cd)
{
//
// initialize the driver API interface
//
CU_CALL( cuInit , (0) );
//
// open the CUDA device
//
CU_CALL( cuDeviceGet , (&cd->cu_device,cd->device_number) );
//
// get information about the CUDA device
//
CU_CALL( cuDeviceGetName , (cd->device_name,(int)sizeof(cd->device_name) - 1,cd->cu_device) );
printf("initialize_cuda(): CUDA code running on a %s (device %d, CUDA %u.%u.%u)\n",cd->device_name,cd->device_number,CUDA_VERSION / 1000,(CUDA_VERSION / 10) % 100,CUDA_VERSION % 10);
//
// create a context
//
CU_CALL( cuDevicePrimaryCtxRetain , (&cd->cu_context,cd->cu_device) );
CU_CALL( cuCtxSetCurrent , (cd->cu_context) );
CU_CALL( cuCtxSetCacheConfig , (CU_FUNC_CACHE_PREFER_L1) );
//
// load precompiled modules
//
CU_CALL( cuModuleLoad , (&cd->cu_module,cd->cubin_file_name) );
//
// get the kernel function pointers
//
CU_CALL( cuModuleGetFunction, (&cd->cu_kernel,cd->cu_module,cd->kernel_name) );
//
// create a command stream (we could have used the default stream)
//
CU_CALL( cuStreamCreate, (&cd->cu_stream,CU_STREAM_NON_BLOCKING) );
//
// allocate host and device memory
//
for(int i = 0;i < 2;i++)
if(cd->data_size[i] > 0u)
{
CU_CALL( cuMemAllocHost , ((void **)&cd->host_data[i] ,(size_t)cd->data_size[i]) );
CU_CALL( cuMemAlloc , (&cd->device_data[i],(size_t)cd->data_size[i]) );
}
else
cd->host_data[i] = NULL;
//
// catch any lingering errors
//
synchronize_cuda(cd);
}
//
// terminate the CUDA driver API interface
//
static void terminate_cuda(cuda_data_t *cd)
{
CU_CALL( cuStreamDestroy, (cd->cu_stream) );
for(int i = 0;i < 2;i++)
if(cd->data_size[i] > 0u)
{
CU_CALL( cuMemFreeHost , (cd->host_data[i]) );
CU_CALL( cuMemFree , (cd->device_data[i]) );
}
CU_CALL( cuModuleUnload , (cd->cu_module) );
CU_CALL( cuDevicePrimaryCtxRelease, (cd->cu_device) );
}
//
// copy data from the host to the device and from the device to the host
//
static void host_to_device_copy(cuda_data_t *cd,int idx)
{
if(idx < 0 || idx > 1 || cd->data_size[idx] == 0u)
{
fprintf(stderr,"host_to_device_copy(): bad idx\n");
exit(1);
}
CU_CALL( cuMemcpyHtoD , (cd->device_data[idx],(void *)cd->host_data[idx],(size_t)cd->data_size[idx]) );
synchronize_cuda(cd);
}
static void device_to_host_copy(cuda_data_t *cd,int idx)
{
if(idx < 0 || idx > 1 || cd->data_size[idx] == 0u)
{
fprintf(stderr,"device_to_host_copy(): bad idx\n");
exit(1);
}
CU_CALL( cuMemcpyDtoH , ((void *)cd->host_data[idx],cd->device_data[idx],(size_t)cd->data_size[idx]) );
synchronize_cuda(cd);
}
//
// launch a CUDA kernel (with 0 bytes of shared memory and no extra options)
//
static void launch_kernel(cuda_data_t *cd)
{
if(cd->block_dim_x != (unsigned int)RECOMMENDED_CUDA_BLOCK_SIZE)
fprintf(stderr,"launch_kernel(): block_dim_x should be equal to %d\n",RECOMMENDED_CUDA_BLOCK_SIZE);
CU_CALL( cuLaunchKernel , (cd->cu_kernel,cd->grid_dim_x,1u,1u,cd->block_dim_x,1u,1u,0u,cd->cu_stream,&cd->arg[0],NULL) );
synchronize_cuda(cd);
}
#endif
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