CUresult CreateCuFunction(const char* name, CuModule* module, int3 blockShape,
FunctionPtr* ppFunction) {
CUfunction func;
CUresult result = cuModuleGetFunction(&func, module->Handle(), name);
if(CUDA_SUCCESS != result) return result;
FunctionPtr f(new CuFunction);
CuFuncAttr& attr = f->_attributes;
cuFuncGetAttribute(&attr.maxThreadsPerBlock,
CU_FUNC_ATTRIBUTE_MAX_THREADS_PER_BLOCK, func);
cuFuncGetAttribute(&attr.sharedSizeBytes,
CU_FUNC_ATTRIBUTE_SHARED_SIZE_BYTES, func);
cuFuncGetAttribute(&attr.constSizeBytes,
CU_FUNC_ATTRIBUTE_CONST_SIZE_BYTES, func);
cuFuncGetAttribute(&attr.localSizeBytes,
CU_FUNC_ATTRIBUTE_LOCAL_SIZE_BYTES, func);
cuFuncGetAttribute(&attr.numRegs,
CU_FUNC_ATTRIBUTE_NUM_REGS, func);
cuFuncGetAttribute(&attr.ptxVersion,
CU_FUNC_ATTRIBUTE_PTX_VERSION, func);
cuFuncGetAttribute(&attr.binaryVersion,
CU_FUNC_ATTRIBUTE_BINARY_VERSION, func);
f->_function = func;
f->_module = module;
f->_functionName = name;
f->_blockShape = blockShape;
ppFunction->swap(f);
return CUDA_SUCCESS;
}
SEXP
R_auto_cuFuncGetAttribute(SEXP r_attrib, SEXP r_hfunc)
{
SEXP r_ans = R_NilValue;
int pi;
CUfunction_attribute attrib = (CUfunction_attribute) INTEGER(r_attrib)[0];
CUfunction hfunc = (CUfunction) getRReference(r_hfunc);
CUresult ans;
ans = cuFuncGetAttribute(& pi, attrib, hfunc);
if(ans)
return(R_cudaErrorInfo(ans));
r_ans = ScalarInteger(pi) ;
return(r_ans);
}
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;
}
static int cuda_property(void *c, gpudata *buf, gpukernel *k, int prop_id,
void *res) {
cuda_context *ctx = NULL;
if (c != NULL) {
ctx = (cuda_context *)c;
ASSERT_CTX(ctx);
} else if (buf != NULL) {
ASSERT_BUF(buf);
ctx = buf->ctx;
} else if (k != NULL) {
ASSERT_KER(k);
ctx = k->ctx;
}
/* I know that 512 and 1024 are magic numbers.
There is an indication in buffer.h, though. */
if (prop_id < 512) {
if (ctx == NULL)
return GA_VALUE_ERROR;
} else if (prop_id < 1024) {
if (buf == NULL)
return GA_VALUE_ERROR;
} else {
if (k == NULL)
return GA_VALUE_ERROR;
}
switch (prop_id) {
char *s;
CUdevice id;
int i;
size_t sz;
case GA_CTX_PROP_DEVNAME:
cuda_enter(ctx);
ctx->err = cuCtxGetDevice(&id);
if (ctx->err != CUDA_SUCCESS) {
cuda_exit(ctx);
return GA_IMPL_ERROR;
}
/* 256 is what the CUDA API uses so it's good enough for me */
s = malloc(256);
if (s == NULL) {
cuda_exit(ctx);
return GA_MEMORY_ERROR;
}
ctx->err = cuDeviceGetName(s, 256, id);
if (ctx->err != CUDA_SUCCESS) {
cuda_exit(ctx);
return GA_IMPL_ERROR;
}
*((char **)res) = s;
cuda_exit(ctx);
return GA_NO_ERROR;
case GA_CTX_PROP_MAXLSIZE:
cuda_enter(ctx);
ctx->err = cuCtxGetDevice(&id);
if (ctx->err != CUDA_SUCCESS) {
cuda_exit(ctx);
return GA_IMPL_ERROR;
}
ctx->err = cuDeviceGetAttribute(&i, CU_DEVICE_ATTRIBUTE_MAX_BLOCK_DIM_X,
id);
if (ctx->err != CUDA_SUCCESS) {
cuda_exit(ctx);
return GA_IMPL_ERROR;
}
*((size_t *)res) = i;
cuda_exit(ctx);
return GA_NO_ERROR;
case GA_CTX_PROP_LMEMSIZE:
cuda_enter(ctx);
ctx->err = cuCtxGetDevice(&id);
if (ctx->err != CUDA_SUCCESS) {
cuda_exit(ctx);
return GA_IMPL_ERROR;
}
ctx->err = cuDeviceGetAttribute(&i, CU_DEVICE_ATTRIBUTE_MAX_SHARED_MEMORY_PER_BLOCK,
id);
if (ctx->err != CUDA_SUCCESS) {
cuda_exit(ctx);
return GA_IMPL_ERROR;
}
*((size_t *)res) = i;
cuda_exit(ctx);
return GA_NO_ERROR;
case GA_CTX_PROP_NUMPROCS:
cuda_enter(ctx);
ctx->err = cuCtxGetDevice(&id);
if (ctx->err != CUDA_SUCCESS) {
cuda_exit(ctx);
return GA_IMPL_ERROR;
}
ctx->err = cuDeviceGetAttribute(&i,
CU_DEVICE_ATTRIBUTE_MULTIPROCESSOR_COUNT,
id);
if (ctx->err != CUDA_SUCCESS) {
cuda_exit(ctx);
return GA_IMPL_ERROR;
}
*((unsigned int *)res) = i;
cuda_exit(ctx);
return GA_NO_ERROR;
case GA_CTX_PROP_MAXGSIZE:
cuda_enter(ctx);
ctx->err = cuCtxGetDevice(&id);
if (ctx->err != CUDA_SUCCESS) {
cuda_exit(ctx);
return GA_IMPL_ERROR;
}
ctx->err = cuDeviceGetAttribute(&i, CU_DEVICE_ATTRIBUTE_MAX_GRID_DIM_X,
id);
if (ctx->err != CUDA_SUCCESS) {
cuda_exit(ctx);
return GA_IMPL_ERROR;
}
*((size_t *)res) = i;
cuda_exit(ctx);
return GA_NO_ERROR;
case GA_CTX_PROP_BLAS_OPS:
#ifdef WITH_CUDA_CUBLAS
*((gpuarray_blas_ops **)res) = &cublas_ops;
return GA_NO_ERROR;
#else
*((void **)res) = NULL;
return GA_DEVSUP_ERROR;
#endif
case GA_CTX_PROP_BIN_ID:
*((const char **)res) = ctx->bin_id;
return GA_NO_ERROR;
case GA_CTX_PROP_ERRBUF:
*((gpudata **)res) = ctx->errbuf;
return GA_NO_ERROR;
case GA_CTX_PROP_TOTAL_GMEM:
cuda_enter(ctx);
ctx->err = cuMemGetInfo(&sz, (size_t *)res);
cuda_exit(ctx);
return ctx->err == CUDA_SUCCESS ? GA_NO_ERROR : GA_IMPL_ERROR;
case GA_CTX_PROP_FREE_GMEM:
cuda_enter(ctx);
ctx->err = cuMemGetInfo((size_t *)res, &sz);
cuda_exit(ctx);
return ctx->err == CUDA_SUCCESS ? GA_NO_ERROR : GA_IMPL_ERROR;
case GA_BUFFER_PROP_REFCNT:
*((unsigned int *)res) = buf->refcnt;
return GA_NO_ERROR;
case GA_BUFFER_PROP_SIZE:
*((size_t *)res) = buf->sz;
return GA_NO_ERROR;
case GA_BUFFER_PROP_CTX:
case GA_KERNEL_PROP_CTX:
*((void **)res) = (void *)ctx;
return GA_NO_ERROR;
case GA_KERNEL_PROP_MAXLSIZE:
cuda_enter(ctx);
ctx->err = cuFuncGetAttribute(&i,
CU_FUNC_ATTRIBUTE_MAX_THREADS_PER_BLOCK,
k->k);
cuda_exit(ctx);
if (ctx->err != CUDA_SUCCESS)
return GA_IMPL_ERROR;
*((size_t *)res) = i;
return GA_NO_ERROR;
case GA_KERNEL_PROP_PREFLSIZE:
cuda_enter(ctx);
ctx->err = cuCtxGetDevice(&id);
if (ctx->err != CUDA_SUCCESS) {
cuda_exit(ctx);
return GA_IMPL_ERROR;
}
ctx->err = cuDeviceGetAttribute(&i, CU_DEVICE_ATTRIBUTE_WARP_SIZE, id);
if (ctx->err != CUDA_SUCCESS) {
cuda_exit(ctx);
return GA_IMPL_ERROR;
}
cuda_exit(ctx);
*((size_t *)res) = i;
return GA_NO_ERROR;
case GA_KERNEL_PROP_NUMARGS:
*((unsigned int *)res) = k->argcount;
return GA_NO_ERROR;
case GA_KERNEL_PROP_TYPES:
*((const int **)res) = k->types;
return GA_NO_ERROR;
default:
return GA_INVALID_ERROR;
}
}
static void print_function_attrs(CUmodule cuda_module, const char *func_name)
{
CUfunction kernel;
CUresult rc;
int max_threads_per_block;
int shared_mem_sz;
int const_mem_sz;
int local_mem_sz;
int num_regs;
int ptx_version;
int binary_version;
int cache_mode_ca;
int min_grid_sz;
int max_block_sz;
int i;
struct {
CUfunction_attribute attr;
int *vptr;
} catalog[] = {
{ CU_FUNC_ATTRIBUTE_MAX_THREADS_PER_BLOCK, &max_threads_per_block },
{ CU_FUNC_ATTRIBUTE_SHARED_SIZE_BYTES, &shared_mem_sz },
{ CU_FUNC_ATTRIBUTE_CONST_SIZE_BYTES, &const_mem_sz },
{ CU_FUNC_ATTRIBUTE_LOCAL_SIZE_BYTES, &local_mem_sz },
{ CU_FUNC_ATTRIBUTE_NUM_REGS, &num_regs },
{ CU_FUNC_ATTRIBUTE_PTX_VERSION, &ptx_version },
{ CU_FUNC_ATTRIBUTE_BINARY_VERSION, &binary_version },
{ CU_FUNC_ATTRIBUTE_CACHE_MODE_CA, &cache_mode_ca },
};
rc = cuModuleGetFunction(&kernel, cuda_module, func_name);
if (rc != CUDA_SUCCESS)
cuda_error(rc, "cuModuleGetFunction");
for (i=0; i < lengthof(catalog); i++)
{
rc = cuFuncGetAttribute(catalog[i].vptr,
catalog[i].attr,
kernel);
if (rc != CUDA_SUCCESS)
cuda_error(rc, "cuFuncGetAttribute");
}
rc = cuOccupancyMaxPotentialBlockSize(&min_grid_sz,
&max_block_sz,
kernel,
cb_occupancy_shmem_size,
dynamic_shmem_per_block,
1024 * 1024);
if (rc != CUDA_SUCCESS)
cuda_error(rc, "cuOccupancyMaxPotentialBlockSize");
printf("Kernel Function: %s\n"
" Max threads per block: %d\n"
" Shared memory usage: %d\n"
" Constant memory usage: %d\n"
" Local memory usage: %d\n"
" Number of registers: %d\n"
" PTX version: %d\n"
" Binary version: %d\n"
" Global memory caching: %s\n"
" Max potential block size: %u\n"
" (shmem usage: %ld/thread + %ld/block)\n",
func_name,
max_threads_per_block,
shared_mem_sz,
const_mem_sz,
local_mem_sz,
num_regs,
ptx_version,
binary_version,
cache_mode_ca ? "enabled" : "disabled",
max_block_sz,
dynamic_shmem_per_thread,
dynamic_shmem_per_block);
}
size_t shared_size_bytes() const {
int n;
cuda_check( cuFuncGetAttribute(&n, CU_FUNC_ATTRIBUTE_SHARED_SIZE_BYTES, K) );
return n;
}
/// The maximum number of threads per block, beyond which a launch of the kernel would fail.
size_t max_threads_per_block(const command_queue&) const {
int n;
cuda_check( cuFuncGetAttribute(&n, CU_FUNC_ATTRIBUTE_MAX_THREADS_PER_BLOCK, K) );
return n;
}
