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blender/intern/cycles/device/device_cuda.cpp

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/*
* Copyright 2011-2013 Blender Foundation
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
#include <climits>
#include <limits.h>
#include <stdio.h>
#include <stdlib.h>
#include <string.h>
#include "device.h"
#include "device_intern.h"
#include "device_split_kernel.h"
#include "buffers.h"
#ifdef WITH_CUDA_DYNLOAD
# include "cuew.h"
#else
# include "util_opengl.h"
# include <cuda.h>
# include <cudaGL.h>
#endif
#include "util_debug.h"
#include "util_logging.h"
#include "util_map.h"
#include "util_md5.h"
#include "util_opengl.h"
#include "util_path.h"
#include "util_string.h"
#include "util_system.h"
#include "util_types.h"
#include "util_time.h"
#include "split/kernel_split_data_types.h"
CCL_NAMESPACE_BEGIN
#ifndef WITH_CUDA_DYNLOAD
/* Transparently implement some functions, so majority of the file does not need
* to worry about difference between dynamically loaded and linked CUDA at all.
*/
namespace {
const char *cuewErrorString(CUresult result)
{
/* We can only give error code here without major code duplication, that
* should be enough since dynamic loading is only being disabled by folks
* who knows what they're doing anyway.
*
* NOTE: Avoid call from several threads.
*/
static string error;
error = string_printf("%d", result);
return error.c_str();
}
const char *cuewCompilerPath(void)
{
return CYCLES_CUDA_NVCC_EXECUTABLE;
}
int cuewCompilerVersion(void)
{
return (CUDA_VERSION / 100) + (CUDA_VERSION % 100 / 10);
}
} /* namespace */
#endif /* WITH_CUDA_DYNLOAD */
class CUDADevice;
class CUDASplitKernel : public DeviceSplitKernel {
CUDADevice *device;
public:
explicit CUDASplitKernel(CUDADevice *device);
virtual size_t state_buffer_size(device_memory& kg, device_memory& data, size_t num_threads);
virtual bool enqueue_split_kernel_data_init(const KernelDimensions& dim,
RenderTile& rtile,
int num_global_elements,
device_memory& kernel_globals,
device_memory& kernel_data_,
device_memory& split_data,
device_memory& ray_state,
device_memory& queue_index,
device_memory& use_queues_flag,
device_memory& work_pool_wgs);
virtual SplitKernelFunction* get_split_kernel_function(string kernel_name, const DeviceRequestedFeatures&);
virtual int2 split_kernel_local_size();
virtual int2 split_kernel_global_size(device_memory& kg, device_memory& data, DeviceTask *task);
};
class CUDADevice : public Device
{
public:
DedicatedTaskPool task_pool;
CUdevice cuDevice;
CUcontext cuContext;
CUmodule cuModule;
map<device_ptr, bool> tex_interp_map;
map<device_ptr, uint> tex_bindless_map;
int cuDevId;
int cuDevArchitecture;
bool first_error;
struct PixelMem {
GLuint cuPBO;
CUgraphicsResource cuPBOresource;
GLuint cuTexId;
int w, h;
};
map<device_ptr, PixelMem> pixel_mem_map;
/* Bindless Textures */
device_vector<uint> bindless_mapping;
bool need_bindless_mapping;
CUdeviceptr cuda_device_ptr(device_ptr mem)
{
return (CUdeviceptr)mem;
}
static bool have_precompiled_kernels()
{
string cubins_path = path_get("lib");
return path_exists(cubins_path);
}
virtual bool show_samples() const
{
/* The CUDADevice only processes one tile at a time, so showing samples is fine. */
return true;
}
/*#ifdef NDEBUG
#define cuda_abort()
#else
#define cuda_abort() abort()
#endif*/
void cuda_error_documentation()
{
if(first_error) {
fprintf(stderr, "\nRefer to the Cycles GPU rendering documentation for possible solutions:\n");
fprintf(stderr, "https://docs.blender.org/manual/en/dev/render/cycles/gpu_rendering.html\n\n");
first_error = false;
}
}
#define cuda_assert(stmt) \
{ \
CUresult result = stmt; \
\
if(result != CUDA_SUCCESS) { \
string message = string_printf("CUDA error: %s in %s", cuewErrorString(result), #stmt); \
if(error_msg == "") \
error_msg = message; \
fprintf(stderr, "%s\n", message.c_str()); \
/*cuda_abort();*/ \
cuda_error_documentation(); \
} \
} (void)0
bool cuda_error_(CUresult result, const string& stmt)
{
if(result == CUDA_SUCCESS)
return false;
string message = string_printf("CUDA error at %s: %s", stmt.c_str(), cuewErrorString(result));
if(error_msg == "")
error_msg = message;
fprintf(stderr, "%s\n", message.c_str());
cuda_error_documentation();
return true;
}
#define cuda_error(stmt) cuda_error_(stmt, #stmt)
void cuda_error_message(const string& message)
{
if(error_msg == "")
error_msg = message;
fprintf(stderr, "%s\n", message.c_str());
cuda_error_documentation();
}
void cuda_push_context()
{
cuda_assert(cuCtxSetCurrent(cuContext));
}
void cuda_pop_context()
{
cuda_assert(cuCtxSetCurrent(NULL));
}
CUDADevice(DeviceInfo& info, Stats &stats, bool background_)
: Device(info, stats, background_)
{
first_error = true;
background = background_;
cuDevId = info.num;
cuDevice = 0;
cuContext = 0;
need_bindless_mapping = false;
/* intialize */
if(cuda_error(cuInit(0)))
return;
/* setup device and context */
if(cuda_error(cuDeviceGet(&cuDevice, cuDevId)))
return;
CUresult result;
if(background) {
result = cuCtxCreate(&cuContext, 0, cuDevice);
}
else {
result = cuGLCtxCreate(&cuContext, 0, cuDevice);
if(result != CUDA_SUCCESS) {
result = cuCtxCreate(&cuContext, 0, cuDevice);
background = true;
}
}
if(cuda_error_(result, "cuCtxCreate"))
return;
int major, minor;
cuDeviceGetAttribute(&major, CU_DEVICE_ATTRIBUTE_COMPUTE_CAPABILITY_MAJOR, cuDevId);
cuDeviceGetAttribute(&minor, CU_DEVICE_ATTRIBUTE_COMPUTE_CAPABILITY_MINOR, cuDevId);
cuDevArchitecture = major*100 + minor*10;
cuda_pop_context();
}
~CUDADevice()
{
task_pool.stop();
if(info.has_bindless_textures) {
tex_free(bindless_mapping);
}
cuda_assert(cuCtxDestroy(cuContext));
}
bool support_device(const DeviceRequestedFeatures& /*requested_features*/)
{
int major, minor;
cuDeviceGetAttribute(&major, CU_DEVICE_ATTRIBUTE_COMPUTE_CAPABILITY_MAJOR, cuDevId);
cuDeviceGetAttribute(&minor, CU_DEVICE_ATTRIBUTE_COMPUTE_CAPABILITY_MINOR, cuDevId);
/* We only support sm_20 and above */
if(major < 2) {
cuda_error_message(string_printf("CUDA device supported only with compute capability 2.0 or up, found %d.%d.", major, minor));
return false;
}
return true;
}
bool use_adaptive_compilation()
{
return DebugFlags().cuda.adaptive_compile;
}
bool use_split_kernel()
{
return DebugFlags().cuda.split_kernel;
}
/* Common NVCC flags which stays the same regardless of shading model,
* kernel sources md5 and only depends on compiler or compilation settings.
*/
string compile_kernel_get_common_cflags(
const DeviceRequestedFeatures& requested_features, bool split=false)
{
const int cuda_version = cuewCompilerVersion();
const int machine = system_cpu_bits();
const string kernel_path = path_get("kernel");
const string include = kernel_path;
string cflags = string_printf("-m%d "
"--ptxas-options=\"-v\" "
"--use_fast_math "
"-DNVCC "
"-D__KERNEL_CUDA_VERSION__=%d "
"-I\"%s\"",
machine,
cuda_version,
include.c_str());
if(use_adaptive_compilation()) {
cflags += " " + requested_features.get_build_options();
}
const char *extra_cflags = getenv("CYCLES_CUDA_EXTRA_CFLAGS");
if(extra_cflags) {
cflags += string(" ") + string(extra_cflags);
}
#ifdef WITH_CYCLES_DEBUG
cflags += " -D__KERNEL_DEBUG__";
#endif
if(split) {
cflags += " -D__SPLIT__";
}
return cflags;
}
bool compile_check_compiler() {
const char *nvcc = cuewCompilerPath();
if(nvcc == NULL) {
cuda_error_message("CUDA nvcc compiler not found. "
"Install CUDA toolkit in default location.");
return false;
}
const int cuda_version = cuewCompilerVersion();
VLOG(1) << "Found nvcc " << nvcc
<< ", CUDA version " << cuda_version
<< ".";
const int major = cuda_version / 10, minor = cuda_version & 10;
if(cuda_version == 0) {
cuda_error_message("CUDA nvcc compiler version could not be parsed.");
return false;
}
if(cuda_version < 75) {
printf("Unsupported CUDA version %d.%d detected, "
"you need CUDA 7.5 or newer.\n",
major, minor);
return false;
}
else if(cuda_version != 75 && cuda_version != 80) {
printf("CUDA version %d.%d detected, build may succeed but only "
"CUDA 7.5 and 8.0 are officially supported.\n",
major, minor);
}
return true;
}
string compile_kernel(const DeviceRequestedFeatures& requested_features, bool split=false)
{
/* Compute cubin name. */
int major, minor;
cuDeviceGetAttribute(&major, CU_DEVICE_ATTRIBUTE_COMPUTE_CAPABILITY_MAJOR, cuDevId);
cuDeviceGetAttribute(&minor, CU_DEVICE_ATTRIBUTE_COMPUTE_CAPABILITY_MINOR, cuDevId);
/* Attempt to use kernel provided with Blender. */
if(!use_adaptive_compilation()) {
const string cubin = path_get(string_printf(split ? "lib/kernel_split_sm_%d%d.cubin"
: "lib/kernel_sm_%d%d.cubin",
major, minor));
VLOG(1) << "Testing for pre-compiled kernel " << cubin << ".";
if(path_exists(cubin)) {
VLOG(1) << "Using precompiled kernel.";
return cubin;
}
}
const string common_cflags =
compile_kernel_get_common_cflags(requested_features, split);
/* Try to use locally compiled kernel. */
const string kernel_path = path_get("kernel");
const string kernel_md5 = path_files_md5_hash(kernel_path);
/* We include cflags into md5 so changing cuda toolkit or changing other
* compiler command line arguments makes sure cubin gets re-built.
*/
const string cubin_md5 = util_md5_string(kernel_md5 + common_cflags);
const string cubin_file = string_printf(split ? "cycles_kernel_split_sm%d%d_%s.cubin"
: "cycles_kernel_sm%d%d_%s.cubin",
major, minor,
cubin_md5.c_str());
const string cubin = path_cache_get(path_join("kernels", cubin_file));
VLOG(1) << "Testing for locally compiled kernel " << cubin << ".";
if(path_exists(cubin)) {
VLOG(1) << "Using locally compiled kernel.";
return cubin;
}
#ifdef _WIN32
if(have_precompiled_kernels()) {
if(major < 2) {
cuda_error_message(string_printf(
"CUDA device requires compute capability 2.0 or up, "
"found %d.%d. Your GPU is not supported.",
major, minor));
}
else {
cuda_error_message(string_printf(
"CUDA binary kernel for this graphics card compute "
"capability (%d.%d) not found.",
major, minor));
}
return "";
}
#endif
/* Compile. */
if(!compile_check_compiler()) {
return "";
}
const char *nvcc = cuewCompilerPath();
const string kernel = path_join(kernel_path,
path_join("kernels",
path_join("cuda", split ? "kernel_split.cu" : "kernel.cu")));
double starttime = time_dt();
printf("Compiling CUDA kernel ...\n");
path_create_directories(cubin);
string command = string_printf("\"%s\" "
"-arch=sm_%d%d "
"--cubin \"%s\" "
"-o \"%s\" "
"%s ",
nvcc,
major, minor,
kernel.c_str(),
cubin.c_str(),
common_cflags.c_str());
printf("%s\n", command.c_str());
if(system(command.c_str()) == -1) {
cuda_error_message("Failed to execute compilation command, "
"see console for details.");
return "";
}
/* Verify if compilation succeeded */
if(!path_exists(cubin)) {
cuda_error_message("CUDA kernel compilation failed, "
"see console for details.");
return "";
}
printf("Kernel compilation finished in %.2lfs.\n", time_dt() - starttime);
return cubin;
}
bool load_kernels(const DeviceRequestedFeatures& requested_features)
{
/* check if cuda init succeeded */
if(cuContext == 0)
return false;
/* check if GPU is supported */
if(!support_device(requested_features))
return false;
/* get kernel */
string cubin = compile_kernel(requested_features, use_split_kernel());
if(cubin == "")
return false;
/* open module */
cuda_push_context();
string cubin_data;
CUresult result;
if(path_read_text(cubin, cubin_data))
result = cuModuleLoadData(&cuModule, cubin_data.c_str());
else
result = CUDA_ERROR_FILE_NOT_FOUND;
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);
}
void load_bindless_mapping()
{
if(info.has_bindless_textures && need_bindless_mapping) {
tex_free(bindless_mapping);
tex_alloc("__bindless_mapping", bindless_mapping, INTERPOLATION_NONE, EXTENSION_REPEAT);
need_bindless_mapping = false;
}
}
void mem_alloc(const char *name, device_memory& mem, MemoryType /*type*/)
{
if(name) {
VLOG(1) << "Buffer allocate: " << name << ", "
<< string_human_readable_number(mem.memory_size()) << " bytes. ("
<< string_human_readable_size(mem.memory_size()) << ")";
}
cuda_push_context();
CUdeviceptr device_pointer;
size_t size = mem.memory_size();
cuda_assert(cuMemAlloc(&device_pointer, size));
mem.device_pointer = (device_ptr)device_pointer;
mem.device_size = size;
stats.mem_alloc(size);
cuda_pop_context();
}
void mem_copy_to(device_memory& mem)
{
cuda_push_context();
if(mem.device_pointer)
cuda_assert(cuMemcpyHtoD(cuda_device_ptr(mem.device_pointer), (void*)mem.data_pointer, mem.memory_size()));
cuda_pop_context();
}
void mem_copy_from(device_memory& mem, int y, int w, int h, int elem)
{
size_t offset = elem*y*w;
size_t size = elem*w*h;
cuda_push_context();
if(mem.device_pointer) {
cuda_assert(cuMemcpyDtoH((uchar*)mem.data_pointer + offset,
(CUdeviceptr)(mem.device_pointer + offset), size));
}
else {
memset((char*)mem.data_pointer + offset, 0, size);
}
cuda_pop_context();
}
void mem_zero(device_memory& mem)
{
if(mem.data_pointer) {
memset((void*)mem.data_pointer, 0, mem.memory_size());
}
cuda_push_context();
if(mem.device_pointer)
cuda_assert(cuMemsetD8(cuda_device_ptr(mem.device_pointer), 0, mem.memory_size()));
cuda_pop_context();
}
void mem_free(device_memory& mem)
{
if(mem.device_pointer) {
cuda_push_context();
cuda_assert(cuMemFree(cuda_device_ptr(mem.device_pointer)));
cuda_pop_context();
mem.device_pointer = 0;
stats.mem_free(mem.device_size);
mem.device_size = 0;
}
}
void const_copy_to(const char *name, void *host, size_t size)
{
CUdeviceptr mem;
size_t bytes;
cuda_push_context();
cuda_assert(cuModuleGetGlobal(&mem, &bytes, cuModule, name));
//assert(bytes == size);
cuda_assert(cuMemcpyHtoD(mem, host, size));
cuda_pop_context();
}
void tex_alloc(const char *name,
device_memory& mem,
InterpolationType interpolation,
ExtensionType extension)
{
VLOG(1) << "Texture allocate: " << name << ", "
<< string_human_readable_number(mem.memory_size()) << " bytes. ("
<< string_human_readable_size(mem.memory_size()) << ")";
/* Check if we are on sm_30 or above.
* We use arrays and bindles textures for storage there */
bool has_bindless_textures = info.has_bindless_textures;
/* General variables for both architectures */
string bind_name = name;
size_t dsize = datatype_size(mem.data_type);
size_t size = mem.memory_size();
CUaddress_mode address_mode = CU_TR_ADDRESS_MODE_WRAP;
switch(extension) {
case EXTENSION_REPEAT:
address_mode = CU_TR_ADDRESS_MODE_WRAP;
break;
case EXTENSION_EXTEND:
address_mode = CU_TR_ADDRESS_MODE_CLAMP;
break;
case EXTENSION_CLIP:
address_mode = CU_TR_ADDRESS_MODE_BORDER;
break;
default:
assert(0);
break;
}
CUfilter_mode filter_mode;
if(interpolation == INTERPOLATION_CLOSEST) {
filter_mode = CU_TR_FILTER_MODE_POINT;
}
else {
filter_mode = CU_TR_FILTER_MODE_LINEAR;
}
CUarray_format_enum format;
switch(mem.data_type) {
case TYPE_UCHAR: format = CU_AD_FORMAT_UNSIGNED_INT8; break;
case TYPE_UINT: format = CU_AD_FORMAT_UNSIGNED_INT32; break;
case TYPE_INT: format = CU_AD_FORMAT_SIGNED_INT32; break;
case TYPE_FLOAT: format = CU_AD_FORMAT_FLOAT; break;
case TYPE_HALF: format = CU_AD_FORMAT_HALF; break;
default: assert(0); return;
}
/* General variables for Fermi */
CUtexref texref = NULL;
if(!has_bindless_textures) {
if(mem.data_depth > 1) {
/* Kernel uses different bind names for 2d and 3d float textures,
* so we have to adjust couple of things here.
*/
vector<string> tokens;
string_split(tokens, name, "_");
bind_name = string_printf("__tex_image_%s_3d_%s",
tokens[2].c_str(),
tokens[3].c_str());
}
cuda_push_context();
cuda_assert(cuModuleGetTexRef(&texref, cuModule, bind_name.c_str()));
cuda_pop_context();
if(!texref) {
return;
}
}
/* Data Storage */
if(interpolation == INTERPOLATION_NONE) {
if(has_bindless_textures) {
mem_alloc(NULL, mem, MEM_READ_ONLY);
mem_copy_to(mem);
cuda_push_context();
CUdeviceptr cumem;
size_t cubytes;
cuda_assert(cuModuleGetGlobal(&cumem, &cubytes, cuModule, bind_name.c_str()));
if(cubytes == 8) {
/* 64 bit device pointer */
uint64_t ptr = mem.device_pointer;
cuda_assert(cuMemcpyHtoD(cumem, (void*)&ptr, cubytes));
}
else {
/* 32 bit device pointer */
uint32_t ptr = (uint32_t)mem.device_pointer;
cuda_assert(cuMemcpyHtoD(cumem, (void*)&ptr, cubytes));
}
cuda_pop_context();
}
else {
mem_alloc(NULL, mem, MEM_READ_ONLY);
mem_copy_to(mem);
cuda_push_context();
cuda_assert(cuTexRefSetAddress(NULL, texref, cuda_device_ptr(mem.device_pointer), size));
cuda_assert(cuTexRefSetFilterMode(texref, CU_TR_FILTER_MODE_POINT));
cuda_assert(cuTexRefSetFlags(texref, CU_TRSF_READ_AS_INTEGER));
cuda_pop_context();
}
}
/* Texture Storage */
else {
CUarray handle = NULL;
cuda_push_context();
if(mem.data_depth > 1) {
CUDA_ARRAY3D_DESCRIPTOR desc;
desc.Width = mem.data_width;
desc.Height = mem.data_height;
desc.Depth = mem.data_depth;
desc.Format = format;
desc.NumChannels = mem.data_elements;
desc.Flags = 0;
cuda_assert(cuArray3DCreate(&handle, &desc));
}
else {
CUDA_ARRAY_DESCRIPTOR desc;
desc.Width = mem.data_width;
desc.Height = mem.data_height;
desc.Format = format;
desc.NumChannels = mem.data_elements;
cuda_assert(cuArrayCreate(&handle, &desc));
}
if(!handle) {
cuda_pop_context();
return;
}
/* Allocate 3D, 2D or 1D memory */
if(mem.data_depth > 1) {
CUDA_MEMCPY3D param;
memset(&param, 0, sizeof(param));
param.dstMemoryType = CU_MEMORYTYPE_ARRAY;
param.dstArray = handle;
param.srcMemoryType = CU_MEMORYTYPE_HOST;
param.srcHost = (void*)mem.data_pointer;
param.srcPitch = mem.data_width*dsize*mem.data_elements;
param.WidthInBytes = param.srcPitch;
param.Height = mem.data_height;
param.Depth = mem.data_depth;
cuda_assert(cuMemcpy3D(&param));
}
else if(mem.data_height > 1) {
CUDA_MEMCPY2D param;
memset(&param, 0, sizeof(param));
param.dstMemoryType = CU_MEMORYTYPE_ARRAY;
param.dstArray = handle;
param.srcMemoryType = CU_MEMORYTYPE_HOST;
param.srcHost = (void*)mem.data_pointer;
param.srcPitch = mem.data_width*dsize*mem.data_elements;
param.WidthInBytes = param.srcPitch;
param.Height = mem.data_height;
cuda_assert(cuMemcpy2D(&param));
}
else
cuda_assert(cuMemcpyHtoA(handle, 0, (void*)mem.data_pointer, size));
/* Fermi and Kepler */
mem.device_pointer = (device_ptr)handle;
mem.device_size = size;
stats.mem_alloc(size);
/* Bindless Textures - Kepler */
if(has_bindless_textures) {
int flat_slot = 0;
if(string_startswith(name, "__tex_image")) {
int pos = string(name).rfind("_");
flat_slot = atoi(name + pos + 1);
}
else {
assert(0);
}
CUDA_RESOURCE_DESC resDesc;
memset(&resDesc, 0, sizeof(resDesc));
resDesc.resType = CU_RESOURCE_TYPE_ARRAY;
resDesc.res.array.hArray = handle;
resDesc.flags = 0;
CUDA_TEXTURE_DESC texDesc;
memset(&texDesc, 0, sizeof(texDesc));
texDesc.addressMode[0] = address_mode;
texDesc.addressMode[1] = address_mode;
texDesc.addressMode[2] = address_mode;
texDesc.filterMode = filter_mode;
texDesc.flags = CU_TRSF_NORMALIZED_COORDINATES;
CUtexObject tex = 0;
cuda_assert(cuTexObjectCreate(&tex, &resDesc, &texDesc, NULL));
/* Safety check */
if((uint)tex > UINT_MAX) {
assert(0);
}
/* Resize once */
if(flat_slot >= bindless_mapping.size()) {
/* Allocate some slots in advance, to reduce amount
* of re-allocations.
*/
bindless_mapping.resize(flat_slot + 128);
}
/* Set Mapping and tag that we need to (re-)upload to device */
bindless_mapping.get_data()[flat_slot] = (uint)tex;
tex_bindless_map[mem.device_pointer] = (uint)tex;
need_bindless_mapping = true;
}
/* Regular Textures - Fermi */
else {
cuda_assert(cuTexRefSetArray(texref, handle, CU_TRSA_OVERRIDE_FORMAT));
cuda_assert(cuTexRefSetFilterMode(texref, filter_mode));
cuda_assert(cuTexRefSetFlags(texref, CU_TRSF_NORMALIZED_COORDINATES));
}
cuda_pop_context();
}
/* Fermi, Data and Image Textures */
if(!has_bindless_textures) {
cuda_push_context();
cuda_assert(cuTexRefSetAddressMode(texref, 0, address_mode));
cuda_assert(cuTexRefSetAddressMode(texref, 1, address_mode));
if(mem.data_depth > 1) {
cuda_assert(cuTexRefSetAddressMode(texref, 2, address_mode));
}
cuda_assert(cuTexRefSetFormat(texref, format, mem.data_elements));
cuda_pop_context();
}
/* Fermi and Kepler */
tex_interp_map[mem.device_pointer] = (interpolation != INTERPOLATION_NONE);
}
void tex_free(device_memory& mem)
{
if(mem.device_pointer) {
if(tex_interp_map[mem.device_pointer]) {
cuda_push_context();
cuArrayDestroy((CUarray)mem.device_pointer);
cuda_pop_context();
/* Free CUtexObject (Bindless Textures) */
if(info.has_bindless_textures && tex_bindless_map[mem.device_pointer]) {
uint flat_slot = tex_bindless_map[mem.device_pointer];
cuTexObjectDestroy(flat_slot);
}
tex_interp_map.erase(tex_interp_map.find(mem.device_pointer));
mem.device_pointer = 0;
stats.mem_free(mem.device_size);
mem.device_size = 0;
}
else {
tex_interp_map.erase(tex_interp_map.find(mem.device_pointer));
mem_free(mem);
}
}
}
void path_trace(RenderTile& rtile, int sample, bool branched)
{
if(have_error())
return;
cuda_push_context();
CUfunction cuPathTrace;
CUdeviceptr d_buffer = cuda_device_ptr(rtile.buffer);
CUdeviceptr d_rng_state = cuda_device_ptr(rtile.rng_state);
/* get kernel function */
if(branched) {
cuda_assert(cuModuleGetFunction(&cuPathTrace, cuModule, "kernel_cuda_branched_path_trace"));
}
else {
cuda_assert(cuModuleGetFunction(&cuPathTrace, cuModule, "kernel_cuda_path_trace"));
}
if(have_error())
return;
/* pass in parameters */
void *args[] = {&d_buffer,
&d_rng_state,
&sample,
&rtile.x,
&rtile.y,
&rtile.w,
&rtile.h,
&rtile.offset,
&rtile.stride};
/* launch kernel */
int threads_per_block;
cuda_assert(cuFuncGetAttribute(&threads_per_block, CU_FUNC_ATTRIBUTE_MAX_THREADS_PER_BLOCK, cuPathTrace));
/*int num_registers;
cuda_assert(cuFuncGetAttribute(&num_registers, CU_FUNC_ATTRIBUTE_NUM_REGS, cuPathTrace));
printf("threads_per_block %d\n", threads_per_block);
printf("num_registers %d\n", num_registers);*/
int xthreads = (int)sqrt(threads_per_block);
int ythreads = (int)sqrt(threads_per_block);
int xblocks = (rtile.w + xthreads - 1)/xthreads;
int yblocks = (rtile.h + ythreads - 1)/ythreads;
cuda_assert(cuFuncSetCacheConfig(cuPathTrace, CU_FUNC_CACHE_PREFER_L1));
cuda_assert(cuLaunchKernel(cuPathTrace,
xblocks , yblocks, 1, /* blocks */
xthreads, ythreads, 1, /* threads */
0, 0, args, 0));
cuda_assert(cuCtxSynchronize());
cuda_pop_context();
}
void film_convert(DeviceTask& task, device_ptr buffer, device_ptr rgba_byte, device_ptr rgba_half)
{
if(have_error())
return;
cuda_push_context();
CUfunction cuFilmConvert;
CUdeviceptr d_rgba = map_pixels((rgba_byte)? rgba_byte: rgba_half);
CUdeviceptr d_buffer = cuda_device_ptr(buffer);
/* get kernel function */
if(rgba_half) {
cuda_assert(cuModuleGetFunction(&cuFilmConvert, cuModule, "kernel_cuda_convert_to_half_float"));
}
else {
cuda_assert(cuModuleGetFunction(&cuFilmConvert, cuModule, "kernel_cuda_convert_to_byte"));
}
float sample_scale = 1.0f/(task.sample + 1);
/* pass in parameters */
void *args[] = {&d_rgba,
&d_buffer,
&sample_scale,
&task.x,
&task.y,
&task.w,
&task.h,
&task.offset,
&task.stride};
/* launch kernel */
int threads_per_block;
cuda_assert(cuFuncGetAttribute(&threads_per_block, CU_FUNC_ATTRIBUTE_MAX_THREADS_PER_BLOCK, cuFilmConvert));
int xthreads = (int)sqrt(threads_per_block);
int ythreads = (int)sqrt(threads_per_block);
int xblocks = (task.w + xthreads - 1)/xthreads;
int yblocks = (task.h + ythreads - 1)/ythreads;
cuda_assert(cuFuncSetCacheConfig(cuFilmConvert, CU_FUNC_CACHE_PREFER_L1));
cuda_assert(cuLaunchKernel(cuFilmConvert,
xblocks , yblocks, 1, /* blocks */
xthreads, ythreads, 1, /* threads */
0, 0, args, 0));
unmap_pixels((rgba_byte)? rgba_byte: rgba_half);
cuda_pop_context();
}
void shader(DeviceTask& task)
{
if(have_error())
return;
cuda_push_context();
CUfunction cuShader;
CUdeviceptr d_input = cuda_device_ptr(task.shader_input);
CUdeviceptr d_output = cuda_device_ptr(task.shader_output);
CUdeviceptr d_output_luma = cuda_device_ptr(task.shader_output_luma);
/* get kernel function */
if(task.shader_eval_type >= SHADER_EVAL_BAKE) {
cuda_assert(cuModuleGetFunction(&cuShader, cuModule, "kernel_cuda_bake"));
}
else {
cuda_assert(cuModuleGetFunction(&cuShader, cuModule, "kernel_cuda_shader"));
}
/* do tasks in smaller chunks, so we can cancel it */
const int shader_chunk_size = 65536;
const int start = task.shader_x;
const int end = task.shader_x + task.shader_w;
int offset = task.offset;
bool canceled = false;
for(int sample = 0; sample < task.num_samples && !canceled; sample++) {
for(int shader_x = start; shader_x < end; shader_x += shader_chunk_size) {
int shader_w = min(shader_chunk_size, end - shader_x);
/* pass in parameters */
void *args[8];
int arg = 0;
args[arg++] = &d_input;
args[arg++] = &d_output;
if(task.shader_eval_type < SHADER_EVAL_BAKE) {
args[arg++] = &d_output_luma;
}
args[arg++] = &task.shader_eval_type;
if(task.shader_eval_type >= SHADER_EVAL_BAKE) {
args[arg++] = &task.shader_filter;
}
args[arg++] = &shader_x;
args[arg++] = &shader_w;
args[arg++] = &offset;
args[arg++] = &sample;
/* launch kernel */
int threads_per_block;
cuda_assert(cuFuncGetAttribute(&threads_per_block, CU_FUNC_ATTRIBUTE_MAX_THREADS_PER_BLOCK, cuShader));
int xblocks = (shader_w + threads_per_block - 1)/threads_per_block;
cuda_assert(cuFuncSetCacheConfig(cuShader, CU_FUNC_CACHE_PREFER_L1));
cuda_assert(cuLaunchKernel(cuShader,
xblocks , 1, 1, /* blocks */
threads_per_block, 1, 1, /* threads */
0, 0, args, 0));
cuda_assert(cuCtxSynchronize());
if(task.get_cancel()) {
canceled = true;
break;
}
}
task.update_progress(NULL);
}
cuda_pop_context();
}
CUdeviceptr map_pixels(device_ptr mem)
{
if(!background) {
PixelMem pmem = pixel_mem_map[mem];
CUdeviceptr buffer;
size_t bytes;
cuda_assert(cuGraphicsMapResources(1, &pmem.cuPBOresource, 0));
cuda_assert(cuGraphicsResourceGetMappedPointer(&buffer, &bytes, pmem.cuPBOresource));
return buffer;
}
return cuda_device_ptr(mem);
}
void unmap_pixels(device_ptr mem)
{
if(!background) {
PixelMem pmem = pixel_mem_map[mem];
cuda_assert(cuGraphicsUnmapResources(1, &pmem.cuPBOresource, 0));
}
}
void pixels_alloc(device_memory& mem)
{
if(!background) {
PixelMem pmem;
pmem.w = mem.data_width;
pmem.h = mem.data_height;
cuda_push_context();
glGenBuffers(1, &pmem.cuPBO);
glBindBuffer(GL_PIXEL_UNPACK_BUFFER, pmem.cuPBO);
if(mem.data_type == TYPE_HALF)
glBufferData(GL_PIXEL_UNPACK_BUFFER, pmem.w*pmem.h*sizeof(GLhalf)*4, NULL, GL_DYNAMIC_DRAW);
else
glBufferData(GL_PIXEL_UNPACK_BUFFER, pmem.w*pmem.h*sizeof(uint8_t)*4, NULL, GL_DYNAMIC_DRAW);
glBindBuffer(GL_PIXEL_UNPACK_BUFFER, 0);
glGenTextures(1, &pmem.cuTexId);
glBindTexture(GL_TEXTURE_2D, pmem.cuTexId);
if(mem.data_type == TYPE_HALF)
glTexImage2D(GL_TEXTURE_2D, 0, GL_RGBA16F_ARB, pmem.w, pmem.h, 0, GL_RGBA, GL_HALF_FLOAT, NULL);
else
glTexImage2D(GL_TEXTURE_2D, 0, GL_RGBA8, pmem.w, pmem.h, 0, GL_RGBA, GL_UNSIGNED_BYTE, NULL);
glTexParameteri(GL_TEXTURE_2D, GL_TEXTURE_MIN_FILTER, GL_NEAREST);
glTexParameteri(GL_TEXTURE_2D, GL_TEXTURE_MAG_FILTER, GL_NEAREST);
glBindTexture(GL_TEXTURE_2D, 0);
CUresult result = cuGraphicsGLRegisterBuffer(&pmem.cuPBOresource, pmem.cuPBO, CU_GRAPHICS_MAP_RESOURCE_FLAGS_NONE);
if(result == CUDA_SUCCESS) {
cuda_pop_context();
mem.device_pointer = pmem.cuTexId;
pixel_mem_map[mem.device_pointer] = pmem;
mem.device_size = mem.memory_size();
stats.mem_alloc(mem.device_size);
return;
}
else {
/* failed to register buffer, fallback to no interop */
glDeleteBuffers(1, &pmem.cuPBO);
glDeleteTextures(1, &pmem.cuTexId);
cuda_pop_context();
background = true;
}
}
Device::pixels_alloc(mem);
}
void pixels_copy_from(device_memory& mem, int y, int w, int h)
{
if(!background) {
PixelMem pmem = pixel_mem_map[mem.device_pointer];
cuda_push_context();
glBindBuffer(GL_PIXEL_UNPACK_BUFFER, pmem.cuPBO);
uchar *pixels = (uchar*)glMapBuffer(GL_PIXEL_UNPACK_BUFFER, GL_READ_ONLY);
size_t offset = sizeof(uchar)*4*y*w;
memcpy((uchar*)mem.data_pointer + offset, pixels + offset, sizeof(uchar)*4*w*h);
glUnmapBuffer(GL_PIXEL_UNPACK_BUFFER);
glBindBuffer(GL_PIXEL_UNPACK_BUFFER, 0);
cuda_pop_context();
return;
}
Device::pixels_copy_from(mem, y, w, h);
}
void pixels_free(device_memory& mem)
{
if(mem.device_pointer) {
if(!background) {
PixelMem pmem = pixel_mem_map[mem.device_pointer];
cuda_push_context();
cuda_assert(cuGraphicsUnregisterResource(pmem.cuPBOresource));
glDeleteBuffers(1, &pmem.cuPBO);
glDeleteTextures(1, &pmem.cuTexId);
cuda_pop_context();
pixel_mem_map.erase(pixel_mem_map.find(mem.device_pointer));
mem.device_pointer = 0;
stats.mem_free(mem.device_size);
mem.device_size = 0;
return;
}
Device::pixels_free(mem);
}
}
void draw_pixels(device_memory& mem, int y, int w, int h, int dx, int dy, int width, int height, bool transparent,
const DeviceDrawParams &draw_params)
{
if(!background) {
PixelMem pmem = pixel_mem_map[mem.device_pointer];
float *vpointer;
cuda_push_context();
/* for multi devices, this assumes the inefficient method that we allocate
* all pixels on the device even though we only render to a subset */
size_t offset = 4*y*w;
if(mem.data_type == TYPE_HALF)
offset *= sizeof(GLhalf);
else
offset *= sizeof(uint8_t);
glBindBuffer(GL_PIXEL_UNPACK_BUFFER, pmem.cuPBO);
glBindTexture(GL_TEXTURE_2D, pmem.cuTexId);
if(mem.data_type == TYPE_HALF)
glTexSubImage2D(GL_TEXTURE_2D, 0, 0, 0, w, h, GL_RGBA, GL_HALF_FLOAT, (void*)offset);
else
glTexSubImage2D(GL_TEXTURE_2D, 0, 0, 0, w, h, GL_RGBA, GL_UNSIGNED_BYTE, (void*)offset);
glBindBuffer(GL_PIXEL_UNPACK_BUFFER, 0);
glEnable(GL_TEXTURE_2D);
if(transparent) {
glEnable(GL_BLEND);
glBlendFunc(GL_ONE, GL_ONE_MINUS_SRC_ALPHA);
}
glColor3f(1.0f, 1.0f, 1.0f);
if(draw_params.bind_display_space_shader_cb) {
draw_params.bind_display_space_shader_cb();
}
if(!vertex_buffer)
glGenBuffers(1, &vertex_buffer);
glBindBuffer(GL_ARRAY_BUFFER, vertex_buffer);
/* invalidate old contents - avoids stalling if buffer is still waiting in queue to be rendered */
glBufferData(GL_ARRAY_BUFFER, 16 * sizeof(float), NULL, GL_STREAM_DRAW);
vpointer = (float *)glMapBuffer(GL_ARRAY_BUFFER, GL_WRITE_ONLY);
if(vpointer) {
/* texture coordinate - vertex pair */
vpointer[0] = 0.0f;
vpointer[1] = 0.0f;
vpointer[2] = dx;
vpointer[3] = dy;
vpointer[4] = (float)w/(float)pmem.w;
vpointer[5] = 0.0f;
vpointer[6] = (float)width + dx;
vpointer[7] = dy;
vpointer[8] = (float)w/(float)pmem.w;
vpointer[9] = (float)h/(float)pmem.h;
vpointer[10] = (float)width + dx;
vpointer[11] = (float)height + dy;
vpointer[12] = 0.0f;
vpointer[13] = (float)h/(float)pmem.h;
vpointer[14] = dx;
vpointer[15] = (float)height + dy;
glUnmapBuffer(GL_ARRAY_BUFFER);
}
glTexCoordPointer(2, GL_FLOAT, 4 * sizeof(float), 0);
glVertexPointer(2, GL_FLOAT, 4 * sizeof(float), (char *)NULL + 2 * sizeof(float));
glEnableClientState(GL_VERTEX_ARRAY);
glEnableClientState(GL_TEXTURE_COORD_ARRAY);
glDrawArrays(GL_TRIANGLE_FAN, 0, 4);
glDisableClientState(GL_TEXTURE_COORD_ARRAY);
glDisableClientState(GL_VERTEX_ARRAY);
glBindBuffer(GL_ARRAY_BUFFER, 0);
if(draw_params.unbind_display_space_shader_cb) {
draw_params.unbind_display_space_shader_cb();
}
if(transparent)
glDisable(GL_BLEND);
glBindTexture(GL_TEXTURE_2D, 0);
glDisable(GL_TEXTURE_2D);
cuda_pop_context();
return;
}
Device::draw_pixels(mem, y, w, h, dx, dy, width, height, transparent, draw_params);
}
void thread_run(DeviceTask *task)
{
if(task->type == DeviceTask::PATH_TRACE) {
RenderTile tile;
bool branched = task->integrator_branched;
/* Upload Bindless Mapping */
load_bindless_mapping();
if(!use_split_kernel()) {
/* keep rendering tiles until done */
while(task->acquire_tile(this, tile)) {
int start_sample = tile.start_sample;
int end_sample = tile.start_sample + tile.num_samples;
for(int sample = start_sample; sample < end_sample; sample++) {
if(task->get_cancel()) {
if(task->need_finish_queue == false)
break;
}
path_trace(tile, sample, branched);
tile.sample = sample + 1;
task->update_progress(&tile, tile.w*tile.h);
}
task->release_tile(tile);
}
}
else {
DeviceRequestedFeatures requested_features;
if(!use_adaptive_compilation()) {
requested_features.max_closure = 64;
}
CUDASplitKernel split_kernel(this);
split_kernel.load_kernels(requested_features);
while(task->acquire_tile(this, tile)) {
device_memory void_buffer;
split_kernel.path_trace(task, tile, void_buffer, void_buffer);
task->release_tile(tile);
if(task->get_cancel()) {
if(task->need_finish_queue == false)
break;
}
}
}
}
else if(task->type == DeviceTask::SHADER) {
/* Upload Bindless Mapping */
load_bindless_mapping();
shader(*task);
cuda_push_context();
cuda_assert(cuCtxSynchronize());
cuda_pop_context();
}
}
class CUDADeviceTask : public DeviceTask {
public:
CUDADeviceTask(CUDADevice *device, DeviceTask& task)
: DeviceTask(task)
{
run = function_bind(&CUDADevice::thread_run, device, this);
}
};
int get_split_task_count(DeviceTask& /*task*/)
{
return 1;
}
void task_add(DeviceTask& task)
{
if(task.type == DeviceTask::FILM_CONVERT) {
/* must be done in main thread due to opengl access */
film_convert(task, task.buffer, task.rgba_byte, task.rgba_half);
cuda_push_context();
cuda_assert(cuCtxSynchronize());
cuda_pop_context();
}
else {
task_pool.push(new CUDADeviceTask(this, task));
}
}
void task_wait()
{
task_pool.wait();
}
void task_cancel()
{
task_pool.cancel();
}
friend class CUDASplitKernelFunction;
friend class CUDASplitKernel;
};
/* redefine the cuda_assert macro so it can be used outside of the CUDADevice class
* now that the definition of that class is complete
*/
#undef cuda_assert
#define cuda_assert(stmt) \
{ \
CUresult result = stmt; \
\
if(result != CUDA_SUCCESS) { \
string message = string_printf("CUDA error: %s in %s", cuewErrorString(result), #stmt); \
if(device->error_msg == "") \
device->error_msg = message; \
fprintf(stderr, "%s\n", message.c_str()); \
/*cuda_abort();*/ \
device->cuda_error_documentation(); \
} \
} (void)0
/* split kernel */
class CUDASplitKernelFunction : public SplitKernelFunction{
CUDADevice* device;
CUfunction func;
public:
CUDASplitKernelFunction(CUDADevice *device, CUfunction func) : device(device), func(func) {}
/* enqueue the kernel, returns false if there is an error */
bool enqueue(const KernelDimensions &dim, device_memory &/*kg*/, device_memory &/*data*/)
{
return enqueue(dim, NULL);
}
/* enqueue the kernel, returns false if there is an error */
bool enqueue(const KernelDimensions &dim, void *args[])
{
device->cuda_push_context();
if(device->have_error())
return false;
/* we ignore dim.local_size for now, as this is faster */
int threads_per_block;
cuda_assert(cuFuncGetAttribute(&threads_per_block, CU_FUNC_ATTRIBUTE_MAX_THREADS_PER_BLOCK, func));
int xthreads = (int)sqrt(threads_per_block);
int ythreads = (int)sqrt(threads_per_block);
int xblocks = (dim.global_size[0] + xthreads - 1)/xthreads;
int yblocks = (dim.global_size[1] + ythreads - 1)/ythreads;
cuda_assert(cuFuncSetCacheConfig(func, CU_FUNC_CACHE_PREFER_L1));
cuda_assert(cuLaunchKernel(func,
xblocks , yblocks, 1, /* blocks */
xthreads, ythreads, 1, /* threads */
0, 0, args, 0));
device->cuda_pop_context();
return !device->have_error();
}
};
CUDASplitKernel::CUDASplitKernel(CUDADevice *device) : DeviceSplitKernel(device), device(device)
{
}
size_t CUDASplitKernel::state_buffer_size(device_memory& /*kg*/, device_memory& /*data*/, size_t num_threads)
{
device_vector<uint> size_buffer;
size_buffer.resize(1);
device->mem_alloc(NULL, size_buffer, MEM_READ_WRITE);
device->cuda_push_context();
uint threads = num_threads;
CUdeviceptr d_size = device->cuda_device_ptr(size_buffer.device_pointer);
struct args_t {
uint* num_threads;
CUdeviceptr* size;
};
args_t args = {
&threads,
&d_size
};
CUfunction state_buffer_size;
cuda_assert(cuModuleGetFunction(&state_buffer_size, device->cuModule, "kernel_cuda_state_buffer_size"));
cuda_assert(cuLaunchKernel(state_buffer_size,
1, 1, 1,
1, 1, 1,
0, 0, &args, 0));
device->cuda_pop_context();
device->mem_copy_from(size_buffer, 0, 1, 1, sizeof(uint));
device->mem_free(size_buffer);
return *size_buffer.get_data();
}
bool CUDASplitKernel::enqueue_split_kernel_data_init(const KernelDimensions& dim,
RenderTile& rtile,
int num_global_elements,
device_memory& /*kernel_globals*/,
device_memory& /*kernel_data*/,
device_memory& split_data,
device_memory& ray_state,
device_memory& queue_index,
device_memory& use_queues_flag,
device_memory& work_pool_wgs)
{
device->cuda_push_context();
CUdeviceptr d_split_data = device->cuda_device_ptr(split_data.device_pointer);
CUdeviceptr d_ray_state = device->cuda_device_ptr(ray_state.device_pointer);
CUdeviceptr d_queue_index = device->cuda_device_ptr(queue_index.device_pointer);
CUdeviceptr d_use_queues_flag = device->cuda_device_ptr(use_queues_flag.device_pointer);
CUdeviceptr d_work_pool_wgs = device->cuda_device_ptr(work_pool_wgs.device_pointer);
CUdeviceptr d_rng_state = device->cuda_device_ptr(rtile.rng_state);
CUdeviceptr d_buffer = device->cuda_device_ptr(rtile.buffer);
int end_sample = rtile.start_sample + rtile.num_samples;
int queue_size = dim.global_size[0] * dim.global_size[1];
struct args_t {
CUdeviceptr* split_data_buffer;
int* num_elements;
CUdeviceptr* ray_state;
CUdeviceptr* rng_state;
int* start_sample;
int* end_sample;
int* sx;
int* sy;
int* sw;
int* sh;
int* offset;
int* stride;
CUdeviceptr* queue_index;
int* queuesize;
CUdeviceptr* use_queues_flag;
CUdeviceptr* work_pool_wgs;
int* num_samples;
CUdeviceptr* buffer;
};
args_t args = {
&d_split_data,
&num_global_elements,
&d_ray_state,
&d_rng_state,
&rtile.start_sample,
&end_sample,
&rtile.x,
&rtile.y,
&rtile.w,
&rtile.h,
&rtile.offset,
&rtile.stride,
&d_queue_index,
&queue_size,
&d_use_queues_flag,
&d_work_pool_wgs,
&rtile.num_samples,
&d_buffer
};
CUfunction data_init;
cuda_assert(cuModuleGetFunction(&data_init, device->cuModule, "kernel_cuda_path_trace_data_init"));
if(device->have_error()) {
return false;
}
CUDASplitKernelFunction(device, data_init).enqueue(dim, (void**)&args);
device->cuda_pop_context();
return !device->have_error();
}
SplitKernelFunction* CUDASplitKernel::get_split_kernel_function(string kernel_name, const DeviceRequestedFeatures&)
{
CUfunction func;
device->cuda_push_context();
cuda_assert(cuModuleGetFunction(&func, device->cuModule, (string("kernel_cuda_") + kernel_name).data()));
if(device->have_error()) {
device->cuda_error_message(string_printf("kernel \"kernel_cuda_%s\" not found in module", kernel_name.data()));
return NULL;
}
device->cuda_pop_context();
return new CUDASplitKernelFunction(device, func);
}
int2 CUDASplitKernel::split_kernel_local_size()
{
return make_int2(32, 1);
}
int2 CUDASplitKernel::split_kernel_global_size(device_memory& /*kg*/, device_memory& /*data*/, DeviceTask */*task*/)
{
/* TODO(mai): implement something here to detect ideal work size */
return make_int2(256, 256);
}
bool device_cuda_init(void)
{
#ifdef WITH_CUDA_DYNLOAD
static bool initialized = false;
static bool result = false;
if(initialized)
return result;
initialized = true;
int cuew_result = cuewInit();
if(cuew_result == CUEW_SUCCESS) {
VLOG(1) << "CUEW initialization succeeded";
if(CUDADevice::have_precompiled_kernels()) {
VLOG(1) << "Found precompiled kernels";
result = true;
}
#ifndef _WIN32
else if(cuewCompilerPath() != NULL) {
VLOG(1) << "Found CUDA compiler " << cuewCompilerPath();
result = true;
}
else {
VLOG(1) << "Neither precompiled kernels nor CUDA compiler wad found,"
<< " unable to use CUDA";
}
#endif
}
else {
VLOG(1) << "CUEW initialization failed: "
<< ((cuew_result == CUEW_ERROR_ATEXIT_FAILED)
? "Error setting up atexit() handler"
: "Error opening the library");
}
return result;
#else /* WITH_CUDA_DYNLOAD */
return true;
#endif /* WITH_CUDA_DYNLOAD */
}
Device *device_cuda_create(DeviceInfo& info, Stats &stats, bool background)
{
return new CUDADevice(info, stats, background);
}
void device_cuda_info(vector<DeviceInfo>& devices)
{
CUresult result;
int count = 0;
result = cuInit(0);
if(result != CUDA_SUCCESS) {
if(result != CUDA_ERROR_NO_DEVICE)
fprintf(stderr, "CUDA cuInit: %s\n", cuewErrorString(result));
return;
}
result = cuDeviceGetCount(&count);
if(result != CUDA_SUCCESS) {
fprintf(stderr, "CUDA cuDeviceGetCount: %s\n", cuewErrorString(result));
return;
}
vector<DeviceInfo> display_devices;
for(int num = 0; num < count; num++) {
char name[256];
int attr;
if(cuDeviceGetName(name, 256, num) != CUDA_SUCCESS)
continue;
int major;
cuDeviceGetAttribute(&major, CU_DEVICE_ATTRIBUTE_COMPUTE_CAPABILITY_MAJOR, num);
if(major < 2) {
continue;
}
DeviceInfo info;
info.type = DEVICE_CUDA;
info.description = string(name);
info.num = num;
info.advanced_shading = (major >= 2);
info.has_bindless_textures = (major >= 3);
info.pack_images = false;
int pci_location[3] = {0, 0, 0};
cuDeviceGetAttribute(&pci_location[0], CU_DEVICE_ATTRIBUTE_PCI_DOMAIN_ID, num);
cuDeviceGetAttribute(&pci_location[1], CU_DEVICE_ATTRIBUTE_PCI_BUS_ID, num);
cuDeviceGetAttribute(&pci_location[2], CU_DEVICE_ATTRIBUTE_PCI_DEVICE_ID, num);
info.id = string_printf("CUDA_%s_%04x:%02x:%02x",
name,
(unsigned int)pci_location[0],
(unsigned int)pci_location[1],
(unsigned int)pci_location[2]);
/* if device has a kernel timeout, assume it is used for display */
if(cuDeviceGetAttribute(&attr, CU_DEVICE_ATTRIBUTE_KERNEL_EXEC_TIMEOUT, num) == CUDA_SUCCESS && attr == 1) {
info.description += " (Display)";
info.display_device = true;
display_devices.push_back(info);
}
else
devices.push_back(info);
}
if(!display_devices.empty())
devices.insert(devices.end(), display_devices.begin(), display_devices.end());
}
string device_cuda_capabilities(void)
{
CUresult result = cuInit(0);
if(result != CUDA_SUCCESS) {
if(result != CUDA_ERROR_NO_DEVICE) {
return string("Error initializing CUDA: ") + cuewErrorString(result);
}
return "No CUDA device found\n";
}
int count;
result = cuDeviceGetCount(&count);
if(result != CUDA_SUCCESS) {
return string("Error getting devices: ") + cuewErrorString(result);
}
string capabilities = "";
for(int num = 0; num < count; num++) {
char name[256];
if(cuDeviceGetName(name, 256, num) != CUDA_SUCCESS) {
continue;
}
capabilities += string("\t") + name + "\n";
int value;
#define GET_ATTR(attr) \
{ \
if(cuDeviceGetAttribute(&value, \
CU_DEVICE_ATTRIBUTE_##attr, \
num) == CUDA_SUCCESS) \
{ \
capabilities += string_printf("\t\tCU_DEVICE_ATTRIBUTE_" #attr "\t\t\t%d\n", \
value); \
} \
} (void)0
/* TODO(sergey): Strip all attributes which are not useful for us
* or does not depend on the driver.
*/
GET_ATTR(MAX_THREADS_PER_BLOCK);
GET_ATTR(MAX_BLOCK_DIM_X);
GET_ATTR(MAX_BLOCK_DIM_Y);
GET_ATTR(MAX_BLOCK_DIM_Z);
GET_ATTR(MAX_GRID_DIM_X);
GET_ATTR(MAX_GRID_DIM_Y);
GET_ATTR(MAX_GRID_DIM_Z);
GET_ATTR(MAX_SHARED_MEMORY_PER_BLOCK);
GET_ATTR(SHARED_MEMORY_PER_BLOCK);
GET_ATTR(TOTAL_CONSTANT_MEMORY);
GET_ATTR(WARP_SIZE);
GET_ATTR(MAX_PITCH);
GET_ATTR(MAX_REGISTERS_PER_BLOCK);
GET_ATTR(REGISTERS_PER_BLOCK);
GET_ATTR(CLOCK_RATE);
GET_ATTR(TEXTURE_ALIGNMENT);
GET_ATTR(GPU_OVERLAP);
GET_ATTR(MULTIPROCESSOR_COUNT);
GET_ATTR(KERNEL_EXEC_TIMEOUT);
GET_ATTR(INTEGRATED);
GET_ATTR(CAN_MAP_HOST_MEMORY);
GET_ATTR(COMPUTE_MODE);
GET_ATTR(MAXIMUM_TEXTURE1D_WIDTH);
GET_ATTR(MAXIMUM_TEXTURE2D_WIDTH);
GET_ATTR(MAXIMUM_TEXTURE2D_HEIGHT);
GET_ATTR(MAXIMUM_TEXTURE3D_WIDTH);
GET_ATTR(MAXIMUM_TEXTURE3D_HEIGHT);
GET_ATTR(MAXIMUM_TEXTURE3D_DEPTH);
GET_ATTR(MAXIMUM_TEXTURE2D_LAYERED_WIDTH);
GET_ATTR(MAXIMUM_TEXTURE2D_LAYERED_HEIGHT);
GET_ATTR(MAXIMUM_TEXTURE2D_LAYERED_LAYERS);
GET_ATTR(MAXIMUM_TEXTURE2D_ARRAY_WIDTH);
GET_ATTR(MAXIMUM_TEXTURE2D_ARRAY_HEIGHT);
GET_ATTR(MAXIMUM_TEXTURE2D_ARRAY_NUMSLICES);
GET_ATTR(SURFACE_ALIGNMENT);
GET_ATTR(CONCURRENT_KERNELS);
GET_ATTR(ECC_ENABLED);
GET_ATTR(TCC_DRIVER);
GET_ATTR(MEMORY_CLOCK_RATE);
GET_ATTR(GLOBAL_MEMORY_BUS_WIDTH);
GET_ATTR(L2_CACHE_SIZE);
GET_ATTR(MAX_THREADS_PER_MULTIPROCESSOR);
GET_ATTR(ASYNC_ENGINE_COUNT);
GET_ATTR(UNIFIED_ADDRESSING);
GET_ATTR(MAXIMUM_TEXTURE1D_LAYERED_WIDTH);
GET_ATTR(MAXIMUM_TEXTURE1D_LAYERED_LAYERS);
GET_ATTR(CAN_TEX2D_GATHER);
GET_ATTR(MAXIMUM_TEXTURE2D_GATHER_WIDTH);
GET_ATTR(MAXIMUM_TEXTURE2D_GATHER_HEIGHT);
GET_ATTR(MAXIMUM_TEXTURE3D_WIDTH_ALTERNATE);
GET_ATTR(MAXIMUM_TEXTURE3D_HEIGHT_ALTERNATE);
GET_ATTR(MAXIMUM_TEXTURE3D_DEPTH_ALTERNATE);
GET_ATTR(TEXTURE_PITCH_ALIGNMENT);
GET_ATTR(MAXIMUM_TEXTURECUBEMAP_WIDTH);
GET_ATTR(MAXIMUM_TEXTURECUBEMAP_LAYERED_WIDTH);
GET_ATTR(MAXIMUM_TEXTURECUBEMAP_LAYERED_LAYERS);
GET_ATTR(MAXIMUM_SURFACE1D_WIDTH);
GET_ATTR(MAXIMUM_SURFACE2D_WIDTH);
GET_ATTR(MAXIMUM_SURFACE2D_HEIGHT);
GET_ATTR(MAXIMUM_SURFACE3D_WIDTH);
GET_ATTR(MAXIMUM_SURFACE3D_HEIGHT);
GET_ATTR(MAXIMUM_SURFACE3D_DEPTH);
GET_ATTR(MAXIMUM_SURFACE1D_LAYERED_WIDTH);
GET_ATTR(MAXIMUM_SURFACE1D_LAYERED_LAYERS);
GET_ATTR(MAXIMUM_SURFACE2D_LAYERED_WIDTH);
GET_ATTR(MAXIMUM_SURFACE2D_LAYERED_HEIGHT);
GET_ATTR(MAXIMUM_SURFACE2D_LAYERED_LAYERS);
GET_ATTR(MAXIMUM_SURFACECUBEMAP_WIDTH);
GET_ATTR(MAXIMUM_SURFACECUBEMAP_LAYERED_WIDTH);
GET_ATTR(MAXIMUM_SURFACECUBEMAP_LAYERED_LAYERS);
GET_ATTR(MAXIMUM_TEXTURE1D_LINEAR_WIDTH);
GET_ATTR(MAXIMUM_TEXTURE2D_LINEAR_WIDTH);
GET_ATTR(MAXIMUM_TEXTURE2D_LINEAR_HEIGHT);
GET_ATTR(MAXIMUM_TEXTURE2D_LINEAR_PITCH);
GET_ATTR(MAXIMUM_TEXTURE2D_MIPMAPPED_WIDTH);
GET_ATTR(MAXIMUM_TEXTURE2D_MIPMAPPED_HEIGHT);
GET_ATTR(COMPUTE_CAPABILITY_MAJOR);
GET_ATTR(COMPUTE_CAPABILITY_MINOR);
GET_ATTR(MAXIMUM_TEXTURE1D_MIPMAPPED_WIDTH);
GET_ATTR(STREAM_PRIORITIES_SUPPORTED);
GET_ATTR(GLOBAL_L1_CACHE_SUPPORTED);
GET_ATTR(LOCAL_L1_CACHE_SUPPORTED);
GET_ATTR(MAX_SHARED_MEMORY_PER_MULTIPROCESSOR);
GET_ATTR(MAX_REGISTERS_PER_MULTIPROCESSOR);
GET_ATTR(MANAGED_MEMORY);
GET_ATTR(MULTI_GPU_BOARD);
GET_ATTR(MULTI_GPU_BOARD_GROUP_ID);
#undef GET_ATTR
capabilities += "\n";
}
return capabilities;
}
CCL_NAMESPACE_END
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