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blender/intern/cycles/device/device_cuda.cpp
Sergey Sharybin 2af7637f20 Cycles: Add option to directly link against CUDA libraries 
The main purpose of such linking is to make Blender compatible with
NVidia's debuggers and profilers which are doing some LD_PRELOAD
magic to intercept some function calls. Such magic conflicts with
our CUDA wrangler magic and causes segmentation faults.

The option is disabled by default, so there's no affect on any of
artists.

In order to make Blender linked directly against CUDA library use
the WITH_CUDA_DYNLOAD CMake option (it's marked as advanced).
2016-01-14 12:27:22 +05:00

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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 <stdio.h>
#include <stdlib.h>
#include <string.h>
#include "device.h"
#include "device_intern.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"
/* use feature-adaptive kernel compilation.
* Requires CUDA toolkit to be installed and currently only works on Linux.
*/
/* #define KERNEL_USE_ADAPTIVE */
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 : public Device
{
public:
DedicatedTaskPool task_pool;
CUdevice cuDevice;
CUcontext cuContext;
CUmodule cuModule;
map<device_ptr, bool> tex_interp_map;
int cuDevId;
int cuDevArchitecture;
bool first_error;
bool use_texture_storage;
struct PixelMem {
GLuint cuPBO;
CUgraphicsResource cuPBOresource;
GLuint cuTexId;
int w, h;
};
map<device_ptr, PixelMem> pixel_mem_map;
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);
}
/*#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, "http://www.blender.org/manual/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_;
use_texture_storage = true;
cuDevId = info.num;
cuDevice = 0;
cuContext = 0;
/* 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;
cuDeviceComputeCapability(&major, &minor, cuDevId);
cuDevArchitecture = major*100 + minor*10;
/* In order to use full 6GB of memory on Titan cards, use arrays instead
* of textures. On earlier cards this seems slower, but on Titan it is
* actually slightly faster in tests. */
use_texture_storage = (cuDevArchitecture < 300);
cuda_pop_context();
}
~CUDADevice()
{
task_pool.stop();
cuda_assert(cuCtxDestroy(cuContext));
}
bool support_device(const DeviceRequestedFeatures& /*requested_features*/)
{
int major, minor;
cuDeviceComputeCapability(&major, &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;
}
string compile_kernel(const DeviceRequestedFeatures& requested_features)
{
/* compute cubin name */
int major, minor;
cuDeviceComputeCapability(&major, &minor, cuDevId);
string cubin;
/* attempt to use kernel provided with blender */
if(requested_features.experimental)
cubin = path_get(string_printf("lib/kernel_experimental_sm_%d%d.cubin", major, minor));
else
cubin = path_get(string_printf("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;
}
/* not found, try to use locally compiled kernel */
string kernel_path = path_get("kernel");
string md5 = path_files_md5_hash(kernel_path);
#ifdef KERNEL_USE_ADAPTIVE
string feature_build_options = requested_features.get_build_options();
string device_md5 = util_md5_string(feature_build_options);
cubin = string_printf("cycles_kernel_%s_sm%d%d_%s.cubin",
device_md5.c_str(),
major, minor,
md5.c_str());
#else
if(requested_features.experimental)
cubin = string_printf("cycles_kernel_experimental_sm%d%d_%s.cubin", major, minor, md5.c_str());
else
cubin = string_printf("cycles_kernel_sm%d%d_%s.cubin", major, minor, md5.c_str());
#endif
cubin = path_user_get(path_join("cache", cubin));
VLOG(1) << "Testing for locally compiled kernel " << cubin;
/* if exists already, use it */
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
/* if not, find CUDA compiler */
const char *nvcc = cuewCompilerPath();
if(nvcc == NULL) {
cuda_error_message("CUDA nvcc compiler not found. Install CUDA toolkit in default location.");
return "";
}
int cuda_version = cuewCompilerVersion();
VLOG(1) << "Found nvcc " << nvcc << ", CUDA version " << cuda_version;
if(cuda_version == 0) {
cuda_error_message("CUDA nvcc compiler version could not be parsed.");
return "";
}
if(cuda_version < 60) {
printf("Unsupported CUDA version %d.%d detected, you need CUDA 6.5.\n", cuda_version/10, cuda_version%10);
return "";
}
else if(cuda_version != 65)
printf("CUDA version %d.%d detected, build may succeed but only CUDA 6.5 is officially supported.\n", cuda_version/10, cuda_version%10);
/* compile */
string kernel = path_join(kernel_path, path_join("kernels", path_join("cuda", "kernel.cu")));
string include = kernel_path;
const int machine = system_cpu_bits();
double starttime = time_dt();
printf("Compiling CUDA kernel ...\n");
path_create_directories(cubin);
string command = string_printf("\"%s\" -arch=sm_%d%d -m%d --cubin \"%s\" "
"-o \"%s\" --ptxas-options=\"-v\" --use_fast_math -I\"%s\" "
"-DNVCC -D__KERNEL_CUDA_VERSION__=%d",
nvcc, major, minor, machine, kernel.c_str(), cubin.c_str(), include.c_str(), cuda_version);
#ifdef KERNEL_USE_ADAPTIVE
command += " " + feature_build_options;
#else
if(requested_features.experimental) {
command += " -D__KERNEL_EXPERIMENTAL__";
}
#endif
const char* extra_cflags = getenv("CYCLES_CUDA_EXTRA_CFLAGS");
if(extra_cflags) {
command += string(" ") + string(extra_cflags);
}
#ifdef WITH_CYCLES_DEBUG
command += " -D__KERNEL_DEBUG__";
#endif
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);
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 mem_alloc(device_memory& mem, MemoryType /*type*/)
{
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)
{
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)
{
/* todo: support 3D textures, only CPU for now */
VLOG(1) << "Texture allocate: " << name << ", " << mem.memory_size() << " bytes.";
/* determine format */
CUarray_format_enum format;
size_t dsize = datatype_size(mem.data_type);
size_t size = mem.memory_size();
bool use_texture = (interpolation != INTERPOLATION_NONE) || use_texture_storage;
if(use_texture) {
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;
default: assert(0); return;
}
CUtexref texref = NULL;
cuda_push_context();
cuda_assert(cuModuleGetTexRef(&texref, cuModule, name));
if(!texref) {
cuda_pop_context();
return;
}
if(interpolation != INTERPOLATION_NONE) {
CUarray handle = NULL;
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;
}
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));
cuda_assert(cuTexRefSetArray(texref, handle, CU_TRSA_OVERRIDE_FORMAT));
if(interpolation == INTERPOLATION_CLOSEST) {
cuda_assert(cuTexRefSetFilterMode(texref, CU_TR_FILTER_MODE_POINT));
}
else if(interpolation == INTERPOLATION_LINEAR) {
cuda_assert(cuTexRefSetFilterMode(texref, CU_TR_FILTER_MODE_LINEAR));
}
else {/* CUBIC and SMART are unsupported for CUDA */
cuda_assert(cuTexRefSetFilterMode(texref, CU_TR_FILTER_MODE_LINEAR));
}
cuda_assert(cuTexRefSetFlags(texref, CU_TRSF_NORMALIZED_COORDINATES));
mem.device_pointer = (device_ptr)handle;
mem.device_size = size;
stats.mem_alloc(size);
}
else {
cuda_pop_context();
mem_alloc(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));
}
switch(extension) {
case EXTENSION_REPEAT:
cuda_assert(cuTexRefSetAddressMode(texref, 0, CU_TR_ADDRESS_MODE_WRAP));
cuda_assert(cuTexRefSetAddressMode(texref, 1, CU_TR_ADDRESS_MODE_WRAP));
break;
case EXTENSION_EXTEND:
cuda_assert(cuTexRefSetAddressMode(texref, 0, CU_TR_ADDRESS_MODE_CLAMP));
cuda_assert(cuTexRefSetAddressMode(texref, 1, CU_TR_ADDRESS_MODE_CLAMP));
break;
case EXTENSION_CLIP:
cuda_assert(cuTexRefSetAddressMode(texref, 0, CU_TR_ADDRESS_MODE_BORDER));
cuda_assert(cuTexRefSetAddressMode(texref, 1, CU_TR_ADDRESS_MODE_BORDER));
break;
}
cuda_assert(cuTexRefSetFormat(texref, format, mem.data_elements));
cuda_pop_context();
}
else {
mem_alloc(mem, MEM_READ_ONLY);
mem_copy_to(mem);
cuda_push_context();
CUdeviceptr cumem;
size_t cubytes;
cuda_assert(cuModuleGetGlobal(&cumem, &cubytes, cuModule, name));
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();
}
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();
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((float)threads_per_block);
int ythreads = (int)sqrt((float)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((float)threads_per_block);
int ythreads = (int)sqrt((float)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;
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 = false;
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;
/* 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);
}
task->release_tile(tile);
}
}
else if(task->type == DeviceTask::SHADER) {
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();
}
};
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 compiled " << 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, minor;
cuDeviceComputeCapability(&major, &minor, num);
if(major < 2) {
continue;
}
DeviceInfo info;
info.type = DEVICE_CUDA;
info.description = string(name);
info.id = string_printf("CUDA_%d", num);
info.num = num;
info.advanced_shading = (major >= 2);
info.extended_images = (major >= 3);
info.pack_images = false;
/* 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.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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