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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"
#include "util_cuda.h"
#include "util_debug.h"
#include "util_map.h"
#include "util_opengl.h"
#include "util_path.h"
#include "util_system.h"
#include "util_types.h"
#include "util_time.h"
CCL_NAMESPACE_BEGIN
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 const char *cuda_error_string(CUresult result)
{
switch(result) {
case CUDA_SUCCESS: return "No errors";
case CUDA_ERROR_INVALID_VALUE: return "Invalid value";
case CUDA_ERROR_OUT_OF_MEMORY: return "Out of memory";
case CUDA_ERROR_NOT_INITIALIZED: return "Driver not initialized";
case CUDA_ERROR_DEINITIALIZED: return "Driver deinitialized";
case CUDA_ERROR_NO_DEVICE: return "No CUDA-capable device available";
case CUDA_ERROR_INVALID_DEVICE: return "Invalid device";
case CUDA_ERROR_INVALID_IMAGE: return "Invalid kernel image";
case CUDA_ERROR_INVALID_CONTEXT: return "Invalid context";
case CUDA_ERROR_CONTEXT_ALREADY_CURRENT: return "Context already current";
case CUDA_ERROR_MAP_FAILED: return "Map failed";
case CUDA_ERROR_UNMAP_FAILED: return "Unmap failed";
case CUDA_ERROR_ARRAY_IS_MAPPED: return "Array is mapped";
case CUDA_ERROR_ALREADY_MAPPED: return "Already mapped";
case CUDA_ERROR_NO_BINARY_FOR_GPU: return "No binary for GPU";
case CUDA_ERROR_ALREADY_ACQUIRED: return "Already acquired";
case CUDA_ERROR_NOT_MAPPED: return "Not mapped";
case CUDA_ERROR_NOT_MAPPED_AS_ARRAY: return "Mapped resource not available for access as an array";
case CUDA_ERROR_NOT_MAPPED_AS_POINTER: return "Mapped resource not available for access as a pointer";
case CUDA_ERROR_ECC_UNCORRECTABLE: return "Uncorrectable ECC error detected";
case CUDA_ERROR_UNSUPPORTED_LIMIT: return "CUlimit not supported by device";
case CUDA_ERROR_INVALID_SOURCE: return "Invalid source";
case CUDA_ERROR_FILE_NOT_FOUND: return "File not found";
case CUDA_ERROR_SHARED_OBJECT_SYMBOL_NOT_FOUND: return "Link to a shared object failed to resolve";
case CUDA_ERROR_SHARED_OBJECT_INIT_FAILED: return "Shared object initialization failed";
case CUDA_ERROR_INVALID_HANDLE: return "Invalid handle";
case CUDA_ERROR_NOT_FOUND: return "Not found";
case CUDA_ERROR_NOT_READY: return "CUDA not ready";
case CUDA_ERROR_LAUNCH_FAILED: return "Launch failed";
case CUDA_ERROR_LAUNCH_OUT_OF_RESOURCES: return "Launch exceeded resources";
case CUDA_ERROR_LAUNCH_TIMEOUT: return "Launch exceeded timeout";
case CUDA_ERROR_LAUNCH_INCOMPATIBLE_TEXTURING: return "Launch with incompatible texturing";
case CUDA_ERROR_UNKNOWN: return "Unknown error";
default: return "Unknown CUDA error value";
}
}
/*#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://wiki.blender.org/index.php/Doc:2.6/Manual/Render/Cycles/GPU_Rendering\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", cuda_error_string(result), #stmt); \
if(error_msg == "") \
error_msg = message; \
fprintf(stderr, "%s\n", message.c_str()); \
/*cuda_abort();*/ \
cuda_error_documentation(); \
} \
}
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(), cuda_error_string(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(stats)
{
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 < 350);
cuda_pop_context();
}
~CUDADevice()
{
task_pool.stop();
cuda_assert(cuCtxDestroy(cuContext))
}
bool support_device(bool experimental)
{
int major, minor;
cuDeviceComputeCapability(&major, &minor, cuDevId);
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()
{
/* compute cubin name */
int major, minor;
cuDeviceComputeCapability(&major, &minor, cuDevId);
/* attempt to use kernel provided with blender */
string cubin = path_get(string_printf("lib/kernel_sm_%d%d.cubin", major, minor));
if(path_exists(cubin))
return cubin;
/* not found, try to use locally compiled kernel */
string kernel_path = path_get("kernel");
string md5 = path_files_md5_hash(kernel_path);
cubin = string_printf("cycles_kernel_sm%d%d_%s.cubin", major, minor, md5.c_str());
cubin = path_user_get(path_join("cache", cubin));
/* if exists already, use it */
if(path_exists(cubin))
return cubin;
#ifdef _WIN32
if(cuHavePrecompiledKernels()) {
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 */
string nvcc = cuCompilerPath();
if(nvcc == "") {
cuda_error_message("CUDA nvcc compiler not found. Install CUDA toolkit in default location.");
return "";
}
int cuda_version = cuCompilerVersion();
if(cuda_version == 0) {
cuda_error_message("CUDA nvcc compiler version could not be parsed.");
return "";
}
if(cuda_version < 50) {
printf("Unsupported CUDA version %d.%d detected, you need CUDA 5.0.\n", cuda_version/10, cuda_version%10);
return "";
}
else if(cuda_version > 50)
printf("CUDA version %d.%d detected, build may succeed but only CUDA 5.0 is officially supported.\n", cuda_version/10, cuda_version%10);
/* compile */
string kernel = path_join(kernel_path, "kernel.cu");
string include = kernel_path;
const int machine = system_cpu_bits();
string arch_flags;
/* CUDA 5.x build flags for different archs */
if(major == 2) {
/* sm_2x */
arch_flags = "--maxrregcount=32 --use_fast_math";
}
else if(major == 3) {
/* sm_3x */
arch_flags = "--maxrregcount=32 --use_fast_math";
}
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\" %s -I\"%s\" -DNVCC -D__KERNEL_CUDA_VERSION__=%d",
nvcc.c_str(), major, minor, machine, kernel.c_str(), cubin.c_str(), arch_flags.c_str(), include.c_str(), cuda_version);
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(bool experimental)
{
/* check if cuda init succeeded */
if(cuContext == 0)
return false;
/* check if GPU is supported with current feature set */
if(!support_device(experimental))
return false;
/* get kernel */
string cubin = compile_kernel();
if(cubin == "")
return false;
/* open module */
cuda_push_context();
CUresult result = cuModuleLoad(&cuModule, cubin.c_str());
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;
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)((uchar*)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.memory_size());
}
}
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, bool interpolation, bool periodic)
{
/* determine format */
CUarray_format_enum format;
size_t dsize = datatype_size(mem.data_type);
size_t size = mem.memory_size();
bool use_texture = interpolation || 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) {
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(¶m, 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(¶m))
}
else
cuda_assert(cuMemcpyHtoA(handle, 0, (void*)mem.data_pointer, size))
cuda_assert(cuTexRefSetArray(texref, handle, CU_TRSA_OVERRIDE_FORMAT))
cuda_assert(cuTexRefSetFilterMode(texref, CU_TR_FILTER_MODE_LINEAR))
cuda_assert(cuTexRefSetFlags(texref, CU_TRSF_NORMALIZED_COORDINATES))
mem.device_pointer = (device_ptr)handle;
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))
}
if(periodic) {
cuda_assert(cuTexRefSetAddressMode(texref, 0, CU_TR_ADDRESS_MODE_WRAP))
cuda_assert(cuTexRefSetAddressMode(texref, 1, CU_TR_ADDRESS_MODE_WRAP))
}
else {
cuda_assert(cuTexRefSetAddressMode(texref, 0, CU_TR_ADDRESS_MODE_CLAMP))
cuda_assert(cuTexRefSetAddressMode(texref, 1, CU_TR_ADDRESS_MODE_CLAMP))
}
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;
}
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.memory_size());
}
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 */
int offset = 0;
cuda_assert(cuParamSetv(cuPathTrace, offset, &d_buffer, sizeof(d_buffer)))
offset += sizeof(d_buffer);
cuda_assert(cuParamSetv(cuPathTrace, offset, &d_rng_state, sizeof(d_rng_state)))
offset += sizeof(d_rng_state);
offset = align_up(offset, __alignof(sample));
cuda_assert(cuParamSeti(cuPathTrace, offset, sample))
offset += sizeof(sample);
cuda_assert(cuParamSeti(cuPathTrace, offset, rtile.x))
offset += sizeof(rtile.x);
cuda_assert(cuParamSeti(cuPathTrace, offset, rtile.y))
offset += sizeof(rtile.y);
cuda_assert(cuParamSeti(cuPathTrace, offset, rtile.w))
offset += sizeof(rtile.w);
cuda_assert(cuParamSeti(cuPathTrace, offset, rtile.h))
offset += sizeof(rtile.h);
cuda_assert(cuParamSeti(cuPathTrace, offset, rtile.offset))
offset += sizeof(rtile.offset);
cuda_assert(cuParamSeti(cuPathTrace, offset, rtile.stride))
offset += sizeof(rtile.stride);
cuda_assert(cuParamSetSize(cuPathTrace, offset))
/* launch kernel: todo find optimal size, cache config for fermi */
int xthreads = 16;
int ythreads = 16;
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(cuFuncSetBlockShape(cuPathTrace, xthreads, ythreads, 1))
cuda_assert(cuLaunchGrid(cuPathTrace, xblocks, yblocks))
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"))
/* pass in parameters */
int offset = 0;
cuda_assert(cuParamSetv(cuFilmConvert, offset, &d_rgba, sizeof(d_rgba)))
offset += sizeof(d_rgba);
cuda_assert(cuParamSetv(cuFilmConvert, offset, &d_buffer, sizeof(d_buffer)))
offset += sizeof(d_buffer);
float sample_scale = 1.0f/(task.sample + 1);
offset = align_up(offset, __alignof(sample_scale));
cuda_assert(cuParamSetf(cuFilmConvert, offset, sample_scale))
offset += sizeof(sample_scale);
cuda_assert(cuParamSeti(cuFilmConvert, offset, task.x))
offset += sizeof(task.x);
cuda_assert(cuParamSeti(cuFilmConvert, offset, task.y))
offset += sizeof(task.y);
cuda_assert(cuParamSeti(cuFilmConvert, offset, task.w))
offset += sizeof(task.w);
cuda_assert(cuParamSeti(cuFilmConvert, offset, task.h))
offset += sizeof(task.h);
cuda_assert(cuParamSeti(cuFilmConvert, offset, task.offset))
offset += sizeof(task.offset);
cuda_assert(cuParamSeti(cuFilmConvert, offset, task.stride))
offset += sizeof(task.stride);
cuda_assert(cuParamSetSize(cuFilmConvert, offset))
/* launch kernel: todo find optimal size, cache config for fermi */
int xthreads = 16;
int ythreads = 16;
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(cuFuncSetBlockShape(cuFilmConvert, xthreads, ythreads, 1))
cuda_assert(cuLaunchGrid(cuFilmConvert, xblocks, yblocks))
unmap_pixels((rgba_byte)? rgba_byte: rgba_half);
cuda_pop_context();
}
void shader(DeviceTask& task)
{
if(have_error())
return;
cuda_push_context();
CUfunction cuDisplace;
CUdeviceptr d_input = cuda_device_ptr(task.shader_input);
CUdeviceptr d_output = cuda_device_ptr(task.shader_output);
/* get kernel function */
cuda_assert(cuModuleGetFunction(&cuDisplace, cuModule, "kernel_cuda_shader"))
/* pass in parameters */
int offset = 0;
cuda_assert(cuParamSetv(cuDisplace, offset, &d_input, sizeof(d_input)))
offset += sizeof(d_input);
cuda_assert(cuParamSetv(cuDisplace, offset, &d_output, sizeof(d_output)))
offset += sizeof(d_output);
int shader_eval_type = task.shader_eval_type;
offset = align_up(offset, __alignof(shader_eval_type));
cuda_assert(cuParamSeti(cuDisplace, offset, task.shader_eval_type))
offset += sizeof(task.shader_eval_type);
cuda_assert(cuParamSeti(cuDisplace, offset, task.shader_x))
offset += sizeof(task.shader_x);
cuda_assert(cuParamSetSize(cuDisplace, offset))
/* launch kernel: todo find optimal size, cache config for fermi */
int xthreads = 16;
int xblocks = (task.shader_w + xthreads - 1)/xthreads;
cuda_assert(cuFuncSetCacheConfig(cuDisplace, CU_FUNC_CACHE_PREFER_L1))
cuda_assert(cuFuncSetBlockShape(cuDisplace, xthreads, 1, 1))
cuda_assert(cuLaunchGrid(cuDisplace, xblocks, 1))
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_RGBA, 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;
stats.mem_alloc(mem.memory_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.memory_size());
return;
}
Device::pixels_free(mem);
}
}
void draw_pixels(device_memory& mem, int y, int w, int h, int dy, int width, int height, bool transparent)
{
if(!background) {
PixelMem pmem = pixel_mem_map[mem.device_pointer];
cuda_push_context();
/* for multi devices, this assumes the ineffecient 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);
glBindBufferARB(GL_PIXEL_UNPACK_BUFFER_ARB, 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);
glBindBufferARB(GL_PIXEL_UNPACK_BUFFER_ARB, 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);
glPushMatrix();
glTranslatef(0.0f, (float)dy, 0.0f);
glBegin(GL_QUADS);
glTexCoord2f(0.0f, 0.0f);
glVertex2f(0.0f, 0.0f);
glTexCoord2f((float)w/(float)pmem.w, 0.0f);
glVertex2f((float)width, 0.0f);
glTexCoord2f((float)w/(float)pmem.w, (float)h/(float)pmem.h);
glVertex2f((float)width, (float)height);
glTexCoord2f(0.0f, (float)h/(float)pmem.h);
glVertex2f(0.0f, (float)height);
glEnd();
glPopMatrix();
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, dy, width, height, transparent);
}
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);
}
};
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();
}
};
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", CUDADevice::cuda_error_string(result));
return;
}
result = cuDeviceGetCount(&count);
if(result != CUDA_SUCCESS) {
fprintf(stderr, "CUDA cuDeviceGetCount: %s\n", CUDADevice::cuda_error_string(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;
DeviceInfo info;
info.type = DEVICE_CUDA;
info.description = string(name);
info.id = string_printf("CUDA_%d", num);
info.num = num;
int major, minor;
cuDeviceComputeCapability(&major, &minor, num);
info.advanced_shading = (major >= 2);
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());
}
CCL_NAMESPACE_END
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