forked from bartvdbraak/blender
7902fa57b6
* Reshuffle SSE #ifdefs to try to avoid compilation errors enabling SSE on 32 bit. * Remove CUDA kernel launch size exception on Mac, is not needed. * Make OSL file compilation quiet like c/cpp files.
1041 lines
27 KiB
C++
1041 lines
27 KiB
C++
/*
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* Copyright 2011, Blender Foundation.
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*
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* This program is free software; you can redistribute it and/or
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* modify it under the terms of the GNU General Public License
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* as published by the Free Software Foundation; either version 2
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* of the License, or (at your option) any later version.
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*
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* This program is distributed in the hope that it will be useful,
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* but WITHOUT ANY WARRANTY; without even the implied warranty of
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* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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* GNU General Public License for more details.
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*
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* You should have received a copy of the GNU General Public License
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* along with this program; if not, write to the Free Software Foundation,
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* Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA.
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*/
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#include <stdio.h>
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#include <stdlib.h>
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#include <string.h>
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#include "device.h"
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#include "device_intern.h"
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#include "buffers.h"
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#include "util_cuda.h"
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#include "util_debug.h"
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#include "util_map.h"
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#include "util_opengl.h"
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#include "util_path.h"
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#include "util_system.h"
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#include "util_types.h"
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#include "util_time.h"
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CCL_NAMESPACE_BEGIN
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class CUDADevice : public Device
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{
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public:
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TaskPool task_pool;
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CUdevice cuDevice;
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CUcontext cuContext;
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CUmodule cuModule;
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map<device_ptr, bool> tex_interp_map;
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int cuDevId;
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bool first_error;
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struct PixelMem {
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GLuint cuPBO;
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CUgraphicsResource cuPBOresource;
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GLuint cuTexId;
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int w, h;
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};
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map<device_ptr, PixelMem> pixel_mem_map;
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CUdeviceptr cuda_device_ptr(device_ptr mem)
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{
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return (CUdeviceptr)mem;
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}
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static const char *cuda_error_string(CUresult result)
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{
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switch(result) {
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case CUDA_SUCCESS: return "No errors";
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case CUDA_ERROR_INVALID_VALUE: return "Invalid value";
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case CUDA_ERROR_OUT_OF_MEMORY: return "Out of memory";
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case CUDA_ERROR_NOT_INITIALIZED: return "Driver not initialized";
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case CUDA_ERROR_DEINITIALIZED: return "Driver deinitialized";
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case CUDA_ERROR_NO_DEVICE: return "No CUDA-capable device available";
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case CUDA_ERROR_INVALID_DEVICE: return "Invalid device";
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case CUDA_ERROR_INVALID_IMAGE: return "Invalid kernel image";
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case CUDA_ERROR_INVALID_CONTEXT: return "Invalid context";
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case CUDA_ERROR_CONTEXT_ALREADY_CURRENT: return "Context already current";
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case CUDA_ERROR_MAP_FAILED: return "Map failed";
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case CUDA_ERROR_UNMAP_FAILED: return "Unmap failed";
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case CUDA_ERROR_ARRAY_IS_MAPPED: return "Array is mapped";
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case CUDA_ERROR_ALREADY_MAPPED: return "Already mapped";
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case CUDA_ERROR_NO_BINARY_FOR_GPU: return "No binary for GPU";
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case CUDA_ERROR_ALREADY_ACQUIRED: return "Already acquired";
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case CUDA_ERROR_NOT_MAPPED: return "Not mapped";
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case CUDA_ERROR_NOT_MAPPED_AS_ARRAY: return "Mapped resource not available for access as an array";
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case CUDA_ERROR_NOT_MAPPED_AS_POINTER: return "Mapped resource not available for access as a pointer";
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case CUDA_ERROR_ECC_UNCORRECTABLE: return "Uncorrectable ECC error detected";
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case CUDA_ERROR_UNSUPPORTED_LIMIT: return "CUlimit not supported by device";
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case CUDA_ERROR_INVALID_SOURCE: return "Invalid source";
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case CUDA_ERROR_FILE_NOT_FOUND: return "File not found";
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case CUDA_ERROR_SHARED_OBJECT_SYMBOL_NOT_FOUND: return "Link to a shared object failed to resolve";
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case CUDA_ERROR_SHARED_OBJECT_INIT_FAILED: return "Shared object initialization failed";
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case CUDA_ERROR_INVALID_HANDLE: return "Invalid handle";
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case CUDA_ERROR_NOT_FOUND: return "Not found";
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case CUDA_ERROR_NOT_READY: return "CUDA not ready";
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case CUDA_ERROR_LAUNCH_FAILED: return "Launch failed";
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case CUDA_ERROR_LAUNCH_OUT_OF_RESOURCES: return "Launch exceeded resources";
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case CUDA_ERROR_LAUNCH_TIMEOUT: return "Launch exceeded timeout";
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case CUDA_ERROR_LAUNCH_INCOMPATIBLE_TEXTURING: return "Launch with incompatible texturing";
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case CUDA_ERROR_UNKNOWN: return "Unknown error";
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default: return "Unknown CUDA error value";
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}
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}
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/*#ifdef NDEBUG
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#define cuda_abort()
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#else
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#define cuda_abort() abort()
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#endif*/
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void cuda_error_documentation()
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{
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if(first_error) {
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fprintf(stderr, "\nRefer to the Cycles GPU rendering documentation for possible solutions:\n");
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fprintf(stderr, "http://wiki.blender.org/index.php/Doc:2.6/Manual/Render/Cycles/GPU_Rendering\n\n");
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first_error = false;
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}
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}
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#define cuda_assert(stmt) \
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{ \
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CUresult result = stmt; \
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\
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if(result != CUDA_SUCCESS) { \
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string message = string_printf("CUDA error: %s in %s", cuda_error_string(result), #stmt); \
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if(error_msg == "") \
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error_msg = message; \
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fprintf(stderr, "%s\n", message.c_str()); \
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/*cuda_abort();*/ \
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cuda_error_documentation(); \
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} \
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}
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bool cuda_error_(CUresult result, const string& stmt)
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{
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if(result == CUDA_SUCCESS)
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return false;
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string message = string_printf("CUDA error at %s: %s", stmt.c_str(), cuda_error_string(result));
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if(error_msg == "")
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error_msg = message;
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fprintf(stderr, "%s\n", message.c_str());
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cuda_error_documentation();
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return true;
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}
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#define cuda_error(stmt) cuda_error_(stmt, #stmt)
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void cuda_error_message(const string& message)
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{
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if(error_msg == "")
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error_msg = message;
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fprintf(stderr, "%s\n", message.c_str());
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cuda_error_documentation();
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}
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void cuda_push_context()
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{
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cuda_assert(cuCtxSetCurrent(cuContext))
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}
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void cuda_pop_context()
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{
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cuda_assert(cuCtxSetCurrent(NULL));
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}
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CUDADevice(DeviceInfo& info, Stats &stats, bool background_) : Device(stats)
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{
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first_error = true;
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background = background_;
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cuDevId = info.num;
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cuDevice = 0;
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cuContext = 0;
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/* intialize */
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if(cuda_error(cuInit(0)))
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return;
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/* setup device and context */
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if(cuda_error(cuDeviceGet(&cuDevice, cuDevId)))
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return;
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CUresult result;
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if(background) {
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result = cuCtxCreate(&cuContext, 0, cuDevice);
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}
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else {
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result = cuGLCtxCreate(&cuContext, 0, cuDevice);
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if(result != CUDA_SUCCESS) {
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result = cuCtxCreate(&cuContext, 0, cuDevice);
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background = true;
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}
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}
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if(cuda_error_(result, "cuCtxCreate"))
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return;
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cuda_pop_context();
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}
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~CUDADevice()
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{
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task_pool.stop();
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cuda_push_context();
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cuda_assert(cuCtxDetach(cuContext))
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}
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bool support_device(bool experimental)
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{
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if(!experimental) {
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int major, minor;
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cuDeviceComputeCapability(&major, &minor, cuDevId);
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if(major < 2) {
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cuda_error_message(string_printf("CUDA device supported only with compute capability 2.0 or up, found %d.%d.", major, minor));
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return false;
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}
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}
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return true;
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}
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string compile_kernel()
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{
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/* compute cubin name */
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int major, minor;
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cuDeviceComputeCapability(&major, &minor, cuDevId);
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/* attempt to use kernel provided with blender */
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string cubin = path_get(string_printf("lib/kernel_sm_%d%d.cubin", major, minor));
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if(path_exists(cubin))
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return cubin;
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/* not found, try to use locally compiled kernel */
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string kernel_path = path_get("kernel");
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string md5 = path_files_md5_hash(kernel_path);
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cubin = string_printf("cycles_kernel_sm%d%d_%s.cubin", major, minor, md5.c_str());
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cubin = path_user_get(path_join("cache", cubin));
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/* if exists already, use it */
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if(path_exists(cubin))
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return cubin;
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#ifdef _WIN32
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if(cuHavePrecompiledKernels()) {
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if(major < 2)
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cuda_error_message(string_printf("CUDA device requires compute capability 2.0 or up, found %d.%d. Your GPU is not supported.", major, minor));
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else
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cuda_error_message(string_printf("CUDA binary kernel for this graphics card compute capability (%d.%d) not found.", major, minor));
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return "";
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}
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#endif
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/* if not, find CUDA compiler */
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string nvcc = cuCompilerPath();
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if(nvcc == "") {
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cuda_error_message("CUDA nvcc compiler not found. Install CUDA toolkit in default location.");
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return "";
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}
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int cuda_version = cuCompilerVersion();
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if(cuda_version == 0) {
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cuda_error_message("CUDA nvcc compiler version could not be parsed.");
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return "";
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}
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if(cuda_version != 50)
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printf("CUDA version %d.%d detected, build may succeed but only CUDA 5.0 is officially supported.\n", cuda_version/10, cuda_version%10);
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/* compile */
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string kernel = path_join(kernel_path, "kernel.cu");
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string include = kernel_path;
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const int machine = system_cpu_bits();
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string arch_flags;
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/* build flags depending on CUDA version and arch */
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if(cuda_version < 50) {
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/* CUDA 4.x */
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if(major == 1) {
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/* sm_1x */
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arch_flags = "--maxrregcount=24 --opencc-options -OPT:Olimit=0";
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}
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else if(major == 2) {
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/* sm_2x */
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arch_flags = "--maxrregcount=24";
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}
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else {
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/* sm_3x */
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arch_flags = "--maxrregcount=32";
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}
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}
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else {
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/* CUDA 5.x */
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if(major == 1) {
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/* sm_1x */
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arch_flags = "--maxrregcount=24 --opencc-options -OPT:Olimit=0 --use_fast_math";
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}
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else if(major == 2) {
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/* sm_2x */
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arch_flags = "--maxrregcount=32 --use_fast_math";
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}
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else {
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/* sm_3x */
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arch_flags = "--maxrregcount=32 --use_fast_math";
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}
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}
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double starttime = time_dt();
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printf("Compiling CUDA kernel ...\n");
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path_create_directories(cubin);
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string command = string_printf("\"%s\" -arch=sm_%d%d -m%d --cubin \"%s\" "
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"-o \"%s\" --ptxas-options=\"-v\" %s -I\"%s\" -DNVCC -D__KERNEL_CUDA_VERSION__=%d",
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nvcc.c_str(), major, minor, machine, kernel.c_str(), cubin.c_str(), arch_flags.c_str(), include.c_str(), cuda_version);
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printf("%s\n", command.c_str());
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if(system(command.c_str()) == -1) {
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cuda_error_message("Failed to execute compilation command, see console for details.");
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return "";
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}
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/* verify if compilation succeeded */
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if(!path_exists(cubin)) {
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cuda_error_message("CUDA kernel compilation failed, see console for details.");
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return "";
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}
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printf("Kernel compilation finished in %.2lfs.\n", time_dt() - starttime);
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return cubin;
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}
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bool load_kernels(bool experimental)
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{
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/* check if cuda init succeeded */
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if(cuContext == 0)
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return false;
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/* check if GPU is supported with current feature set */
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if(!support_device(experimental))
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return false;
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/* get kernel */
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string cubin = compile_kernel();
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if(cubin == "")
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return false;
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/* open module */
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cuda_push_context();
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CUresult result = cuModuleLoad(&cuModule, cubin.c_str());
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if(cuda_error_(result, "cuModuleLoad"))
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cuda_error_message(string_printf("Failed loading CUDA kernel %s.", cubin.c_str()));
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cuda_pop_context();
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return (result == CUDA_SUCCESS);
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}
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void mem_alloc(device_memory& mem, MemoryType type)
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{
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cuda_push_context();
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CUdeviceptr device_pointer;
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size_t size = mem.memory_size();
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cuda_assert(cuMemAlloc(&device_pointer, size))
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mem.device_pointer = (device_ptr)device_pointer;
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stats.mem_alloc(size);
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cuda_pop_context();
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}
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void mem_copy_to(device_memory& mem)
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{
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cuda_push_context();
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if(mem.device_pointer)
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cuda_assert(cuMemcpyHtoD(cuda_device_ptr(mem.device_pointer), (void*)mem.data_pointer, mem.memory_size()))
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cuda_pop_context();
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}
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void mem_copy_from(device_memory& mem, int y, int w, int h, int elem)
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{
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size_t offset = elem*y*w;
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size_t size = elem*w*h;
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cuda_push_context();
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if(mem.device_pointer) {
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cuda_assert(cuMemcpyDtoH((uchar*)mem.data_pointer + offset,
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(CUdeviceptr)((uchar*)mem.device_pointer + offset), size))
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}
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else {
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memset((char*)mem.data_pointer + offset, 0, size);
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}
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cuda_pop_context();
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}
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void mem_zero(device_memory& mem)
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{
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memset((void*)mem.data_pointer, 0, mem.memory_size());
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cuda_push_context();
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if(mem.device_pointer)
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cuda_assert(cuMemsetD8(cuda_device_ptr(mem.device_pointer), 0, mem.memory_size()))
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cuda_pop_context();
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}
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void mem_free(device_memory& mem)
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{
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if(mem.device_pointer) {
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cuda_push_context();
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cuda_assert(cuMemFree(cuda_device_ptr(mem.device_pointer)))
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cuda_pop_context();
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mem.device_pointer = 0;
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stats.mem_free(mem.memory_size());
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}
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}
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void const_copy_to(const char *name, void *host, size_t size)
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{
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CUdeviceptr mem;
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size_t bytes;
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cuda_push_context();
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cuda_assert(cuModuleGetGlobal(&mem, &bytes, cuModule, name))
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//assert(bytes == size);
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cuda_assert(cuMemcpyHtoD(mem, host, size))
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cuda_pop_context();
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}
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void tex_alloc(const char *name, device_memory& mem, bool interpolation, bool periodic)
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{
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/* determine format */
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CUarray_format_enum format;
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size_t dsize = datatype_size(mem.data_type);
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size_t size = mem.memory_size();
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switch(mem.data_type) {
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case TYPE_UCHAR: format = CU_AD_FORMAT_UNSIGNED_INT8; break;
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case TYPE_UINT: format = CU_AD_FORMAT_UNSIGNED_INT32; break;
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case TYPE_INT: format = CU_AD_FORMAT_SIGNED_INT32; break;
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case TYPE_FLOAT: format = CU_AD_FORMAT_FLOAT; break;
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default: assert(0); return;
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}
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CUtexref texref = NULL;
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cuda_push_context();
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cuda_assert(cuModuleGetTexRef(&texref, cuModule, name))
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if(!texref) {
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cuda_pop_context();
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return;
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}
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if(interpolation) {
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CUarray handle = NULL;
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CUDA_ARRAY_DESCRIPTOR desc;
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desc.Width = mem.data_width;
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desc.Height = mem.data_height;
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desc.Format = format;
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desc.NumChannels = mem.data_elements;
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cuda_assert(cuArrayCreate(&handle, &desc))
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if(!handle) {
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cuda_pop_context();
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return;
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}
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if(mem.data_height > 1) {
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CUDA_MEMCPY2D param;
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memset(¶m, 0, sizeof(param));
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param.dstMemoryType = CU_MEMORYTYPE_ARRAY;
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param.dstArray = handle;
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param.srcMemoryType = CU_MEMORYTYPE_HOST;
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param.srcHost = (void*)mem.data_pointer;
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param.srcPitch = mem.data_width*dsize*mem.data_elements;
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param.WidthInBytes = param.srcPitch;
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param.Height = mem.data_height;
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cuda_assert(cuMemcpy2D(¶m))
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}
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else
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cuda_assert(cuMemcpyHtoA(handle, 0, (void*)mem.data_pointer, size))
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cuda_assert(cuTexRefSetArray(texref, handle, CU_TRSA_OVERRIDE_FORMAT))
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cuda_assert(cuTexRefSetFilterMode(texref, CU_TR_FILTER_MODE_LINEAR))
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cuda_assert(cuTexRefSetFlags(texref, CU_TRSF_NORMALIZED_COORDINATES))
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mem.device_pointer = (device_ptr)handle;
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stats.mem_alloc(size);
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}
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else {
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cuda_pop_context();
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mem_alloc(mem, MEM_READ_ONLY);
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mem_copy_to(mem);
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|
|
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();
|
|
|
|
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)
|
|
{
|
|
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 */
|
|
cuda_assert(cuModuleGetFunction(&cuPathTrace, cuModule, "kernel_cuda_path_trace"))
|
|
|
|
/* 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 tonemap(DeviceTask& task, device_ptr buffer, device_ptr rgba)
|
|
{
|
|
if(have_error())
|
|
return;
|
|
|
|
cuda_push_context();
|
|
|
|
CUfunction cuFilmConvert;
|
|
CUdeviceptr d_rgba = map_pixels(rgba);
|
|
CUdeviceptr d_buffer = cuda_device_ptr(buffer);
|
|
|
|
/* get kernel function */
|
|
cuda_assert(cuModuleGetFunction(&cuFilmConvert, cuModule, "kernel_cuda_tonemap"))
|
|
|
|
/* 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);
|
|
|
|
int sample = task.sample;
|
|
offset = align_up(offset, __alignof(sample));
|
|
|
|
cuda_assert(cuParamSeti(cuFilmConvert, offset, task.sample))
|
|
offset += sizeof(task.sample);
|
|
|
|
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(task.rgba);
|
|
|
|
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);
|
|
glBufferData(GL_PIXEL_UNPACK_BUFFER, pmem.w*pmem.h*sizeof(GLfloat)*3, NULL, GL_DYNAMIC_DRAW);
|
|
|
|
glBindBuffer(GL_PIXEL_UNPACK_BUFFER, 0);
|
|
|
|
glGenTextures(1, &pmem.cuTexId);
|
|
glBindTexture(GL_TEXTURE_2D, pmem.cuTexId);
|
|
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 = sizeof(uint8_t)*4*y*w;
|
|
|
|
glBindBufferARB(GL_PIXEL_UNPACK_BUFFER_ARB, pmem.cuPBO);
|
|
glBindTexture(GL_TEXTURE_2D, pmem.cuTexId);
|
|
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;
|
|
|
|
/* 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);
|
|
|
|
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::TONEMAP) {
|
|
/* must be done in main thread due to opengl access */
|
|
tonemap(task, task.buffer, task.rgba);
|
|
|
|
cuda_push_context();
|
|
cuda_assert(cuCtxSynchronize())
|
|
cuda_pop_context();
|
|
}
|
|
else {
|
|
task_pool.push(new CUDADeviceTask(this, task));
|
|
}
|
|
}
|
|
|
|
void task_wait()
|
|
{
|
|
task_pool.wait_work();
|
|
}
|
|
|
|
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
|
|
|