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blender/intern/cycles/util/util_cuda.cpp

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Cycles render engine, initial commit. This is the engine itself, blender modifications and build instructions will follow later. Cycles uses code from some great open source projects, many thanks them: * BVH building and traversal code from NVidia's "Understanding the Efficiency of Ray Traversal on GPUs": http://code.google.com/p/understanding-the-efficiency-of-ray-traversal-on-gpus/ * Open Shading Language for a large part of the shading system: http://code.google.com/p/openshadinglanguage/ * Blender for procedural textures and a few other nodes. * Approximate Catmull Clark subdivision from NVidia Mesh tools: http://code.google.com/p/nvidia-mesh-tools/ * Sobol direction vectors from: http://web.maths.unsw.edu.au/~fkuo/sobol/ * Film response functions from: http://www.cs.columbia.edu/CAVE/software/softlib/dorf.php
2011-04-27 11:58:34 +00:00
/*
* Copyright 2011, Blender Foundation.
*
* This program is free software; you can redistribute it and/or
* modify it under the terms of the GNU General Public License
* as published by the Free Software Foundation; either version 2
* of the License, or (at your option) any later version.
*
* This program is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with this program; if not, write to the Free Software Foundation,
* Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA.
*/
Cycles: * OpenCL now only uses GPU/Accelerator devices, it's only confusing if CPU device is used, easy to enable in the code for debugging. * OpenCL kernel binaries are now cached for faster startup after the first time compiling. * CUDA kernels can now be compiled and cached at runtime if the CUDA toolkit is installed. This means that even if the build does not have CUDA enabled, it's still possible to use it as long as you install the toolkit.
2011-09-09 12:04:39 +00:00
#include <stdlib.h>
Cycles render engine, initial commit. This is the engine itself, blender modifications and build instructions will follow later. Cycles uses code from some great open source projects, many thanks them: * BVH building and traversal code from NVidia's "Understanding the Efficiency of Ray Traversal on GPUs": http://code.google.com/p/understanding-the-efficiency-of-ray-traversal-on-gpus/ * Open Shading Language for a large part of the shading system: http://code.google.com/p/openshadinglanguage/ * Blender for procedural textures and a few other nodes. * Approximate Catmull Clark subdivision from NVidia Mesh tools: http://code.google.com/p/nvidia-mesh-tools/ * Sobol direction vectors from: http://web.maths.unsw.edu.au/~fkuo/sobol/ * Film response functions from: http://www.cs.columbia.edu/CAVE/software/softlib/dorf.php
2011-04-27 11:58:34 +00:00
#include "util_cuda.h"
#include "util_debug.h"
#include "util_dynlib.h"
Cycles: some warning fixes, cpu device task tweaks, avoid unnecessary tonemap in non-viewport render, and some utility functions.
2011-09-08 18:58:07 +00:00
#include "util_path.h"
#include "util_string.h"
Cycles render engine, initial commit. This is the engine itself, blender modifications and build instructions will follow later. Cycles uses code from some great open source projects, many thanks them: * BVH building and traversal code from NVidia's "Understanding the Efficiency of Ray Traversal on GPUs": http://code.google.com/p/understanding-the-efficiency-of-ray-traversal-on-gpus/ * Open Shading Language for a large part of the shading system: http://code.google.com/p/openshadinglanguage/ * Blender for procedural textures and a few other nodes. * Approximate Catmull Clark subdivision from NVidia Mesh tools: http://code.google.com/p/nvidia-mesh-tools/ * Sobol direction vectors from: http://web.maths.unsw.edu.au/~fkuo/sobol/ * Film response functions from: http://www.cs.columbia.edu/CAVE/software/softlib/dorf.php
2011-04-27 11:58:34 +00:00
/* function defininitions */
tcuInit *cuInit;
tcuDriverGetVersion *cuDriverGetVersion;
tcuDeviceGet *cuDeviceGet;
tcuDeviceGetCount *cuDeviceGetCount;
tcuDeviceGetName *cuDeviceGetName;
tcuDeviceComputeCapability *cuDeviceComputeCapability;
tcuDeviceTotalMem *cuDeviceTotalMem;
tcuDeviceGetProperties *cuDeviceGetProperties;
tcuDeviceGetAttribute *cuDeviceGetAttribute;
tcuCtxCreate *cuCtxCreate;
tcuCtxDestroy *cuCtxDestroy;
tcuCtxAttach *cuCtxAttach;
tcuCtxDetach *cuCtxDetach;
tcuCtxPushCurrent *cuCtxPushCurrent;
tcuCtxPopCurrent *cuCtxPopCurrent;
tcuCtxGetDevice *cuCtxGetDevice;
tcuCtxSynchronize *cuCtxSynchronize;
tcuModuleLoad *cuModuleLoad;
tcuModuleLoadData *cuModuleLoadData;
tcuModuleLoadDataEx *cuModuleLoadDataEx;
tcuModuleLoadFatBinary *cuModuleLoadFatBinary;
tcuModuleUnload *cuModuleUnload;
tcuModuleGetFunction *cuModuleGetFunction;
tcuModuleGetGlobal *cuModuleGetGlobal;
tcuModuleGetTexRef *cuModuleGetTexRef;
tcuModuleGetSurfRef *cuModuleGetSurfRef;
tcuMemGetInfo *cuMemGetInfo;
tcuMemAlloc *cuMemAlloc;
tcuMemAllocPitch *cuMemAllocPitch;
tcuMemFree *cuMemFree;
tcuMemGetAddressRange *cuMemGetAddressRange;
tcuMemAllocHost *cuMemAllocHost;
tcuMemFreeHost *cuMemFreeHost;
tcuMemHostAlloc *cuMemHostAlloc;
tcuMemHostGetDevicePointer *cuMemHostGetDevicePointer;
tcuMemHostGetFlags *cuMemHostGetFlags;
tcuMemcpyHtoD *cuMemcpyHtoD;
tcuMemcpyDtoH *cuMemcpyDtoH;
tcuMemcpyDtoD *cuMemcpyDtoD;
tcuMemcpyDtoA *cuMemcpyDtoA;
tcuMemcpyAtoD *cuMemcpyAtoD;
tcuMemcpyHtoA *cuMemcpyHtoA;
tcuMemcpyAtoH *cuMemcpyAtoH;
tcuMemcpyAtoA *cuMemcpyAtoA;
tcuMemcpy2D *cuMemcpy2D;
tcuMemcpy2DUnaligned *cuMemcpy2DUnaligned;
tcuMemcpy3D *cuMemcpy3D;
tcuMemcpyHtoDAsync *cuMemcpyHtoDAsync;
tcuMemcpyDtoHAsync *cuMemcpyDtoHAsync;
tcuMemcpyDtoDAsync *cuMemcpyDtoDAsync;
tcuMemcpyHtoAAsync *cuMemcpyHtoAAsync;
tcuMemcpyAtoHAsync *cuMemcpyAtoHAsync;
tcuMemcpy2DAsync *cuMemcpy2DAsync;
tcuMemcpy3DAsync *cuMemcpy3DAsync;
tcuMemsetD8 *cuMemsetD8;
tcuMemsetD16 *cuMemsetD16;
tcuMemsetD32 *cuMemsetD32;
tcuMemsetD2D8 *cuMemsetD2D8;
tcuMemsetD2D16 *cuMemsetD2D16;
tcuMemsetD2D32 *cuMemsetD2D32;
tcuFuncSetBlockShape *cuFuncSetBlockShape;
tcuFuncSetSharedSize *cuFuncSetSharedSize;
tcuFuncGetAttribute *cuFuncGetAttribute;
tcuFuncSetCacheConfig *cuFuncSetCacheConfig;
tcuArrayCreate *cuArrayCreate;
tcuArrayGetDescriptor *cuArrayGetDescriptor;
tcuArrayDestroy *cuArrayDestroy;
tcuArray3DCreate *cuArray3DCreate;
tcuArray3DGetDescriptor *cuArray3DGetDescriptor;
tcuTexRefCreate *cuTexRefCreate;
tcuTexRefDestroy *cuTexRefDestroy;
tcuTexRefSetArray *cuTexRefSetArray;
tcuTexRefSetAddress *cuTexRefSetAddress;
tcuTexRefSetAddress2D *cuTexRefSetAddress2D;
tcuTexRefSetFormat *cuTexRefSetFormat;
tcuTexRefSetAddressMode *cuTexRefSetAddressMode;
tcuTexRefSetFilterMode *cuTexRefSetFilterMode;
tcuTexRefSetFlags *cuTexRefSetFlags;
tcuTexRefGetAddress *cuTexRefGetAddress;
tcuTexRefGetArray *cuTexRefGetArray;
tcuTexRefGetAddressMode *cuTexRefGetAddressMode;
tcuTexRefGetFilterMode *cuTexRefGetFilterMode;
tcuTexRefGetFormat *cuTexRefGetFormat;
tcuTexRefGetFlags *cuTexRefGetFlags;
tcuSurfRefSetArray *cuSurfRefSetArray;
tcuSurfRefGetArray *cuSurfRefGetArray;
tcuParamSetSize *cuParamSetSize;
tcuParamSeti *cuParamSeti;
tcuParamSetf *cuParamSetf;
tcuParamSetv *cuParamSetv;
tcuParamSetTexRef *cuParamSetTexRef;
tcuLaunch *cuLaunch;
tcuLaunchGrid *cuLaunchGrid;
tcuLaunchGridAsync *cuLaunchGridAsync;
tcuEventCreate *cuEventCreate;
tcuEventRecord *cuEventRecord;
tcuEventQuery *cuEventQuery;
tcuEventSynchronize *cuEventSynchronize;
tcuEventDestroy *cuEventDestroy;
tcuEventElapsedTime *cuEventElapsedTime;
tcuStreamCreate *cuStreamCreate;
tcuStreamQuery *cuStreamQuery;
tcuStreamSynchronize *cuStreamSynchronize;
tcuStreamDestroy *cuStreamDestroy;
tcuGraphicsUnregisterResource *cuGraphicsUnregisterResource;
tcuGraphicsSubResourceGetMappedArray *cuGraphicsSubResourceGetMappedArray;
tcuGraphicsResourceGetMappedPointer *cuGraphicsResourceGetMappedPointer;
tcuGraphicsResourceSetMapFlags *cuGraphicsResourceSetMapFlags;
tcuGraphicsMapResources *cuGraphicsMapResources;
tcuGraphicsUnmapResources *cuGraphicsUnmapResources;
tcuGetExportTable *cuGetExportTable;
tcuCtxSetLimit *cuCtxSetLimit;
tcuCtxGetLimit *cuCtxGetLimit;
tcuGLCtxCreate *cuGLCtxCreate;
tcuGraphicsGLRegisterBuffer *cuGraphicsGLRegisterBuffer;
tcuGraphicsGLRegisterImage *cuGraphicsGLRegisterImage;
tcuCtxSetCurrent *cuCtxSetCurrent;
CCL_NAMESPACE_BEGIN
/* utility macros */
#define CUDA_LIBRARY_FIND(name) \
name = (t##name*)dynamic_library_find(lib, #name); \
assert(name);
#define CUDA_LIBRARY_FIND_V2(name) \
name = (t##name*)dynamic_library_find(lib, #name "_v2"); \
assert(name);
/* initialization function */
bool cuLibraryInit()
{
static bool initialized = false;
static bool result = false;
if(initialized)
return result;
initialized = true;
/* library paths */
#ifdef _WIN32
/* expected in c:/windows/system or similar, no path needed */
const char *path = "nvcuda.dll";
#elif defined(__APPLE__)
/* default installation path */
const char *path = "/usr/local/cuda/lib/libcuda.dylib";
#else
const char *path = "libcuda.so";
#endif
/* load library */
DynamicLibrary *lib = dynamic_library_open(path);
if(lib == NULL)
return false;
/* detect driver version */
int driver_version = 1000;
CUDA_LIBRARY_FIND(cuDriverGetVersion);
if(cuDriverGetVersion)
cuDriverGetVersion(&driver_version);
/* we require version 4.0 */
if(driver_version < 4000)
return false;
/* fetch all function pointers */
CUDA_LIBRARY_FIND(cuInit);
CUDA_LIBRARY_FIND(cuDeviceGet);
CUDA_LIBRARY_FIND(cuDeviceGetCount);
CUDA_LIBRARY_FIND(cuDeviceGetName);
CUDA_LIBRARY_FIND(cuDeviceComputeCapability);
CUDA_LIBRARY_FIND(cuDeviceTotalMem);
CUDA_LIBRARY_FIND(cuDeviceGetProperties);
CUDA_LIBRARY_FIND(cuDeviceGetAttribute);
CUDA_LIBRARY_FIND(cuCtxCreate);
CUDA_LIBRARY_FIND(cuCtxDestroy);
CUDA_LIBRARY_FIND(cuCtxAttach);
CUDA_LIBRARY_FIND(cuCtxDetach);
CUDA_LIBRARY_FIND(cuCtxPushCurrent);
CUDA_LIBRARY_FIND(cuCtxPopCurrent);
CUDA_LIBRARY_FIND(cuCtxGetDevice);
CUDA_LIBRARY_FIND(cuCtxSynchronize);
CUDA_LIBRARY_FIND(cuModuleLoad);
CUDA_LIBRARY_FIND(cuModuleLoadData);
CUDA_LIBRARY_FIND(cuModuleUnload);
CUDA_LIBRARY_FIND(cuModuleGetFunction);
CUDA_LIBRARY_FIND(cuModuleGetGlobal);
CUDA_LIBRARY_FIND(cuModuleGetTexRef);
CUDA_LIBRARY_FIND(cuMemGetInfo);
CUDA_LIBRARY_FIND(cuMemAlloc);
CUDA_LIBRARY_FIND(cuMemAllocPitch);
CUDA_LIBRARY_FIND(cuMemFree);
CUDA_LIBRARY_FIND(cuMemGetAddressRange);
CUDA_LIBRARY_FIND(cuMemAllocHost);
CUDA_LIBRARY_FIND(cuMemFreeHost);
CUDA_LIBRARY_FIND(cuMemHostAlloc);
CUDA_LIBRARY_FIND(cuMemHostGetDevicePointer);
CUDA_LIBRARY_FIND(cuMemcpyHtoD);
CUDA_LIBRARY_FIND(cuMemcpyDtoH);
CUDA_LIBRARY_FIND(cuMemcpyDtoD);
CUDA_LIBRARY_FIND(cuMemcpyDtoA);
CUDA_LIBRARY_FIND(cuMemcpyAtoD);
CUDA_LIBRARY_FIND(cuMemcpyHtoA);
CUDA_LIBRARY_FIND(cuMemcpyAtoH);
CUDA_LIBRARY_FIND(cuMemcpyAtoA);
CUDA_LIBRARY_FIND(cuMemcpy2D);
CUDA_LIBRARY_FIND(cuMemcpy2DUnaligned);
CUDA_LIBRARY_FIND(cuMemcpy3D);
CUDA_LIBRARY_FIND(cuMemcpyHtoDAsync);
CUDA_LIBRARY_FIND(cuMemcpyDtoHAsync);
CUDA_LIBRARY_FIND(cuMemcpyHtoAAsync);
CUDA_LIBRARY_FIND(cuMemcpyAtoHAsync);
CUDA_LIBRARY_FIND(cuMemcpy2DAsync);
CUDA_LIBRARY_FIND(cuMemcpy3DAsync);
CUDA_LIBRARY_FIND(cuMemsetD8);
CUDA_LIBRARY_FIND(cuMemsetD16);
CUDA_LIBRARY_FIND(cuMemsetD32);
CUDA_LIBRARY_FIND(cuMemsetD2D8);
CUDA_LIBRARY_FIND(cuMemsetD2D16);
CUDA_LIBRARY_FIND(cuMemsetD2D32);
CUDA_LIBRARY_FIND(cuFuncSetBlockShape);
CUDA_LIBRARY_FIND(cuFuncSetSharedSize);
CUDA_LIBRARY_FIND(cuFuncGetAttribute);
CUDA_LIBRARY_FIND(cuArrayCreate);
CUDA_LIBRARY_FIND(cuArrayGetDescriptor);
CUDA_LIBRARY_FIND(cuArrayDestroy);
CUDA_LIBRARY_FIND(cuArray3DCreate);
CUDA_LIBRARY_FIND(cuArray3DGetDescriptor);
CUDA_LIBRARY_FIND(cuTexRefCreate);
CUDA_LIBRARY_FIND(cuTexRefDestroy);
CUDA_LIBRARY_FIND(cuTexRefSetArray);
CUDA_LIBRARY_FIND(cuTexRefSetAddress);
CUDA_LIBRARY_FIND(cuTexRefSetAddress2D);
CUDA_LIBRARY_FIND(cuTexRefSetFormat);
CUDA_LIBRARY_FIND(cuTexRefSetAddressMode);
CUDA_LIBRARY_FIND(cuTexRefSetFilterMode);
CUDA_LIBRARY_FIND(cuTexRefSetFlags);
CUDA_LIBRARY_FIND(cuTexRefGetAddress);
CUDA_LIBRARY_FIND(cuTexRefGetArray);
CUDA_LIBRARY_FIND(cuTexRefGetAddressMode);
CUDA_LIBRARY_FIND(cuTexRefGetFilterMode);
CUDA_LIBRARY_FIND(cuTexRefGetFormat);
CUDA_LIBRARY_FIND(cuTexRefGetFlags);
CUDA_LIBRARY_FIND(cuParamSetSize);
CUDA_LIBRARY_FIND(cuParamSeti);
CUDA_LIBRARY_FIND(cuParamSetf);
CUDA_LIBRARY_FIND(cuParamSetv);
CUDA_LIBRARY_FIND(cuParamSetTexRef);
CUDA_LIBRARY_FIND(cuLaunch);
CUDA_LIBRARY_FIND(cuLaunchGrid);
CUDA_LIBRARY_FIND(cuLaunchGridAsync);
CUDA_LIBRARY_FIND(cuEventCreate);
CUDA_LIBRARY_FIND(cuEventRecord);
CUDA_LIBRARY_FIND(cuEventQuery);
CUDA_LIBRARY_FIND(cuEventSynchronize);
CUDA_LIBRARY_FIND(cuEventDestroy);
CUDA_LIBRARY_FIND(cuEventElapsedTime);
CUDA_LIBRARY_FIND(cuStreamCreate);
CUDA_LIBRARY_FIND(cuStreamQuery);
CUDA_LIBRARY_FIND(cuStreamSynchronize);
CUDA_LIBRARY_FIND(cuStreamDestroy);
/* cuda 2.1 */
CUDA_LIBRARY_FIND(cuModuleLoadDataEx);
CUDA_LIBRARY_FIND(cuModuleLoadFatBinary);
CUDA_LIBRARY_FIND(cuGLCtxCreate);
CUDA_LIBRARY_FIND(cuGraphicsGLRegisterBuffer);
CUDA_LIBRARY_FIND(cuGraphicsGLRegisterImage);
/* cuda 2.3 */
CUDA_LIBRARY_FIND(cuMemHostGetFlags);
CUDA_LIBRARY_FIND(cuGraphicsGLRegisterBuffer);
CUDA_LIBRARY_FIND(cuGraphicsGLRegisterImage);
/* cuda 3.0 */
CUDA_LIBRARY_FIND(cuMemcpyDtoDAsync);
CUDA_LIBRARY_FIND(cuFuncSetCacheConfig);
CUDA_LIBRARY_FIND(cuGraphicsUnregisterResource);
CUDA_LIBRARY_FIND(cuGraphicsSubResourceGetMappedArray);
CUDA_LIBRARY_FIND(cuGraphicsResourceGetMappedPointer);
CUDA_LIBRARY_FIND(cuGraphicsResourceSetMapFlags);
CUDA_LIBRARY_FIND(cuGraphicsMapResources);
CUDA_LIBRARY_FIND(cuGraphicsUnmapResources);
CUDA_LIBRARY_FIND(cuGetExportTable);
/* cuda 3.1 */
CUDA_LIBRARY_FIND(cuModuleGetSurfRef);
CUDA_LIBRARY_FIND(cuSurfRefSetArray);
CUDA_LIBRARY_FIND(cuSurfRefGetArray);
CUDA_LIBRARY_FIND(cuCtxSetLimit);
CUDA_LIBRARY_FIND(cuCtxGetLimit);
/* functions which changed 3.1 -> 3.2 for 64 bit stuff, the cuda library
has both the old ones for compatibility and new ones with _v2 postfix,
we load the _v2 ones here. */
CUDA_LIBRARY_FIND_V2(cuDeviceTotalMem);
CUDA_LIBRARY_FIND_V2(cuCtxCreate);
CUDA_LIBRARY_FIND_V2(cuModuleGetGlobal);
CUDA_LIBRARY_FIND_V2(cuMemGetInfo);
CUDA_LIBRARY_FIND_V2(cuMemAlloc);
CUDA_LIBRARY_FIND_V2(cuMemAllocPitch);
CUDA_LIBRARY_FIND_V2(cuMemFree);
CUDA_LIBRARY_FIND_V2(cuMemGetAddressRange);
CUDA_LIBRARY_FIND_V2(cuMemAllocHost);
CUDA_LIBRARY_FIND_V2(cuMemHostGetDevicePointer);
CUDA_LIBRARY_FIND_V2(cuMemcpyHtoD);
CUDA_LIBRARY_FIND_V2(cuMemcpyDtoH);
CUDA_LIBRARY_FIND_V2(cuMemcpyDtoD);
CUDA_LIBRARY_FIND_V2(cuMemcpyDtoA);
CUDA_LIBRARY_FIND_V2(cuMemcpyAtoD);
CUDA_LIBRARY_FIND_V2(cuMemcpyHtoA);
CUDA_LIBRARY_FIND_V2(cuMemcpyAtoH);
CUDA_LIBRARY_FIND_V2(cuMemcpyAtoA);
CUDA_LIBRARY_FIND_V2(cuMemcpyHtoAAsync);
CUDA_LIBRARY_FIND_V2(cuMemcpyAtoHAsync);
CUDA_LIBRARY_FIND_V2(cuMemcpy2D);
CUDA_LIBRARY_FIND_V2(cuMemcpy2DUnaligned);
CUDA_LIBRARY_FIND_V2(cuMemcpy3D);
CUDA_LIBRARY_FIND_V2(cuMemcpyHtoDAsync);
CUDA_LIBRARY_FIND_V2(cuMemcpyDtoHAsync);
CUDA_LIBRARY_FIND_V2(cuMemcpyDtoDAsync);
CUDA_LIBRARY_FIND_V2(cuMemcpy2DAsync);
CUDA_LIBRARY_FIND_V2(cuMemcpy3DAsync);
CUDA_LIBRARY_FIND_V2(cuMemsetD8);
CUDA_LIBRARY_FIND_V2(cuMemsetD16);
CUDA_LIBRARY_FIND_V2(cuMemsetD32);
CUDA_LIBRARY_FIND_V2(cuMemsetD2D8);
CUDA_LIBRARY_FIND_V2(cuMemsetD2D16);
CUDA_LIBRARY_FIND_V2(cuMemsetD2D32);
CUDA_LIBRARY_FIND_V2(cuArrayCreate);
CUDA_LIBRARY_FIND_V2(cuArrayGetDescriptor);
CUDA_LIBRARY_FIND_V2(cuArray3DCreate);
CUDA_LIBRARY_FIND_V2(cuArray3DGetDescriptor);
CUDA_LIBRARY_FIND_V2(cuTexRefSetAddress);
CUDA_LIBRARY_FIND_V2(cuTexRefSetAddress2D);
CUDA_LIBRARY_FIND_V2(cuTexRefGetAddress);
CUDA_LIBRARY_FIND_V2(cuGraphicsResourceGetMappedPointer);
CUDA_LIBRARY_FIND_V2(cuGLCtxCreate);
/* cuda 4.0 */
CUDA_LIBRARY_FIND(cuCtxSetCurrent);
Cycles: * Add back option to bundle CUDA kernel binaries with builds. * Disable runtime CUDA kernel compilation on Windows, couldn't get this working, since it seems to depend on visual studio being installed, even though for this particular case it shouldn't be needed. CMake only at the moment. * Runtime compilation on linux/mac should now work if nvcc is not installed in the default location, but available in PATH.
2011-11-10 12:52:17 +00:00
#ifndef WITH_CUDA_BINARIES
#ifdef _WIN32
return false; /* runtime build doesn't work at the moment */
#else
Cycles: * OpenCL now only uses GPU/Accelerator devices, it's only confusing if CPU device is used, easy to enable in the code for debugging. * OpenCL kernel binaries are now cached for faster startup after the first time compiling. * CUDA kernels can now be compiled and cached at runtime if the CUDA toolkit is installed. This means that even if the build does not have CUDA enabled, it's still possible to use it as long as you install the toolkit.
2011-09-09 12:04:39 +00:00
if(cuCompilerPath() == "")
return false;
Cycles: * Add back option to bundle CUDA kernel binaries with builds. * Disable runtime CUDA kernel compilation on Windows, couldn't get this working, since it seems to depend on visual studio being installed, even though for this particular case it shouldn't be needed. CMake only at the moment. * Runtime compilation on linux/mac should now work if nvcc is not installed in the default location, but available in PATH.
2011-11-10 12:52:17 +00:00
#endif
#endif
Cycles: * OpenCL now only uses GPU/Accelerator devices, it's only confusing if CPU device is used, easy to enable in the code for debugging. * OpenCL kernel binaries are now cached for faster startup after the first time compiling. * CUDA kernels can now be compiled and cached at runtime if the CUDA toolkit is installed. This means that even if the build does not have CUDA enabled, it's still possible to use it as long as you install the toolkit.
2011-09-09 12:04:39 +00:00
Cycles render engine, initial commit. This is the engine itself, blender modifications and build instructions will follow later. Cycles uses code from some great open source projects, many thanks them: * BVH building and traversal code from NVidia's "Understanding the Efficiency of Ray Traversal on GPUs": http://code.google.com/p/understanding-the-efficiency-of-ray-traversal-on-gpus/ * Open Shading Language for a large part of the shading system: http://code.google.com/p/openshadinglanguage/ * Blender for procedural textures and a few other nodes. * Approximate Catmull Clark subdivision from NVidia Mesh tools: http://code.google.com/p/nvidia-mesh-tools/ * Sobol direction vectors from: http://web.maths.unsw.edu.au/~fkuo/sobol/ * Film response functions from: http://www.cs.columbia.edu/CAVE/software/softlib/dorf.php
2011-04-27 11:58:34 +00:00
/* success */
result = true;
return result;
}
Cycles: some warning fixes, cpu device task tweaks, avoid unnecessary tonemap in non-viewport render, and some utility functions.
2011-09-08 18:58:07 +00:00
string cuCompilerPath()
{
#ifdef _WIN32
Cycles: * OpenCL now only uses GPU/Accelerator devices, it's only confusing if CPU device is used, easy to enable in the code for debugging. * OpenCL kernel binaries are now cached for faster startup after the first time compiling. * CUDA kernels can now be compiled and cached at runtime if the CUDA toolkit is installed. This means that even if the build does not have CUDA enabled, it's still possible to use it as long as you install the toolkit.
2011-09-09 12:04:39 +00:00
const char *defaultpath = "C:/CUDA/bin";
const char *executable = "nvcc.exe";
Cycles: some warning fixes, cpu device task tweaks, avoid unnecessary tonemap in non-viewport render, and some utility functions.
2011-09-08 18:58:07 +00:00
#else
Cycles: * OpenCL now only uses GPU/Accelerator devices, it's only confusing if CPU device is used, easy to enable in the code for debugging. * OpenCL kernel binaries are now cached for faster startup after the first time compiling. * CUDA kernels can now be compiled and cached at runtime if the CUDA toolkit is installed. This means that even if the build does not have CUDA enabled, it's still possible to use it as long as you install the toolkit.
2011-09-09 12:04:39 +00:00
const char *defaultpath = "/usr/local/cuda/bin";
const char *executable = "nvcc";
Cycles: some warning fixes, cpu device task tweaks, avoid unnecessary tonemap in non-viewport render, and some utility functions.
2011-09-08 18:58:07 +00:00
#endif
Cycles: * OpenCL now only uses GPU/Accelerator devices, it's only confusing if CPU device is used, easy to enable in the code for debugging. * OpenCL kernel binaries are now cached for faster startup after the first time compiling. * CUDA kernels can now be compiled and cached at runtime if the CUDA toolkit is installed. This means that even if the build does not have CUDA enabled, it's still possible to use it as long as you install the toolkit.
2011-09-09 12:04:39 +00:00
const char *binpath = getenv("CUDA_BIN_PATH");
string nvcc;
if(binpath)
nvcc = path_join(binpath, executable);
else
nvcc = path_join(defaultpath, executable);
Cycles: * Add back option to bundle CUDA kernel binaries with builds. * Disable runtime CUDA kernel compilation on Windows, couldn't get this working, since it seems to depend on visual studio being installed, even though for this particular case it shouldn't be needed. CMake only at the moment. * Runtime compilation on linux/mac should now work if nvcc is not installed in the default location, but available in PATH.
2011-11-10 12:52:17 +00:00
if(path_exists(nvcc))
return nvcc;
#ifndef _WIN32
if(system("which nvcc") == 0)
return "nvcc";
#endif
return "";
Cycles: some warning fixes, cpu device task tweaks, avoid unnecessary tonemap in non-viewport render, and some utility functions.
2011-09-08 18:58:07 +00:00
}
Cycles render engine, initial commit. This is the engine itself, blender modifications and build instructions will follow later. Cycles uses code from some great open source projects, many thanks them: * BVH building and traversal code from NVidia's "Understanding the Efficiency of Ray Traversal on GPUs": http://code.google.com/p/understanding-the-efficiency-of-ray-traversal-on-gpus/ * Open Shading Language for a large part of the shading system: http://code.google.com/p/openshadinglanguage/ * Blender for procedural textures and a few other nodes. * Approximate Catmull Clark subdivision from NVidia Mesh tools: http://code.google.com/p/nvidia-mesh-tools/ * Sobol direction vectors from: http://web.maths.unsw.edu.au/~fkuo/sobol/ * Film response functions from: http://www.cs.columbia.edu/CAVE/software/softlib/dorf.php
2011-04-27 11:58:34 +00:00
CCL_NAMESPACE_END
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