* Add CUDA compiler version detection to cmake/scons/runtime
* Remove noinline in kernel_shader.h and reenable --use_fast_math if CUDA 5.x
is used, these were workarounds for CUDA 4.2 bugs
* Change max number of registers to 32 for sm 2.x (based on performance tests
from Martijn Berger and confirmed here), and also for NVidia OpenCL.
Overall it seems that with these changes and the latest CUDA 5.0 download, that
performance is as good as or better than the 2.67b release with the scenes and
graphics cards I tested.
precompiled cubins instead,
Logic here is following now:
- If there're precompiled cubins, assume CUDA compute is available,
otherwise
- If cuda toolkit found, assume CUDA compute is available
- In all other cases CUDA compute is not available
For windows there're still check for only precompiled binaries,
no runtime compilation is allowed.
Ended up with such decision after discussion with Brecht. The thing
is, if we'll support runtime compilation on windows we'll end up
having lots of reports about different aspects of something doesn't
work (you need particular toolkit version, msvc installed, environment
variables set properly and so) and giving feedback on such reports
will waste time.
* 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.
* Disable precompiled cuda binaries, always do at run time
* Change preview samples default to 10
* Hide volume panels since they don't do anything yet
* 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.
