pyCUDA for ARM (armv7l) Linux GNUroot Debian on NVIDIA Shield Tablet [Tegra K1] - EXPERIMENTAL: much of cuda driver API works but no cuda runtime API. REQUIRES: Linux for Tegra cuda-6.5-toolkit [.deb package] and libcuda.so.1.1 in /usr/lib (from Jetson TK1 Driver Package) @ https://developer.nvidia.com/linux-tegra-rel-21
- Object cleanup tied to lifetime of objects. This idiom, often called RAII in C++, makes it much easier to write correct, leak- and crash-free code. PyCUDA knows about dependencies, too, so (for example) it won’t detach from a context before all memory allocated in it is also freed.
- Convenience. Abstractions like pycuda.driver.SourceModule and pycuda.gpuarray.GPUArray make CUDA programming even more convenient than with Nvidia’s C-based runtime.
- Completeness. PyCUDA puts the full power of CUDA’s driver API at your disposal, if you wish. It also includes code for interoperability with OpenGL.
- Automatic Error Checking. All CUDA errors are automatically translated into Python exceptions.
- Speed. PyCUDA’s base layer is written in C++, so all the niceties above are virtually free.
- Helpful Documentation and a Wiki.
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
|File Name & Checksum SHA256 Checksum Help||Version||File Type||Upload Date|
|pycuda_arm_linux-2015.1.3-py2.7-linux-armv7l.egg (3.8 MB) Copy SHA256 Checksum SHA256||2.7||Egg||Dec 22, 2015|