Pycuda lets you access nvidia‘s cuda parallel computation api from python. several wrappers of the cuda api already exist–so what’s so special about pycuda?
* 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.
* 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.
this package contains header files used by pyopencl modules.