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? .. image:: https://badge.fury.io/py/pycuda.png :target: http://pypi.python.org/pypi/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. 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 `_. Relatedly, like-minded computing goodness for `OpenCL `_ is provided by PyCUDA's sister project `PyOpenCL `_.