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Yes, but it can be difficult to figure out the best way to make said carefully optimized numpy operations for anything moderately complicated. It can also be di
by gh02t 8y ago
Yes, but it can be difficult to figure out the best way to make said carefully optimized numpy operations for anything moderately complicated. It can also be difficult or impossible to avoid extra memory allocations in numpy. Sometimes it's just quicker to bang out the obvious loop-based implementation in numba or cython.
Also, numba does in fact support targeting the GPU,̶ b̶u̶t̶ ̶I̶ ̶t̶h̶i̶n̶k̶ ̶i̶t̶ ̶r̶e̶q̶u̶i̶r̶e̶s̶ ̶a̶ ̶l̶i̶c̶e̶n̶s̶e̶ ̶f̶o̶r̶ ̶n̶u̶m̶b̶a̶p̶r̶o̶ ̶(̶i̶.̶e̶.̶ ̶n̶o̶t̶ ̶f̶r̶e̶e̶,̶ ̶t̶h̶o̶u̶g̶h̶ ̶l̶a̶s̶t̶ ̶I̶ ̶u̶s̶e̶d̶ ̶i̶t̶ ̶t̶h̶e̶y̶ ̶h̶a̶d̶ ̶f̶r̶e̶e̶ ̶l̶i̶c̶e̶n̶s̶e̶s̶ ̶f̶o̶r̶ ̶s̶t̶u̶d̶e̶n̶t̶s̶)̶.̶ (edit: it's free now, see below).
- gaius 8y agoAlso, numba does in fact support targeting the GPU Numba CUDA is free with Anaconda
- gh02t 8y agoThanks, I remember it used to cost money but I couldn't remember if it still did.
- gaius 8y agoI guess NVidia figure they can make more selling cards than charging for the library !
- mkl 8y agoNumba is not made by NVidia. It is [1] made by Anaconda (formerly Continuum Analytics), which was co-founded by Travis Oliphant, the primary author of NumPy. [1] (primarily - it's open source)
- gaius 8y agoRight, but the NVidia drivers are free for it now, whereas they didn’t used to be according to the OP.
- gh02t 8y agoThey aren't drivers, it's just the ability to generate CUDA kernels in Numba. It has nothing to do with Nvidia supporting it, they were not involved AFAIK.
- gaius 8y agoInteresting, thanks :-) either way, we’re all set to accelerate Python code on the GPU! Personally I intend to focus my efforts here rather than learning Julia.