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This seems like an FFT based benchmark.... I believe NumPy for licensing reasons includes a port of old FFTPACK which is only single threaded. (Py)FFTW or others are surely much faster.

So the test seems to compare one thread of a CPU launched in 2016 running a port of 40year old fortran code to a optimised FFT library on a GPU launched in 2020.

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The sample is really designed to show the simplicity of the syntax, and the performance is just a side effect. Where you'll see a bigger performance difference with numPy/cuPy is when kernel fusion happens where MatX is typically able to fuse many things into a single kernel at compile-time and cuPy launches many kernels. If you have a specific type of expression you'd like to compare please let us know.

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