3 ms·
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 othe
by zzbn00 3y ago
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.
- cburdick13 3y agoThe 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.