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That's because newer GPUs support newer instructions sets. Like AVX, AVX2, AVX512, but basically a new set every year instead of every 10 years like in CPU lan
by dist-epoch 3y ago
That's because newer GPUs support newer instructions sets.
Like AVX, AVX2, AVX512, but basically a new set every year instead of every 10 years like in CPU land.
And it's not just about speed, they provide new functionality. So at some point supporting older GPUs significantly slows down those who have the newer GPUs.
The next architecture after Kepler, Pascal, added huge new capabilities, that's why nobody supports Kepler anymore, it's too limited.
> wanting to try out some very basic exercises
Should be possible to do that with an older Python (3.5?) and associated libraries. Versions around 2016 should work.
- rahimnathwani 3y agoI seem to recall ~6 years ago I had to recompile an ML library because my CPU didn’t support AVX2. So even though the release binaries required AVX2, the source code was written in a way that it could work without it. I wonder whether this required specific effort by the developers of that library, or whether it was taken care of by some underlying tooling? Can you write CUDA code today that uses the latest features but can be compiled for older cards as well?