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> Of course, the other part (in Nvidia's favor) is that a lot of scientific work is GPU based now. Not just ML. It’s not just the hardware like you’re talking
by 6gvONxR4sf7o 4y ago
> Of course, the other part (in Nvidia's favor) is that a lot of scientific work is GPU based now. Not just ML.
It’s not just the hardware like you’re talking about. The tooling has grown up insanely well too. You used to have to write CUDA or similar if you wanted a simulation on a GPU. Now you can write it in a high level language in a way that looks pretty close to the math.
- godelski 4y agoVery true! I should have appended this under the algorithmic improvements. This is also a reason ML has exploded. Tensorflow and Pytorch enabled easy GPU usage and so we can spend a lot less time programming and debugging. (even writing CUDA subroutines is easier!) I mean pytorch is basically numpy but with GPU access so it is fantastic for any optimization, even non ml. I haven't played around with JAX but I hear it is better for more statistical stuff because of this.