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I wrote that the usage of PyTorch is much higher than bare cuda, not making a claim that one is better than the other. Obviously you can use cuda to write more
by gumby 3y ago
I wrote that the usage of PyTorch is much higher than bare cuda, not making a claim that one is better than the other.
Obviously you can use cuda to write more than ML algos, but that’s its overwhelming use case.
Thus my point is if AMD ported PyTorch to their hardware (and PT is not cuda-only) it would create a more level playing field on which they could compete (in a cousin vs cousin battle) by eliminating the switching cost for the majority of developers.
This is the same reason cpu mfrs have compiler ports but generally don’t have to worry about instruction set level compatibility.
- godelski 3y agoBut you also suggested that cuda is less critical. But there's so much that is dependent on cuda, even if it is directly visible. You're right, that if AMD does fully integrate into Pytorch, something they've been working on btw, then yes this will be a big step up for AMD as ML is one of the biggest sectors. But it's important to realize that this is not as easy of a task as it sounds. They have been working on this for years and every step of the way Nvidia is still improving too.
- weebull 3y ago> Thus my point is if AMD ported PyTorch to their hardware (and PT is not cuda-only) it would create a more level playing field on which they could compete It is ported (I think by AMD). I use it daily. Biggest problem is that the people maintaining PyTorch aren't very interested as they don't use it themselves. Hence there are silly bugs in it. Users contribute fixes and they get closed down as "unsupported" or get plain misunderstood.