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Apple's MLX adding CUDA support

(github.com)
548 points nsagent | 1 comments | 14 Jul 25 21:40 UTC | HN request time: 0.474s | source
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albertzeyer ◴[14 Jul 25 22:59 UTC] No.44566290[source]▶
This is exciting. So this is using unified memory of CUDA? I wonder how well that works. Is the behavior of the unified memory in CUDA actually the same as for Apple silicon? For Apple silicon, as I understand, the memory is anyway shared between GPU and CPU. But for CUDA, this is not the case. So when you have some tensor on CPU, how will it end up on GPU then? This needs a copy somehow. Or is this all hidden by CUDA?
replies(3): >>44566325 #>>44566412 #>>44571076 #
1. ethan_smith ◴[15 Jul 25 13:40 UTC] No.44571076[source]▶
CUDA's Unified Memory uses page migration with on-demand faulting to create the illusion of shared memory, whereas Apple Silicon has true shared physical memory, resulting in different performance characteristics despite the similar programming model.