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That's not going to work because each GPU has a different internal architecture and aligning the way data is fed with how stream processors operate is different
by treprinum 3y ago
That's not going to work because each GPU has a different internal architecture and aligning the way data is fed with how stream processors operate is different for each architecture (stuff like how memory buffers are organized/aligned/paged etc.). AMD is very incompatible to Nvidia at the lowest level so things/approaches that are fast on Nvidia can be 10x slower on AMD and vice versa.
- dheera 3y ago> things/approaches that are fast on Nvidia can be 10x slower on AMD and vice versa. That's fine but the job of software is to abstract that out. The code should at least compile, even if it is 10x less efficient and if multiple awkward sets of instructions need to be used instead of one. If Pytorch can be recompiled for AMD overnight with zero effort (only `ln -s amdcc nvcc`, `ln -s /usr/local/cuda /usr/local/amda`) they will gain some footing against Nvidia.