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I think the flops comparison you’ve presented is not fair: for nvidia it is “tensor” floops, not generic float multiplication (which is 10 times smaller), while
by asteroidbelt 5y ago
I think the flops comparison you’ve presented is not fair: for nvidia it is “tensor” floops, not generic float multiplication (which is 10 times smaller), while for intel it is any float multiplication.
So for i9 the number would be higher if fma operations used, no?
- programmer_dude 5y agoTensor flops is significant since this is exactly the use case for which it was designed. So IMO the comparison is fair.
- deleted 5y ago[deleted]
- asteroidbelt 5y agoIt doesn’t make sense. Why it is fair to compare matrix multiplication with generic float operations? It should be either comparison of matrix multiplication to matrix multiplication or generic float to generic float.
- etaioinshrdlu 5y agoWell, one confounding factor is that CPU Flops are more generic, for any algorithm. GPU Flops as mentioned work better on tensor cases. However, when we do have tensors, the GPU and CPU would both work to their full potential, and thus the flops comparison ought to be valid.