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tinygrad/docs/nvidia_notes
George Hotz 1ae0e88627 nvidia notes
2021-05-26 14:27:00 -07:00

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A100 has 432 tensor cores
8x4x8 FP16 matmul = 256 FMAs
8x4x4 TF32 matmul = 128 FMAs
432 * 256 * 1410 mhz * 2(m and a) = 312 TOPS
Why aren't the other accelerators 3D like this?
--
SNPE is using 4x4x4 -> 4x4 (64 FMAs) in the convs.
Then it's accumulating in that matrix.
256 ALUs (1 FMA per cycle)
652 mhz
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319 GFLOPS