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H100 peak matmul FLOPS
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import torch | |
from triton.testing import do_bench | |
import torch._inductor.config as config | |
config.max_autotune_gemm_backends = "cutlass" | |
torch.set_default_device('cuda') | |
a = torch.randn(4224, 8192, dtype=torch.bfloat16) | |
b = torch.randn(2048, 8192, dtype=torch.bfloat16).t() | |
def get_flops(f): | |
ms = do_bench(f, warmup=100, rep=10000) | |
print(ms) | |
print((1e3/ms) * a.shape[0] * a.shape[1] * b.shape[1] * 2 / 1e12, 'TF') | |
f = lambda: torch.mm(a, b) | |
f = torch.compile(f, mode="max-autotune-no-cudagraphs") | |
# Also set `sudo nvidia-smi boost-slider --vboost 1`, which shifts more power from l2 cache to tensor cores | |
get_flops(f) # 780.1689058368037 TF |
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