mirror of https://github.com/commaai/tinygrad.git
18 lines
536 B
Python
18 lines
536 B
Python
import time
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import torch
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for dtype in [torch.float16, torch.float32]:
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for N in [256, 512, 1024, 2048, 4096]:
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FLOPS = N*N*N*2
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b = torch.rand((N,N), dtype=dtype).cuda()
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c = torch.rand((N,N), dtype=dtype).cuda()
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def torch_prog(b, c):
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st = time.perf_counter()
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a = b@c
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torch.cuda.synchronize()
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return time.perf_counter() - st
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tm = min([torch_prog(b, c) for _ in range(20)])
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print(f"{N*N:10d} {tm*1e6:9.2f} us, would be {FLOPS*1e-9/tm:9.2f} GFLOPS {N:4d}x{N:4d}x{N:4d} matmul in {dtype}")
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