IQ.Pilot Release Commit @ bec7652
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#!/usr/bin/env python3
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from tinygrad import Tensor, Device, GlobalCounters, Context, dtypes
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from tinygrad.helpers import getenv, colored
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SZ = 8_000_000_000
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GPUS = getenv("GPUS", 4) # TODO: expose a way in tinygrad to access this
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if __name__ == "__main__":
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# create tensors
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tens = [Tensor.ones(SZ, dtype=dtypes.uint8, device=f"{Device.DEFAULT}:{i}").contiguous() for i in range(GPUS)]
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Tensor.realize(*tens)
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bw = [[0.0]*GPUS for _ in range(GPUS)]
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for i in range(GPUS):
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for j in range(GPUS):
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GlobalCounters.reset()
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with Context(DEBUG=2):
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if i == j:
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# this copy would be optimized out, just add 1
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(tens[i]+1).realize()
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else:
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tens[i].to(f"{Device.DEFAULT}:{j}").realize()
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t = max(GlobalCounters.time_sum_s, 1e-9)
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bw[i][j] = SZ / t / 1e9 # GB/s
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def fmt(x):
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c = "green" if x > 50 else "yellow" if x > 20 else "red"
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return colored(f"{x:6.1f}", c)
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# header
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print(" " * 8 + " ".join(f"{'d'+str(j):>6}" for j in range(GPUS)))
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# rows
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for i in range(GPUS):
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print(f"{'s'+str(i):>6} -> " + " ".join(fmt(x) for x in bw[i]))
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15
artifacts/package_sources/tinygrad/examples/tools/gpuburn.py
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15
artifacts/package_sources/tinygrad/examples/tools/gpuburn.py
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from tinygrad import Tensor, Device, TinyJit, dtypes
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GPUS = Device[Device.DEFAULT].count()
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N = 6144
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@TinyJit
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def many_matmul(A, B):
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out = A
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for _ in range(8): out = out@B
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return out
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if __name__ == "__main__":
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A = Tensor.ones(GPUS, N, N, dtype=dtypes.half).shard(devices=tuple([f"{Device.DEFAULT}:{i}" for i in range(GPUS)]), axis=0).contiguous()
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B = Tensor.ones(GPUS, N, N, dtype=dtypes.half).shard(devices=tuple([f"{Device.DEFAULT}:{i}" for i in range(GPUS)]), axis=0).contiguous()
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while 1: many_matmul(A, B)
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