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fix(macrobenchmarks): use random optimizer moments, not zeros, in CPU sim #949

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Merged
zhixiangli merged 1 commit into from
Jul 3, 2026
Merged

fix(macrobenchmarks): use random optimizer moments, not zeros, in CPU sim #949

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11 changes: 8 additions & 3 deletions ...erf/macrobenchmarks/workloads/hf-pytorch-lightning-cpu/helm_chart/llama_3_1_8b_cpu_sim.py
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Original file line number Diff line number Diff line change
Expand Up @@ -252,15 +252,20 @@ def _materialize_adamw_state(optimizer):
state = optimizer.state[p]
if state:
continue
# Random, not zero: an all-zero buffer is trivially compressible/
# dedupable (page merging, a future transport compression layer,
# etc.), which would let this ~2/3 of the checkpoint transfer
# faster than the real, non-degenerate floats a trained
# optimizer actually produces -- skewing the IO benchmark.
state["step"] = torch.zeros((), dtype=torch.float32)
state["exp_avg"] = torch.zeros_like(
state["exp_avg"] = torch.randn_like(
p, memory_format=torch.preserve_format
)
state["exp_avg_sq"] = torch.zeros_like(
state["exp_avg_sq"] = torch.rand_like(
p, memory_format=torch.preserve_format
)
if group["amsgrad"]:
state["max_exp_avg_sq"] = torch.zeros_like(
state["max_exp_avg_sq"] = torch.rand_like(
p, memory_format=torch.preserve_format
)

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