Why it matters

Reproducibility matters for science + debugging. Understanding shapes ML process.

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The architecture

Sources: parallel reductions, atomics, cuDNN algorithms.

Deterministic mode: forces specific algorithms.

GPU reproducibilitySourcesreductions + atomicsDeterministic modetorch.use_deterministic_algorithms(True)Trade-offslower trainingFull determinism sometimes 2x slower; use for debugging + final runs
Reproducibility trade-off.
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How it works end to end

PyTorch: torch.use_deterministic_algorithms(True).

Seeds: numpy, torch, random.

cuDNN: benchmark=False, deterministic=True.

Cost: 20-100% slower.