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Simulating fault tolerance with stage skipping in pipeline-parallel training [R]

AI 摘要

Templar's recent work explores fault tolerance in Crucible, their distributed pre-training platform, aiming to maintain training with healthy workers when a pipeline stage fails. Simulations with a 178M model, eight replicas, and four stages per replica showed that a 1% per-replica failure probability per global step, where each outage removed a stage for six global steps, resulted in validation loss staying close to the no-failure baseline. Each configuration was compared against its own no-failure run.

为什么是这条

This report uniquely details how Templar's simulations, unlike prior work, specifically test fault tolerance by skipping stages with fixed projections.

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2026年9月22日 23:01
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