The Definitive Guide toAI Data Centers
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Checkpoint overlap (share of training time with a background checkpoint drain running): nearly every one of 40 production runs kept its median under 10% in VAST's analysis, and VAST sizes global checkpoint bandwidth on 10%

10% overlapobserved

Value kindobserved — Reported measurements, counts, and specifications keep the precision and scope stated by their source; an exact specification is not treated as a range.
ScopeVAST defines overlap as the fraction of training time during which background checkpoint I/O is running; its 800B-parameter example (3.6-minute median drain on a 40-minute interval) comes to about 9%. Across 40 runs on more than 1,024 GPUs, almost every run kept median overlap under 10%, and VAST concludes 10% is sufficient for its sizing model. The figure describes those runs; a project's drain window still comes from its own state-age, pause and commit limits.
As of2025
SourceVAST Data, 'Optimizing Checkpoint Bandwidth for LLM Training' (overlap results and sizing model)
Reviewchecking…review by 2027-04-20 · standard cadence
Recorded changeslast 2026-10-19 · 2 revisions tracked
Claim idcheckpoint-vs-compute-overlap-target-found

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