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T⋆=2 C MT^\star = \sqrt{2\,C\,M}

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which is minimized at T⋆=2 C MT^\star = \sqrt{2\,C\,M}. Two consequences follow directly, and both are visible in how production systems have actually evolved. First, because M for a job shrinks roughly in proportion to the number of components that can fail — more GPUs, more NICs, more power supplies, more chances for any one of them to fault — the optimal interval T⋆T^\star shrinks with cluster scale, roughly as the square root of the failure rate. Second, the only way to hold T⋆T^\star low as M falls is to drive C , the checkpoint write cost itself, down; otherwise the optimum forces either constant checkpointing overhead or unacceptable recomputation loss.

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T⋆=2 C M.T^\star = \sqrt{2\,C\,M}.

Equation 11 · Datacenters

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This equation states an equality: the expressions on both sides have the same value under the article’s assumptions.

which is minimized at T⋆=2 C MT^\star = \sqrt{2\,C\,M}. Two consequences follow directly, and both are visible in how production systems have actually evolved. First, because M for a job shrinks roughly in proportion to the number of components that can fail — more GPUs, more NICs, more power supplies, more chances for any one of them to fault — the optimal interval T⋆T^\star shrinks with cluster scale, roughly as the square root of the failure rate. Second, the only way to hold T⋆T^\star low as M falls is to drive C , the checkpoint write cost itself, down; otherwise the optimum forces either constant checkpointing overhead or unacceptable recomputation loss.

Meanings in this article

  • CC: the wall-clock cost of writing one checkpoint and M be the job’s mean time between failures.
  • MM: the because.
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