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Scheduling overhead

The fixed cost of dispatching a task and returning its result. When it approaches the cost of the task body, adding parallelism stops helping.

A fixed cost per task, which is why task size matters more than task count. A task taking a millisecond spends most of its life being scheduled; batching a hundred of them into one changes the ratio decisively.

Performance & optimizationDistributed compute

Related terms

  • Batching: Grouping several small units of work into one task so that scheduling overhead does not dominate the time spent doing useful work.
  • Partition: One independently processable chunk of a dataset. Partition size is the main lever on how well a workload parallelizes.
  • Scheduler: The component on the head node that decides which compute node runs each task, honoring the resources that task requested.
  • Speedup: How many times faster a distributed run is than the same work on one worker. Ideal speedup equals worker count; real speedup falls short of it.