# 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.

Source: https://university.eugo.io/glossary/speedup

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The gap comes from scheduling overhead, uneven partitions, serialization, and shared resources like object storage.

## Related terms

- [Scheduling overhead](https://university.eugo.io/glossary/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.
- [Long tail](https://university.eugo.io/glossary/long-tail) — The situation where most tasks finish quickly but one or two run much longer, so the whole run waits on them while workers sit idle.
- [Compute-bound](https://university.eugo.io/glossary/compute-bound) — A workload whose runtime is limited by how fast calculations can be performed. Adding workers to a compute-bound job generally makes it finish sooner.