Gustafson's Law
Version 1.0.0 · Updated 2026-07-30
CORE DEFINITION
Contrary to Amdahl's law, if the problem size can scale with the number of processors, the effect of parallel computing can improve linearly.
SCAFFOLDING EFFECT
Reduce cognitive load
Scalable thinking. When a problem is decomposable and its size is variable, adding resources can yield linear benefits. This explains why big data processing can scale indefinitely.
Anchor fast decisions
Contrary to Amdahl's emphasis that 'fixed tasks have limited speedup', Gustafson points out that if the task size scales with resources (e.g., big data), the total completion time can decrease nearly linearly with parallelism, and the speedup depends on the proportion of the scalable part.
MINIMUM ACTION
In progress 0/5Practice this model in one real situation:
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Source support: Explicit
- en.wikipedia.orghttps://en.wikipedia.org/wiki/Gustafson%27s_lawverified
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