Pollack's Rule
Updated 2026-08-05
INTRODUCTION
English translation pending.
CORE DEFINITION
An empirical observation in computer architecture, attributed to Fred Pollack, holding that the performance gain from adding complexity to a processor scales with the square root of the increase in transistor count. Doubling the resources therefore yields far less than double the performance, because added transistors mainly buy parallelism and cache whose benefit is limited by communication, synchronization, and power. The core claim is that complexity has sublinear returns. The qualification is that the rule is a rough empirical tendency rather than a physical law.
SCAFFOLDING EFFECT
Reduce cognitive load
- Use Return Estimate: Predict the square-root return before approving any addition of complexity. - Use Cost Comparison: Stop adding layers once the marginal gain falls below the cost of maintaining them. - Use Structural Fix: Choose architectural redesign or a better algorithm over simply adding more parts.
Anchor fast decisions
Additional transistors mostly buy more parallel units and larger caches, but the benefit of parallelism is limited by how much work can be split and by the cost of coordinating the pieces. Communication, synchronization, and heat removal consume a growing share of the gain, so each doubling delivers less than the one before. The result is a sublinear relationship between complexity and performance, which is why further investment in the same structure eventually stops paying.
MINIMUM ACTION
In progress 0/1Practice this model in one real situation:
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Source support: Explicit
- en.wikipedia.orghttps://en.wikipedia.org/wiki/Pollack's_ruleverified
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