Empirical comparison of equality saturation versus stochastic search on five benchmarks to evaluate if e-graphs are superior for rewrite-based optimization.
Optimism in Equality Saturation
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abstract
Equality saturation is a program optimization technique based on non-destructive rewriting and a form of abstract interpretation called e-class analysis. Existing e-class analyses are pessimistic and therefore typically imprecise when analyzing cyclic programs, such as those in SSA form. We show that a straightforward optimistic variant of e-class analysis can result in unsoundness, due to a subtlety in how e-graphs represent programs. We propose an abstract interpretation algorithm that circumvents this issue and can optimistically analyze e-graphs during equality saturation. This results in a unified algorithm for optimistic analysis and non-destructive rewriting. We implement a prototype abstract interpreter and equality saturation tool for SSA programs. Our tool exhibits precision improvements over pure abstract interpretation (without rewriting) and pessimistic e-class analysis on example programs. Additionally, its performance is comparable to existing abstract interpretation and e-class analysis techniques.
fields
cs.PL 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
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Rewrite System Showdown: Stochastic Search vs. EqSat
Empirical comparison of equality saturation versus stochastic search on five benchmarks to evaluate if e-graphs are superior for rewrite-based optimization.