Work-in-progress report proposing a lattice-based set-theoretic model for context-sensitive rewrites in relational equality saturation, with case studies in query optimization, conditionals, and lambda applications.
Optimizing Stateful Dataflow with Local Rewrites
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abstract
Optimizing a stateful dataflow language is a challenging task. There are strict correctness constraints for preserving properties expected by downstream consumers, a large space of possible optimizations, and complex analyses that must reason about the behavior of the program over time. Classic compiler techniques with specialized optimization passes yield unpredictable performance and have complex correctness proofs. But with e-graphs, we can dramatically simplify the process of building a correct optimizer while yielding more consistent results! In this short paper, we discuss our early work using e-graphs to develop an optimizer for a the Hydroflow dataflow language. Our prototype demonstrates that composing simple, easy-to-prove rewrite rules is sufficient to match techniques in hand-optimized systems.
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cs.PL 1years
2025 1verdicts
CONDITIONAL 1representative citing papers
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Towards Relational Contextual Equality Saturation
Work-in-progress report proposing a lattice-based set-theoretic model for context-sensitive rewrites in relational equality saturation, with case studies in query optimization, conditionals, and lambda applications.