Proceedings of the ACM on Programming Languages· 2026Q1
Efficient Extraction for Effectful E-graphs
- 1citations
- Q1SCImago
- 2026year
Short summary
Statewalk DP, a new algorithm, extracts effect-aware programs from e-graphs efficiently without external solvers, achieving order-of-magnitude speedups over ILP methods.
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Key points
- Introduces Statewalk DP, an algorithm for effect-aware program extraction from e-graphs.
- Statewalk DP enforces effect ordering without relying on external solvers like ILP.
- The algorithm's tractability depends on 'statewalk width,' which is typically small in practice.
- Achieves order-of-magnitude speedups compared to ILP extraction methods.
- Implemented in EGGCC for imperative Bril programs, showing no longer a compilation bottleneck.
AI-generated from the title and abstract; the full text is not read.
Abstract
E-Graphs have enabled recent advances in program optimization, synthesis, and verification, yet remain difficult to apply to effectful programs whose memory and I/O operations must respect execution order. Existing effect-aware extraction algorithms rely on integer linear programming (ILP) and dominate total runtime. We introduce Statewalk DP, a new extraction algorithm that enforces effect ordering efficiently without external solvers. We prove that finding any effect-safe extraction is NP-complete, but show that Statewalk DP is tractable in statewalk width, a parameter that measures the complexity of dataflow interactions among effects. In practice, statewalk width generally remains small, enabling Statewalk DP to achieve order-of-magnitude speedups over ILP extraction while producing programs comparable to LLVM across our benchmarks. We implement the algorithm in EGGCC, a prototype e-graph-based compiler for imperative Bril programs, and demonstrate that effect-aware extraction is no longer a bottleneck.
The authors' abstract, as published at the source. Proceedings of the ACM on Programming Languages, 2026 · DOI ↗
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Field: Hardware and Architecture
Hardware and ArchitectureComputer Science