On the Optimization of Equivalent Concurrent Computations

TL;DR

This paper introduces a novel approach using extended e-graphs to optimize concurrent computations by identifying and merging equivalent subcomputations, a capability not present in existing equality saturation frameworks.

Contribution

It extends equality saturation techniques to handle concurrent environments, enabling optimization of equivalent concurrent computations through non-local reasoning.

Findings

First framework to optimize concurrent computations via equality saturation.

Successfully merges equivalent concurrent subcomputations.

Provides a new method for optimizing parallel code.

Abstract

In this submission, we explore the use of equality saturation to optimize concurrent computations. A concurrent environment gives rise to new optimization opportunities, like extracting a common concurrent subcomputation. To our knowledge, no existing equality saturation framework allows such an optimization. The challenge with concurrent environments is that they require non-local reasoning since parallel computations are inherently unrelated and disjoint. This submission presents a new approach to optimizing equivalent concurrent computations: extending e-graphs to capture equal concurrent computations in order to replace them with a single computation.