I'm Jules.

With recent algorithmic improvements and easy-to-use libraries, equality saturation is being picked up for hardware design, program synthesis, theorem proving, program optimization, and more. Existing work on using equality saturation for program optimization makes use of external equality saturation libraries such as egg, typically generating a single optimized expression. In the context of a compiler, such an approach uses equality saturation to replace a small number of passes. In this work, we propose an alternative approach that represents equality saturation natively in the compiler’s intermediate representation, facilitating the application of constructive compiler passes that maintain the e-graph state throughout the compilation flow. We take LLVM’s MLIR framework and propose a new MLIR dialect named eqsat that represents e-graphs in MLIR code. This not only provides opportunities to rethink e-matching and extraction techniques by orchestrating existing MLIR passes, such as common subexpression elimination, but also avoids translation overhead between the chosen e-graph library and MLIR. Our eqsat intermediate representation (IR) allows programmers to apply equality saturation on arbitrary domain-specific IRs using the same flow as other compiler transformations in MLIR.

Compilers are indispensable for transforming code written in high-level languages into performant machine code, but their general-purpose optimizations sometimes fall short. Domain experts might be aware of certain optimizations that the compiler is unable to apply or that are only valid in a particular domain. We have developed a system that allows domain experts to express rewrite rules to optimize code in the Julia programming language. Our system builds on e-graphs and equality saturation. It can apply optimizations in the presence of control flow and side effects. As Julia uses multiple dispatch, we allow users to constrain rewrite rules by argument types, and propagate type information through the e-graph representation. We propose an ILP formulation for optimal e-graph extraction taking into account dominance properties for code reuse and introduce CFG skeleton relaxation to rewrite calls to pure functions as well as those with side effects. Use cases demonstrate that our system can perform rewrites on high-level, domain-specific code, as well as on lower-level code such as Julia's broadcasting mechanism. Finally, we analyze the required compilation time.