ROVER: RTL Optimization via Verified E-Graph Rewriting
Samuel Coward, Theo Drane, George A. Constantinides

TL;DR
ROVER automates RTL datapath optimization by using verified e-graph rewriting, enabling efficient exploration of equivalent design variants and achieving significant area reduction.
Contribution
It introduces a novel e-graph based framework for automated, verified RTL optimization that improves design efficiency and provides optimal implementation selection.
Findings
Up to 63% reduction in circuit area.
Automated generation of multiple optimized design variants.
Validated with industrial and open-source benchmarks.
Abstract
Manual RTL design and optimization remains prevalent across the semiconductor industry because commercial logic and high-level synthesis tools are unable to match human designs. Our experience in industrial datapath design demonstrates that manual optimization can typically be decomposed into a sequence of local equivalence preserving transformations. By formulating datapath optimization as a graph rewriting problem we automate design space exploration in a tool we call ROVER. We develop a set of mixed precision RTL rewrite rules inspired by designers at Intel and an accompanying automated validation framework. A particular challenge in datapath design is to determine a productive order in which to apply transformations as this can be design dependent. ROVER resolves this problem by building upon the e-graph data structure, which compactly represents a design space of equivalent…
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Taxonomy
TopicsSemantic Web and Ontologies · Graph Theory and Algorithms · Advanced Database Systems and Queries
