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Autores principales: Coward, Samuel, Drane, Theo, Constantinides, George A.
Formato: Preprint
Publicado: 2024
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Acceso en línea:https://arxiv.org/abs/2406.12421
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author Coward, Samuel
Drane, Theo
Constantinides, George A.
author_facet Coward, Samuel
Drane, Theo
Constantinides, George A.
contents 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 implementations. By applying rewrites to this data structure, ROVER generates a set of efficient and functionally equivalent design options. From the ROVER generated e-graph we select an efficient implementation. To accurately model the circuit area we develop a theoretical cost metric and then an integer linear programming model to extract the optimal implementation. To build trust in the generated design ROVER also produces a back-end verification certificate that can be checked using industrial tools. We apply ROVER to both Intel-provided and open-source benchmarks, and see up to a 63% reduction in circuit area. ROVER is also able to generate a customized library of distinct implementations from a given parameterizable RTL design, improving circuit area across the range of possible instantiations.
format Preprint
id arxiv_https___arxiv_org_abs_2406_12421
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle ROVER: RTL Optimization via Verified E-Graph Rewriting
Coward, Samuel
Drane, Theo
Constantinides, George A.
Hardware Architecture
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 implementations. By applying rewrites to this data structure, ROVER generates a set of efficient and functionally equivalent design options. From the ROVER generated e-graph we select an efficient implementation. To accurately model the circuit area we develop a theoretical cost metric and then an integer linear programming model to extract the optimal implementation. To build trust in the generated design ROVER also produces a back-end verification certificate that can be checked using industrial tools. We apply ROVER to both Intel-provided and open-source benchmarks, and see up to a 63% reduction in circuit area. ROVER is also able to generate a customized library of distinct implementations from a given parameterizable RTL design, improving circuit area across the range of possible instantiations.
title ROVER: RTL Optimization via Verified E-Graph Rewriting
topic Hardware Architecture
url https://arxiv.org/abs/2406.12421