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Practical Boolean Decomposition for Delay-driven LUT Mapping

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arxiv 2406.06241 v1 pith:RHQYP3KO submitted 2024-06-10 cs.LO

classification cs.LO
keywords decompositiondelaymappingdelay-drivenlutstechniquetimeadditionally
verification ladder T0 review T1 audit T2 compute T3 formal
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Ashenhurst-Curtis decomposition (ACD) is a decomposition technique used, in particular, to map combinational logic into lookup tables (LUTs) structures when synthesizing hardware designs. However, available implementations of ACD suffer from excessive complexity, search-space restrictions, and slow run time, which limit their applicability and scalability. This paper presents a novel fast and versatile technique of ACD suitable for delay optimization. We use this new formulation to compute two-level decompositions into a variable number of LUTs and enhance delay-driven LUT mapping by performing ACD on the fly. Compared to state-of-the-art technology mapping, experiments on heavily optimized benchmarks demonstrate an average delay improvement of 12.39%, and area reduction of 2.20% with affordable run time. Additionally, our method improves 4 of the best delay results in the EPFL synthesis competition without employing design-space exploration techniques.

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  1. DeepCell: Self-Supervised Multiview Fusion for Circuit Representation Learning

    cs.LG 2025-02 conditional novelty 6.0 of 10

    DeepCell fuses AIG and post-mapping netlist views with masked autoencoding, achieving 2.77% lower ECO patch cost and 15-16% lower area-delay product in technology mapping.

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