用e图综合数学恒等式

Ian Briggs, P. Panchekha
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引用次数: 1

摘要

恒等式简洁地描述了数学表达式的属性,可以用于更快、更准确的函数实现。然而,目前必须手动发现身份,这需要大量的专业知识。我们提出了一个自动发现这些身份的两阶段合成和重复数据删除管道。在综合步骤中,使用电子图组成一组重写规则,以发现候选身份。然而,这些候选项中的大多数都是重复项,二级重复项删除步骤使用整数线性规划和另一个e-图来丢弃它们。将合成阶段应用于一组61个基准测试,生成7215个候选身份,然后重复数据删除阶段将其减少到125个核心身份。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Synthesizing mathematical identities with e-graphs
Identities compactly describe properties of a mathematical expression and can be leveraged into faster and more accurate function implementations. However, identities must currently be discovered manually, which requires a lot of expertise. We propose a two-phase synthesis and deduplication pipeline that discovers these identities automatically. In the synthesis step, a set of rewrite rules is composed, using an e-graph, to discover candidate identities. However, most of these candidates are duplicates, which a secondary de-duplication step discards using integer linear programming and another e-graph. Applied to a set of 61 benchmarks, the synthesis phase generates 7215 candidate identities which the de-duplication phase then reduces down to 125 core identities.
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