用于高级综合的算术表达式的结构优化

Xitong Gao, Samuel Bayliss, G. Constantinides
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引用次数: 18

摘要

本文介绍了SOAP,它是一种新的工具,可以自动优化FPGA实现的算术表达式结构,作为高级综合流程的一部分,它考虑了来自实际算术的公理规则,如分布性、结合性等。我们明确地以优化的面积/精度权衡为目标,允许为此目的自动重写算术表达式。第一次,我们从软件静态分析中引入了严格的方法,特别是形式语义和抽象解释,来承担高层次合成的源到源转换。提出了新的抽象语义,从原始表达式生成等价表达式的可计算子集。利用形式语义,我们计算了FPGA的计算精度和资源利用率两个目标。这些目标的优化产生由一组表达式组成的帕累托边界。这使合成工具能够灵活地选择满足准确性和资源使用约束的实现。因此,我们超越了现有的文献,不仅优化了实现的精度要求,而且改变了实现本身的结构。使用我们的工具在单个精度下优化各种真实世界和人工生成的示例的结构,我们提高了它们的准确性或资源利用率高达60%。
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SOAP: Structural optimization of arithmetic expressions for high-level synthesis
This paper introduces SOAP, a new tool to automatically optimize the structure of arithmetic expressions for FPGA implementation as part of a high level synthesis flow, taking into account axiomatic rules derived from real arithmetic, such as distributivity, associativity and others. We explicitly target an optimized area/accuracy trade-off, allowing arithmetic expressions to be automatically re-written for this purpose. For the first time, we bring rigorous approaches from software static analysis, specifically formal semantics and abstract interpretation, to bear on source-to-source transformation for high-level synthesis. New abstract semantics are developed to generate a computable subset of equivalent expressions from an original expression. Using formal semantics, we calculate two objectives, the accuracy of computation and an estimate of resource utilization in FPGA. The optimization of these objectives produces a Pareto frontier consisting of a set of expressions. This gives the synthesis tool the flexibility to choose an implementation satisfying constraints on both accuracy and resource usage. We thus go beyond existing literature by not only optimizing the precision requirements of an implementation, but changing the structure of the implementation itself. Using our tool to optimize the structure of a variety of real world and artificially generated examples in single precision, we improve either their accuracy or the resource utilization by up to 60%.
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