寻优Ashenhurst分解方法及其在FPGA合成中的应用

T. Stanion, C. Sechen
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引用次数: 24

摘要

在本文中,我们提出了一种寻找切换函数的良好Ashenhurst分解的算法。目前执行这类分解的大多数方法都是基于Roth-Karp算法。本文提出的算法是基于在BDD中找到最优切割。该算法与以往的分解算法的不同之处在于,切割决定了约束集和自由集的大小和组成。其他方法检查任意大小的所有可能的边界集。我们已经将这种方法应用于将函数分解为k变量函数的集合。当使用基于查找表(LUT)的FPGA实现函数时,这是必需的步骤。结果与现有的Roth-Karp分解方法的实现相比非常有利。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Method for Finding Good Ashenhurst Decompositions and Its Application to FPGA Synthesis
In this paper, we present an algorithm for finding a good Ashenhurst decomposition of a switching function. Most current methods for performing this type of decomposition are based on the Roth-Karp algorithm. The algorithm presented here is based on finding an optimal cut in a BDD. This algorithm differs from previous decomposition algorithms in that the cut determines the size and composition of the bound set and the free set. Other methods examine all possible bound sets of an arbitrary size. We have applied this method to decomposing functions into sets of k-variable functions. This is a required step when implementing a function using a lookup table (LUT) based FPGA. The results compare very favorably to existing implementations of Roth-Karp decomposition methods.
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