首页> 外文会议>Design Automation, 1995. DAC '95. 32nd Conference on >A Method for Finding Good Ashenhurst Decompositions and Its Application to FPGA Synthesis
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A Method for Finding Good Ashenhurst Decompositions and Its Application to FPGA Synthesis

机译:寻找良好Ashenhurst分解的方法及其在FPGA综合中的应用

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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.
机译:在本文中,我们提出了一种用于寻找开关函数的良好Ashenhurst分解的算法。当前执行这种类型分解的大多数方法都是基于Roth-Karp算法。此处提出的算法基于找到BDD中的最佳切割。该算法与以前的分解算法的不同之处在于,剪切确定了边界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。我们已将此方法应用于将函数分解为k个变量函数的集合。当使用基于查找表(LUT)的FPGA实现功能时,这是必需的步骤。结果与Roth-Karp分解方法的现有实现相比非常有利。

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