*PHDD:浮点电路验证的有效图形表示

Yirng-An Chen, R. Bryant
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引用次数: 46

摘要

像* bmd、hdd和K* bmd这样的数据结构为将布尔向量映射为整数值而不是浮点值的函数提供了紧凑的表示。我们提出了一种新的数据结构,称为乘法幂混合决策图(* phdd),为将布尔向量映射为整数或浮点值的函数提供了一种紧凑的表示。表示IEEE浮点编码的图形的大小与字长呈线性关系。浮点乘法的复杂度随着字长呈线性增长。浮点加法的复杂度随指数部分的大小呈指数增长,而随尾数部分的大小呈线性增长。基于层次验证方法,我们在舍入阶段之前应用*博士来验证整数乘数和浮点乘数。对于整数乘法器,我们的结果至少比* bmd快6倍。以前验证浮点乘数的尝试需要人工干预。我们在舍入阶段之前自动验证浮点乘数。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
*PHDD: an efficient graph representation for floating point circuit verification
Data structures such as *BMDs, HDDs, and K*BMDs provide compact representations for functions which map Boolean vectors into integer values, but not floating point values. We propose a new data structure, called Multiplicative Power Hybrid Decision Diagrams (*PHDDs), to provide a compact representation for functions that map Boolean vectors into integer or floating point values. The size of the graph to represent the IEEE floating point encoding is linear with the word size. The complexity of floating point multiplication grows linearly with the word size. The complexity of floating point addition grows exponentially with the size of the exponent part, but linearly with the size of the mantissa part. We applied *PHDDs to verify integer multipliers and floating point multipliers before the rounding stage, based on a hierarchical verification approach. For integer multipliers, our results are at least 6 times faster than *BMDs. Previous attempts at verifying floating point multipliers required manual intervention. We verified floating point multipliers before the rounding stage automatically.
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