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Generation of tightly controlled equivalence classes for experimental design of heuristics for graph-based NP-hard problems.

机译:严格控制的等效类的生成,用于基于图的NP-hard问题的启发式实验设计。

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Computer-aided design (CAD) of VLSI circuits relies on heuristics that optimize cost functions related to a graph model of a circuit. Since the problems are typically NP-hard, the quality of solutions can vary significantly. The current methodology to evaluate the performance of such heuristics is not at the level of experimental design that is the norm in disciplines such as bio-medical sciences and others. A major impediment is the lack of well-defined equivalence classes of circuits. Comparison of two heuristics based on a number of unrelated, single instances of circuits is flawed—it can be shown that any incremental improvements that are observed may well be offset by variations induced by a number of isomorphic instances of the same circuit.; The goal of this thesis is to introduce a method to synthesize, for any reference circuit, a well-defined and tightly controlled circuit class to support experimental design methodology for problems such as partitioning, placement, and routing. Each member of the class must be sufficiently ‘close’ to its reference circuit: if the reference is a multiplier, all circuits in the class should have a multiplier-like structure. Such tight control has not been achieved in earlier research. Characterizations such as the same number of vertices and nets (hyperedges), the same number of levels, the same Rent's exponent are necessary but not sufficient. The control that we need is achieved by characterizing the graph in terms of a well-defined order. Significantly, we demonstrate that an equivalent characteristic graph ordering can be achieved by minimizing any of the following cost functions: (1) crossing number, (2) netspan number, or (3) cellspan number. This brings out the difficulty of the characterization problem: finding such an order is NP-hard.; We address the ordering problem of the reference graph G with an effective heuristic that finds the order of the characteristic spanning tree st(G) and show that the crossing number of G and st(G) are tightly correlated for graphs that represent typical VLSI circuits. The characteristic signature of the graph now includes the order of the spanning tree and the netspan number corresponding to this order.; We develop a synthesis method such that each member of the circuit class, a sibling, satisfies this signature. Siblings retain all significant characteristics of their reference circuit. We demonstrate the scalability of the proposed approach through a number of experiments. The sibling classes are shown to have results within ±(4–9)% of the parent circuit—under all physical design tools at our disposal.
机译:VLSI电路的计算机辅助设计(CAD)依赖于启发式算法,该启发式算法可优化与电路图形模型相关的成本函数。由于问题通常是NP难题,因此解决方案的质量可能会有很大差异。当前评估此类启发式方法性能的方法还没有达到实验设计的水平,该水平是诸如生物医学科学等学科的规范。一个主要障碍是缺乏明确定义的等效电路类别。基于多个不相关的单个电路实例的两种启发式方法的比较存在缺陷-可以证明,观察到的任何增量改进都可能被同一电路的多个同构实例引起的变化所抵消。本文的目的是为任何参考电路引入一种综合方法,该方法定义明确并受到严格控制,以支持针对分区,布局和布线等问题的实验设计方法。该类的每个成员必须充分“接近”其参考电路:如果参考是一个乘法器,则该类中的所有电路都应具有类似乘法器的结构。在早期的研究中还没有实现这种严格的控制。相同数量的顶点和网(超边),相同数量的层,相同的Rent指数等特征是必要的,但还不够。我们需要的控制是通过根据明确定义的顺序表征图形来实现的。重要的是,我们证明可以通过最小化以下任何成本函数来实现等效的特征图排序:(1)交叉数,(2)跨网数或(3)单元跨数。这带来了表征问题的困难:找到这样的顺序是NP-难的。我们使用有效的启发式方法解决参考图 G 的排序问题,该启发式方法找到生成树st G )的顺序并显示对于表示典型VLSI电路的图形, G st G )的交叉数紧密相关。图的特征签名现在包括生成树的顺序和与此顺序相对应的网跨号。我们开发了一种综合方法,使电路类的每个成员( sibling )都满足此签名。兄弟姐妹保留了其参考电路的所有重要特征。我们通过大量实验证明了该方法的可扩展性。在我们可以使用的所有物理设计工具下,同级类的结果均显示在父电路的±(4–9)%之内。

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