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首页> 外文期刊>IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems >Multiway partitioning via geometric embeddings, orderings, and dynamic programming
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Multiway partitioning via geometric embeddings, orderings, and dynamic programming

机译:通过几何嵌入,排序和动态编程进行多路分区

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This paper presents effective algorithms for multiway partitioning. Confirming ideas originally due to Hall (1970), we demonstrate that geometric embeddings of the circuit netlist can lead to high-quality k-way partitionings. The netlist embeddings are derived via the computation of d eigenvectors of the Laplacian for a graph representation of the netlist. As Hall did not specify how to partition such geometric embeddings, we explore various geometric partitioning objectives and algorithms, and find that they are limited because they do not integrate topological information from the netlist. Thus, we also present a new partitioning algorithm that exploits both the geometric embedding and netlist information, as well as a restricted partitioning formulation that requires each cluster of the k-way partitioning to be contiguous in a given linear ordering. We begin with a d-dimensional spectral embedding and construct a heuristic 1-dimensional ordering of the modules (combining spacefilling curve with 3-Opt approaches originally proposed for the traveling salesman problem). We then apply dynamic programming to efficiently compute the optimal k-way split of the ordering for a variety of objective functions, including Scaled Cost and Absorption. This approach can transparently integrate user-specified cluster size bounds. Experiments show that this technique yields multiway partitionings with lower Sealed Cost than previous spectral approaches.
机译:本文提出了有效的多路分区算法。最初由Hall(1970)提出的想法得到了证实,我们证明了电路网表的几何嵌入可以导致高质量的k路分区。网表嵌入是通过计算拉普拉斯算子的特征向量来得到网表的图形表示的。由于Hall没有指定如何对这种几何嵌入进行划分,因此我们探索了各种几何划分目标和算法,并发现它们是有限的,因为它们未集成网表中的拓扑信息。因此,我们还提出了一种新的分区算法,该算法利用了几何嵌入和网表信息,以及一种受限的分区公式,该公式要求k路分区的每个群集在给定的线性顺序中是连续的。我们从d维频谱嵌入开始,并构造模块的启发式一维排序(将空间填充曲线与最初针对旅行商问题提出的3-Opt方法相结合)。然后,我们应用动态编程来针对各种目标函数(包括按比例缩放的成本和吸收率)有效地计算定单的最优k向拆分。这种方法可以透明地集成用户指定的群集大小范围。实验表明,与以前的频谱方法相比,该技术可产生多路划分,且密封成本更低。

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