首页> 外文期刊>IEEE transactions on very large scale integration (VLSI) systems >Multilevel hypergraph partitioning: applications in VLSI domain
【24h】

Multilevel hypergraph partitioning: applications in VLSI domain

机译:多级超图分区:VLSI域中的应用

获取原文
获取原文并翻译 | 示例

摘要

In this paper, we present a new hypergraph-partitioning algorithm that is based on the multilevel paradigm. In the multilevel paradigm, a sequence of successively coarser hypergraphs is constructed. A bisection of the smallest hypergraph is computed and it is used to obtain a bisection of the original hypergraph by successively projecting and refining the bisection to the next level finer hypergraph. We have developed new hypergraph coarsening strategies within the multilevel framework. We evaluate their performance both in terms of the size of the hyperedge cut on the bisection, as well as on the run time for a number of very large scale integration circuits. Our experiments show that our multilevel hypergraph-partitioning algorithm produces high-quality partitioning in a relatively small amount of time. The quality of the partitionings produced by our scheme are on the average 6%-23% better than those produced by other state-of-the-art schemes. Furthermore, our partitioning algorithm is significantly faster, often requiring 4-10 times less time than that required by the other schemes. Our multilevel hypergraph-partitioning algorithm scales very well for large hypergraphs. Hypergraphs with over 100 000 vertices can be bisected in a few minutes on today's workstations. Also, on the large hypergraphs, our scheme outperforms other schemes (in hyperedge cut) quite consistently with larger margins (9%-30%).
机译:在本文中,我们提出了一种基于多级范例的新的超图分割算法。在多级范例中,构造了一系列顺序较粗的超图。计算最小的超图的二等分,并通过连续投影并将二等分细化为下一级更精细的超图,将其用于获取原始超图的二等分。我们在多层框架内开发了新的超图粗化策略。我们根据两等分上的超边缘切割的大小以及许多超大规模集成电路的运行时间来评估其性能。我们的实验表明,我们的多级超图分割算法可在相对较短的时间内产生高质量的分割。我们的方案所产生的分区质量平均比其他最新方案所产生的分区质量高6%-23%。此外,我们的分区算法明显更快,通常比其他方案所需的时间少4-10倍。我们的多级超图分区算法可以很好地缩放大型超图。在当今的工作站上,可以在几分钟内将具有超过10万个顶点的超图一分为二。同样,在大型超图上,我们的方案(在超切边中)以较大的利润率(9%-30%)始终优于其他方案。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号