Corolla partitioning for distributed logic simulation of VLSI-circuits

C. Sporrer, H. Bauer
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引用次数: 46

Abstract

Time Warp has evolved to a common technique for distributed simulation. Speedup in Time Warp simulation systems mainly depends on two overhead factors: first, the load on the simulators has to be well balanced and second, communication and rollbacks have to be kept to a minimum. Both of these factors are influenced by the partitioning of the simulated system. In this paper, we focus on various static partitioning schemes used to partition digital circuits for distributed simulation. A new hierarchical partitioning approach is presented, compared and rated with other partitioning schemes by evaluating benchmark circuits. Partitioning is done in two steps: a fine grained clustering step based on corollas and a coarse grained step forming partitions using the connectivity matrix. The corolla approach yields very good partitioning results even for a large number of partitions. The achieved speedups are almost linear (up to 12 partitions for larger circuits), as long as the partition sizes are large enough so that communication between the simulators is not a bottleneck. The results reveal the great impact of partitioning on the acceleration of distributed logic simulation and show the effectiveness of the presented corolla partitioning scheme.
用于vlsi电路分布式逻辑仿真的花冠划分
时间扭曲已经发展成为一种常见的分布式模拟技术。Time Warp模拟系统中的加速主要取决于两个开销因素:首先,模拟器上的负载必须得到很好的平衡,其次,通信和回滚必须保持在最低限度。这两个因素都受到模拟系统划分的影响。本文重点介绍了用于分布式仿真的数字电路划分的各种静态划分方案。提出了一种新的分层分划方法,并通过对基准电路的评价与其他分划方案进行了比较和评价。分区分两个步骤完成:基于花冠的细粒度聚类步骤和使用连接矩阵形成分区的粗粒度步骤。即使对于大量分区,花冠方法也会产生非常好的分区结果。实现的加速几乎是线性的(对于较大的电路,最多可以达到12个分区),只要分区大小足够大,这样模拟器之间的通信就不会成为瓶颈。结果表明,分划对分布式逻辑仿真的加速有很大的影响,并证明了分划方案的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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