{"title":"Prototype for a large-scale static timing analyzer running on an IBM Blue Gene","authors":"A. Holder, C. Carothers, Kerim Kalafala","doi":"10.1109/IPDPSW.2010.5470757","DOIUrl":null,"url":null,"abstract":"This paper focuses on parallelization of the classic static timing analysis (STA) algorithm for verifying timing characteristics of digital integrated circuits. Given ever-increasing circuit complexities, including the need to analyze circuits with billions of transistors, across potentially thousands of process corners, with accuracy tolerances down to the picosecond range, sequential execution of STA algorithms is quickly becoming a bottleneck to the overall chip design closure process. A message passing based parallel processing technique for performing STA leveraging an IBM Blue Gene/L supercomputing platform is presented. Results are collected for a small industrial 65 nm benchmarking design, where the algorithm demonstrates speedup of nearly 39 times on 64 processors and a peak of 119 times (without partitioning costs, speedup is 263 times) on 1024 processors. With an idealized synthetic circuit, the algorithm demonstrated 259 times speedup, 925 times speedup without partitioning overhead, on 1024 processors. To the best of our knowledge, this is the first result demonstrating scalable STA on the IBM Blue Gene.","PeriodicalId":329280,"journal":{"name":"2010 IEEE International Symposium on Parallel & Distributed Processing, Workshops and Phd Forum (IPDPSW)","volume":"114 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 IEEE International Symposium on Parallel & Distributed Processing, Workshops and Phd Forum (IPDPSW)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IPDPSW.2010.5470757","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
This paper focuses on parallelization of the classic static timing analysis (STA) algorithm for verifying timing characteristics of digital integrated circuits. Given ever-increasing circuit complexities, including the need to analyze circuits with billions of transistors, across potentially thousands of process corners, with accuracy tolerances down to the picosecond range, sequential execution of STA algorithms is quickly becoming a bottleneck to the overall chip design closure process. A message passing based parallel processing technique for performing STA leveraging an IBM Blue Gene/L supercomputing platform is presented. Results are collected for a small industrial 65 nm benchmarking design, where the algorithm demonstrates speedup of nearly 39 times on 64 processors and a peak of 119 times (without partitioning costs, speedup is 263 times) on 1024 processors. With an idealized synthetic circuit, the algorithm demonstrated 259 times speedup, 925 times speedup without partitioning overhead, on 1024 processors. To the best of our knowledge, this is the first result demonstrating scalable STA on the IBM Blue Gene.
本文重点研究了用于验证数字集成电路时序特性的经典静态时序分析算法的并行化。考虑到电路复杂性的不断增加,包括需要分析具有数十亿晶体管的电路,可能跨越数千个工艺角,精度公差低至皮秒范围,STA算法的顺序执行正迅速成为整体芯片设计闭合过程的瓶颈。提出了一种利用IBM Blue Gene/L超级计算平台执行STA的基于消息传递的并行处理技术。结果是针对小型工业65纳米基准测试设计收集的,其中该算法在64个处理器上的加速速度接近39倍,在1024个处理器上的加速速度峰值为119倍(没有分区成本,加速速度为263倍)。在一个理想的合成电路中,该算法在1024个处理器上加速了259倍,在没有分区开销的情况下加速了925倍。据我们所知,这是在IBM Blue Gene上演示可伸缩STA的第一个结果。