On fast timing closure: speeding up incremental path-based timing analysis with mapreduce

Tsung-wei Huang, Martin D. F. Wong

Research output: Chapter in book/report/conference proceedingConference proceedingpeer-review

5 Citations (Scopus)

Abstract

Incremental path-based timing analysis (PBA) is a pivotal step in the timing optimization flow. A core building block analyzes the timing path-by-path subject to a critical amount of incremental changes on the design. However, this process in nature demands an extremely high computational complexity and has been a major bottleneck in accelerating timing closure. Therefore, we introduce in this paper a fast and scalable algorithm of incremental PBA with MapReduce – a recently popular programming paradigm in big-data era. Inspired by the spirit of MapReduce, we formulate our problem into tasks that are associated with keys and values and perform massively-parallel map and reduce operations on a distributed system. Experimental results demonstrated that our approach can not only easily analyze huge deisgns in a few minutes, but also quickly revalidate the timing after the incremental changes. Our results are beneficial for speeding up the lengthy design cycle of timing closure.
Original languageEnglish
Title of host publication2015 ACM/IEEE International Workshop on System Level Interconnect Prediction (SLIP)
PublisherIEEE
Pages1-6
Number of pages6
ISBN (Electronic)9781467381895
DOIs
Publication statusPublished - Jun 2015
Event2015 ACM/IEEE International Workshop on System Level Interconnect Prediction (SLIP) - San Francisco, United States
Duration: 6 Jun 20156 Jun 2015
https://ieeexplore.ieee.org/xpl/conhome/7160953/proceeding (Link to conference proceedings)

Publication series

NameProceedings of ACM/IEEE International Workshop on System Level Interconnect Prediction (SLIP)

Conference

Conference2015 ACM/IEEE International Workshop on System Level Interconnect Prediction (SLIP)
Country/TerritoryUnited States
CitySan Francisco
Period6/06/156/06/15
Internet address

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