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 language | English (US) |
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Journal | International Workshop on System Level Interconnect Prediction, SLIP |
Volume | 2015-January |
DOIs | |
State | Published - 2015 |
Event | ACM/IEEE International Workshop on System Level Interconnect Prediction, SLIP 2015 - San Francisco, United States Duration: Jun 6 2015 → … |
ASJC Scopus subject areas
- Hardware and Architecture
- Electrical and Electronic Engineering
- Computer Science Applications
- Applied Mathematics