Engineering a scalable Boolean matching based on EDA SaaS 2.0

Abstract

Software as a Service (SaaS) 1.0 signifcantly lowers the infrastructure and maintenance cost and increases the accessibility of the software by hosting software via the web. Compared with SaaS 1.0, SaaS 2.0 is more flexible since it leverages software tools from both server and client sides with closer interaction between them. The SaaS 2.0 paradigm provides new opportunities and challenges for EDA. In this paper, we take Boolean matching, one of the core sub algorithms in logic synthesis for field programmable gate arrays (FPGAs), as a case study. We investigate the advantages and challenges of implementing a scalable EDA algorithm under SaaS 2.0 paradigm from a technical perspective. We propose SaaS-BM, a new Boolean matching algorithm customized to take full advantage of the cloud while addressing concerns such as security and the internet bandwidth limit. Extensive experiments are performed under a networked environment with concurrent accesses. Integrated into a post-mapping re-synthesis algorithm minimizing area, the proposed SaaS-BM is 863X times faster than state-of-the-art SAT-based Boolean matching with 0.5% area overhead. Compared with a recent Bloom Filter-based Boolean matching algorithm, our proposed SaaS-BM is 53X times faster on large circuits with no area overhead.