A new canonical form for fast boolean matching in logic synthesis and verification
Proceedings of the 42nd annual Design Automation Conference
FPGA technology mapping: a study of optimality
Proceedings of the 42nd annual Design Automation Conference
Exploiting symmetry in SAT-based Boolean matching for heterogeneous FPGA technology mapping
Proceedings of the 2007 IEEE/ACM international conference on Computer-aided design
Boolean factoring and decomposition of logic networks
Proceedings of the 2008 IEEE/ACM International Conference on Computer-Aided Design
Compressing Binary Decision Diagrams
Proceedings of the 2008 conference on ECAI 2008: 18th European Conference on Artificial Intelligence
Building a faster boolean matcher using bloom filter
Proceedings of the 18th annual ACM/SIGDA international symposium on Field programmable gate arrays
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
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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 net-worked 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.