Fast custom instruction identification by convex subgraph enumeration

Authors:
Kubilay Atasu;Oskar Mencer;Wayne Luk;Can Ozturan;Gunhan Dundar
Affiliations:
Department of Computing, Imperial College London, UK;Department of Computing, Imperial College London, UK;Department of Computing, Imperial College London, UK;Department of Computer Engineering, Bogazici University, Istanbul, Turkey;Department of Electrical and Electronics Engineering, Bogazici University, Istanbul, Turkey
Venue:
ASAP '08 Proceedings of the 2008 International Conference on Application-Specific Systems, Architectures and Processors
Year:
2008

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Abstract

Automatic generation of custom instruction processors from high-level application descriptions enables fast design space exploration, while offering very favorable performance and silicon area combinations. This work introduces a novel method for adapting the instruction set to match an application captured in a high-level language. A simplified model is used to find the optimal instructions via enumeration of maximal convex subgraphs of application data flow graphs (DFGs). Our experiments involving a set of multimedia and cryptography benchmarks show that an order of magnitude performance improvement can be achieved using only a limited amount of hardware resources. In most cases, our algorithm takes less than a second to execute.