7696

A Compiler and Runtime for Heterogeneous Computing

Joshua Auerbach, David F. Bacon, Ioana Burcea, Perry Cheng, Stephen J. Fink, Rodric Rabbah, Sunil Shukla
IBM Thomas J. Watson Research Center
49th Annual Design Automation Conference (DAC ’12), 2012

@inproceedings{Auerbach:2012:CRH:2228360.2228411,

   author={Auerbach, Joshua and Bacon, David F. and Burcea, Ioana and Cheng, Perry and Fink, Stephen J. and Rabbah, Rodric and Shukla, Sunil},

   title={A compiler and runtime for heterogeneous computing},

   booktitle={Proceedings of the 49th Annual Design Automation Conference},

   series={DAC ’12},

   year={2012},

   isbn={978-1-4503-1199-1},

   location={San Francisco, California},

   pages={271–276},

   numpages={6},

   url={http://doi.acm.org/10.1145/2228360.2228411},

   doi={10.1145/2228360.2228411},

   acmid={2228411},

   publisher={ACM},

   address={New York, NY, USA},

   keywords={FPGA, GPU, Java, heterogeneous, streaming}

}

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Heterogeneous systems show a lot of promise for extracting high-performance by combining the benefits of conventional architectures with specialized accelerators in the form of graphics processors (GPUs) and reconfigurable hardware (FPGAs). Extracting this performance often entails programming in disparate languages and models, making it hard for a programmer to work equally well on all aspects of an application. Further, relatively little attention is paid to co-execution—the problem of orchestrating program execution using multiple distinct computational elements that work seamlessly together. We present Liquid Metal, a comprehensive compiler and runtime system for a new programming language called Lime. Our work enables the use of a single language for programming heterogeneous computing platforms, and the seamless co-execution of the resultant programs on CPUs and accelerators that include GPUs and FPGAs. We have developed a number of Lime applications, and successfully compiled some of these for co-execution on various GPU and FPGA enabled architectures. Our experience so far leads us to believe the Liquid Metal approach is promising and can make the computational power of heterogeneous architectures more easily accessible to mainstream programmers.
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