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Verifying Relative Safety, Accuracy, and Termination for Program Approximations

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NASA Formal Methods (NFM 2016)

Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 9690))

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Abstract

Approximate computing is an emerging area for trading off the accuracy of an application for improved performance, lower energy costs, and tolerance to unreliable hardware. However, developers must ensure that the leveraged approximations do not introduce significant, intolerable divergence from the reference implementation, as specified by several established robustness criteria. In this work, we show the application of automated differential verification towards verifying relative safety, accuracy, and termination criteria for a class of program approximations. We use mutual summaries to express relative specifications for approximations, and SMT-based invariant inference to automate the verification of such specifications. We perform a detailed feasibility study showing promise of applying automated verification to the domain of approximate computing in a cost-effective manner.

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Notes

  1. 1.

    We required the user to provide a simple additional predicate and unroll the first loop once.

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Acknowledgments

We thank Adrian Sampson for his feedback and for helping out with benchmark selection, and Akash Lal for helping out with Houdini. This work was supported in part by NSF award CCF 1255776 and SRC contract 2013-TJ-2426.

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Authors and Affiliations

  1. University of Utah, Salt Lake City, UT, USA

    Shaobo He & Zvonimir Rakamarić

  2. Microsoft Research, Redmond, WA, USA

    Shuvendu K. Lahiri

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  1. Shaobo He
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  2. Shuvendu K. Lahiri
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  3. Zvonimir Rakamarić
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Correspondence to Shaobo He .

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Editors and Affiliations

  1. University of Minnesota, Minneapolis, Minnesota, USA

    Sanjai Rayadurgam

  2. NASA Ames Research Center , Moffett Field, California, USA

    Oksana Tkachuk

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He, S., Lahiri, S.K., Rakamarić, Z. (2016). Verifying Relative Safety, Accuracy, and Termination for Program Approximations. In: Rayadurgam, S., Tkachuk, O. (eds) NASA Formal Methods. NFM 2016. Lecture Notes in Computer Science(), vol 9690. Springer, Cham. https://doi.org/10.1007/978-3-319-40648-0_19

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  • DOI: https://doi.org/10.1007/978-3-319-40648-0_19

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