Research Output
TAFFO: Tuning Assistant for Floating to Fixed Point Optimization
  While many approximate computing methods are quite application-dependent, reducing the size of the data representation used in the computation has a more general applicability. We present a tuning assistant for floating to fixed point optimization (TAFFO), an LLVM-based framework designed to assist programmers in the precision tuning of software. We discuss the framework architecture and we provide guidelines to effectively tradeoff precision to improve the time-to-solution. We evaluate our framework on a well-known approximate computing benchmark suite, AXBENCH, achieving a speedup on 5 out of 6 benchmarks (up to 366%) with only a limited loss in precision (

  • Type:

    Article

  • Date:

    29 April 2019

  • Publication Status:

    Published

  • Publisher

    Institute of Electrical and Electronics Engineers (IEEE)

  • DOI:

    10.1109/les.2019.2913774

  • Cross Ref:

    10.1109/les.2019.2913774

  • ISSN:

    1943-0663

  • Funders:

    Historic Funder (pre-Worktribe)

Citation

Cherubin, S., Cattaneo, D., Chiari, M., Bello, A. D., & Agosta, G. (2020). TAFFO: Tuning Assistant for Floating to Fixed Point Optimization. IEEE Embedded Systems Letters, 12(1), 5-8. https://doi.org/10.1109/les.2019.2913774

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