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Low-Cost Value Predictors Using Frequent Value Locality

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High Performance Computing (ISHPC 2002)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2327))

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Abstract

The practice of speculation in resolving data dependences has been recently studied as a means of extracting more instruction level parallelism (ILP). Each instruction’s outcome is predicted by value predictors. The instruction and its dependent instructions can be executed in parallel, thereby exploiting ILP aggressively. One of the serious hurdles for realizing data speculation is the huge hardware budget required by the predictors. In this paper, we propose techniques that exploit frequent value locality, resulting in a significant budget reduction. Based on these proposals, we evaluate two value predictors, named the zero-value predictor and the 0/1-value predictor. The zero-value predictor generates only value 0. Similarly, the 0/1-value predictor generates only values 0 and 1. Simulation results show that the proposed predictors have greater performance than does the last-value predictor which requires a hardware budget twice as large as that of the predictors. Therefore, the zero- and the 0/1-value predictors are promising candidates for cost-effective and practical value predictors which can be implemented in real microprocessors.

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Author information

Authors and Affiliations

  1. Department of Artificial Intelligence, USA

    Toshinori Sato & Itsujiro Arita

  2. Center for Microelectronic Systems, Kyushu Institute of Technology, Japan

    Toshinori Sato

Authors
  1. Toshinori Sato
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  2. Itsujiro Arita
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Editor information

Editors and Affiliations

  1. Institute of Software Science, University of Vienna, Liechtensteinstr. 22, 1090, Vienna, Austria

    Hans P. Zima

  2. Department of Information and Computer Science, Nara Women’s University, Kitauoyanishimachi, Nara City, 630-8506, Japan

    Kazuki Joe

  3. Institute of Information Science and Electronics, University of Tsukuba, Tenno-dai 1-1-1, Tsukuba, Ibaraki, 305-8577, Japan

    Mitsuhisa Sato

  4. Internet Systems Research Laboratories, NEC Corporation, 4-1-1, Miyazaki, Miyamae, Kawasaki, Kanagawa, 216-8555, Japan

    Yoshiki Seo

  5. Kyoto University, Yoshidahonmachi, Sakyo-ku, Kyoto, 606-8501, Japan

    Masaaki Shimasaki

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© 2002 Springer-Verlag Berlin Heidelberg

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Sato, T., Arita, I. (2002). Low-Cost Value Predictors Using Frequent Value Locality. In: Zima, H.P., Joe, K., Sato, M., Seo, Y., Shimasaki, M. (eds) High Performance Computing. ISHPC 2002. Lecture Notes in Computer Science, vol 2327. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-47847-7_11

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  • DOI: https://doi.org/10.1007/3-540-47847-7_11

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-43674-4

  • Online ISBN: 978-3-540-47847-8

  • eBook Packages: Springer Book Archive

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