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Profile-based selection of load value and address predictors

  • II System Architecture
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High Performance Computing (ISHPC 1999)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1615))

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Abstract

In this paper, we investigate hybrid predictors for data speculation. In order to increase opportunities for data speculation as well as improve prediction accuracy, we propose to combine a load address predictor with a load value predictor. For each instruction, by choosing the more accurate predictor, we improve prediction accuracy. We investigate two types of hybrid predictors. One has an adaptive mechanism for choosing the more accurate one dynamically, and the other decides the selection statically using execution profiles. The latter one has the benefit that the hardware cost of the selecting mechanism is removed. We have evaluated the predictors using a cycle-by-cycle simulator and found that contribution of the static hybrid predictor to processor performance is comparable to that of the dynamic one.

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Authors and Affiliations

  1. Toshiba Microelectronics Engineering Laboratory, 580-1, Horikawa-Cho, Saiwai-Ku, 210-8520, Kawasaki, Japan

    Toshinori Sato

Authors
  1. Toshinori Sato
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Editor information

Constantine Polychronopoulos Kazuki Joe Akira Fukuda Shinji Tomita

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© 1999 Springer-Verlag Berlin Heidelberg

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Sato, T. (1999). Profile-based selection of load value and address predictors. In: Polychronopoulos, C., Fukuda, K.J.A., Tomita, S. (eds) High Performance Computing. ISHPC 1999. Lecture Notes in Computer Science, vol 1615. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0094908

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  • DOI: https://doi.org/10.1007/BFb0094908

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-65969-3

  • Online ISBN: 978-3-540-48821-7

  • eBook Packages: Springer Book Archive

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