Table size reduction for data value predictors by exploiting narrow width values

  • Authors:
  • Toshinori Sato;Itsujiro Arita

  • Affiliations:
  • Department of Artificial Intelligence, Kyushu Institute of Technilogy, 680-4 Kawazu, lizuka, 820-8502 Japan;Department of Artificial Intelligence, Kyushu Institute of Technilogy, 680-4 Kawazu, lizuka, 820-8502 Japan

  • Venue:
  • Proceedings of the 14th international conference on Supercomputing
  • Year:
  • 2000

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Abstract

Recently, the practice of speculation in resolving data dependences has been studied as a means of extracting more instruction level parallelism (ILP). An outcome of an instruction is predicted by value predictors. The instruction and its dependent instructions can be executed simultaneously, thereby exploiting ILP aggressively. One of the serious hurdles for realizing data speculation is huge hardware budget of the predictors. In this paper, we propose a technique reducing the budget by exploiting narrow width values. The hardware budget of value predictors is reduced by up to 45.1%. Simulation results show that the technique, called 2-mode scheme, maintains processor performance with slight decrease of the value prediction accuracy.