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- Karel Driesen
- Department of Computer Science, University of California, Santa Barbara, CA
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- Urs Hölzle
- Department of Computer Science, University of California, Santa Barbara, CA
説明
<jats:p>Indirect branch prediction is likely to become increasingly important in the future because indirect branches occur more frequently in object-oriented programs. With misprediction rates of around 25% on current processors, indirect branches can incur a significant fraction of branch misprediction overhead even though they remain less frequent than the more predictable conditional branches. We investigate a wide range of two-level predictors dedicated exclusively to indirect branches. Starting with predictors that use full-precision addresses and unlimited tables, we progressively introduce hardware constraints and minimize the loss of predictor performance at each step. For programs from the SPECint95 suite as well as a suite of large C++ applications, a two-level predictor achieves a misprediction rate of 9.8% with a 1K-entry table and 7.3% with an 8K-entry table, representing more than a threefold improvement over an ideal BTB. A hybrid predictor further reduces the misprediction rates to 8.98% (1K) and 5.95% (8K).</jats:p>
収録刊行物
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- ACM SIGARCH Computer Architecture News
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ACM SIGARCH Computer Architecture News 26 (3), 167-178, 1998-04-16
Association for Computing Machinery (ACM)
