Target Prediction For Indirect Jumps

Po-Yung Chang, E. Hao, Y. Patt
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引用次数: 153

Abstract

As the issue rate and pipeline depth of high performance superscalar processors increase, the amount of speculative work issued also increases. Because speculative work must be thrown away in the event of a branch misprediction, wide-issue, deeply pipelined processors must employ accurate branch predictors to effectively exploit their performance potential. Many existing branch prediction schemes are capable of accurately predicting the direction of conditional branches. However, these schemes are ineffective in predicting the targets of indirect jumps achieving, on average, a prediction accuracy rate of 51.8% for the SPECint95 benchmarks. In this paper, we propose a new prediction mechanism, the target cache, for predicting indirect jump targets. For the perl and gcc benchmarks, this mechanism reduces the indirect jump misprediction rate by 93.4% and 63.35% and the overall execution time by 14% and 5%.
间接跳跃的目标预测
随着高性能超标量处理器的发行率和流水线深度的增加,发行的投机工作也在增加。因为在分支预测错误的情况下,推测性工作必须被抛弃,所以广泛的、深度流水线化的处理器必须使用准确的分支预测器来有效地利用它们的性能潜力。现有的许多分支预测方案都能够准确地预测条件分支的方向。然而,这些方案在预测间接跳跃目标方面是无效的,平均而言,SPECint95基准的预测准确率为51.8%。本文提出了一种新的预测机制——目标缓存,用于预测间接跳转目标。对于perl和gcc基准测试,该机制将间接跳转错误预测率降低了93.4%和63.35%,并将总执行时间降低了14%和5%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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