Difficult-path branch prediction using subordinate microthreads
Difficult-path branch prediction using subordinate microthreads
复制标题
使用从属微线程的困难路径分支预测
DOI：
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发表时间：
2002
期刊：
影响因子：
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通讯作者：
Adi Yoaz
中科院分区：
文献类型：
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作者：
R. Chappell;F. Tseng;Y. Patt;Adi Yoaz
随着微处理器核心变得越来越深，分支机构错误预测的惩罚继续增加。因此，提高分支预测准确性仍然是一个重要的挑战。同时下属微读（SSMT）提供了提高分支预测准确性的手段。 SSMT计算机运行多个并发微读以支持主线程。我们建议动态构建微读，这些微读可以沿经常预测的路径进行投机和准确的预报分支结果。该机制旨在完全在硬件中实现。我们介绍了这样做的详细信息。我们展示了如何选择正确的路径，如何生成准确的预测以及如何及时获取此信息。与Specint95和Specint2000基准套件上的非常激进的基线机器相比，我们的平均增益为8.4％（最大42％）。
Branch misprediction penalties continue to increase as microprocessor cores become wider and deeper. Thus, improving branch prediction accuracy remains an important challenge. Simultaneous subordinate microthreading (SSMT) provides a means to improve branch prediction accuracy. SSMT machines run multiple, concurrent microthreads in support of the primary thread. We propose to dynamically construct microthreads that can speculatively and accurately pre-compute branch outcomes along frequently mispredicted paths. The mechanism is intended to be implemented entirely in hardware. We present the details for doing so. We show how to select the right paths, how to generate accurate predictions, and how to get this information in a timely way. We achieve an average gain of 8.4% (42% maximum) over a very aggressive baseline machine on the SPECint95 and SPECint2000 benchmark suites.