深度流水线处理器上推测性跟踪重用的限制

M. Pilla, Amarildo T. da Costa, F. França, B. Childers, M. Soffa
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引用次数: 12

摘要

跟踪重用通过跳过冗余指令序列的执行来提高处理器的性能。然而,许多可重用跟踪在完成重用测试时并没有准备好所有的输入。对于这些情况,我们开发了一种新技术,称为通过推测跟踪(RST)进行重用,其中可以预测跟踪输入。我们研究了具有深管道的现代处理器的RST限制,以及约束资源对性能的影响。我们表明,我们的方法比非推测性跟踪重用技术重用了更多的跟踪,与非推测性跟踪重用相比,速度提高了43%,当内存访问被重用时,速度提高了57%。
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The limits of speculative trace reuse on deeply pipelined processors
Trace reuse improves the performance of processors by skipping the execution of sequences of redundant instructions. However, many reusable traces do not have all of their inputs ready by the time the reuse test is done. For these cases, we developed a new technique called reuse through speculation on traces (RST), where trace inputs may be predicted. We study the limits of RST for modern processors with deep pipelines, as well as the effects of constraining resources on performance. We show that our approach reuses more traces than the nonspeculative trace reuse technique, with speedups of 43% over a nonspeculative trace reuse and 57% when memory accesses are reused.
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