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On reducing misspeculations in a pipelined scheduler

机译:关于减少流水线调度程序中的错误推测

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摘要

Pipelining the scheduling logic, which exposes and exploits the instruction level parallelism, degrades processor performance. In a 4-issue processor, our evaluations show that pipelining the scheduling logic over two cycles degrades performance by 10% in SPEC-2000 integer benchmarks. Such a performance degradation is due to sacrificing the ability to execute dependent instructions in consecutive cycles. Speculative selection is a previously proposed technique that boosts the performance of a processor with a pipelined scheduling logic. However, this new speculation source increases the overall number of misspeculated instructions, and this unuseful work wastes energy. In this work we introduce a non-speculative mechanism named Dependence Level Scheduler (DLS) which not only tolerates the scheduling-logic latency but also reduces the number of misspeculated instructions with respect to a scheduler with speculative selection. In DLS, the selection of a group of one-cycle instructions (producer-level) is overlapped with the wake up in advance of its group of dependent instructions. DLS is not speculative because the group of woken in advance instructions will compete for selection only after issuing all producer-level instructions. On average, DLS reduces the number of misspeculated instructions with respect to a speculative scheduler by 17.9%. From the IPC point of view, the speculative scheduler outperforms DLS by 0.3%. Moreover, we propose two non-speculative improvements to DLS.
机译:对调度逻辑进行流水线处理会暴露和利用指令级并行性,从而降低处理器性能。在4个问题的处理器中,我们的评估表明,在SPEC-2000整数基准测试中,对调度逻辑进行两个周期的流水线处理会使性能降低10%。这种性能下降是由于牺牲了在连续周期中执行相关指令的能力。推测性选择是先前提出的技术,其利用流水线调度逻辑来提高处理器的性能。但是,这种新的推测来源增加了错误推测的指令的总数,并且这种无用的工作浪费了能量。在这项工作中,我们引入了一种称为依赖级别调度程序(DLS)的非推测性机制,该机制不仅可以容忍调度逻辑延迟,而且相对于具有推测性选择的调度器而言,它可以减少错误推测的指令数量。在DLS中,一组单周期指令(生产者级别)的选择与它的从属指令组之前的唤醒重叠。 DLS不是投机性的,因为仅在发出所有生产者级别的指令后,这组预先唤醒的指令才会竞争选择。平均而言,DLS可以将与投机调度程序有关的错误推测指令的数量减少17.9%。从IPC的角度来看,推测性调度程序的性能优于DLS 0.3%。此外,我们提出了DLS的两个非推测性改进。

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