首页> 外文会议>ACM/IEEE International Symposium on Computer Architecture >EOLE: Paving the Way for an Effective Implementation of Value Prediction
【24h】

EOLE: Paving the Way for an Effective Implementation of Value Prediction

机译:Eole:铺平有效实施价值预测的方式

获取原文

摘要

Even in the multicore era, there is a continuous demand to increase the performance of single-threaded applications. However, the conventional path of increasing both issue width and instruction window size inevitably leads to the power wall. Value prediction (VP) was proposed in the mid 90's as an alternative path to further enhance the performance of wide-issue superscalar processors. Still, it was considered up to recently that a performance-effective implementation of Value Prediction would add tremendous complexity and power consumption in almost every stage of the pipeline. Nonetheless, recent work in the field of VP has shown that given an efficient confidence estimation mechanism, prediction validation could be removed from the out-of-order engine and delayed until commit time. As a result, recovering from mispredictions via selective replay can be avoided and a much simpler mechanism - pipeline squashing - can be used, while the out-of-order engine remains mostly unmodified. Yet, VP and validation at commit time entails strong constraints on the Physical Register File. Write ports are needed to write predicted results and read ports are needed in order to validate them at commit time, potentially rendering the overall number of ports unbearable. Fortunately, VP also implies that many single-cycle ALU instructions have their operands predicted in the front-end and can be executed in-place, in-order. Similarly, the execution of single-cycle instructions whose result has been predicted can be delayed until commit time since predictions are validated at commit time. Consequently, a significant number of instructions - 10% to 60% in our experiments - can bypass the out-of-order engine, allowing the reduction of the issue width, which is a major contributor to both out-of-order engine complexity and register file port requirement. This reduction paves the way for a truly practical implementation of Value Prediction. Furthermore, since Value Prediction in itself usually increases performance, our resulting {Early I Out-of-Order I Late} Execution architecture, EOLE, is often more efficient than a baseline VP-augmented 6-issue superscalar while having a significantly narrower 4-issue out-of-order engine.
机译:即使在多核时代,也有一种不断的需求来提高单线程应用的性能。然而,常规路径增加发布宽度和指令窗口尺寸不可避免地导致电源壁。在90年代中期提出了价值预测(VP)作为进一步提高宽发行超标型处理器性能的替代路径。尽管如此,近来仍然认为价值预测的性能有效实施将在流水线的几乎每个阶段增加巨大的复杂性和功耗。尽管如此,VP领域的最近工作表明,给定有效置信度估计机制,可以从订单超出发动机中取出预测验证并延迟直到提交时间。结果,可以避免通过选择性重放从错误预测中恢复,并且可以使用更简单的机制 - 管道挤压 - 可以使用超出订单仍未修改。然而,提交时间的vp和验证需要对物理寄存器文件的强制限制。写入端口需要写入预测结果,并且需要读取端口以便在提交时间验证它们,可能呈现无法忍受的端口数量。幸运的是,VP还意味着许多单循环的ALU指令在前端预测了它们的操作数,可以在原时期地执行。类似地,执行所需的单周期指令的执行可以延迟,直到提取时间,因为预测在提交时间验证。因此,在我们的实验中,大量指令 - 10%至60% - 可以绕过无序的发动机,允许减少问题宽度,这是既有秩序的发动机复杂性的主要贡献者注册文件端口要求。这种减少铺平了真正实际实施价值预测的方式。此外,由于价值预测本身通常会增加性能,因此我们的由此产生的{早期i ondound i迟到}执行架构,Eole通常比基线VP-Augmented 6-期限超标集更高效,同时具有明显较窄的4-发出签出的引擎。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号