论文标题
定制量身定制的随机森林套件，以适应预摘要
Custom Tailored Suite of Random Forests for Prefetcher Adaptation
论文作者
论文摘要
为了缩小内存和处理器之间的差距，进而提高了性能，在数据/指令预摘要设计领域已经有很多工作。预摘要部署在内存层次结构的每个级别中，但通常，每个预摘要都在设计中设计而无需全面地考虑系统中的其他预购器。结果，这些单独的预摘要设计并不总是相互补充，这会导致平均性能增长和/或许多负异常值。在这项工作中，我们提出了suitap（用于适应预摘要系统配置的随机森林套件），这是一种硬件预摘要适配器，该适配器使用一套随机森林来确定在运行时确定应在每个内存级别上处于每个内存水平上，以便它们相互补充。与没有预脱水器的设计相比，使用Suitap我们在Spec2017 Suite带有12KB开销的Spec2017 Suite中平均将IPC提高了46％。此外，我们还使用suitap减少了负异常值。
To close the gap between memory and processors, and in turn improve performance, there has been an abundance of work in the area of data/instruction prefetcher designs. Prefetchers are deployed in each level of the memory hierarchy, but typically, each prefetcher gets designed without comprehensively accounting for other prefetchers in the system. As a result, these individual prefetcher designs do not always complement each other, and that leads to low average performance gains and/or many negative outliers. In this work, we propose SuitAP (Suite of random forests for Adaptation of Prefetcher system configuration), which is a hardware prefetcher adapter that uses a suite of random forests to determine at runtime which prefetcher should be ON at each memory level, such that they complement each other. Compared to a design with no prefetchers, using SuitAP we improve IPC by 46% on average across traces generated from SPEC2017 suite with 12KB overhead. Moreover, we also reduce negative outliers using SuitAP.
