SHF: Large: Collaborative Research: Reliable Performance for Modern Systems

今天的计算机系统比以往任何时候都更强大，但已经变得如此复杂，以至于程序员现在很难开发出高性能的软件。即使是程序中的微小变化或用户系统中的差异也会导致显着的减速。目前，没有办法保证一个程序在测试过程中的表现。这种情况使得追踪效率低下的根源或修复它们变得极其困难。其结果是降低了服务器的功耗和计算效率，降低了客户端平台上的用户体验。本研究旨在为现代计算机系统提供可靠的性能。通过在计算机运行程序的方式中引入随机性，一个性能可靠的系统将显著降低任何小的变化对性能产生重大影响的概率。例如，考虑由冲突引起的高速缓存未命中。使用标准缓存，重复访问相同的元素总是会导致未命中，从而降低性能。 在随机缓存或随机对象放置中，同一行不太可能被重复驱逐。研究人员正在设计和评估软件和硬件中的随机算法的使用，分别和组合，以补救现代系统中病理行为的众多来源。其结果将使性能便携的应用程序，免疫不幸的相互作用与微处理器组件。

Today's computer systems are more powerful than ever, but have become so complex that it is now difficult for programmers to produce high-performance software. Even slight changes in programs or differences in a user's system can cause dramatic slowdowns. Currently, there is no way to guarantee that a program will perform as well as it did during testing. This situation makes it extremely difficult to track down the sources of inefficiencies or repair them. The result is reduced power and computational efficiency on servers, and a degraded user experience on client platforms.This research aims to deliver reliable performance on modern computer systems. By introducing randomness into the way a computer runs programs, a reliably performant system will significantly reduce the probability that any small change will have a large impact on performance. For instance, consider a cache miss caused by a conflict. With standard caches, repeated access to the same elements would always cause misses, degrading performance. In a randomized cache or with randomized object placement, it would be very unlikely for the same line to be repeatedly evicted. The investigators are designing and evaluating the use of both randomized algorithms in software and hardware, separately and in combination, to remedy the numerous sources of pathological behavior in modern systems. The result will enable performance-portable applications that are immune to unfortunate interactions with microprocessor components.