CSR-AES: Feedback-Driven Adaptive Multithreading

本研究项目研究如何扩展动态多线程的可扩展模型，以涵盖三个关键功能-多道编程、进程间通信和对I/O的支持-无需费力的手动规划、调优或配置。这项研究特别注重使用被证明是好的“反馈驱动”战略来实现这一目标。研究人员正在开发一种多程序多线程系统，以体现这些策略，并提供一种研究工具，用于发现交互适应工作的其他特性。“基于历史的反馈”是正在研究的技术之一，它为证明有效的日程安排和资源分配战略提供了一个有希望的基础。这项研究希望让多处理器更高效、更容易被绝大多数计算机用户使用，而不仅仅是专业的计算机科学家。在研究过程中开发的开源软件可以免费提供给万维网上的任何人。有关多处理器调度的课程材料通过麻省理工学院开放式课程计划分发。

This research project investigates how to extend the scalable model ofdynamic multithreading to encompass three key functionalities ---multiprogramming, interprocess communication, and support for I/O ---without requiring painstaking manual planning, tuning, or configuring. The research focuses particularly on using provably good``feedback-driven'' strategies to accomplish this end. Theresearchers are developing a multiprogrammed multithreaded system toembody these strategies and provide a research vehicle for discovering additional properties of interacting adaptive jobs. Among thetechniques under study is ``history-based feedback,'' which offers apromising foundation for provably effective scheduling and resourceallocation strategies. This research hopes to make multiprocessors more efficient and easierto use by the vast majority of computer users, not just by expertcomputer scientists. Open-source software developed in the course ofthe research is freely available to anyone on the World Wide Web. Course materials on multiprocessor scheduling are distributed via theMIT OpenCourseWare project.