CAREER: Improving the Access-Execute Balance in High Performance Processors

程序行为研究表明，目前大多数高性能处理器花费更多的时间来计算地址和访问数据，而不是执行应用程序所需的功能操作。本研究包括研究平衡的多问题架构的设计问题，以改善访问-执行平衡，最大化各功能单元之间的解耦，利用更高的并发性并实现更高的性能。用于缓解访问执行不平衡的技术包括：(1)并行执行多个访问任务，(2)为复杂访问原语提供架构支持，(3)提供特定于应用程序的访问原语。还将研究如何提高访问和执行进程之间的并发性。在许多解耦的访问-执行体系结构中，队列已经利用了访问和执行之间的并发性，但是依赖于数据的控制依赖关系通常禁止将数据预取到队列。本研究将探讨在存在数据依赖控制依赖项的情况下促进队列预期加载的技术。该研究将建立在PI之前对访问执行解耦和其他方案的研究基础上，以提高内存访问的性能。PI正在将创新技术，如主动学习和合作学习纳入课堂。她想在她的课程中强调设计、设计自动化和实验方面。作为课程改进的一部分，正在开发一门新的高级计算机体系结构研究生课程和一门使用fpga的数字设计本科课程和实验室。PI还计划参与高中学生的外展活动以及针对妇女和少数民族的特别项目。总体目标是促进研究生、本科生和大学预科阶段的有效学习。＊＊＊

Program behavior studies reveal that most current high performance processors spend more time computing addresses and accessing data than performing the functional operations required by application programs. This research consists of investigating issues in the design of a balanced multiple issues architecture that improves the access-execute balance, maximized the decoupling between the various functional units, exploits higher concurrency and achieves higher performance. The techniques used to alleviate access- execute imbalance include (I) executing multiple access tasks in parallel, (ii) providing architectural support for complex access primitives, and (iii) providing application- specific access primitives. Also performed will be investigations on improving concurrency between access and execute processes. Concurrency between access and execution has been exploited by queues in many decoupled access- execute architectures, but data dependent control dependencies often prohibit prefetching of data to queues. This research will investigate techniques to facilitate anticipatory loading to queues even in presence of data dependent control dependencies. The research will build on the PI's previous studies on accessexecute decoupling and other schemes to improve the performance of memory accessing. The PI is incorporating innovative techniques such as active learning, and cooperative learning into the classroom. She wants to emphasize design, design automation, and experimental aspects in her courses. As part of curriculum improvement, a new graduate course on Advanced Computer architecture and an undergraduate course and laboratory on Digital Design using FPGAs are being developed. The PI also plans to participate in outreach activities for high-school students and special programs for women and minorities. The overall objective is to stimulate efficient learning at graduate, undergraduate and pre-college levels of education. ***