Using Simultaneous Multithreaded Processors for Soft Real-Time Applications

使用同步多线程处理器进行软实时应用

• 批准号: 0209198
• 负责人: Sarita Adve
• 金额: $ 30万
• 依托单位: University of Illinois at Urbana-Champaign
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2002
• 资助国家: 美国
• 起止时间: 2002-07-01 至 2006-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0209198&HistoricalAwards=false
• 关键词: Using; Simultaneous; Multithreaded; Processors; Soft

This research concerns the use of simultaneous multithreaded (SMT) processors for soft real-time applications such as multimedia applications. SMT processors have the potential to provide high throughput by running multiple threads at the same time, and soft real-time applications are anincreasingly important workload. The use of SMT processors for real-time applications, however, has largely been unexplored.Most work on SMT has been driven by the goal of increasing throughput. Real-time applications additionally require high schedulability (i.e., the ability to meet deadlines) and predictability. Further, such applications often run in energy and thermal power constrained environments. This workseeks to develop co-schedule selection and resource sharing algorithms (and consequent admission tests) for SMT processors that will (1) maximize instruction throughput, (2) maximize schedulability, (3)maximize execution time predictability, (4) minimize energy, and (5) minimize thermal power, for soft real-time applications such as multimedia applications. This is the first work that considers the issues of temporal schedulability and predictability, and integrates them with energy and thermal considerations, for real-time applications and SMT. Without this research, an increasingly important class of workloads would be unable to exploit an architectural advance that has provided large benefits in other domains.

这项研究涉及使用的同时多线程（SMT）处理器的软实时应用，如多媒体应用。 SMT处理器具有通过同时运行多个线程来提供高吞吐量的潜力，并且软实时应用是越来越重要的工作负载。 然而，SMT处理器在实时应用中的应用在很大程度上还没有被探索过，大多数关于SMT的工作都是为了提高吞吐量。 实时应用另外需要高可扩展性（即，满足最后期限的能力）和可预测性。 此外，这样的应用通常在能量和热功率受限的环境中运行。本研究旨在为SMT处理器开发协同调度选择和资源共享算法（以及随后的接纳测试），这些算法将（1）最大化指令吞吐量，（2）最大化可扩展性，（3）最大化执行时间可预测性，（4）最小化能量，（5）最小化热功率，用于软实时应用，如多媒体应用。 这是第一个考虑时间可预测性和可预测性问题的工作，并将其与能量和热因素相结合，用于实时应用和SMT。 如果没有这项研究，越来越重要的一类工作负载将无法利用在其他领域提供巨大好处的架构进步。