CSR:Small:Failure-Aware Monitoring and Management of Online Availability and Performance for Dependable Computing Clusters

CSR：Small：可靠计算集群在线可用性和性能的故障感知监控和管理摘要：该奖项是根据2009年《美国复苏和再投资法案》(Public Law 111-5)资助的。计算集群和集群联盟在规模和其组件和交互的复杂性方面持续增长。在这些系统中，部件故障成为常态，而不是例外。故障的发生及其对系统性能和运行成本的影响正成为系统设计者和管理员日益关注的问题。千万亿级计算的成功将取决于提供大规模可靠性的能力。故障管理和故障感知资源管理是理解突发、全系统现象和自我管理资源负载的关键技术，本项目研究了一套用于系统级可用性保证的故障感知监控和管理的创新技术。在这个项目中，我们将开发一个框架和机制，用于大型集群中故障感知的自主资源管理，量化故障发生之间的时间和空间相关性，以进行主动故障管理，并设计资源分配和重新配置方法，以处理现代大型复杂集群中频繁发生的组件故障导致的系统可用性和生产率问题。该项目的更广泛影响包括出版和传播研究成果和开发的软件制品。这项研究为该项目的学生和教职员工以及新墨西哥州的本科生和工程学学生提供了合作研究的机会。关于可靠的高性能计算的研究材料也将被灌输到本科生和研究生的计算机科学和工程课程中。

CSR:Small:Failure-Aware Monitoring and Management of Online Availability and Performance for Dependable Computing ClustersAbstract:This award is funded under the American Recovery and Reinvestment Act of 2009 (Public Law 111-5).Computational clusters and clusters coalitions continue to grow in scale and in the complexity of their components and interactions. In these systems, component failures become norms instead of exceptions. Failure occurrence as well as its impact on system performance and operation costs is becoming an increasingly important concern to system designers and administrators. The success of petascale computing will depend on the ability to provide dependability at scale. Failure management and failure-aware resource management are crucial techniques for understanding emergent, system-wide phenomena and self-managing resource burdens.This project investigates a set of innovative techniques on failure-aware monitoring and management for system-level availability assurance. In this project, we will develop a framework along with mechanisms for failure-aware autonomic resource management in large clusters, quantify the temporal and spatial correlations among failure occurrences for proactive failure management, and devise resource allocation and reconfiguration approaches to deal with the system availability and productivity issues caused by component failures that occur frequently in modern large and complex clusters. Broader impacts of the project include the publication and dissemination of research results and developed software artifacts. The research enables collaborative research opportunities for students and faculty in the program, as well as undergraduate science and engineering students in New Mexico. Research-based materials about dependable high-performance computing will also be instilled into the undergraduate and graduate computer science and engineering curriculum.