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

CSR：Small：Failure-Aware Monitoring and Management of Online Availability and Performance for Dependency Computing制造商摘要：该奖项由2009年美国复苏和再投资法案（Public Law 111-5）资助。计算集群和集群联盟的规模及其组件和交互的复杂性不断增长。在这些系统中，组件故障成为常态而不是例外。故障的发生以及它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越来越重要的关注点。千万亿次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系统级突发现象和自我管理资源负担的关键技术，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沿着的机制，在大型集群中的故障感知自主资源管理，量化的时间和空间的相关性之间的故障发生的主动故障管理，并设计资源分配和重新配置的方法来处理系统的可用性和生产力的问题，经常发生在现代大型和复杂的集群组件故障。该项目更广泛的影响包括研究成果和开发的软件产品的出版和传播。该研究为该项目的学生和教师以及新墨西哥州的本科理工科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计算机科学与工程课程中。

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.