RUI: Automatic Identification of I/O Bottleneck and Run-time Optimization for Cluster Virtualization

将虚拟化技术扩展到高性能的集群平台会产生令人兴奋的新可能性。然而，虚拟化环境中的I/O效率，特别是磁盘I/O，仍然很少被理解，也很少被测试。本研究的目的是调查虚拟集群的基本技术，这些技术不仅促进严格的性能研究，而且还确定性能受到影响的地方，然后优化系统以减轻此类瓶颈的影响。本研究将极大地有助于理解虚拟I/O，识别I/O瓶颈和优化I/O，从而促进集群系统最有效地利用虚拟化技术。该项目还将通过促进研究和吸引代表性不足的群体来促进学生在科学和工程领域的职业发展，从而为社会做出贡献。

Extending virtualization technology into high-performance, cluster platforms generates exciting new possibilities. However, I/O efficiency in virtualized environments, specifically with respect to disk I/O, remains little understood and hardly tested. The objective of this research is to investigate fundamental techniques for virtual clusters that not only facilitate rigorous performance studies, but also identify places where performance is suffering and then optimize the system to lessen the impact of such bottlenecks. This research will greatly contribute to understanding virtualized I/O, identifying I/O bottlenecks and optimizing I/O, and thus facilitate the cluster systems to most effectively utilize virtualization technology. This project will also contribute to the society through promoting research and engaging under-represented groups that leads students to advancing their careers in science and engineering.