High Performance Parallel I/O

该项目解决了成功部署大规模并行I/O服务器的挑战，以满足现代数据密集型应用程序的需求多媒体检索，我们和数据库服务器，可视化和图形，以及空间和时间数据库。 我们的目标是开发并行I/O系统的调度和资源管理算法，并增加我们对复杂的底层资源权衡的理解。 这些问题包括处理并行I/O的基本调度问题，包括与预取和缓存、在线调度、多用户公平服务和截止日期约束的实时并行I/O相关的问题。 其次，在这项研究中设计的算法将直接应用到多媒体系统，包括可变比特率（VBR）的视频检索，和Web，数据库和应用服务器处理大量的并发，交互I/O等领域。

This project addresses the challenges of successfully deploying large-scale parallel I/O servers to meet the demands of modern data-intensive applications multimedia retrieval, We and database servers, visualization and graphics, and spatial and temporal databases. The goals are to develop scheduling and resource management algorithms for parallel I/O systems, and increase our understanding of the complex underlying resource tradeoffs. These include basic scheduling issues dealing with parallel I/O, including those related to prefetching and caching, on -line scheduling, fair servicing of multiple users and deadline-constrained real-time parallel I/O. Secondly the algorithms designed in this research will be directly applied to areas like multimedia systems, including variable-bit rate (VBR) video retrieval, and Web, database and application servers dealing with large numbers of concurrent, interacting I/Os.