Buffer Management for Parallel I/O Systems

本研究涉及与并行I/O系统的有效使用相关的问题。这些问题包括数据放置、缓存和预取问题，以及它们在决定系统性能方面的相互作用。该项目涉及开发包含这些需求的健壮的并行I/O模型，并设计新的算法以获得所需的性能水平。这包括在单个和多个交互计算和I/O流的上下文中确定适当的资源管理策略，以及开发合适的算法策略。重点是在线缓冲区管理和预取算法。在数据放置和替换中使用随机化，以及在其实施中产生的问题正在考虑之中。理论分析算法是基于一个竞争的框架来比较不同的在线方法，并确定有前途的候选人。将实施合适的候选人，并对其绩效进行实证验证。受影响的领域包括（但不限于）现代数据库和多媒体系统等数据密集型应用程序。

This research deals with issues related to the efficient use of parallel I/O systems. These include problems of data placement, caching, and prefetching and their interaction in determining system performance. The project involves the development of robust parallel I/O models that incorporate these requirements, and designing new algorithms to obtain desired performance levels. This includes identifying the appropriate policies for resource management in the context of both single and multiple interacting computational and I/O streams, and the development of suitable algorithmic strategies. The focus is on on-line buffer management and prefetching algorithms with bounded lookahead. The use of randomization in data placement and replacement, and issues arising in their implementation are under consideration. Theoretical analysis of the algorithms is based on a competitive framework to compare different on-line methods, and identify promising candidates. Suitable candidates will be implemented and their performance validated empirically. The areas of impact include, though are not restricted to, data-intensive applications like modern database and multimedia systems.