Buffer Management for Parallel I/O Systems

这项研究涉及与并行I/O系统的有效使用有关的问题。这些问题包括数据放置、缓存和预取以及它们在确定系统性能时的交互问题。该项目涉及开发包含这些要求的健壮的并行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相互作用的计算和I/O流的背景下确定用于资源管理的适当策略，以及制定适当的算法战略。重点研究了在线缓冲区管理和预取算法，并给出了有限前视的算法。正在考虑在数据放置和替换中使用随机化，以及在实施过程中出现的问题。算法的理论分析是基于竞争框架，比较不同的在线方法，并确定有前途的候选者。将实施合适的候选者，并对其性能进行经验验证。受影响的领域包括但不限于数据密集型应用程序，如现代数据库和多媒体系统。

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.