Interoperable Data Files for High-Performance Computing

该提案解决了提供对可互操作数据文件的高性能访问的问题。 科学数据库一直被吹捧为科学应用所面临的I/O问题的解决方案。 这些系统基于关系、面向对象或混合数据模型，有助于缩短数据访问时间。 在某些情况下，它们甚至允许并行访问数据库。 然而，这些系统没有解决互操作性的问题。 我们建议综合我们以前在这两个领域的独立研究，以创建支持高性能并行访问和互操作性的数据文件。 更重要的是，我们建议开发访问方法作为系统接口的一部分，其中包含高性能的集体I/O的概念，可以从访问模式中学习以进一步提高未来访问模式的性能的功能，以及允许用户定义抽象文件类型并指定布局和其他提示的数据描述语言，这些提示将在保持互操作性的同时提高访问能力。

This proposal addresses the problem of providing high-performance access to interoperable data files. Scientific databases have been touted as being the solution to the I/O problems faced by scientific applications. Based on relational, object-oriented, or hybird data models, these systems help to improve the access times to the data. In some cases they even permit parallel access to the database. However, these systems do not address the problem of interoperability. We propose to synthesize our previously-independent research in both of these areas to create data files that support both high-performance parallel access and interoperability. More importantly, we propose to develop access methods as a part of the system interface that incorporate the notion of collective I/O for high-performance, functions that can learn from access patterns to further improve on performance for future access patterns, and a data description language that allows users to define abstract file types and specify layouts and other hints that will improve access while maintaining interoperability.