HEC: Collaborative Research: Techniques for Streaming File Systems and Databases

HEC：协作研究：流文件系统和数据库技术

• 批准号: 0621439
• 负责人: Michael Bender
• 金额: $ 14.14万
• 依托单位: SUNY at Stony Brook
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2006
• 资助国家: 美国
• 起止时间: 2006-08-01 至 2010-01-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0621439&HistoricalAwards=false
• 关键词: HEC; Collaborative; Research; Techniques; Streaming

The performance of many high-end computing applications is limited by the capacity of memory systems to deliver data. As processor speeds increase, I/O performance continues to lag substantially. Thus, I/O is likely to remain a critical bottleneck for high-end computing. In this research project The PIs propose to build a prototype of a streaming B-tree for deployment in a database or file system. This prototype will realize t fast insertions, fast range queries, and platform independence. The PIs will simultaneously work on how to deal with different-sized keys, how to support transactions, how to scale to multiple disks and processes, and how to provide O/S support for cache-obliviousness and memory-mapped massive data. The proposed work represents a promising new direction in how to manipulate massive data and overcome classic I/O bottlenecks.

许多高端计算应用程序的性能受到存储系统传输数据能力的限制。随着处理器速度的提高，I/O性能继续严重滞后。因此，I/O可能仍然是高端计算的关键瓶颈。在这个研究项目中，pi建议构建一个流b树的原型，用于部署在数据库或文件系统中。该原型将实现快速插入、快速范围查询和平台无关性。pi将同时研究如何处理不同大小的键，如何支持事务，如何扩展到多个磁盘和进程，以及如何为缓存遗忘和内存映射的海量数据提供O/S支持。在如何处理海量数据和克服经典I/O瓶颈方面，提出的工作代表了一个有希望的新方向。