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提供数据的能力的限制。随着处理器速度的提高，I/O性能继续大大落后。因此，I/O可能仍然是高端计算的关键瓶颈。在该研究项目中，PIS建议构建流媒体B-Tree的原型，以在数据库或文件系统中部署。该原型将实现快速插入，快速范围查询和平台独立性。 PI将同时致力于如何处理不同尺寸的密钥，如何支持交易，如何扩展到多个磁盘和流程以及如何为符合缓存和内存映射的大量数据提供O/S支持。拟议的工作代表了如何操纵大量数据并克服经典I/O瓶颈的新方向。