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Database Processing on a Cube-Connected Multicomputer System(Computer and Information Science)

立方体连接的多计算机系统上的数据库处理（计算机与信息科学）

基本信息

批准号：
8710855
负责人：
Chaitanya Baru
金额：
$ 5.96万
依托单位：
Regents of the University of Michigan - Ann Arbor
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
1987
资助国家：
美国
起止时间：
1987-09-01 至 1990-02-28
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=8710855&HistoricalAwards=false
关键词：
Database Processing Cube Connected Multicomputer

项目摘要

This project investigates novel algorithms for database processing in multicomputer systems. Parallel architectures for database processing need to incorporate both parallel processors (CPU's) and parallel I/O (disk access) capability. This research is focused on a boolean n-cube connected architecture, with a disk attached to each node, thereby providing parallel I/O. The need to support parallel I/O gives rise to two important issues: data combination and non-uniform data distribution. Since the cube interconnection subsumes many other structures such as trees, rings, etc., this property is exploited to efficiently support data combination in a variety of database operations such as Selection, Aggregation, Join, and Projection. The research involves both analytic and simulation study of various database operations under a variety of initial and intermediate data distribution conditions, using a 64-node hypercucbe. Modern fabrication techniques make it possible to produce hundreds or even thousands of computing elements (processors) at low cost. The significance of this research is that parallel processing algorithms are critical to harnessing the fabrication potential to produce real benefit for applications such as database processing. Support is provided under the Research Initiation activity for New Investigators.

本项目研究数据库的新算法多计算机系统中的处理。并行架构，数据库处理需要合并两个并行处理器 (CPU的）和并行I/O（磁盘访问）能力。本研究是专注于一个布尔n立方体连接的架构，磁盘连接到每个节点，从而提供并行I/O。的支持并行I/O的需求带来了两个重要问题：数据合并和非均匀数据分布。以来立方体互连包含许多其它结构，树木、年轮等，该特性被有效地利用，支持各种数据库操作中数据组合，如选择、聚合、连接和投影。研究包括各种数据库分析和模拟研究各种初始和中间数据下的操作分布条件，使用64节点hypercube。现代制造技术使生产数百甚至数千个计算元件（处理器），低成本本研究的意义在于，处理算法对于利用制造为应用产生真实的效益的潜力，数据库处理研究提供支持新研究者的启动活动。