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Algorithmics for Parallel Computation

并行计算算法

基本信息

批准号：
8906949
负责人：
Zvi Kedem
金额：
$ 55.08万
依托单位：
New York University
依托单位国家：
美国
项目类别：
Continuing Grant
财政年份：
1989
资助国家：
美国
起止时间：
1989-08-15 至 1994-07-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=8906949&HistoricalAwards=false
关键词：
Algorithmics Parallel Computation

项目摘要

This project investigates algorithmics for parallel computation. There are two thrusts to this work: 1. The development of a core of parallel algorithmic design paradigms and the designing of parallel algorithms for problems arising in major application domains. Prior work in this area is only a first stage and much remains to be done. This project studies many unresolved issues fundamental to parallel algorithms from an algorithmic and data structures, along with probabilistic and randomized algorithms from an algorithmic perspective. Specific areas for algorithmic research include parallel algorithms for key problems from computational geometry, pattern recognition, and programming languages. In this connection, it is crucial to develop fundamental techniques and design paradigms for parallel algorithms in application areas such as computer vision, construction of retargetable compilers, molecular biology, and rewriting systems. 2. The investigation of principles for mapping parallel models of computation onto parallel architectures. The mapping of parallel algorithms onto available and emerging technologies has to be better understood so as to gain new insights into the opportunities and constraints of parallel computing. On the algorithmic side, this calls for developing general techniques for coping with problems like synchrony, memory granularity (and memory access, in general), and communication load.

本计画研究平行计算的演算法。那里是这项工作的两个重点： 1. 并行算法设计范例核心的发展并设计了一些并行算法，用于解决应用领域。这一领域的前期工作只是第一阶段，还有许多工作要做。这个项目研究许多悬而未决的问题从算法和数据到并行算法的基础结构，沿着概率和随机算法，算法视角算法研究的特定领域包括计算中关键问题并行算法几何学、模式识别和编程语言。在这连接，这是至关重要的发展基本技术和设计并行算法在计算机等应用领域的范例视觉，可重定向编译器的构建，分子生物学，以及重写系统. 2. 并行模型映射原理的研究并行计算架构。平行映射算法到现有的和新兴的技术必须更好，了解，以便获得对机会的新见解，并行计算的限制。在算法方面，这要求开发通用技术来处理问题，同步、内存粒度（以及一般的内存访问），以及通信负载