Parallel Computation and Learning

并行计算和学习

• 批准号: 9200884
• 负责人: Leslie Valiant
• 金额: $ 27万
• 依托单位: Harvard University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 1992
• 资助国家: 美国
• 起止时间: 1992-09-15 至 1996-02-29
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9200884&HistoricalAwards=false
• 关键词: Parallel; Computation; Learning

The research is in two areas: general purpose parallel computing, and models of neural computation. The first area will investigate the possibility of finding a standardizing bridging model for parallel computing, at a level intermediate between the architecture and language levels. Such a standard would insulate the development of software and hardware and thereby speed the success of the parallel computing industry. The bulk-synchronous parallel (BSP) model will be considered as the prime candidate. The second area of research will further develop a discrete model of neural computation that is both weak enough that its constituents are plausibly simulated by human cortex, yet strong enough that some basic tasks of learning and memory can be implemented on it.

本研究分两个方面：通用并行 计算和神经计算模型。 第一个领域将调查找到一个 并行计算的标准化桥接模型， 介于体系结构和语言之间的中间层 程度. 这样的标准将隔离发展， 软件和硬件，从而加快成功的 并行计算产业 批量同步并行 (BSP)模型将被视为主要候选人。 的 第二个研究领域将进一步开发一个离散模型 神经计算的能力都很弱 成分是由人类皮层模拟的，然而， 强大到足以让一些基本的学习和记忆任务 在这上面实施。