Parallel Computing and Complex Systems

9303150 Cohen该奖项用于购买一台并行计算机和几个高性能工作站，以支持布兰代斯大学计算机科学系的研究。该部门从事三个主要研究领域：并行和语言，数据压缩和人工智能。该部门是布兰代斯复杂系统中心的一部分，并行和大型复杂系统研究的主题是所有三个小组共同的。并行规划课题组的研究课题包括并行算法的设计与分析；以及高级并行语言的设计和实现，这些语言有助于快速构建易于验证正确性的程序，并且可以编译以在MIMD和SIMD机器上高效运行。数据压缩组的研究课题包括可变大小矢量的自适应矢量量化，自适应视频压缩，编码理论中的问题，包括错误弹性通信，高速数据压缩硬件的设计，以及字典编纂的上下文预测。AI小组的研究课题包括从现有数据库和文本语料库中提取数据，记忆在存储提取数据中的作用，以及构建数据驱动并表现出目标导向行为的集成代理。

9303150 Cohen This award is for the acquisition of a parallel computer and several high performance work stations to support research in the Computer Science Department of Brandeis University. The department is engaged in three major areas of research: Parallelism and Languages, Data Compression, and Artificial Intelligence. The department is part of the Brandeis Center for Complex Systems and the theme of parallelism and the study of large complex systems is common to all three groups. The research topics to be explored by the parallel programming group include the design and analysis of parallel algorithms; and the design and implementation of high level parallel languages which facilitate the rapid construction of programs that can easily be verified to be correct and which can be compiled to run efficiently on MIMD and SIMD machines. Research topics of the data compression group include adaptive vector quantization with variable size vectors, adaptive video compression, issues in coding theory that include error resilient communication, the design of high speed data compression hardware, and context prediction for lexicography. Research topics for the AI group include data extraction from existing databases and text corpora, the role of memory in storing extracted data, and the construction of integrated agents that are data driven and exhibit goal directed behavior.