CAREER: Scalable Combinatorial Scientific Computing

职业：可扩展的组合科学计算

• 批准号: 0643969
• 负责人: Umit Catalyurek
• 金额: $ 40万
• 依托单位: Ohio State University Research Foundation -DO NOT USE
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-03-01 至 2013-02-28
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0643969&HistoricalAwards=false
• 关键词: CAREER; Scalable; Combinatorial; Scientific; Computing

CAREER: Scalable Combinatorial Scientific ComputingPI: Umit V. CatalyurekAbstract:Combinatorial algorithms are an important enabling technology for scientific computing, especially for large-scale problems and high performance computing. The overarching goals of this project are development of 1) a mathematical and computational infrastructure for solving graph and hypergraph-based combinatorial problems on extreme-scale architectures and 2) techniques and tools for analysis of complex and multivalent interaction networks.In this project, effective novel combinatorial models, such as hypergraph, k-partite hypergraph and directed hypergraph models, are developed for modeling complex workflows (computation, communication and data dependencies, and data access patterns) of large-scale scientific applications and the complicated interactions of chemical and biological entities. New scalable algorithms, based on a multi-level framework, are designed for graph and hypergraph clustering and partitioning, and dynamic load balancing problems. Scalable graph coloring techniques and graph search-based analysis techniques for semantic graphs are developed on top of an extensible distributed memory graph/hypergraph runtime middleware.The technical impact of this work will be in designing efficient models and algorithms for the above mentioned computationally challenging problems. Hence, in many fields of science the work will allow the use of parallel computing where it was not possible before. The education and outreach activities of this project include a summer program for high school students from underrepresented groups, significant expansion of graduate courses, undergraduate student involvement in research projects, and graduate student education through multi-disciplinary projects. The implementations of the novel models and algorithms developed in the project will be distributed as open source to maximize the impact and dissemination of the research results.

职业：可扩展的组合科学计算PI：Umit V. Catalyrek摘要：组合算法是科学计算的重要使能技术，特别是对于大规模问题和高性能计算。该项目的主要目标是：1）开发一个数学和计算基础设施，用于解决极端规模架构上的图和基于超图的组合问题; 2）开发用于分析复杂和多价相互作用网络的技术和工具。在该项目中，有效的新型组合模型，如超图，k-部超图和有向超图模型，是为模拟大规模科学应用的复杂工作流程（计算，通信和数据依赖性，以及数据访问模式）以及化学和生物实体的复杂相互作用而开发的。基于一个多层次的框架，新的可扩展的算法，设计用于图和超图的聚类和划分，以及动态负载平衡问题。在可扩展的分布式内存图/超图运行时中间件的基础上，开发了可扩展的图着色技术和基于图搜索的语义图分析技术，为上述计算难题设计了有效的模型和算法。因此，在许多科学领域，这项工作将允许在以前不可能的地方使用并行计算。该项目的教育和推广活动包括为来自代表性不足群体的高中生提供暑期课程，显著扩大研究生课程，本科生参与研究项目，以及通过多学科项目进行研究生教育。该项目中开发的新模型和算法的实现将作为开源分发，以最大限度地发挥研究成果的影响和传播。