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SI2-SSE: GraphPack: Unified Graph Processing with Parallel Boost Graph Library, GraphBLAS, and High-Level Generic Algorithm Interfaces

SI2-SSE: GraphPack: Unified Graph Processing with Parallel Boost Graph Library, GraphBLAS, and High-Level Generic Algorithm Interfaces
SI2-SSE:GraphPack:具有 Parallel Boost Graph Library、GraphBLAS 和高级通用算法接口的统一图形处理
批准号:
1716828
负责人:
Andrew Lumsdaine
金额:
$49.94万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2016
资助国家:
美国
项目状态:
已结题
起止时间:
2016-10-01 至 2022-09-30

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中文摘要
翻译
用计算机对物理现象进行建模和仿真现在是几乎所有科学和工程领域的发展和发现的重要工具。 计算结合理论和实验,现已被公认为科学研究的“第三支柱”。 最近,数据分析(检查原始数据并得出有关该信息的结论的科学)已成为科学发现的重要计算工具-一种可能与建模和模拟一样重要的工具。 在数据分析的广泛领域中,图形的使用是描述离散对象之间关系的强大概念工具。 由于数据分析的重要性日益增长,许多研究小组已经将注意力转向开发解决大规模图形问题的新方法。 虽然这一领域的研究成果很有价值,但所产生的软件产品往往范围有限,而且/或者质量不足以重复使用。该项目将通过创建GraphPack来解决这个问题,GraphPack是一个全面的统一图形库,具有一致的用户界面并支持多个最先进的计算平台。这项工作将在科学和工程应用领域、更大的社会和经济领域(取决于图形分析)以及教育领域产生广泛的影响。GraphPack将提高易用性并扩大图算法的适用性。GraphPack的应用领域包括知识发现、基因组学、蛋白质组学、电子设计自动化、森林管理、互联网路由、电网管理等等。GraphPack将是一个可靠而全面的工具包,适用于各种各样的问题和架构,通过使当前的技术水平随时可用,释放社区的能力。GraphPack将开发一组一致且全面的抽象,以在单峰和混合并行的上下文中表达各种各样的(通用)图算法和数据结构。这些抽象将被纳入抽象概念,并将提供选定的具体有效的实现。虽然通用性是一个重要的目标,但GraphPack还将为图形算法提供一个简化的用户界面,用于简单性比完全调优性能更重要的情况。GraphPack还将提供一个GraphBLAS接口,该接口基于最近的努力,提供一组基于线性代数概念的标准化图形操作。通过提供具有高效并行实现的多个接口,GraphPack将使各种应用程序能够利用高性能图形算法。
英文摘要
Modeling and simulating physical phenomena with computers is now an important tool for development and discovery in almost all fields of science and engineering. Joining theory and experimentation, computation is now recognized as the "third pillar" of scientific research. More recently, data analytics (the science of examining raw data with the purpose of drawing conclusions about that information) has emerged as an important computational tool for scientific discovery - a tool that is likely to be as important as, if not more important than, modeling and simulation. Within the broad domain of data analytics, the use of graphs is a powerful conceptual tool that describes relationships between discrete objects. Because of the growing importance of data analytics, many research groups have turned their attention to developing new approaches for solving large-scale graph problems. While the research results in this area have been valuable, the software products that have been produced tend to be limited in scope and/or not of sufficient quality to be reused. This project will address this problem by creation of GraphPack, a comprehensive unified graph library with a coherent user interface and support for multiple state-of-the-art compute platforms. This work will have broad impacts in scientific and engineering application areas, larger social and economic areas depending on graph analytics, and in education. GraphPack will improve the ease of use and broaden the applicability of graph algorithms. Application areas include such diverse areas as knowledge discovery, genomics, proteomics, electronic design automation, forest management, Internet routing, power grid management, and many more.GraphPack will be a reliable and comprehensive toolkit applicable across a wide variety of problems and architectures that will unleash the capabilities of the community by making the current state of the art readily available. GraphPack will develop a consistent and comprehensive set of abstractions necessary to express a wide variety of (generic) graph algorithms and data structures in the context of unimodal as well as hybrid parallelism. These abstractions will be incorporated as abstract concepts, and selected concrete efficient implementations will be provided. While genericity is an important goal, GraphPack will also provide a simplified user interface for graph algorithms for the situations where simplicity is more important than fully tuned performance. GraphPack will also provide a GraphBLAS interface based on the recent efforts to provide a standardized set of graph operations based on the concepts of linear algebra. By providing multiple interfaces with efficient parallel implementations, GraphPack will enable a wide variety of applications to take advantage of high-performance graph algorithms.
期刊论文(14)
专著(0)
科研奖励(0)
会议论文
Evaluation of Graph Analytics Frameworks Using the GAP Benchmark Suite
使用 GAP 基准套件评估图形分析框架
DOI: 10.1109/iiswc50251.2020.00029
发表时间: 2020
期刊: IEEE International Symposium on Workload Characterization (IISWC 2020
影响因子: --
作者: [Azad, Ariful, Aznaveh, Mohsen Mahmoudi, Beamer, Scott, Blanco, Mark, Chen, Jinhao, D'Alessandro, Luke, Dathathri, Roshan, Davis, Tim, Deweese, Kevin, Firoz, Jesun]
通讯作者: Firoz, Jesun
DOI: 10.1145/3387902.3392634
发表时间: 2020-05
期刊: Proceedings of the 17th ACM International Conference on Computing Frontiers
影响因子: --
作者: [Xu T. Liu;M. Halappanavar;K. Barker;A. Lumsdaine;A. Gebremedhin]
通讯作者: Xu T. Liu;M. Halappanavar;K. Barker;A. Lumsdaine;A. Gebremedhin
Distributed-memory fast maximal independent set
分布式内存快速最大独立集
DOI: 10.1109/hpec.2017.8091032
发表时间: 2017
期刊: HPEC
影响因子: --
作者: [Kanewala, Thejaka, Zalewski, Marcin, Lumsdaine, Andrew]
通讯作者: Lumsdaine, Andrew
DOI: 10.1109/pact.2019.00040
发表时间: 2019-09
期刊: 2019 28th International Conference on Parallel Architectures and Compilation Techniques (PACT)
影响因子: --
作者: [J. Firoz;Marcin Zalewski;A. Lumsdaine]
通讯作者: J. Firoz;Marcin Zalewski;A. Lumsdaine
共 13 条
    SI2-SSE: GraphPack: Unified Graph Processing with Parallel Boost Graph Library, GraphBLAS, and High-Level Generic Algorithm Interfaces
    • 批准号:
      1642439
    • 项目类别:
      Standard Grant
    • 资助金额:
      $49.94万
    • 财政年份:
      2016
    • 负责人:
      Andrew Lumsdaine
    • 依托单位:
    SHF: Large: Collaborative Research: PXGL: Cyberinfrastructure for Scalable Graph Execution
    • 批准号:
      1111888
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      Continuing Grant
    • 资助金额:
      $110.0万
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      2011
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    CSR-PSCE, TM: A Declarative Approach to Managing the Complexity of Massively Parallel Programs
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      0834722
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      2008
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    Collaborative Research: Modular Metaprogramming
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      0702717
    • 项目类别:
      Standard Grant
    • 资助金额:
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    • 财政年份:
      2007
    • 负责人:
      Andrew Lumsdaine
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