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

用计算机模拟和模拟物理现象现在几乎是所有科学和工程领域发展和发现的重要工具。作为理论和实验的结合点，计算现在被公认为科学研究的“第三支柱”。最近，数据分析(研究原始数据以得出有关信息的结论的科学)已成为科学发现的重要计算工具--这一工具很可能与建模和模拟一样重要，甚至更重要。在数据分析的广泛领域中，图表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与日俱增，许多研究小组都将注意力转向开发解决大规模图问题的新方法。虽然这一领域的研究成果很有价值，但已生产的软件产品往往范围有限和/或质量不足以重复使用。这个项目将通过创建GraphPack来解决这个问题，GraphPack是一个全面的统一图形库，具有连贯的用户界面和对多种最先进的计算平台的支持。这项工作将在科学和工程应用领域、依赖于图形分析的更大的社会和经济领域以及教育领域产生广泛的影响。GraphPack将提高图形算法的易用性并拓宽其适用性。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将是一个可靠和全面的工具包，适用于各种问题和体系结构，通过使当前最先进的技术随时可用来释放社区的能力。GraphPack将开发一套一致和全面的抽象，以在单峰和混合并行的环境中表达各种(通用)图形算法和数据结构。这些抽象将被合并为抽象概念，并将提供选定的具体有效实现。虽然通用性是一个重要的目标，但GraphPack还将为图形算法提供简化的用户界面，用于简单性比完全调优的性能更重要的情况。GraphPack还将基于最近的努力提供GraphBLAS接口，以提供基于线性代数概念的标准化图形操作集。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的图形算法。

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.