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

Indiana University, Bloomington IN

Investigators

Abstract

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.