skip to main content
US FlagAn official website of the United States government
dot gov icon
Official websites use .gov
A .gov website belongs to an official government organization in the United States.
https lock icon
Secure .gov websites use HTTPS
A lock ( lock ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites.

Explore Research Products in the PAR
It may take a few hours for recently added research products to appear in PAR search results.


Title: GraphBLAS C API: Ideas for future versions of the specification
The GraphBLAS C specification provisional release 1.0 is complete. To manage the scope of the project, we had to defer important functionality to a future version of the specification. For example, we are well aware that many algorithms benefit from an inspector-executor execution strategy. We also know that users would benefit from a number of standard predefined semirings as well as more general user-defined types. These and other features are described in this paper in the context of a future release of the GraphBLAS C API.  more » « less
Award ID(s):
1629657 1740333
PAR ID:
10047271
Author(s) / Creator(s):
; ; ; ;
Date Published:
Journal Name:
2017 IEEE High Performance Extreme Computing Conference (HPEC)
Page Range / eLocation ID:
1 to 6
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. ; ; ; ; ; ; (, 2019 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW))
    In 2013, we released a position paper to launch a community effort to define a common set of building blocks for constructing graph algorithms in the language of linear algebra. This led to the GraphBLAS. We released a specification for the C programming language binding to the GraphBLAS in 2017. Since that release, multiple libraries that conform to the GraphBLAS C specification have been produced. In this position paper, we launch the next phase of this ongoing community effort: a project to assemble a set of high level graph algorithms built on top of the GraphBLAS. While many of these algorithms are well-known with high quality implementations available, they have not been assembled in one place and integrated with the GraphBLAS. We call this project the LAGraph graph algorithms project and with this position paper, we put out a call for collaborators to join us. While the initial goal is to just assemble these algorithms into a single framework, the long term goal is a library of production-worthy code, with the LAGraph library serving as an open source repository of verified graph algorithms that use the GraphBLAS. 
    more » « less
  2. ; ; ; ; ; ; (, Proceedings of the Workshop on Graphs, Architectures, Programming, and Learning)
    In 2013, we released a position paper to launch a community effort to define a common set of building blocks for constructing graph algorithms in the language of linear algebra. This led to the GraphBLAS. We released a specification for the C programming language binding to the GraphBLAS in 2017. Since that release, multiple libraries that conform to the GraphBLAS C specification have been produced. In this position paper, we launch the next phase of this ongoing community effort: a project to assemble a set of high level graph algorithms built on top of the GraphBLAS. While many of these algorithms are well-known with high quality implementations available, they have not been assembled in one place and integrated with the GraphBLAS. We call this project the LAGraph graph algorithms project and with this position paper, we put out a call for collaborators to join us. While the initial goal is to just assemble these algorithms into a single framework, the long term goal is a library of production-worthy code, with the LAGraph library serving as an open source repository of verified graph algorithms that use the GraphBLAS. 
    more » « less
  3. ; ; ; ; (, Graph Algorithms Building Blocks)
    The purpose of the GraphBLAS Forum is to standardize linear-algebraic building blocks for graph computations. An important part of this standardization effort is to translate the mathematical specification into an actual Application Programming Interface (API) that (i) is faithful to the mathematics and (ii) enables efficient implementations on modern hardware. This paper documents the approach taken by the C language specification subcommittee and presents the main concepts, constructs, and objects within the GraphBLAS API. Use of the API is illustrated by showing an implementation of the betweenness centrality algorithm. 
    more » « less
  4. ; ; ; ; (, GrAPL: Workshop on Graphs, Architectures, Programming, and Learning (IPDPSW))
    The GraphBLAS are building blocks for expressing graph algorithms in terms of linear algebra. Currently, the GraphBLAS are defined as a C API. Implementations of the GraphBLAS have exposed limitations in expressiveness and performance due to limitations in C. A move to C++ should address many of these limitations while providing a simpler API. Furthermore, for methods based on user-defined types and operators, the performance should be significantly better. C++has grown into a pervasive programming language across many domains. We see a compelling argument to define a GraphBLAS C++ API. This paper presents our roadmap for the development of a GraphBLAS C++ API. Open issues are highlighted with the goal of fostering discussion and generating feedback within the GraphBLAS user community to guide us as we develop the GraphBLAS C++ API. 
    more » « less
  5. ; ; ; ; ; ; (, 2021 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW))
    Graph algorithms can be expressed in terms of linear algebra. GraphBLAS is a library of low-level building blocks for such algorithms that targets algorithm developers. LAGraph builds on top of the GraphBLAS to target users of graph algorithms with high-level algorithms common in network analysis. In this paper, we describe the first release of the LAGraph library, the design decisions behind the library, and performance using the GAP benchmark suite. LAGraph, however, is much more than a library. It is also a project to document and analyze the full range of algorithms enabled by the GraphBLAS. To that end, we have developed a compact and intuitive notation for describing these algorithms. In this paper, we present that notation with examples from the GAP benchmark suite. 
    more » « less
  • Citation Formats
  • MLA
  • APA
  • Chicago
  • BibTeX
  • Save / Share this Record
  • Send to Email