research-article

A GraphBLAS implementation in pure Java

Authors:

Florentin Dörre,

Alexander Krause,

Martin JunghannsAuthors Info & Claims

GRADES-NDA '21: Proceedings of the 4th ACM SIGMOD Joint International Workshop on Graph Data Management Experiences & Systems (GRADES) and Network Data Analytics (NDA)

Article No.: 5, Pages 1 - 9

https://doi.org/10.1145/3461837.3464627

Published: 20 June 2021 Publication History

Abstract

Analyzing connected data in forms of graphs is more relevant than ever. To allow users to write their own custom graph algorithms, graph computation models such as GraphBLAS have been developed. Unfortunately, the popular Java programming language was mostly neglected by existing GraphBLAS implementations so far. To overcome that issue, we present our implementation of essential GraphBLAS concepts in the Java programming language in this paper. For our purpose, we extended the linear algebra library Efficient Java Matrix Library (EJML). To show the benefits of our implementation, we compare us against existing graph algorithm libraries in Java using real world graphs and three graph algorithms.

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Cited By

Milner CJananthan HKepner JGadepally VJones MMichaleas PPatel RPisharody SWachman GPentland A(2024)Teaching Network Traffic Matrices in an Interactive Game Environment2024 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW)10.1109/IPDPSW63119.2024.00097(459-467)Online publication date: 27-May-2024
https://doi.org/10.1109/IPDPSW63119.2024.00097
Zalipynis R(2021)Array DBMSProceedings of the VLDB Endowment10.14778/3476311.347640414:12(3186-3189)Online publication date: 1-Jul-2021
https://dl.acm.org/doi/10.14778/3476311.3476404

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Published In

cover image ACM Conferences

GRADES-NDA '21: Proceedings of the 4th ACM SIGMOD Joint International Workshop on Graph Data Management Experiences & Systems (GRADES) and Network Data Analytics (NDA)

June 2021

77 pages

ISBN:9781450384773

DOI:10.1145/3461837

Program Chairs:
Vasiliki Kalavri
Boston University
,
Nikolay Yakovets
Eindhoven Univeristy of Technology

Copyright © 2021 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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SIGMOD: ACM Special Interest Group on Management of Data

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 20 June 2021

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SIGMOD/PODS '21

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SIGMOD

SIGMOD/PODS '21: International Conference on Management of Data

June 20 - 25, 2021

Virtual Event, China

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Cited By

Milner CJananthan HKepner JGadepally VJones MMichaleas PPatel RPisharody SWachman GPentland A(2024)Teaching Network Traffic Matrices in an Interactive Game Environment2024 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW)10.1109/IPDPSW63119.2024.00097(459-467)Online publication date: 27-May-2024
https://doi.org/10.1109/IPDPSW63119.2024.00097
Zalipynis R(2021)Array DBMSProceedings of the VLDB Endowment10.14778/3476311.347640414:12(3186-3189)Online publication date: 1-Jul-2021
https://dl.acm.org/doi/10.14778/3476311.3476404

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