Trading Memory versus Workload Overhead in Graph Pattern Matching on Multiprocessor Systems

Alexander Krause, Frank Ebner, Dirk Habich, Wolfgang Lehner

2019

Abstract

Graph pattern matching (GPM) is a core primitive in graph analysis with many applications. Efficient processing of GPM on modern NUMA systems poses several challenges, such as an intelligent storage of the graph itself or keeping track of vertex locality information. During query processing, intermediate results need to be communicated, but target partitions are not always directly identifiable, which requires all workers to scan for requested vertices. To optimize this performance bottleneck, we introduce a Bloom filter based workload reduction approach and discuss the benefits and drawbacks of different implementations. Furthermore, we show the trade-offs between invested memory and performance gain, compared to fully redundant storage.

Paper Citation

in Harvard Style

Krause A., Ebner F., Habich D. and Lehner W. (2019). Trading Memory versus Workload Overhead in Graph Pattern Matching on Multiprocessor Systems.In Proceedings of the 8th International Conference on Data Science, Technology and Applications - Volume 1: DATA, ISBN 978-989-758-377-3, pages 400-407. DOI: 10.5220/0008116904000407

in Bibtex Style

@conference{data19,
author={Alexander Krause and Frank Ebner and Dirk Habich and Wolfgang Lehner},
title={Trading Memory versus Workload Overhead in Graph Pattern Matching on Multiprocessor Systems},
booktitle={Proceedings of the 8th International Conference on Data Science, Technology and Applications - Volume 1: DATA,},
year={2019},
pages={400-407},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0008116904000407},
isbn={978-989-758-377-3},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 8th International Conference on Data Science, Technology and Applications - Volume 1: DATA,
TI - Trading Memory versus Workload Overhead in Graph Pattern Matching on Multiprocessor Systems
SN - 978-989-758-377-3
AU - Krause A.
AU - Ebner F.
AU - Habich D.
AU - Lehner W.
PY - 2019
SP - 400
EP - 407
DO - 10.5220/0008116904000407