Computing k-Bisimulations for Large Graphs: A Comparison and Efficiency Analysis
Summarizing graphs w.r.t. structural features is important to reduce the graph’s size and make tasks like indexing, querying, and visualization feasible. Our generic parallel BRS algorithm efficiently summarizes large graphs w.r.t. a custom equivalence relation ∼ defined on the graph’s vertices V. Moreover, the definition of ∼ can be chained k ≥ 1 times, so the defined equivalence relation becomes a k-bisimulation. We evaluate the runtime and memory performance of the BRS algorithm for k-bisimulation with k = 1, … , 10 against two algorithms found in the literature (a sequential algorithm due to Kaushik et al. and a parallel algorithm of Sch ̈atzle et al.), which we implemented in the same software stack as BRS. We use five real-world and synthetic graph datasets containing 100 million to two billion edges. Our results show that the generic BRS algorithm outperforms the respective native bisimulation algorithms on all datasets for all k ≥ 5 and for smaller k in some cases. The BRS implementations of the two bisimulation algorithms run almost as fast as each other. Thus, the BRS algorithm is an effective parallelization of the sequential Kaushik et al. bisimulation algorithm.
Thu 20 JulDisplayed time zone: London change
15:30 - 17:15 | ICGT Session 8: Tools & ApplicationsResearch Papers at Willow Chair(s): Rachid Echahed University of Grenoble - CNRS Remote Participants: Zoom Link, YouTube Livestream | ||
15:30 30mTalk | Implementing the λGT Language: A Functional Language with Graphs as First-Class Data Research Papers DOI File Attached | ||
16:00 30mTalk | Computing k-Bisimulations for Large Graphs: A Comparison and Efficiency Analysis Research Papers DOI Pre-print | ||
16:30 30mTalk | Advanced Consistency Restoration with Higher-Order Short-Cut Rules Research Papers P: Lars Fritsche TU Darmstadt, Germany, Jens Kosiol Universität Kassel, Adrian Möller TU Darmstadt, Germany, Andy Schürr TU Darmstadt, Germany DOI | ||
17:00 15mDay closing | ICGT Conference Closing Research Papers Maribel Fernandez King's College London, Reiko Heckel University of Leicester, Chris Poskitt Singapore Management University |