Projects per year
Abstract
Developing parallel graph algorithms with correctness guarantees is nontrivial even for experienced programmers. Is it possible to parallelize existing sequential graph algorithms, without recasting the algorithms into a parallel model? Better yet, can the parallelization guarantee to converge at correct answers as long as the sequential algorithms provided are correct? GRAPE tackles these questions, to make parallel graph computations accessible to a large group of users. This paper presents (a) the parallel model of GRAPE, based on partial evaluation and incremental computation, and (b) a performance study, showing that GRAPE achieves performance comparable to the state-of-the-art systems.
Original language | English |
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Pages (from-to) | 30-41 |
Number of pages | 12 |
Journal | IEEE Data Engineering Bulletin |
Volume | 40 |
Issue number | 3 |
Publication status | Published - 30 Sept 2017 |
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Dive into the research topics of 'GRAPE: Conducting Parallel Graph Computations without Developing Parallel Algorithms'. Together they form a unique fingerprint.Projects
- 2 Finished
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GRACE-Resource Bounded Graph Query Answering
Fan, W. (Principal Investigator)
1/11/15 → 31/10/21
Project: Research
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VADA: Value Added Data Systems: Principles and Architecture
Libkin, L. (Principal Investigator), Buneman, P. (Co-investigator), Fan, W. (Co-investigator) & Pieris, A. (Co-investigator)
1/04/15 → 30/09/20
Project: Research