A Transactional Model for Parallel Programming of Graph Applications on Computing Clusters

Anand Tripathi, Vinit Padhye, Tara Sasank Sunkara, Jeremy Tucker, Bhagavathidhass Thirunavukarasu, Varun Pandey, Rahul R. Sharma

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Scopus citations


We present here the results of our investigation of a transactional model of parallel programming on cluster computing systems. This model is specifically targeted for graph applications with the goal of harnessing unstructured parallelism inherently present in many such problems. In this model, tasks for vertex-centric computations are executed optimistically in parallel as serializable transactions. A key-value based globally shared object store is implemented in the main memory of the cluster nodes for storing the graph data. Task computations read and modify data in the distributed global store, without any explicitly programmed message-passing in the application code. Based on this model we developed a framework for parallel programming of graph applications on computing clusters. We present here the programming abstractions provided by this framework and its architecture. Using several graph problems we illustrate the simplicity of the abstractions provided by this model. These problems include graph coloring, k-nearest neighbors, and single-source shortest path computation. We also illustrate how incremental computations can be supported by this programming model. Using these problems we evaluate the transactional programming model and the mechanisms provided by this framework.

Original languageEnglish (US)
Title of host publicationProceedings - 2017 IEEE 10th International Conference on Cloud Computing, CLOUD 2017
EditorsGeoffrey C. Fox
PublisherIEEE Computer Society
Number of pages8
ISBN (Electronic)9781538619933
StatePublished - Sep 8 2017
Event10th IEEE International Conference on Cloud Computing, CLOUD 2017 - Honolulu, United States
Duration: Jun 25 2017Jun 30 2017

Publication series

NameIEEE International Conference on Cloud Computing, CLOUD
ISSN (Print)2159-6182
ISSN (Electronic)2159-6190


Other10th IEEE International Conference on Cloud Computing, CLOUD 2017
Country/TerritoryUnited States

Bibliographical note

Funding Information:
Acknowledgements: This work was supported by NSF Award 1319333 and computing resources were provided by NSF award 1512877 and the Minnesota Supercomputing Institute.

Publisher Copyright:
© 2017 IEEE.

Copyright 2017 Elsevier B.V., All rights reserved.


  • Cluster computing
  • Concurrency control
  • Distributed Systems
  • Graph problems
  • Parallel computing
  • Transaction models


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