Skip to main content
SpringerLink
Log in
Book cover

International Supercomputing Conference

ISC 2014: Supercomputing pp 365–381Cite as

Fast and Energy-efficient Breadth-First Search on a Single NUMA System

  • Conference paper

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 8488))

Abstract

Breadth-first search (BFS) is an important graph analysis kernel. The Graph500 benchmark measures a computer’s BFS performance using the traversed edges per second (TEPS) ratio. Our previous nonuniform memory access (NUMA)-optimized BFS reduced memory accesses to remote RAM on a NUMA architecture system; its performance was 11 GTEPS (giga TEPS) on a 4-way Intel Xeon E5-4640 system. Herein, we investigated the computational complexity of the bottom-up, a major bottleneck in NUMA-optimized BFS. We clarify the relationship between vertex out-degree and bottom-up performance. In November 2013, our new implementation achieved a Graph500 benchmark performance of 37.66 GTEPS (fastest for a single node) on an SGI Altix UV1000 (one-rack) and 31.65 GTEPS (fastest for a single server) on a 4-way Intel Xeon E5-4650 system. Furthermore, we achieved the highest Green Graph500 performance of 153.17 MTEPS/W (mega TEPS per watt) on an Xperia-A SO-04E with a Qualcomm Snapdragon S4 Pro APQ8064.

This is a preview of subscription content, log in via an institution.

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Edmonds, J., Karp, R.M.: Theoretical improvements in algorithmic efficiency for network flow problems. Journal of the ACM 19(2), 248–264 (1972)

    Article  Google Scholar 

  2. Cormen, T., Leiserson, C., Rivest, R.: Introduction to Algorithms. MIT Press, Cambridge (1990)

    MATH  Google Scholar 

  3. Brandes, U.: A Faster Algorithm for Betweenness Centrality. J. Math. Sociol. 25(2), 163–177 (2001)

    Article  Google Scholar 

  4. Frasca, M., Madduri, K., Raghavan, P.: NUMA-Aware Graph Mining Techniques for Performance and Energy Efficiency. In: Proc. ACM/IEEE Int. Conf. High Performance Computing, Networking, Storage and Analysis (SC 2012), pp. 1–11. IEEE Computer Society (2012)

    Google Scholar 

  5. Girvan, M., Newman, M.E.J.: Community structure in social and biological networks. Proc. Natl. Acad. Sci. USA 99, 7821–7826 (2002)

    Article  MathSciNet  Google Scholar 

  6. Yasui, Y., Fujisawa, K., Goto, K., Kamiyama, N., Takamatsu, M.: NETAL: High-performance Implementation of Network Analysis Library Considering Computer Memory Hierarchy. J. Oper. Res. Soc. Japan 54(4), 259–280 (2011)

    MathSciNet  MATH  Google Scholar 

  7. Fujisawa, K., Endo, T., Yasui, Y., Sato, H., Matsuzawa, N., Matsuoka, S., Waki, H.: Petascale General Solver for Semidefinite Programming Problems with Over Two Million Constraints. In: Proc. IEEE Int. Symp. Parallel and Distributed Processing (IPDPS 2014). IEEE Computer Society (2014)

    Google Scholar 

  8. Murphy, R.C., Wheeler, K.B., Barrett, B.W., Ang, J.A.: Introducing the Graph500. In: Cray User Group 2010 Proceedings (2010)

    Google Scholar 

  9. Hoefler, T.: GreenGraph500 Submission Rules, http://green.graph500.org/greengraph500rules.pdf

  10. Leskovec, J., Chakrabarti, D., Kleinberg, J., Faloutsos, C., Ghahramani, Z.: Kronecker Graphs: An Approach to Modeling Networks. J. Mach. Learning Res. 11, 985–1042 (2010)

    MathSciNet  MATH  Google Scholar 

  11. Chakrabarti, D., Zhan, Y., Faloutsos, C.: R-MAT: A Recursive Model for Graph Mining. In: Proc. 4th SIAM Int. Conf. Data Mining, pp. 442–446. SIAM (2004)

    Google Scholar 

  12. Bader, D.A., Madduri, K.: Designing Multithreaded Algorithms for Breadth-First Search and st-connectivity on the Cray MTA-2. In: Proc. 2006 Int. Conf. Parallel Processing (ICPP 2006), pp. 523–530. IEEE Computer Society (2006)

    Google Scholar 

  13. Agarwal, V., Petrini, F., Pasetto, D., Bader, D.A.: Scalable Graph Exploration on Multicore Processors. In: Proc. ACM/IEEE Int. Conf. High Performance Computing, Networking, Storage and Analysis (SC 2010), pp. 1–11. IEEE Computer Society (2010)

    Google Scholar 

  14. Beamer, S., Asanović, K., Patterson, D.A.: Searching for a Parent Instead of Fighting Over Children: A Fast Breadth-first Search Implementation for Graph500. EECS Department, University of California, UCB/EECS-2011-117, Berkeley, CA (2011)

    Google Scholar 

  15. Beamer, S., Asanović, K., Patterson, D.A.: Direction-optimizing Breadth-first Search. In: Proc. ACM/IEEE Int. Conf. High Performance Computing, Networking, Storage and Analysis (SC 2012), p. 12. IEEE Computer Society (2012)

    Google Scholar 

  16. Yasui, Y., Fujisawa, K., Goto, K.: NUMA-optimized Parallel Breadth-first Search on Multicore Single-node System. In: Proc. IEEE Int. Conf. BigData 2013. IEEE Computer Society (2013)

    Google Scholar 

  17. Yoo, A., Chow, E., Henderson, K., McLendon, W., Hendrickson, B., Catalyurek, U.: A Scalable Distributed Parallel Breadth-first Search Algorithm on BlueGene/L. In: Proc. ACM/IEEE Conf. Supercomputing (SC 2005), p. 25. IEEE Computer Society (2005)

    Google Scholar 

  18. Buluç, A., Madduri, K.: Parallel Breadth-first Search on Distributed Memory Systems. In: Proc. ACM/IEEE Int. Conf. High Performance Computing, Networking, Storage and Analysis (SC11), p. 65. ACM (2011)

    Google Scholar 

  19. Petrini, F., Checconi, F., Willcock, J., Lumsdaine, A., Choudhury, A.R., Sabharval, Y.: Breaking the Speed and Scalability Barriers for Graph Exploration on Distributed-memory Machines. In: Proc. ACM/IEEE Int. Conf. High Performance Computing, Networking, Storage and Analysis (SC 2012), p. 13. IEEE Computer Society (2012)

    Google Scholar 

  20. Ueno, K., Suzumura, T.: Highly Scalable Graph Search for the Graph500 Benchmark. In: Proc. 21st Int. ACM Symp. High-Performance Parallel and Distributed Computing (HPDC 2012), pp. 149–160. ACM (2012)

    Google Scholar 

  21. Ueno, K., Suzumura, T.: Parallel Distributed Breadth First Search on GPU. In: Proc. IEEE Int. Conf. High Performance Computing (HiPC 2013). IEEE Computer Society (2013)

    Google Scholar 

  22. McAuley, J., Leskovec, J.: Image Labeling on a Network: Using Social-Network Metadata for Image Classification. In: Fitzgibbon, A., Lazebnik, S., Perona, P., Sato, Y., Schmid, C. (eds.) ECCV 2012, Part IV. LNCS, vol. 7575, pp. 828–841. Springer, Heidelberg (2012)

    Chapter  Google Scholar 

  23. Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed Networks in Social Media. In: CHI (2010)

    Google Scholar 

  24. Leskovec, J., Huttenlocher, D., Kleinberg, J.: Predicting Positive and Negative Links in Online Social Networks. In: WWW (2010)

    Google Scholar 

  25. The 9th DIMACS Implementation Challenge, http://www.dis.uniroma1.it/~challenge9/

  26. Backstrom, L., Huttenlocher, D., Kleinberg, J., Lan, X.: Group Formation in Large Social Networks: Membership, Growth, and Evolution. In: KDD (2006)

    Google Scholar 

  27. Leskovec, J., Lang, K., Dasgupta, A., Mahoney, M.: Community Structure in Large Networks: Natural Cluster Sizes and the Absence of Large Well-Defined Clusters. Internet Mathematics 6(1), 29–123 (2009)

    Article  MathSciNet  Google Scholar 

  28. Kwak, H., Lee, C., Park, H., Moon, S.: What is Twitter, a Social Network or a News Media? In: Proceedings of the 19th International Conference on World Wide Web (WWW 2010), pp. 591–600 (2010)

    Google Scholar 

  29. Yang, J., Leskovec, J.: Defining and Evaluating Network Communities based on Ground-truth. In: ICDM (2012)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Kyushu University, Fukuoka, Japan

    Yuichiro Yasui & Katsuki Fujisawa

  2. JAIST, Ishikawa, Japan

    Yukinori Sato

Authors
  1. Yuichiro Yasui
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Katsuki Fujisawa
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Yukinori Sato
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. MIN Faculty, Department of Informatics Scientific Computing, University of Hamburg, Bundestraße 45a, 20146, Hamburg, Germany

    Julian Martin Kunkel

  2. Deutsches Klimarechenzentrum, Bundesstraße 45a, 20146, Hamburg, Germany

    Thomas Ludwig

  3. Germany and Prometeus GmbH, University of Mannheim, Fliederstraße 2, 74915, Waibstadt, Germany

    Hans Werner Meuer

Rights and permissions

Reprints and permissions

Copyright information

© 2014 Springer International Publishing Switzerland

About this paper

Cite this paper

Yasui, Y., Fujisawa, K., Sato, Y. (2014). Fast and Energy-efficient Breadth-First Search on a Single NUMA System. In: Kunkel, J.M., Ludwig, T., Meuer, H.W. (eds) Supercomputing. ISC 2014. Lecture Notes in Computer Science, vol 8488. Springer, Cham. https://doi.org/10.1007/978-3-319-07518-1_23

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-07518-1_23

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-07517-4

  • Online ISBN: 978-3-319-07518-1

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation