Location via proxy:   [ UP ]  
[Report a bug]   [Manage cookies]                
skip to main content
research-article

SPIRIT: a runtime system for distributed irregular tree applications

Published: 27 February 2016 Publication History

Abstract

Repeated, depth-first traversal of trees is a common algorithmic pattern in an important set of applications from diverse domains such as cosmological simulations, data mining, and computer graphics. As these applications operate over massive data sets, it is often necessary to distribute the trees to process all of the data.
In this work, we introduce SPIRIT, a runtime system to ease the writing of distributed tree applications. SPIRIT automates the challenging tasks of tree distribution, optimizing communication and parallelizing independent computations. The common algorithmic pattern in tree traversals is exploited to effectively schedule parallel computations and improve locality. As a result, pipeline parallelism in distributed traversals is identified, which is complemented by load-balancing, and locality-enhancing, message aggregation optimizations. Evaluation of SPIRIT on tree traversal in Point Correlation (PC) shows a scalable system, achieving speedups upto 38x on a 16-node, 64 process system compared to a 1-node, baseline configuration. We also find that SPIRIT results in substantially less communication and achieves significant performance improvements over implementations in other distributed graph systems.

References

[1]
J. Chhugani, C. Kim, H. Shukla, J. Park, P. Dubey, J. Shalf, and H. D. Simon. Billion-particle simd-friendly two-point correlation on large-scale hpc cluster systems. In Proceedings of the International Conference on High Performance Computing, Networking, Storage and Analysis, page 1, 2012.
[2]
D. Gregor and A. Lumsdaine. The parallel bgl: A generic library for distributed graph computations. Parallel Object-Oriented Scientific Computing (POOSC), 2:1--18, 2005.
[3]
Y. Jo and M. Kulkarni. Automatically enhancing locality for tree traversals with traversal splicing. In Proceedings of the ACM international conference on Object oriented programming systems languages and applications, OOPSLA '12, pages 355--374, New York, NY, USA, 2012.
[4]
M. Kulkarni. The Galois System: optimistic parallelization of irregular programs. PhD thesis, Ithaca, NY, USA, 2008. Adviser-Pingali, Keshav.
[5]
Y. Low, D. Bickson, J. Gonzalez, C. Guestrin, A. Kyrola, and J. M. Hellerstein. Distributed graphlab: A framework for machine learning and data mining in the cloud. Proc. VLDB Endow., 5(8):716--727, 2012.
[6]
G. Malewicz, M. H. Austern, A. J. Bik, J. C. Dehnert, I. Horn, N. Leiser, and G. Czajkowski. Pregel: A system for large-scale graph processing. In Proceedings of the 2010 ACM SIGMOD International Conference on Management of Data, pages 135--146, New York, NY, USA, 2010.
[7]
J. H. Reif. Depth-first search is inherently sequential. Information Processing Letters, 20(5):229--234, 1985.

Recommendations

Comments

Information & Contributors

Information

Published In

cover image ACM SIGPLAN Notices
ACM SIGPLAN Notices  Volume 51, Issue 8
PPoPP '16
August 2016
405 pages
ISSN:0362-1340
EISSN:1558-1160
DOI:10.1145/3016078
Issue’s Table of Contents
  • cover image ACM Conferences
    PPoPP '16: Proceedings of the 21st ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming
    February 2016
    420 pages
    ISBN:9781450340922
    DOI:10.1145/2851141
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 27 February 2016
Published in SIGPLAN Volume 51, Issue 8

Check for updates

Author Tags

  1. distributed computing
  2. irregular programs

Qualifiers

  • Research-article

Funding Sources

Contributors

Other Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

  • Downloads (Last 12 months)5
  • Downloads (Last 6 weeks)0
Reflects downloads up to 15 Oct 2024

Other Metrics

Citations

View Options

Get Access

Login options

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

Media

Figures

Other

Tables

Share

Share

Share this Publication link

Share on social media