Publications

STINGER: Spatio-Temporal Interaction Networks and Graphs (STING) Extensible Representation

D.A. Bader, J. Berry, A. Amos-Binks, D. Chavarria-Miranda, C. Hastings, K. Madduri, and S.C. Poulos
Technical Report, May 8, 2009.

Massive Streaming Data Analytics: A Case Study with Clustering Coefficients
David Ediger, Karl Jiang, Jason Riedy, and David A. Bader
4th Workshop on Multithreaded Architectures and Applications (MTAAP), Atlanta, GA, April 23, 2010.

Tracking Structure of Streaming Social Networks
David Ediger, Jason Riedy, Henning Meyerhenke, and David A. Bader
5th Workshop on Multithreaded Architectures and Applications (MTAAP), Anchorage, AK, May 20, 2011.

Tracking Structure of Streaming Social Networks
Jason Riedy, David Ediger, David A. Bader, and Henning Meyerhenke
2011 Graph Exploitation Symposium hosted by MIT Lincoln Labs, August 2011, (presentation).

STING: Spatio-Temporal Interaction Networks and Graphs for Intel Platforms
David A. Bader, Jason Riedy, Henning Meyerhenke, David Ediger, and Timothy Mattson
Presentation at Intel Corporation, Santa Clara, CA, August 2011, (presentation).

Scalable Algorithms for Analysis of Massive, Streaming Graphs
Jason Riedy and Henning Meyerhenke
SIAM Parallel Processing for Scientific Computing, January 2012, (minisymposium organizer).

Parallel Programming for Graph Analysis
David A. Bader, David Ediger, and E. Jason Riedy
The 17th ACM SIGPLAN Annual Symposium on Principles and Practice of Parallel Programming (PPoPP 2012), New Orleans, LA, February 25, 2012.

Analysis of Streaming Social Networks and Graphs on Multicore Architectures
Jason Riedy, Henning Meyerhenke, David A. Bader, David Ediger, and Timothy G. Mattson
37th International Conference on Acoustics, Speech, and Signal Processing (ICASSP), March 2012.

Opportunities and Challenges in Massive Data-Intensive Computing
From Data to Knowledge: Machine-Learning with Real-time and Streaming Applications, Berkeley, CA, May 8, 2012.

Massive Data Analytics Using Heterogeneous Computing
21st International Heterogeneity in Computing Workshop (HCW 2012), held in conjunction with The International Parallel and Distributed Processing Symposium (IPDPS 2012), Shanghai, China, May 21, 2012.

STINGER: High Performance Data Structure for Streaming Graphs
D. Ediger, R. McColl, J. Riedy, and D.A. Bader
The IEEE High Performance Extreme Computing Conference (HPEC), Waltham, MA, September 20-22, 2012.
Best Paper Award

Multithreaded Community Monitoring for Massive Streaming Graph Data
J. Riedy, and D.A. Bader
7th Workshop on Multithreaded Architectures and Applications (MTAAP), Boston, MA, May 24, 2013.

A Statistical Framework for Analyzing Streaming Graphs
J.P. Fairbanks, D. Ediger, R. McColl, D.A. Bader, E. Gilbert
ASONAM2013, Aug 24, 2013.
Code Data Raw Tweets Addendum Slides

A Brief Study of Open Source Graph Databases
R. McColl, D. Ediger, J. Poovey, D. Campbell, D.A. Bader
arXiv.org. Sept. 6, 2013.

A New Parallel Algorithm for Connected Components in Dynamic Graphs
R. McColl, O. Green, and D.A. Bader
The 20th Annual IEEE International Conference on High Performance Computing (HiPC)
Hyderabad, India, December 18-21, 2013.
Slides (PDF)

A Performance Evaluation of Open Source Graph Databases
R. McColl, D. Ediger, J. Poovey, D. Campbell, and D.A. Bader
The 1st Workshop on Parallel Programming for Analytics Applications (PPAA 2014)
held in conjunction with the 19th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming (PPoPP 2014),
Orlando, Florida, February 16, 2014.
Slides (PDF)

Streaming Graph Analytics for Real World Datasets
J.P. Fairbanks, D.A. Bader
Siam Parallel Processing 2014, Feb 21, 2014.

Features

  • Speed: millions of updates per second on commodity hardware.
  • Scale: graphs with millions to billions of vertices and edges.
  • Simplicity: simple code with provided conveniences to allow developers to focus on the algorithms and data, not the data structure.
  • Vertices with:
  • Edges with:
    • Edge Type
    • Weight
    • Timestamps
    • Adjacent vertices of any type
    • Developer-extendable attributes