STINGER: High performance data structure for streaming graphs

David Ediger; Rob McColl; Jason Riedy; David A. Bader

doi:10.1109/HPEC.2012.6408680

STINGER: High performance data structure for streaming graphs

David Ediger, Rob McColl, Jason Riedy, David A. Bader

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

177 Scopus citations

Abstract

The current research focus on 'big data' problems highlights the scale and complexity of analytics required and the high rate at which data may be changing. In this paper, we present our high performance, scalable and portable software, Spatio-Temporal Interaction Networks and Graphs Extensible Representation (STINGER), that includes a graph data structure that enables these applications. Key attributes of STINGER are fast insertions, deletions, and updates on semantic graphs with skewed degree distributions. We demonstrate a process of algorithmic and architectural optimizations that enable high performance on the Cray XMT family and Intel multicore servers. Our implementation of STINGER on the Cray XMT processes over 3 million updates per second on a scale-free graph with 537 million edges.

Original language	English (US)
Title of host publication	2012 IEEE Conference on High Performance Extreme Computing, HPEC 2012
DOIs	https://doi.org/10.1109/HPEC.2012.6408680
State	Published - 2012
Externally published	Yes
Event	2012 IEEE Conference on High Performance Extreme Computing, HPEC 2012 - Waltham, MA, United States Duration: Sep 10 2012 → Sep 12 2012

Publication series

Name	2012 IEEE Conference on High Performance Extreme Computing, HPEC 2012

Other

Other	2012 IEEE Conference on High Performance Extreme Computing, HPEC 2012
Country/Territory	United States
City	Waltham, MA
Period	9/10/12 → 9/12/12

All Science Journal Classification (ASJC) codes

Software

Access to Document

10.1109/HPEC.2012.6408680

Cite this

@inproceedings{06fd9d97ac4543b8ba3b1841a10c6354,

title = "STINGER: High performance data structure for streaming graphs",

abstract = "The current research focus on 'big data' problems highlights the scale and complexity of analytics required and the high rate at which data may be changing. In this paper, we present our high performance, scalable and portable software, Spatio-Temporal Interaction Networks and Graphs Extensible Representation (STINGER), that includes a graph data structure that enables these applications. Key attributes of STINGER are fast insertions, deletions, and updates on semantic graphs with skewed degree distributions. We demonstrate a process of algorithmic and architectural optimizations that enable high performance on the Cray XMT family and Intel multicore servers. Our implementation of STINGER on the Cray XMT processes over 3 million updates per second on a scale-free graph with 537 million edges.",

author = "David Ediger and Rob McColl and Jason Riedy and Bader, {David A.}",

year = "2012",

doi = "10.1109/HPEC.2012.6408680",

language = "English (US)",

isbn = "9781467315760",

series = "2012 IEEE Conference on High Performance Extreme Computing, HPEC 2012",

booktitle = "2012 IEEE Conference on High Performance Extreme Computing, HPEC 2012",

note = "2012 IEEE Conference on High Performance Extreme Computing, HPEC 2012 ; Conference date: 10-09-2012 Through 12-09-2012",

}

Ediger, D, McColl, R, Riedy, J & Bader, DA 2012, STINGER: High performance data structure for streaming graphs. in 2012 IEEE Conference on High Performance Extreme Computing, HPEC 2012., 6408680, 2012 IEEE Conference on High Performance Extreme Computing, HPEC 2012, 2012 IEEE Conference on High Performance Extreme Computing, HPEC 2012, Waltham, MA, United States, 9/10/12. https://doi.org/10.1109/HPEC.2012.6408680

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Y1 - 2012

N2 - The current research focus on 'big data' problems highlights the scale and complexity of analytics required and the high rate at which data may be changing. In this paper, we present our high performance, scalable and portable software, Spatio-Temporal Interaction Networks and Graphs Extensible Representation (STINGER), that includes a graph data structure that enables these applications. Key attributes of STINGER are fast insertions, deletions, and updates on semantic graphs with skewed degree distributions. We demonstrate a process of algorithmic and architectural optimizations that enable high performance on the Cray XMT family and Intel multicore servers. Our implementation of STINGER on the Cray XMT processes over 3 million updates per second on a scale-free graph with 537 million edges.

AB - The current research focus on 'big data' problems highlights the scale and complexity of analytics required and the high rate at which data may be changing. In this paper, we present our high performance, scalable and portable software, Spatio-Temporal Interaction Networks and Graphs Extensible Representation (STINGER), that includes a graph data structure that enables these applications. Key attributes of STINGER are fast insertions, deletions, and updates on semantic graphs with skewed degree distributions. We demonstrate a process of algorithmic and architectural optimizations that enable high performance on the Cray XMT family and Intel multicore servers. Our implementation of STINGER on the Cray XMT processes over 3 million updates per second on a scale-free graph with 537 million edges.

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M3 - Conference contribution

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BT - 2012 IEEE Conference on High Performance Extreme Computing, HPEC 2012

Y2 - 10 September 2012 through 12 September 2012

ER -

STINGER: High performance data structure for streaming graphs

Abstract

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