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David A. Bader, Georgia Institute of Technology
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Graph Algorithm Building Blocks (GABB) 2017
An IEEE IPDPS 2017 Workshop, May 29, 2017, Orlando, Florida, USA
=== Scope and Goals ===
This workshop series started with the narrow goal of exploring the definition of a set of basic building blocks for graph algorithms (http://graphblas.org), analogous to the Basic Linear Algebra Subprograms (BLAS) in numerical linear algebra. Over the years, our scope has expanded. We’ve welcomed a wide range of papers into GABB covering graph computations with an emphasis on high-performance and parallel computing. We expect this trend to continue in 2017.
In particular, while we retain our focus on "building blocks" for graph computations (including those not based on linear algebra), we also welcome work that focuses on libraries and frameworks to support applications that use graph algorithms.
Our target audience is developers of graph algorithms, researchers in high-performance computing working on irregular applications, applied mathematicians working on fundamental algorithmic building blocks for graph computations, and application scientists using graphs in their computational work and data analysis.
=== Submission and Dates ===
Submitted manuscripts may not exceed ten (10) single-spaced double-column pages using 10-point size font on 8.5x11-inch pages (IEEE conference style), including figures, tables, and references (see IPDPS Call for Papers for more details). All papers will be peer-reviewed. Proceedings of the workshops are distributed at the conference and are submitted for inclusion in the IEEE Xplore Digital Library after the conference.
Important dates (updated):
Submissions due: January 31, 2017 EST 23:59pm
Notification: February 21, 2017
Final Camera-Ready Manuscript due: March 15, 2017
- Workshop web page: http://graphanalysis.org
- Submission page: https://easychair.org/co
=== Program Committee ===
An IEEE IPDPS 2017 Workshop, May 29, 2017, Orlando, Florida, USA
=== Scope and Goals ===
This workshop series started with the narrow goal of exploring the definition of a set of basic building blocks for graph algorithms (http://graphblas.org), analogous to the Basic Linear Algebra Subprograms (BLAS) in numerical linear algebra. Over the years, our scope has expanded. We’ve welcomed a wide range of papers into GABB covering graph computations with an emphasis on high-performance and parallel computing. We expect this trend to continue in 2017.
In particular, while we retain our focus on "building blocks" for graph computations (including those not based on linear algebra), we also welcome work that focuses on libraries and frameworks to support applications that use graph algorithms.
Our target audience is developers of graph algorithms, researchers in high-performance computing working on irregular applications, applied mathematicians working on fundamental algorithmic building blocks for graph computations, and application scientists using graphs in their computational work and data analysis.
=== Submission and Dates ===
Submitted manuscripts may not exceed ten (10) single-spaced double-column pages using 10-point size font on 8.5x11-inch pages (IEEE conference style), including figures, tables, and references (see IPDPS Call for Papers for more details). All papers will be peer-reviewed. Proceedings of the workshops are distributed at the conference and are submitted for inclusion in the IEEE Xplore Digital Library after the conference.
Important dates (updated):
Submissions due: January 31, 2017 EST 23:59pm
Notification: February 21, 2017
Final Camera-Ready Manuscript due: March 15, 2017
- Workshop web page: http://graphanalysis.org
- Submission page: https://easychair.org/co
=== Program Committee ===
David A. Bader, Georgia Institute of Technology
Aydın Buluç, Lawrence Berkeley National Lab (co-chair)
Jonathan Berry, Sandia National Labs
John Gilbert, UC Santa Barbara
Vasia Kalavri, KTH Royal Institute of Technology
Jeremy Kepner, MIT Lincoln Labs
Chris Long, US Department of Defense
Andrew Lumsdaine, Pacific Northwest National Lab and University of Washington
Jonathan Berry, Sandia National Labs
John Gilbert, UC Santa Barbara
Vasia Kalavri, KTH Royal Institute of Technology
Jeremy Kepner, MIT Lincoln Labs
Chris Long, US Department of Defense
Andrew Lumsdaine, Pacific Northwest National Lab and University of Washington
Tim Mattson, Intel Corp. (co-chair)
Kamesh Madduri, Penn State University
Henning Meyerhenke, Karlsruhe Institute of Technology
John Owens, University of California, Davis
Fabrizio Petrini, Inter Corp.
Semih Salihoglu, University of Waterloo
Edgar Solomonik, University of Illinois, Urbana-Champaign
Sivan Toledo, Tel-Aviv University
Kamesh Madduri, Penn State University
Henning Meyerhenke, Karlsruhe Institute of Technology
John Owens, University of California, Davis
Fabrizio Petrini, Inter Corp.
Semih Salihoglu, University of Waterloo
Edgar Solomonik, University of Illinois, Urbana-Champaign
Sivan Toledo, Tel-Aviv University
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