SCHEDULE: NOV 10-16, 2012
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Breaking the Speed and Scalability Barriers for Graph Exploration on Distributed-Memory Machines
SESSION: Breadth First Search
EVENT TYPE: Papers
TIME: 11:00AM - 11:30AM
SESSION CHAIR: Umit Catalyurek
AUTHOR(S):Fabio Checconi, Fabrizio Petrini, Jeremiah Willcock, Andrew Lumsdaine, Yogish Sabharwal, Anamitra Choudhury
ROOM:255-EF
ABSTRACT:
In this paper, we describe the challenges involved in
designing a family of highly-efficient Breadth-First Search (BFS)
algorithms and in optimizing these algorithms on the latest two
generations of Blue Gene machines, Blue Gene/P and Blue Gene/Q.
With our recent winning Graph 500 submissions in November
2010, June 2011, and November 2011, we have achieved unprecedented
scalability results in both space and size. On Blue Gene/P,
we have been able to parallelize the largest BFS search presented
in the literature, running a scale 38 problem with 238 vertices and
242 edges on 131,072 processing cores. Using only four racks of an
experimental configuration of Blue Gene/Q, we have achieved the
fastest processing rate reported to date on a BFS search, 254 billion
edges per second on 65,536 processing cores. This paper describes
the algorithmic design and the main classes of optimizations that
we have used to achieve these results.
Chair/Author Details:
Umit Catalyurek (Chair) - Ohio State University
Fabio Checconi - IBM T.J. Watson Research Center
Fabrizio Petrini - IBM T.J. Watson Research Center
Jeremiah Willcock - Indiana University
Andrew Lumsdaine - Indiana University
Yogish Sabharwal - IBM India
Anamitra Choudhury - IBM India
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Breaking the Speed and Scalability Barriers for Graph Exploration on Distributed-Memory Machines
SESSION: Breadth First Search
EVENT TYPE:
TIME: 11:00AM - 11:30AM
SESSION CHAIR: Umit Catalyurek
AUTHOR(S):Fabio Checconi, Fabrizio Petrini, Jeremiah Willcock, Andrew Lumsdaine, Yogish Sabharwal, Anamitra Choudhury
ROOM:255-EF
ABSTRACT:
In this paper, we describe the challenges involved in
designing a family of highly-efficient Breadth-First Search (BFS)
algorithms and in optimizing these algorithms on the latest two
generations of Blue Gene machines, Blue Gene/P and Blue Gene/Q.
With our recent winning Graph 500 submissions in November
2010, June 2011, and November 2011, we have achieved unprecedented
scalability results in both space and size. On Blue Gene/P,
we have been able to parallelize the largest BFS search presented
in the literature, running a scale 38 problem with 238 vertices and
242 edges on 131,072 processing cores. Using only four racks of an
experimental configuration of Blue Gene/Q, we have achieved the
fastest processing rate reported to date on a BFS search, 254 billion
edges per second on 65,536 processing cores. This paper describes
the algorithmic design and the main classes of optimizations that
we have used to achieve these results.
Chair/Author Details:
Umit Catalyurek (Chair) - Ohio State University
Fabio Checconi - IBM T.J. Watson Research Center
Fabrizio Petrini - IBM T.J. Watson Research Center
Jeremiah Willcock - Indiana University
Andrew Lumsdaine - Indiana University
Yogish Sabharwal - IBM India
Anamitra Choudhury - IBM India
Click here to download .ics calendar file