SCHEDULE: NOV 15-20, 2015

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Exploring Network Optimizations for Large-Scale Graph Analytics

SESSION: Graph Analytics on HPC systems

EVENT TYPE: Papers

EVENT TAG(S): Architectures, Clouds and Distributed Computing, Analytics

TIME: 3:30PM - 4:00PM

SESSION CHAIR(S): Dilma Da Silva

AUTHOR(S):Xinyu Que, Fabio Checconi, Fabrizio Petrini, Xing Liu, Daniele Buono

ROOM:19AB

ABSTRACT:

Graph analytics are arguably one of the most demanding workloads for
high-performance interconnection networks. The fine-grained,
high-rate communication patterns expose the limits of the protocol
stacks. The load and communication imbalance generate hard-to-predict
hot-spots, and require computational steering due to unpredictable
data distributions. In this paper we present a lightweight
communication library, implemented on the metal of BlueGene/Q and
Power775/PERCS that we have used to support large-scale graph
algorithms up to 96K processing nodes and 6 million threads. With this
library we have explored several techniques, including computation in
the network for special collective communication patterns such as
parallel prefix and wavefront algorithms. The experimental results
show significant performance improvements when compared to equally
optimized MPI implementations.

Chair/Author Details:

Dilma Da Silva (Chair) - Texas A&M University|

Xinyu Que - IBM Corporation

Fabio Checconi - IBM Corporation

Fabrizio Petrini - IBM Corporation

Xing Liu - IBM Corporation

Daniele Buono - IBM Corporation

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Paper provided by the ACM Digital Library

Paper also available from IEEE Computer Society