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SCHEDULE: NOV 15-20, 2015

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BD-CATS: Big Data Clustering at Trillion Particle Scale

SESSION: Data Clustering

EVENT TYPE: Papers

EVENT TAG(S): Applications, Analytics, Simulation

TIME: 10:30AM - 11:00AM

SESSION CHAIR(S): Vijay Gadepally

AUTHOR(S):Md. Mostofa Ali Patwary, Suren Byna, Nadathur Rajagopalan Satish, Narayanan Sundaram, Zarija Lukic, Vadim Roytershteyn, Michael J. Anderson, Yushu Yao, Mr Prabhat, Pradeep Dubey

ROOM:18CD

ABSTRACT:

Modern cosmology and plasma-physics codes are now capable of
simulating trillions of particles on petascale-systems. Each timestep
output from such simulations is on the order of 10s of TBs. Summarizing
and analyzing raw particle data is challenging, and scientists
often focus on density structures, whether in the real 3D
space, or a high-dimensional phase space. In this work, we develop
a highly scalable version of the clustering algorithm DBSCAN, and
apply it to the largest datasets produced by state-of-the-art codes.
Our system, called BD-CATS, is the first one capable of performing
end-to-end analysis at trillion particle scale. We show analysis of 1.4
trillion particles from a plasma-physics simulation, and a 10,240^3
particle cosmological simulation, utilizing ~100,000 cores in 30
minutes. BD-CATS is helping infer mechanisms behind particle
acceleration in plasma-physics and holds promise for qualitatively
superior clustering in cosmology. Both of these results were previously
intractable at the trillion-particle scale.

Chair/Author Details:

Vijay Gadepally (Chair) - Massachusetts Institute of Technology|

Md. Mostofa Ali Patwary - Intel Corporation

Suren Byna - Lawrence Berkeley National Laboratory

Nadathur Rajagopalan Satish - Intel Corporation

Narayanan Sundaram - Intel Corporation

Zarija Lukic - Lawrence Berkeley National Laboratory

Vadim Roytershteyn - Space Science Institute

Michael J. Anderson - Intel Corporation

Yushu Yao - Lawrence Berkeley National Laboratory

Mr Prabhat - Lawrence Berkeley National Laboratory

Pradeep Dubey - Intel Corporation

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Paper provided by the ACM Digital Library

Paper also available from IEEE Computer Society