sponsored byACMIEEE The International Conference for High Performance 
Computing, Networking, Storage and Analysis
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SCHEDULE: NOV 15-20, 2015

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Parallel Implementation and Performance Optimization of the Configuration-Interaction Method

SESSION: Applications: Material Science


EVENT TAG(S): Applications

TIME: 11:00AM - 11:30AM

SESSION CHAIR(S): Suzanne Shontz

AUTHOR(S):Hongzhang Shan, Samuel Williams, Calvin Johnson, Kenneth McElvain, W. Erich Ormand



The configuration-interaction (CI) method, long a popular approach
to describe quantum many-body systems, is often cast as a very large sparse matrix eigenpair problem with matrices whose dimension can exceed one billion.
Such formulations place high demands on memory capacity and memory bandwidth.
In this paper, we describe an efficient, scalable implementation, BIGSTICK, which, by factorizing both the basis and the interaction into two levels, can reconstruct the
nonzero matrix elements on the fly and reduce the memory requirements by one
or two orders of magnitude allowing researchers to trade reduced resources for increased computational time.
We optimize BIGSTICK on two leading HPC platforms.
Specifically, we not only develop an empirically-driven load balancing strategy that
can evenly distribute the matrix-vector multiplication across 256K threads, we also
developed techniques that improve the performance of the
Lanczos reorthogonalization.
Combined, these optimizations improved performance by 1.3-8x depending on platform and configuration.

Chair/Author Details:

Suzanne Shontz (Chair) - University of Kansas|

Hongzhang Shan - Lawrence Berkeley National Laboratory

Samuel Williams - Lawrence Berkeley National Laboratory

Calvin Johnson - San Diego State University

Kenneth McElvain - University of California, Berkeley

W. Erich Ormand - Lawrence Livermore National Laboratory

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Paper provided by the ACM Digital Library

Paper also available from IEEE Computer Society