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Title: Global‐view coefficients: a data management solution for parallel quantum Monte Carlo applications

Journal Article · · Concurrency and Computation. Practice and Experience
DOI:https://doi.org/10.1002/cpe.3748· OSTI ID:1786171
 [1]; ORCiD logo [2];  [1];  [3];  [4];  [5];  [6];  [1]
  1. Department of Computer Science and Engineering The Ohio State University Columbus OH USA
  2. Mathematics and Computer Science Division Argonne National Laboratory Lemont IL USA
  3. Argonne Leadership Computing Facility Argonne National Laboratory Lemont IL USA
  4. Materials Science and Technology and Computational Chemistry and Materials Division Oak Ridge National Laboratory Oak Ridge TN USA
  5. Deptartment of Physics North Carolina State University Raleigh NC USA
  6. Deptartment of Physics University of Illinois at Urbana‐Champaign Champaign IL USA
+ Show Author Affiliations

Summary Quantum Monte Carlo (QMC) applications perform simulation with respect to an initial state of the quantum mechanical system, which is often captured by using a cubic B‐spline basis. This representation is stored as a read‐only table of coefficients and accesses to the table are generated at random as part of the Monte Carlo simulation. Current QMC applications, such as QWalk and QMCPACK, replicate this table at every process or node, which limits scalability because increasing the number of processors does not enable larger systems to be run. We present a partitioned global address space approach to transparently managing this data using Global Arrays in a manner that allows the memory of multiple nodes to be aggregated. We develop an automated data management system that significantly reduces communication overheads, enabling new capabilities for QMC codes. Experimental results with QWalk and QMCPACK demonstrate the effectiveness of the data management system. Copyright © 2016 John Wiley & Sons, Ltd.

Sponsoring Organization:
USDOE
Grant/Contract Number:
FC02-06ER2575; AC02-06CH11357; FG02-12ER46875
OSTI ID:
1786171
Journal Information:
Concurrency and Computation. Practice and Experience, Journal Name: Concurrency and Computation. Practice and Experience Vol. 28 Journal Issue: 13; ISSN 1532-0626
Publisher:
Wiley Blackwell (John Wiley & Sons)Copyright Statement
Country of Publication:
United Kingdom
Language:
English
Citation Metrics:
Cited by: 3 works
Citation information provided by
Web of Science

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