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

Qingpeng Niu, James Dinan, Sravya Tirukkovalur, Anouar Benali, Jeongnim Kim, Lubos Mitas, Lucas Wagner, P. Sadayappan

Research output: Contribution to journalArticlepeer-review


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.

Original languageEnglish (US)
Pages (from-to)3655-3671
Number of pages17
JournalConcurrency and Computation: Practice and Experience
Issue number13
StatePublished - Sep 10 2016


  • PGAS
  • global arrays
  • quantum Monte Carlo

ASJC Scopus subject areas

  • Software
  • Theoretical Computer Science
  • Computer Networks and Communications
  • Computer Science Applications
  • Computational Theory and Mathematics


Dive into the research topics of 'Global-view coefficients: a data management solution for parallel quantum Monte Carlo applications'. Together they form a unique fingerprint.

Cite this