A global address space approach to automated data management for parallel Quantum Monte Carlo applications

Qingpeng Niu, James Dinan, Sravya Tirukkovalur, Lubos Mitas, Lucas Kyle Wagner, P. Sadayappan

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

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 (PGAS) 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 the QWalk application demonstrate the effectiveness of the data management system.

Original languageEnglish (US)
Title of host publication2012 19th International Conference on High Performance Computing, HiPC 2012
DOIs
StatePublished - Dec 1 2012
Event2012 19th International Conference on High Performance Computing, HiPC 2012 - Pune, India
Duration: Dec 18 2012Dec 21 2012

Publication series

Name2012 19th International Conference on High Performance Computing, HiPC 2012

Other

Other2012 19th International Conference on High Performance Computing, HiPC 2012
CountryIndia
CityPune
Period12/18/1212/21/12

Keywords

  • Global Arrays
  • PGAS
  • Quantum Monte Carlo

ASJC Scopus subject areas

  • Software

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