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XpressSpace: a programming framework for coupling partitioned global address space simulation codes
Author(s) -
Zhang Fan,
Docan Ciprian,
Bui Hoang,
Parashar Manish,
Klasky Scott
Publication year - 2013
Publication title -
concurrency and computation: practice and experience
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.309
H-Index - 67
eISSN - 1532-0634
pISSN - 1532-0626
DOI - 10.1002/cpe.3025
Subject(s) - partitioned global address space , computer science , programming paradigm , parallel computing , abstraction , distributed computing , executable , multiphysics , distributed memory , scalability , runtime system , shared memory , supercomputer , programming language , parallel programming model , concurrency , database , philosophy , physics , epistemology , finite element method , thermodynamics
SUMMARY Complex coupled multiphysics simulations are playing increasingly important roles in scientific and engineering applications such as fusion, combustion, and climate modeling. At the same time, extreme scales, increased levels of concurrency, and the advent of multicores are making programming of high‐end parallel computing systems on which these simulations run challenging. Although partitioned global address space (PGAS) languages attempt to address the problem by providing a shared memory abstraction for parallel processes within a single program, the PGAS model does not easily support data coupling across multiple heterogeneous programs, which is necessary for coupled multiphysics simulations. This paper explores how multiphysics‐coupled simulations can be supported by the PGAS programming model. Specifically, in this paper, we present the design and implementation of the XpressSpace programming system, which extends existing PGAS data sharing and data access models with a semantically specialized shared data space abstraction to enable data coupling across multiple independent PGAS executables. XpressSpace supports a global‐view style programming interface that is consistent with the PGAS memory model, and provides an efficient runtime system that can dynamically capture the data decomposition of global‐view data‐structures such as arrays, and enable fast exchange of these distributed data‐structures between coupled applications. In this paper, we also evaluate the performance and scalability of a prototype implementation of XpressSpace by using different coupling patterns extracted from real world multiphysics simulation scenarios, on the Jaguar Cray XT5 system at Oak Ridge National Laboratory. Copyright © 2013 John Wiley & Sons, Ltd.