Hybrid-view programming of nuclear fusion simulation code in the PGAS parallel programming language XcalableMP

Tsugane, Keisuke; Boku, Taisuke; Murai, Hitoshi; Sato, Mitsuhisa; Tang, William; Wang, Bei

doi:10.1016/j.parco.2016.05.016

Title: Hybrid-view programming of nuclear fusion simulation code in the PGAS parallel programming language XcalableMP

Full Record
Other Related Research

Abstract

Recently, the Partitioned Global Address Space (PGAS) parallel programming model has emerged as a usable distributed memory programming model. XcalableMP (XMP) is a PGAS parallel programming language that extends base languages such as C and Fortran with directives in OpenMP-like style. XMP supports a global-view model that allows programmers to define global data and to map them to a set of processors, which execute the distributed global data as a single thread. In XMP, the concept of a coarray is also employed for local-view programming. In this study, we port Gyrokinetic Toroidal Code - Princeton (GTC-P), which is a three-dimensional gyrokinetic PIC code developed at Princeton University to study the microturbulence phenomenon in magnetically confined fusion plasmas, to XMP as an example of hybrid memory model coding with the global-view and local-view programming models. In local-view programming, the coarray notation is simple and intuitive compared with Message Passing Interface (MPI) programming while the performance is comparable to that of the MPI version. Thus, because the global-view programming model is suitable for expressing the data parallelism for a field of grid space data, we implement a hybrid-view version using a global-view programming model to compute the field and a local-view programmingmore »« less

Authors:

Tsugane, Keisuke ^[1]; Boku, Taisuke ^[1]; Murai, Hitoshi ^[2]; Sato, Mitsuhisa ^[3]; Tang, William ^[4]; Wang, Bei ^[4]

Univ. of Tsukuba, Ibaraki (Japan)
RIKEN, Hyogo (Japan)
Univ. of Tsukuba, Ibaraki (Japan); RIKEN, Hyogo (Japan)
Princeton Univ., Princeton, NJ (United States)

Publication Date:: Wed Jun 01 00:00:00 EDT 2016

Research Org.:: Princeton Plasma Physics Lab. (PPPL), Princeton, NJ (United States)

Sponsoring Org.:: USDOE

OSTI Identifier:: 1332725

Resource Type:: Accepted Manuscript

Journal Name:: Parallel Computing

Additional Journal Information:: Journal Volume: 57; Journal Issue: C; Journal ID: ISSN 0167-8191

Publisher:: Elsevier

Country of Publication:: United States

Language:: English

Subject:: 97 MATHEMATICS AND COMPUTING; GTC-P; partitioned global address space; gyrokinetic PIC code; nuclear fusion simulation; XcalableMP

Citation Formats


                    Tsugane, Keisuke, Boku, Taisuke, Murai, Hitoshi, Sato, Mitsuhisa, Tang, William, and Wang, Bei. Hybrid-view programming of nuclear fusion simulation code in the PGAS parallel programming language XcalableMP.  United States: N. p., 2016. 
Web.  doi:10.1016/j.parco.2016.05.016.

Copy to clipboard


                    Tsugane, Keisuke, Boku, Taisuke, Murai, Hitoshi, Sato, Mitsuhisa, Tang, William, & Wang, Bei. Hybrid-view programming of nuclear fusion simulation code in the PGAS parallel programming language XcalableMP.  United States.  https://doi.org/10.1016/j.parco.2016.05.016

Copy to clipboard


                    Tsugane, Keisuke, Boku, Taisuke, Murai, Hitoshi, Sato, Mitsuhisa, Tang, William, and Wang, Bei. Wed .  
"Hybrid-view programming of nuclear fusion simulation code in the PGAS parallel programming language XcalableMP".  United States.  https://doi.org/10.1016/j.parco.2016.05.016.  https://www.osti.gov/servlets/purl/1332725.

Copy to clipboard


                    
@article{osti_1332725,

  title        = {Hybrid-view programming of nuclear fusion simulation code in the PGAS parallel programming language XcalableMP},

  author       = {Tsugane, Keisuke and Boku, Taisuke and Murai, Hitoshi and Sato, Mitsuhisa and Tang, William and Wang, Bei},

  abstractNote = {Recently, the Partitioned Global Address Space (PGAS) parallel programming model has emerged as a usable distributed memory programming model. XcalableMP (XMP) is a PGAS parallel programming language that extends base languages such as C and Fortran with directives in OpenMP-like style. XMP supports a global-view model that allows programmers to define global data and to map them to a set of processors, which execute the distributed global data as a single thread. In XMP, the concept of a coarray is also employed for local-view programming. In this study, we port Gyrokinetic Toroidal Code - Princeton (GTC-P), which is a three-dimensional gyrokinetic PIC code developed at Princeton University to study the microturbulence phenomenon in magnetically confined fusion plasmas, to XMP as an example of hybrid memory model coding with the global-view and local-view programming models. In local-view programming, the coarray notation is simple and intuitive compared with Message Passing Interface (MPI) programming while the performance is comparable to that of the MPI version. Thus, because the global-view programming model is suitable for expressing the data parallelism for a field of grid space data, we implement a hybrid-view version using a global-view programming model to compute the field and a local-view programming model to compute the movement of particles. Finally, the performance is degraded by 20% compared with the original MPI version, but the hybrid-view version facilitates more natural data expression for static grid space data (in the global-view model) and dynamic particle data (in the local-view model), and it also increases the readability of the code for higher productivity.},

  doi          = {10.1016/j.parco.2016.05.016},

  journal      = {Parallel Computing},

  number       = C,

  volume       = 57,

  place        = {United States},

  year         = {Wed Jun 01 00:00:00 EDT 2016},

  month        = {Wed Jun 01 00:00:00 EDT 2016}

}

Copy to clipboard

Journal Article:

Free Publicly Available Full Text

Accepted Manuscript (DOE)

Publisher's Version of Record

https://doi.org/10.1016/j.parco.2016.05.016

Other availability

Search WorldCat to find libraries that may hold this journal

Citation Metrics:

Cited by: 2 works

Citation information provided by
Web of Science

Save / Share:

Export Metadata

Save to My Library

Similar Records in DOE PAGES and OSTI.GOV collections:

Scaling Irregular Applications through Data Aggregation and Software Multithreading

Conference Morari, Alessandro ; Tumeo, Antonino ; Chavarría-Miranda, Daniel ; ...

Bioinformatics, data analytics, semantic databases, knowledge discovery are emerging high performance application areas that exploit dynamic, linked data structures such as graphs, unbalanced trees or unstructured grids. These data structures usually are very large, requiring significantly more memory than available on single shared memory systems. Additionally, these data structures are difficult to partition on distributed memory systems. They also present poor spatial and temporal locality, thus generating unpredictable memory and network accesses. The Partitioned Global Address Space (PGAS) programming model seems suitable for these applications, because it allows using a shared memory abstraction across distributed-memory clusters. However, current PGAS languagesmore »« less
https://doi.org/10.1109/IPDPS.2014.117
UPC++: A PGAS extension for C++

Conference Zheng, Y ; Kamil, A ; Driscoll, MB ; ...

Partitioned Global Address Space (PGAS) languages are convenient for expressing algorithms with large, random-access data, and they have proven to provide high performance and scalability through lightweight one-sided communication and locality control. While very convenient for moving data around the system, PGAS languages have taken different views on the model of computation, with the static Single Program Multiple Data (SPMD) model providing the best scalability. In this paper we present UPC++, a PGAS extension for C++ that has three main objectives: 1) to provide an object-oriented PGAS programming model in the context of the popular C++ language, 2) to addmore »« less
https://doi.org/10.1109/IPDPS.2014.115

Full Text Available
A Global View Programming Abstraction for Transitioning MPI Codes to PGAS Languages

Conference Mintz, Tiffany M ; Hernandez, Oscar R ; Bernholdt, David E

The multicore generation of scientific high performance computing has provided a platform for the realization of Exascale computing, and has also underscored the need for new paradigms in coding parallel applications. The current standard for writing parallel applications requires programmers to use languages designed for sequential execution. These languages have abstractions that only allow programmers to operate on the process centric local view of data. To provide suitable languages for parallel execution, many research efforts have designed languages based on the Partitioned Global Address Space (PGAS) programming model. Chapel is one of the more recent languages to be developed usingmore »« less
https://doi.org/10.1007/978-3-319-05215-1_9
A Global View Programming Abstraction for Transitioning MPI Codes to PGAS Languages

Conference Mintz, Tiffnay M. ; Hernandez, Oscar ; Berholdt, David E.

The multicore generation of scientific high performance computing has provided a platform for the realization of Exascale computing, and has also underscored the need for new paradigms in coding parallel applications. The current standard for writing parallel applications requires programmers to use languages designed for sequential execution. These languages have abstractions that only allow programmers to operate on the process centric local view of data. To provide suitable languages for parallel execution, many research efforts have designed languages based on the Partitioned Global Address Space (PGAS) programming model. Chapel is one of the more recent languages to be developed usingmore »« less
https://doi.org/10.1007/978-3-319-05215-1_9
Hybrid parallel programming with MPI and Unified Parallel C.

Conference Dinan, J ; Balaji, P ; Lusk, E ; ...

The Message Passing Interface (MPI) is one of the most widely used programming models for parallel computing. However, the amount of memory available to an MPI process is limited by the amount of local memory within a compute node. Partitioned Global Address Space (PGAS) models such as Unified Parallel C (UPC) are growing in popularity because of their ability to provide a shared global address space that spans the memories of multiple compute nodes. However, taking advantage of UPC can require a large recoding effort for existing parallel applications. In this paper, we explore a new hybrid parallel programming modelmore »« less
https://doi.org/10.1145/1787275.1787323

Similar Records