Poster: High-level, one-sided programming models on MPI: a case study with global arrays and NWChem

Authors:
James Dinan;Pavan Balaji;Jeff R. Hammond;Sriram Krishnamoorthy;Vinod Tipparaju
Affiliations:
Argonne National Laboratory, Argonne, IL, USA;Argonne National Laboratory, Argonne, IL, USA;Argonne National Laboratory, Argonne, IL, USA;Pacific Northwest National Laboratory, Richland, WA, USA;Advanced Micro Devices, Austin, TX, USA
Venue:
Proceedings of the 2011 companion on High Performance Computing Networking, Storage and Analysis Companion
Year:
2011

Citing 4
Cited 0

ARMCI: A Portable Remote Memory Copy Libray for Ditributed Array Libraries and Compiler Run-Time Systems

Proceedings of the 11 IPPS/SPDP'99 Workshops Held in Conjunction with the 13th International Parallel Processing Symposium and 10th Symposium on Parallel and Distributed Processing
Advances, Applications and Performance of the Global Arrays Shared Memory Programming Toolkit

International Journal of High Performance Computing Applications
Implementing MPI-IO Atomic Mode and Shared File Pointers Using MPI One-Sided Communication

International Journal of High Performance Computing Applications
Problems with using MPI 1.1 and 2.0 as compilation targets for parallel language implementations

International Journal of High Performance Computing and Networking

Quantified Score

Hi-index	0.00

Visualization

Abstract

Global Arrays (GA) is popular high-level parallel programming model that provides data and computation management facilities to the NWChem computational chemistry suite. GA's global-view data model is supported by the ARMCI partitioned global address space runtime system, which traditionally is implemented natively on each supported platform in order to provide the best performance. The industry standard Message Passing Interface (MPI) also provides one-sided functionality and is available on virtually every supercomputing system. We present the first high performance, portable implementation of ARMCI using MPI one-sided communication. We interface the existing GA infrastructure with ARMCI-MPI and demonstrate that this approach reduces the amount of resources consumed by the runtime system, provides comparable performance, and enhances portability for applications like NWChem.