A high‐level library for multidimensional arrays programming in computational science. (9th January 2018)

• Record Type: Journal Article
• Authors: Chakroun, Imen; Vander Aa, Tom; De Fraine, Bruno; Haber, Tom; Costanza, Pascal; Wuyts, Roel
• Other Names: Trunfio Giuseppe A. guestEditor.; Spataro William guestEditor.; Sirakoulis Georgios Ch. guestEditor.
• Is Part Of: Concurrency and computation. Volume 30:Number 7(2018)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2018-01-09
• Subjects: high performance computing -- hybrid computing -- multidimensional arrays -- PGAS programming model; Parallel processing (Electronic computers) -- Periodicals; Parallel computers -- Periodicals; 004.35
• DOI: 10.1002/cpe.4376
• Languages: English
• ISSNs: 1532-0626

Abstract

Summary: This paper describes ExaShark, a hybrid n‐dimensional array toolkit offered as a high‐level library for scientists to compute large‐scale simulations. It offers a global‐array–like interface while its runtime can be configured to use shared memory threading techniques, inter‐node distribution techniques, or combinations of both. ExaShark takes advantage of the latest HPC technologies, helping to scale to future generation systems. It has been used to develop several scientific applications including stencil codes, solvers, and matrix factorization algorithms. These applications are used to demonstrate that it improves on the state of the art by providing a user‐friendly, generic API without sacrificing performance.