A high‐level library for multidimensional arrays programming in computational science
Imen Chakroun, Tom Vander Aa, Bruno De Fraine, Tom Haber, Pascal Costanza, Roel Wuyts · Concurrency and Computation Practice and Experience · 2018
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.