Search

U.S. national research laboratories and agencies play an integral role in advancing science and technology for the public good. The authors of this article, as research software engineers (RSEs) and allies from eight unique national R&D organizations, came together to explore RSE needs from the perspective of national institutions. We identified three key areas of improvement for future RSEs to pursue science in the national interest: community establishment, hiring and retention, and recognition. To retain and cultivate this essential talent, U.S. national institutions must evolve to support appropriate career pathways for RSEs, and to recognize and reward RSEs' work. [ABSTRACT FROM AUTHOR]

SUMMARY This paper describes PENNANT, a mini-app that operates on general unstructured meshes (meshes with arbitrary polygons), and is designed for advanced architecture research. It contains mesh data structures and physics algorithms adapted from the Los Alamos National Laboratory radiation-hydrodynamics code FLAG and gives a sample of the typical memory access patterns of FLAG. The basic capabilities and optimization approaches of PENNANT are presented. Results are shown from sample performance experiments run on serial, multicore, and graphics processing unit implementations, giving an indication of how PENNANT can be a useful tool for studies of new architectures and programming models. Copyright © 2014 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

SUMMARY There have been few efforts to date to write physics algorithms for general unstructured meshes (meshes composed of arbitrary polygons/polyhedra) on graphics processing units (GPUs). Typical strategies for GPU memory management, such as double-buffering and coalescing memory accesses, are difficult to apply to the irregular memory storage patterns of unstructured meshes. This paper presents results from an initial GPU version of a typical unstructured mesh kernel. Three different memory management strategies are described and implemented. Timing results for all three strategies are presented, in some cases showing speedups of over 20 times compared with the original CPU code.Copyright © 2012 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]