Accelerating Time Integration for the Shallow Water Equations on the Sphere Using GPUs
- Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
- Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
The push towards larger and larger computational platforms has made it possible for climate simulations to resolve climate dynamics across multiple spatial and temporal scales. This direction in climate simulation has created a strong need to develop scalable timestepping methods capable of accelerating throughput on high performance computing. This study details the recent advances in the implementation of implicit time stepping of the spectral element dynamical core within the United States Department of Energy (DOE) Accelerated Climate Model for Energy (ACME) on graphical processing units (GPU) based machines. We demonstrate how solvers in the Trilinos project are interfaced with ACME and GPU kernels to increase computational speed of the residual calculations in the implicit time stepping method for the atmosphere dynamics. We demonstrate the optimization gains and data structure reorganization that facilitates the performance improvements.
- Research Organization:
- Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States). Oak Ridge Leadership Computing Facility (OLCF); Sandia National Laboratories (SNL), Albuquerque, NM, and Livermore, CA (United States)
- Sponsoring Organization:
- USDOE Office of Science (SC), Biological and Environmental Research (BER); USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR)
- Grant/Contract Number:
- AC04-94AL85000; AC05-00OR22725
- OSTI ID:
- 1214700
- Alternate ID(s):
- OSTI ID: 1265329
- Journal Information:
- Procedia Computer Science, Vol. 51, Issue C; ISSN 1877-0509
- Publisher:
- ElsevierCopyright Statement
- Country of Publication:
- United States
- Language:
- English
Web of Science
Acceleration of the IMplicit–EXplicit nonhydrostatic unified model of the atmosphere on manycore processors
|
journal | October 2017 |
Acceleration of the Implicit-Explicit Non-hydrostatic Unified Model of the Atmosphere (NUMA) on Manycore Processors | preprint | January 2017 |
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