Abstract
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 time-stepping methods capable of accelerating throughput on high performance computing. This work details the recent advances in the implementation of implicit time stepping on a spectral element cube-sphere grid using graphical processing units (GPU) based machines. We demonstrate how solvers in the Trilinos project are interfaced with ACME and GPU kernels can significantly increase computational speed of the residual calculations in the implicit time stepping method for the shallow water equations on the sphere. We show the optimization gains and data structure reorganization that facilitates the performance improvements.
Original language | English |
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Pages (from-to) | 2046-2055 |
Number of pages | 10 |
Journal | Procedia Computer Science |
Volume | 51 |
Issue number | 1 |
DOIs | |
State | Published - 2015 |
Event | International Conference on Computational Science, ICCS 2002 - Amsterdam, Netherlands Duration: Apr 21 2002 → Apr 24 2002 |
Funding
The submitted manuscript is based upon work, authored in part by contractors [UT-Battelle LLC, manager of Oak Ridge National Laboratory (ORNL)], and supported by the U.S. Department of Energy, Office of Science, Office of BER and ASCR SciDAC project ”Multiscale Methods for Accurate, Efficient, and Scale-Aware Models of the Earth System,” and computed using OLCF computational resources. Accordingly, the U.S. Government retains a nonexclusive, royalty-free license to publish or reproduce the published form of this contribution, or allow others to do so, for U.S. Government purposes. This study used the resources of the Oak Ridge Leadership Computing Facility at the Oak Ridge National Laboratory, which is supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC05-00OR22725. labelsect:bib
Funders | Funder number |
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UT-Battelle LLC | |
U.S. Department of Energy | |
Office of Science | |
Advanced Scientific Computing Research | |
Biological and Environmental Research | |
Oak Ridge National Laboratory |
Keywords
- GPU
- Implicit timestepping
- Trilinos