Abstract
High performance computing frameworks utilizing CPUs, Nvidia GPUs, and/or Intel Xeon Phis necessitate portable and scalable solutions for application developers. Nvidia GPUs in particular present numerous portability challenges with a different programming model, additional memory hierarchies, and partitioned execution units among streaming multiprocessors. This work presents modifications to the Uintah asynchronous many-task runtime and the Kokkos portability library to enable one single codebase for complex multiphysics applications to run across different architectures. Scalability and performance results are shown on multiple architectures for a globally coupled radiation heat transfer simulation, ranging from a single node to 16,384 Titan compute nodes.
| Original language | English |
|---|---|
| Pages (from-to) | 303-319 |
| Number of pages | 17 |
| Journal | Journal of Computational Science |
| Volume | 27 |
| DOIs | |
| State | Published - Jul 2018 |
Funding
This material is based upon work supported by the Department of Energy, National Nuclear Security Administration , under Award Number(s) DE-NA0002375. This research used resources of the Oak Ridge Leadership Computing Facility, which is a DOE Office of Science User Facility supported under Contract DE-AC05-00OR22725. We would like to acknowledge Oak Ridge Leadership Computing Facility ALCC awards CMB109, “Large Scale Turbulent Clean Coal Combustion” and CSC188, “Demonstration of the Scalability of Programming Environments By Simulating Multi-Scale Applications” for time on Titan. This research used resources of the Argonne Leadership Computing Facility, which is a DOE Office of Science User Facility supported under Contract DE-AC02-06CH11357. Additional support for J. H. comes from the Intel Parallel Computing Centers program. Additionally, we would like to thank all those involved with Uintah past and present.
Keywords
- Asynchronous many-task runtime
- GPU
- Portability
- Radiative heat transfer
- Scalability