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HOMMEXX 1.0: a performance-portable atmospheric dynamical core for the Energy Exascale Earth System Model

Journal Article · · Geoscientific Model Development (Online)

Abstract. We present an architecture-portable and performant implementation of the atmospheric dynamical core (High-Order Methods Modeling Environment, HOMME) of the Energy Exascale Earth System Model (E3SM). The original Fortran implementation is highly performant and scalable on conventional architectures using the Message Passing Interface(MPI) and Open MultiProcessor (OpenMP) programming models.We rewrite the model in C++ and use the Kokkos library to express on-node parallelism in a largely architecture-independent implementation. Kokkos provides an abstraction of a compute node or device,layout-polymorphic multidimensional arrays, and parallel execution constructs. The new implementation achieves the same or better performance on conventional multicore computers and is portable to GPUs. We present performance data for the original and new implementations on multiple platforms, on up to 5400 compute nodes, and study several aspects of the single- and multi-node performance characteristics of the new implementation on conventional CPU (e.g., Intel Xeon), many core CPU (e.g., Intel Xeon Phi Knights Landing),and Nvidia V100 GPU.

Research Organization:
Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). National Energy Research Scientific Computing Center (NERSC)
Sponsoring Organization:
USDOE Office of Science (SC)
Grant/Contract Number:
NA0003525; AC02-05CH11231
OSTI ID:
1529244
Journal Information:
Geoscientific Model Development (Online), Journal Name: Geoscientific Model Development (Online) Journal Issue: 4 Vol. 12; ISSN 1991-9603
Publisher:
European Geosciences UnionCopyright Statement
Country of Publication:
United States
Language:
English

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Cited By (3)

Resilience and fault tolerance in high-performance computing for numerical weather and climate prediction journal February 2021
Efficient IMEX Runge-Kutta methods for nonhydrostatic dynamics preprint January 2019
Using a GPU to Accelerate a Longwave Radiative Transfer Model with Efficient CUDA-Based Methods journal September 2019

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