Reflecting on the Goal and Baseline for Exascale Computing: A Roadmap Based on Weather and Climate Simulations

We present a roadmap towards exascale computing based on true application performance goals. It is based on two state-of-the art European numerical weather prediction models (IFS from ECMWF and COSMO from MeteoSwiss) and their current performance when run at very high spatial resolution on present-day supercomputers. We conclude that these models execute about 100–250 times too slow for operational throughput rates at a horizontal resolution of 1 km, even when executed on a full petascale system with nearly 5000 state-of-the-art hybrid GPU-CPU nodes. Our analysis of the performance in terms of a metric that assesses the efficiency of memory use shows a path to improve the performance of hardware and software in order to meet operational requirements early next decade.

[1]  S. Solomon The Physical Science Basis : Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change , 2007 .

[2]  Bjorn Stevens,et al.  Water in the atmosphere , 2013 .

[3]  A. P. Siebesma,et al.  Climate goals and computing the future of clouds , 2017 .

[4]  Nils Wedi,et al.  A framework for testing global non‐hydrostatic models , 2009 .

[5]  G. M. Stocks,et al.  Order-N multiple scattering approach to electronic structure calculations. , 1995, Physical review letters.

[6]  Torsten Hoefler,et al.  Near-global climate simulation at 1 km resolution: establishing a performance baseline on 4888 GPUs with COSMO 5.0 , 2017 .

[7]  Karl E. Taylor,et al.  An overview of CMIP5 and the experiment design , 2012 .

[8]  Hirofumi Tomita,et al.  Performance Analysis and Optimization of Nonhydrostatic ICosahedral Atmospheric Model (NICAM) on the K Computer and TSUBAME2.5 , 2016, PASC.

[9]  Peter Bauer,et al.  The quiet revolution of numerical weather prediction , 2015, Nature.

[10]  Christoph Schär,et al.  Convergence behavior of convection-resolving simulations of summertime deep moist convection over land , 2018 .

[11]  Markus Eisenbach,et al.  A scalable method for ab initio computation of free energies in nanoscale systems , 2009, Proceedings of the Conference on High Performance Computing Networking, Storage and Analysis.

[12]  C. Bretherton,et al.  Convective self‐aggregation feedbacks in near‐global cloud‐resolving simulations of an aquaplanet , 2015 .

[13]  Tobias Gysi,et al.  STELLA: a domain-specific tool for structured grid methods in weather and climate models , 2015, SC15: International Conference for High Performance Computing, Networking, Storage and Analysis.

[14]  D. Lüthi,et al.  Evaluation of the convection‐resolving climate modeling approach on continental scales , 2017 .

[15]  G. Holland,et al.  The future intensification of hourly precipitation extremes , 2016 .