Improving Energy Efficiency and Performance of Weather and Climate Simulations by Leveraging the Heterogeneity of Modern Systems

Le résumé fourni par la source

The increasing need for higher resolution and greater accuracy in weather forecasts and climate simulations continues to drive software and hardware developments in high-performance computing (HPC) systems. To achieve increasingly faster simulations, the adoption of hardware accelerators has proven highly effective in recent years. However, these HPC codes exhibit, in parts, divergent memory access and computation patterns. Hence, their performance benefits strongly depend on how well the software's computational characteristics align with the underlying hardware architecture. While an accelerator may be well-suited for some code regions, other architectures may achieve better performance and energy efficiency elsewhere. We therefore propose a highly heterogeneous setup for a performant and energy-efficient execution of complex HPC codes such as those used in the weather and climate domain, incorporating a variety of processor and accelerator architectures.

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