Report on the performance portability demonstrated for the relevant Weather & Climate Dwarfs

TL;DR

This paper evaluates the performance portability of weather and climate computational patterns across diverse hardware architectures using domain-specific languages within the ESCAPE project.

Contribution

It provides an assessment of porting weather and climate dwarfs to accelerators with various programming models, focusing on performance portability and efficiency.

Findings

Portability achieved with single source code across architectures

Performance efficiency varies with programming models

Domain-specific languages facilitate energy-efficient implementations

Abstract

This document is one of the deliverable reports created for the ESCAPE project. ESCAPE stands for Energy-efficient Scalable Algorithms for Weather Prediction at Exascale. The project develops world-class, extreme-scale computing capabilities for European operational numerical weather prediction and future climate models. This is done by identifying Weather & Climate dwarfs which are key patterns in terms of computation and communication (in the spirit of the Berkeley dwarfs). These dwarfs are then optimised for different hardware architectures (single and multi-node) and alternative algorithms are explored. Performance portability is addressed through the use of domain specific languages. This deliverable provides an evaluation of the work performed within ESCAPE to port different dwarfs to accelerators, using different programming models. A key metric of the evaluation is the performance portability of the resulting porting efforts. Portability means that a single source code containing the numerical operators can be compiled and run in multiple architectures, while performance portability additionally requires that the single source code runs efficiently in all the different architectures. As results of other deliverables like D2.1, D2.4 ESCAPE provides a collection of dwarfs ported to different computing architectures like traditional CPUs, Intel XeonPhi and NVIDIA GPUs. Additionally D3.3 went through an optimization process to obtain efficient and energy efficient dwarfs. In this deliverable we present a review of the different programming models employed and their use to port various dwarfs of ESCAPE. A final evaluation of the different approaches based on different metrics like performance portability, readability of the numerical methods, efforts to port a dwarf and efficiency of the implementation obtained is reported.