This protocol describes the development of the Sustainable Scientific Machine-learning Reporting Toolkit (SSMART). This will be a checklist-based reporting guideline for scientific machine learning (SML) based studies in the physical sciences. The development process will consist of five phases. In phase one, a systematic review will be executed to appraise the current state of reporting methods and energy use in SML-based studies. In phase two, an online Delphi exercise will be used to identify the items to be co…

In this paper, we explore the performance of the main optimising compiler toolchains currently available for high-performance AArch64 processors, namely the Arm Compiler for Linux (ACFL), GNU, LLVM and the NVIDIA HPC (NVHPC) compilers, on the recently released NVIDIA Grace CPU. We evaluate the performance of these compilers using the RAJA Performance Suite (RAJAPerf) to understand where each compiler does best and why. We find that compilers mostly generate well optimised code on baseline sequential runs, with the…

The use of Artificial Intelligence (AI) and Machine Learning (ML) as part of scientific workloads is becoming increasingly widespread. It is imperative to understand how to configure AI and ML applications on HPC systems to optimise their performance and energy efficiency, thereby minimising their environmental impact. In this study, we use MLPerf HPC’s DeepCAM benchmark to assess and explore the energy efficiency of ML applications on different hardware platforms. We highlight the challenges that, despite growing…

This study presents scaling results and a performance analysis across different supercomputers and compilers for the Met Office weather and climate model, LFRic. The model is shown to scale to large numbers of nodes which meets the design criteria, that of exploitation of parallelism to achieve good scaling. The model is written in a Domain-Specific Language, embedded in modern Fortran and uses a Domain-Specific Compiler, PSyclone, to generate the parallel code. The performance analysis shows the effect of choice …

Sparse matrix storage formats have evolved over the years to better exploit the particular strengths of different hardware architectures or to better match the sparsity patterns of matrices, with the aim to optimize operations on the matrices. However, the integration of new formats in existing source code is an invasive procedure that often requires a complete re-writing of the code. Morpheus introduces a framework that abstracts the notion of the different formats in order to optimize the performance of the spar…