IWOMP 2023 Program

Livermore Computing (LC), Lawrence Livermore National Laboratory’s (LLNL’s) supercomputing center, and HPE are deploying the first US exascale system focused on national security. This talk will provide an overview of the preparations for LC’s first exascale system, as well as details of its system architecture. Throughout, the talk will explore considerations for energy efficiency in large-scale systems.

As Chief Technology Officer (CTO) for Livermore Computing (LC) at Lawrence Livermore National Laboratory (LLNL), Bronis R. de Supinski formulates LLNL’s large-scale computing strategy and oversees its implementation. He frequently interacts with supercomputing leaders and oversees many collaborations with industry and academia. He has served as the Chair of the OpenMP Language Committee since 2009. In addition to his work with LLNL, Bronis is also a Professor of Exascale Computing at Queen’s University of Belfast. He is a Fellow of the ACM and the IEEE.

Weather and climate models simulate complex, multi-scale physics. They can deliver substantial value for society utilising their predictive power. However, It can take a decade or more to develop a new model. Moreover, computer architectures and the programming models used to develop the software have evolved on a much shorter timescale and become more complex. How can large science applications achieve the three P’s? In this presentation the Domain Specific Language (DSL) approach being adopted by the Met Office in developing its next generation model, LFRic, will be discussed. How OpenMP is used to on modern CPUs and how it being employed to exploit the computational power of GPUs described. To conclude, some of the implications of the use of DSLs for parallelism, for general purpose languages and programming model specifications such as OpenMP will be considered.

Dr Chris Maynard joined the Met Office in 2012 as a senior scientific software engineer. He was promoted to expert in 2013 and has led the software development of the Met Office next generation model, LFRic. Prior to 2012, at the Edinburgh Parallel Computing Centre (EPCC) he developed and optimised scientific software for supercomputers in diverse scientific fields. He obtained his PhD in 1998 from the University of Edinburgh in theoretical particle physics. His research interests include performance optimisation, parallel programming models, languages and algorithms and from 2018 until 2023 he was jointly Associate Professor in Computer Science at the University of Reading. Since August 2022 Dr Maynard has been a Met Office fellow and leads the performance optimisation of the next generation modelling system, Momentum.