Exascale Computing and Data Handling: Challenges and Opportunities for Weather and Climate Prediction

M Govett, B Bah, P Bauer, D Berod… - Bulletin of the …, 2024 - journals.ametsoc.org
The emergence of exascale computing and artificial intelligence offer tremendous potential
to significantly advance earth system prediction capabilities. However, enormous challenges …

On the use of scale‐dependent precision in Earth system modelling

T Thornes, P Düben, T Palmer - Quarterly Journal of the Royal …, 2017 - Wiley Online Library
Increasing the resolution of numerical models has played a large part in improving the
accuracy of weather and climate forecasts in recent years. Until now, this has required the …

Data-driven mixed precision sparse matrix vector multiplication for GPUs

K Ahmad, H Sundar, M Hall - ACM Transactions on Architecture and …, 2019 - dl.acm.org
We optimize Sparse Matrix Vector multiplication (SpMV) using a mixed precision strategy
(MpSpMV) for Nvidia V100 GPUs. The approach has three benefits:(1) It reduces …

Sparkcl: A unified programming framework for accelerators on heterogeneous clusters

O Segal, P Colangelo, N Nasiri, Z Qian… - arXiv preprint arXiv …, 2015 - arxiv.org
We introduce SparkCL, an open source unified programming framework based on Java,
OpenCL and the Apache Spark framework. The motivation behind this work is to bring …

[HTML][HTML] Benchmark tests for numerical weather forecasts on inexact hardware

PD Düben, TN Palmer - Monthly Weather Review, 2014 - journals.ametsoc.org
Bergman, K., and Coauthors, 2008: Exascale computing study: Technology challenges in
achieving exascale systems. AFRL Contract FA 8-650-07-C-7724, 278 pp.[Available online …

Geostatistical modeling and prediction using mixed precision tile Cholesky factorization

S Abdulah, H Ltaief, Y Sun, MG Genton… - 2019 IEEE 26th …, 2019 - ieeexplore.ieee.org
Geostatistics represents one of the most challenging classes of scientific applications due to
the desire to incorporate an ever increasing number of geospatial locations to accurately …

High performance reconfigurable computing for numerical simulation and deep learning

L Gan, M Yuan, J Yang, W Zhao, W Luk… - CCF Transactions on High …, 2020 - Springer
Due to their customizable on-chip resources, reconfigurable computing platforms such as
FPGAs are able to achieve better time-to-solution and energy-to-solution than general …

FPGA-based tsunami simulation: Performance comparison with GPUs, and roofline model for scalability analysis

K Nagasu, K Sano, F Kono, N Nakasato - Journal of Parallel and Distributed …, 2017 - Elsevier
Abstract MOST (Method Of Splitting Tsunami) is widely used to solve shallow water
equations (SWEs) for simulation of tsunami. This paper presents high-performance and …

Mixed-precision computing in the GRIST dynamical core for weather and climate modelling

S Chen, Y Zhang, Y Wang, Z Liu, X Li… - Geoscientific Model …, 2024 - gmd.copernicus.org
Atmosphere modelling applications become increasingly memory-bound due to the
inconsistent development rates between processor speeds and memory bandwidth. In this …

On the use of programmable hardware and reduced numerical precision in Earth‐system modeling

PD Düben, FP Russell, X Niu, W Luk… - Journal of Advances in …, 2015 - Wiley Online Library
Programmable hardware, in particular Field Programmable Gate Arrays (FPGAs), promises
a significant increase in computational performance for simulations in geophysical fluid …