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 …
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 …
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
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 …
(MpSpMV) for Nvidia V100 GPUs. The approach has three benefits:(1) It reduces …
Sparkcl: A unified programming framework for accelerators on heterogeneous clusters
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 …
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 …
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
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 …
the desire to incorporate an ever increasing number of geospatial locations to accurately …
High performance reconfigurable computing for numerical simulation and deep learning
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 …
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 …
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 …
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
Programmable hardware, in particular Field Programmable Gate Arrays (FPGAs), promises
a significant increase in computational performance for simulations in geophysical fluid …
a significant increase in computational performance for simulations in geophysical fluid …