Contribution to a conference proceedings/Contribution to a book

FZJ-2023-04350

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Challenges and Opportunities in the Adoption of High Performance Computing for Earth Observation in the Exascale Era

Cavallaro, G. (Corresponding author)FZJ* ; Sedona, R.FZJ* ; Riedel, M.FZJ* ; Lintermann, A.FZJ* ; Michielsen, K.FZJ*

2023
Publications Office of the European Union

This record in other databases:  

Please use a persistent id in citations: doi:10.2760/46796

Abstract: High-Performance Computing (HPC) enables precise analysis of large and complex Earth Observation (EO) datasets. However, the adoption of supercomputing in the EO community faces challenges from the increasing heterogeneity of HPC systems, limited expertise, and the need to leverage novel computing technologies. This paper explores the implications of exascale computing advancements and the inherent heterogeneity of HPC architectures. It highlights EU-supported projects optimizing software development and harnessing the capabilities of heterogeneous HPC configurations. Methodologies addressing challenges of modular supercomputing, large-scale Deep Learning (DL) models, and hybrid quantum-classical algorithms are presented, aiming to enhance the utilization of supercomputing in EO for improved research, industrial applications, and SME support.

---

Contributing Institute(s):

1. Jülich Supercomputing Center (JSC)

Research Program(s):

1. 5111 - Domain-Specific Simulation & Data Life Cycle Labs (SDLs) and Research Groups (POF4-511) (POF4-511)
2. RAISE - Research on AI- and Simulation-Based Engineering at Exascale (951733) (951733)
3. EUPEX - EUROPEAN PILOT FOR EXASCALE (101033975) (101033975)
4. EUROCC - National Competence Centres in the framework of EuroHPC (951732) (951732)
5. AIDAS - Joint Virtual Laboratory for AI, Data Analytics and Scalable Simulation (aidas_20200731) (aidas_20200731)

Appears in the scientific report 2023

---