The mission of HDCRS
The HDCRS working group is part of the IEEE GRSS Earth Science Informatics (ESI) Technical Committee which aim is to advance the application of informatics to geosciences and remote sensing.
The main objective of HDCRS is to connect a community of interdisciplinary researchers in remote sensing who are specialized on high-performance and distributed computing, disruptive computing and parallel programming models with specialized hardware. HDCRS disseminates information and knowledge through educational events, special sessions and tutorials at conferences and publication activities. Interested persons from academia and industry are welcome to join and contribute to the group .
Focus on three major fields
Supercomputing and Distributed Computing
Supercomputing refers to the processing of massively complex or data-laden problems using a high number of compute systems working in parallel (i.e., a supercomputer). In distributed computing ,the computer resources are geographically spread around the World and connected via the internet (e.g., cloud computing).
Specialized Hardware Computing
Specialized hardware devices such as GPUs and FPGAs bridge the gap towards onboard and real-time analysis of remote sensing data. The increasing computational demands of remote sensing applications can benefit from these compact hardware devices, taking advantage of their relatively low cost as compared to supercomputers.
Quantum computing exploits explicitly quantum mechanical properties (superposition, entanglement, interference) of matter in order to do calculations. It has the potential to improve performance, decrease computational costs and solve previously intractable problems in remote sensing.
Special Issue on ''Quantum Computing for Earth Observation''
This special issue aims to introduce this extraordinary field to the GRSS community, present the current state-of-the-art in quantum technologies, identify challenges and opportunities, and engage the quantum community for EO in the long-term.
Tutorial on ''Scalable Machine Learning with High Performance and Cloud Computing''
The tutorial provides a complete overview of supercomputing and cloud computing technologies which can solve remote sensing problems that require fast and highly scalable methods.
Special session on ''Data Intensive Computing for Remote Sensing''
This special session collects papers in the most advanced and trendy areas interested in exploiting new high-performance and distributed computing technologies and algorithms to expedite the processing and analysis of big remote sensing data.
Interactive High-Performance Computing with Jupyter
PRACE training course on Interactive High-Performance Computing with Jupyter
Big Data from Space (BiDS)
Conference on research and innovation development in the field of Big Data from Space including technical aspects and applications.
Fully-funded PhD position
Research of advanced deep transfer learning methods for complex learning scenarios in applications from remote sensing. The position is funded by the EU project Center of Excellence' 'Research on AI- and Simulation-Based Engineering at Exascale''.
Internal Research Fellow (PostDoc) for Earth Observation Innovative Digital Technologies
The Φ-lab focuses on innovative AI and Quantum Computing activities which promise to deliver visible impact on the Earth observation sector.