The mission of HDCRS
The HDCRS working group is part of the IEEE GRSS Earth Science Informatics (ESI) Technical Committee. 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, quantum computing and parallel programming models with specialized hardware accelerators.
HDCRS disseminates information and knowledge through educational events, special sessions and tutorials at conferences and publication activities. The group welcomes anyone interested from academia and industry to contribute to our mission.
Focus on three major fields
Supercomputing and Distributed Computing
Supercomputing is the processing of complex or data-intensive problems with a vast number of highly interconnected compute nodes that work in parallel (i.e., HPC). Distributed computing uses multiple compute resources not necessarily located in close proximity to one another but connected via Internet or other networks (e.g., cloud computing).
Specialized Hardware Computing
Specialized hardware accelerators (e.g., GPUs, FPGAs, ASICs) can perform some computing tasks more efficiently than is possible on general-purpose CPUs. Their high processing performance and energy efficiency is due to a combination of specialized operations, parallelism, efficient memory systems, and reduction of overhead.
Quantum computing exploits explicitly quantum mechanical properties (i.e., superposition, entanglement, interference) of matter to perform computations. Emerging quantum technologies (e.g., gate-based and adiabatic quantum computing) have the potential to improve performance and solve previously intractable problems.
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.
Tutorial: "From Big EO Data to Digital Twins: Hybrid AI and Quantum based Paradigms"
The tutorial will cover an introduction in quantum information theory, quantum algorithms and computers, presenting the first results and analyzing the main perspectives for EO applications.
Introduction to Scalable Deep Learning
PRACE training course on scaling machine learning and deep learning models on high performance computing systems
Quantum Computing and Programming in Two Hours
Learn in this Interactive webinar the differences between quantum and traditional computing, and computerss.
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.
Earth Sciences: Instrumentation and Facilities (EAR/IF)
The program supports requests for infrastructure that promote research and education in areas supported by the Division of Earth Sciences (EAR/IF).