Special Session on HPC, Data Lakes, and Computing Continuum
(HPC-ComCon 2024)

Modern computing techniques can store, process, and analyse large amounts of and diversity of data. These techniques could correlate a variety of datasets to gain insight and offer new services and applications. Among others, technologies that are playing a major role in gaining these capabilities are the Internet of Things, Edge Computing, Cloud Computing, High Performance Computing and High Performance Data Analytics. Although developed independently, the integration and interconnection of these technologies, referred to as Computing Continuum, has accelerated the growth of data-driven applications and unleashed numerous opportunities for industry, science, individuals, and society at large. This system of systems can execute complex tasks across multiple systems and multiple technologies. At the same time, numerous challenges are associated. Big data lakes are the inevitable progression of data warehouse technologies that many industries have started to adopt as data management systems. Recently, various research works have arisen on big data lakes under the three research axes, i.e., models, frameworks, and techniques. Also, other research has targeted the marketplace and data pricing problems with all their associated difficulties.

➤ Topics of interest included, but are not limited to
Application development for integrated HPC continuum use cases
Data Marketplaces and Data Lakes
Compute, storage, and communication systems management
Resource management and optimization
AI-powered workflow resource optimization
Managing computation, Scheduling
Performance and scalability
Security of platforms
Artificial intelligence and ML in the HPC continuum
Workflow deployment, orchestration, and monitoring
Programming paradigms/models, algorithms
Bridging Cloud-HPC
Data transfer/communication in the HPC continuum
Software interoperability, compatibility
Management of heterogeneous systems
Energy efficiency and green computing on Computing Continuum
Storing and processing data across the continuum
Assessment and statistical analysis of ensemble models

➤ Organizers
Prof. Dr. Pascal Bouvry, Faculty of Science, Technology and Medicine Department of Computer Science University of Luxembourg, Luxembourg
Dr. Johnatan E. Pecero, Faculty of Science, Technology and Medicine Department of Computer Science University of Luxembourg, Luxembourg
Dr. Grégoire Danoy, Faculty of Science, Technology and Medicine Department of Computer Science University of Luxembourg, Luxembourg
Prof. Dr. Jacek Blazewicz, Institute of Computing Science Poznan University of Technology, Poland
Prof. Dr. Jedrzej Musial, Institute of Computing Science Poznan University of Technology, Poland
Dr. Arijit Roy, Department of Computer Science and Engineering Indian Institute of Technology Patna, India

➤ Program Committee :
Harald Koestler, Department of Computer Science, FAU, Erlangen, Germany
Apivadee Piyatumrong, National Electronics and Computer Technology Center, Bangkok, Thailand
Kittichai Lavangnananda, School of Information Technology, King Mongkut’s University of Technology
Albert Zomaya, University of Sydney, Australia
El-Ghazali Talb, University of Lille, France
Frédéric Guinand, University of Le Havre, France
Samee Khan, Mississippi State University, USA
Ezhilmathi Krishnasamy, University of Luxembourg, Luxembourg
Julien Schleich, University of Luxembourg, Luxembourg
Carlos Jaime Barrios Hernandez, Universidad Industrial de Santander, Bucaramanga, Colombia
Andrei Tchernykh, CISESE Research Center, Ensenada, Mexico
Sergio Nesmachnow, Universidad de la Republica, Uruguay
Ovidiu-Christian Marcu, University of Luxembourg, Luxembourg
Joanna Kołodziej, Cracow University of Technology, Cracow, Poland
Horacio González-Vélez, National College of Ireland, Ireland
Alfredo Goldman, Sao Paolo University, Brazil
Arijit Roy, Indian Institute of Information Technology, Sri City, India
Panagiotis Sarigiannidis, University of Western Macedonia, Greece
Matthias Brust, University of Luxembourg, Luxembourg
François Coallier, Ecole de Technologie Supérieure, Université du Quebec, Canada