Topic 4 - High Performance Architectures and Compilers

Track 4. Data analytics, AI, and Computational Science focus


* Maciej Malawski, AGH University of Science and Technology, Poland
* Radu Prodan, University of Klagenfurt, Austria


● Artificial Intelligence in the IoT-Edge-Cloud continuum
● Data management in Edge devices and the computing continuum
● Innovative applications and case studies
● Large-scale data processing applications in science, engineering, business and healthcare
● Emerging trends for computing, machine learning, approximate computing, and quantum computing.
● Parallel, replicated, and highly-available distributed databases
● Scientific data analytics (Big Data or HPC-based approaches)
● Middleware for processing large-scale data
● Programming models for parallel and distributed data analytics
● Workflow management for data analytics
● Coupling HPC simulations with in-situ data analysis
● Parallel data visualization
● Distributed and parallel transaction, query processing and information retrieval
● Internet-scale data-intensive applications
● Sensor network data management
● Data-intensive computing infrastructures
● Parallel data streaming and data stream mining
● New storage hierarchies in distributed data systems
● Parallel and distributed machine learning, knowledge discovery and data mining
● Privacy and trust in parallel and distributed data management and analytics systems
● IoT data management and analytics
● Parallel and distributed data science applications
● Data analysis in cloud and serverless models