58 citations · 122 across the 12 of their papers we have counts for
12 papers
RCOMPSs: A Scalable Runtime System for R Code Execution on Manycore Systems
Xiran Zhang, Javier Conejero, Sameh Abdulah +5
R has become a cornerstone of scientific and statistical computing due to its extensive package ecosystem, expressive syntax, and strong support for reproducible analysis. However,…
Parallel Reduced Order Modeling for Digital Twins using High-Performance Computing Workflows
S. Ares de Parga, J. R. Bravo, N. Sibuet +9
The integration of reduced-order models (ROMs) with high-performance computing (HPC) is critical for developing digital twins, particularly for real-time monitoring and predictive…
Portability and Scalability Evaluation of Large-Scale Statistical Modeling and Prediction Software through HPC-Ready Containers
Sameh Abdulah, Jorge Ejarque, Omar Marzouk +5
HPC-based applications often have complex workflows with many software dependencies that hinder their portability on contemporary HPC architectures. In addition, these applications…
Block size estimation for data partitioning in HPC applications using machine learning techniques
Riccardo Cantini, Fabrizio Marozzo, Alessio Orsino +5
The extensive use of HPC infrastructures and frameworks for running dataintensive applications has led to a growing interest in data partitioning techniques and strategies. In fact…
The BioExcel methodology for developing dynamic, scalable, reliable and portable computational biomolecular workflows
Jorge Ejarque, Pau Andrio, Adam Hospital +4
Developing complex biomolecular workflows is not always straightforward. It requires tedious developments to enable the interoperability between the different biomolecular simulati…
Enabling Dynamic and Intelligent Workflows for HPC, Data Analytics, and AI Convergence
Jorge Ejarque, Rosa M. Badia, Loïc Albertin +34
The evolution of High-Performance Computing (HPC) platforms enables the design and execution of progressively larger and more complex workflow applications in these systems. The co…