9 citations · 17 across the 8 of their papers we have counts for
8 papers
Distributed Edge Inference: an Experimental Study on Multiview Detection
Gianluca Mittone, Giulio Malenza, Marco Aldinucci +1
Computing is evolving rapidly to cater to the increasing demand for sophisticated services, and Cloud computing lays a solid foundation for flexible on-demand provisioning. However…
Efficiently Distributed Federated Learning
Gianluca Mittone, Robert Birke, Marco Aldinucci
Federated Learning (FL) is experiencing a substantial research interest, with many frameworks being developed to allow practitioners to build federations easily and quickly. Most o…
Building an Accelerated OpenFOAM Proof-of-Concept Application using Modern C++
Giulio Malenza, Giovanni Stabile, Filippo Spiga +2
The modern trend in High-Performance Computing (HPC) involves the use of accelerators such as Graphics Processing Units (GPUs) alongside Central Processing Units (CPUs) to speed up…
Exploring energy consumption of AI frameworks on a 64-core RV64 Server CPU
Giulio Malenza, Francesco Targa, Adriano Marques Garcia +2
In today's era of rapid technological advancement, artificial intelligence (AI) applications require large-scale, high-performance, and data-intensive computations, leading to sign…
The Gaia AVU-GSR solver: a CPU + GPU parallel code toward Exascale systems
Valentina Cesare, Ugo Becciani, Alberto Vecchiato +3
The solver module of the Astrometric Verification Unit - Global Sphere Reconstruction (AVU-GSR) pipeline aims to find the astrometric parameters of stars in the Milky…
A Fault Tolerance Mechanism for Hybrid Scientific Workflows
Alberto Mulone, Doriana Medić, Marco Aldinucci
In large distributed systems, failures are a daily event occurring frequently, especially with growing numbers of computation tasks and locations on which they are deployed. The ad…
Introducing SWIRL: An Intermediate Representation Language for Scientific Workflows
Iacopo Colonnelli, Doriana Medić, Alberto Mulone +3
In the ever-evolving landscape of scientific computing, properly supporting the modularity and complexity of modern scientific applications requires new approaches to workflow exec…
DALLMi: Domain Adaption for LLM-based Multi-label Classifier
Miruna Beţianu, Abele Mălan, Marco Aldinucci +2
Large language models (LLMs) increasingly serve as the backbone for classifying text associated with distinct domains and simultaneously several labels (classes). When encountering…