77 citations · 274 across the 26 of their papers we have counts for
26 papers
Accelerating Sharded Data Parallelism at Scale with Federated Learning
Gianluca Mittone, Marco Aldinucci
The symbiotic scaling of artificial intelligence models and high-performance computing systems continually creates algorithmic challenges in their convergence. Foundation models (F…
The MPI + CUDA Gaia AVU-GSR Parallel Solver Toward Next-generation Exascale Infrastructures
Valentina Cesare, Ugo Becciani, Alberto Vecchiato +4
We ported to the GPU with CUDA the Astrometric Verification Unit-Global Sphere Reconstruction (AVU-GSR) Parallel Solver developed for the ESA Gaia mission, by optimizing a previous…
Benchmarking FedAvg and FedCurv for Image Classification Tasks
Bruno Casella, Roberto Esposito, Carlo Cavazzoni +1
Classic Machine Learning techniques require training on data available in a single data lake. However, aggregating data from different owners is not always convenient for different…
Experimenting with Normalization Layers in Federated Learning on non-IID scenarios
Bruno Casella, Roberto Esposito, Antonio Sciarappa +2
Training Deep Learning (DL) models require large, high-quality datasets, often assembled with data from different institutions. Federated Learning (FL) has been emerging as a metho…
Model-Agnostic Federated Learning
Gianluca Mittone, Walter Riviera, Iacopo Colonnelli +2
Since its debut in 2016, Federated Learning (FL) has been tied to the inner workings of Deep Neural Networks (DNNs). On the one hand, this allowed its development and widespread us…
Experimenting with Emerging RISC-V Systems for Decentralised Machine Learning
Gianluca Mittone, Nicolò Tonci, Robert Birke +10
Decentralised Machine Learning (DML) enables collaborative machine learning without centralised input data. Federated Learning (FL) and Edge Inference are examples of DML. While to…
A Federated Learning Benchmark for Drug-Target Interaction
Gianluca Mittone, Filip Svoboda, Marco Aldinucci +2
Aggregating pharmaceutical data in the drug-target interaction (DTI) domain has the potential to deliver life-saving breakthroughs. It is, however, notoriously difficult due to reg…
The Gaia AVU-GSR parallel solver: preliminary studies of a LSQR-based application in perspective of exascale systems
Valentina Cesare, Ugo Becciani, Alberto Vecchiato +6
The Gaia Astrometric Verification Unit-Global Sphere Reconstruction (AVU-GSR) Parallel Solver aims to find the astrometric parameters for 10 stars in the Milky Way, the a…
Modelling Biological and Ecological Systems with the Calculus of Wrapped Compartments
Marco Aldinucci, Livio Bioglio, Cristina Calcagno +8
The modelling and analysis of biological systems has deep roots in Mathematics, specifically in the field of Ordinary Differential Equations. Alternative approaches based on formal…
Neural Transformers for Intraductal Papillary Mucosal Neoplasms (IPMN) Classification in MRI images
Federica Proietto Salanitri, Giovanni Bellitto, Simone Palazzo +9
Early detection of precancerous cysts or neoplasms, i.e., Intraductal Papillary Mucosal Neoplasms (IPMN), in pancreas is a challenging and complex task, and it may lead to a more f…
FedER: Federated Learning through Experience Replay and Privacy-Preserving Data Synthesis
Matteo Pennisi, Federica Proietto Salanitri, Giovanni Bellitto +4
In the medical field, multi-center collaborations are often sought to yield more generalizable findings by leveraging the heterogeneity of patient and clinical data. However, recen…
Bringing AI pipelines onto cloud-HPC: setting a baseline for accuracy of COVID-19 AI diagnosis
Iacopo Colonnelli, Barbara Cantalupo, Concetto Spampinato +2
HPC is an enabling platform for AI. The introduction of AI workloads in the HPC applications basket has non-trivial consequences both on the way of designing AI applications and on…
StreamFlow: cross-breeding cloud with HPC
Iacopo Colonnelli, Barbara Cantalupo, Ivan Merelli +1
Workflows are among the most commonly used tools in a variety of execution environments. Many of them target a specific environment; few of them make it possible to execute an enti…
Pushing the boundaries of parallel Deep Learning -- A practical approach
Paolo Viviani, Maurizio Drocco, Marco Aldinucci
This work aims to assess the state of the art of data parallel deep neural network training, trying to identify potential research tracks to be exploited for performance improvemen…
OCCAM: a flexible, multi-purpose and extendable HPC cluster
Marco Aldinucci, Stefano Bagnasco, Stefano Lusso +3
The Open Computing Cluster for Advanced data Manipulation (OCCAM) is a multi-purpose flexible HPC cluster designed and operated by a collaboration between the University of Torino…
A Formal Semantics for Data Analytics Pipelines
Maurizio Drocco, Claudia Misale, Guy Tremblay +1
In this report, we present a new programming model based on Pipelines and Operators, which are the building blocks of programs written in PiCo, a DSL for Data Analytics Pipelines.…
A parallel pattern for iterative stencil + reduce
M. Aldinucci, M. Danelutto, M. Drocco +4
We advocate the Loop-of-stencil-reduce pattern as a means of simplifying the implementation of data-parallel programs on heterogeneous multi-core platforms. Loop-of-stencil-reduce…
A Comparison of Big Data Frameworks on a Layered Dataflow Model
Claudia Misale, Maurizio Drocco, Marco Aldinucci +1
In the world of Big Data analytics, there is a series of tools aiming at simplifying programming applications to be executed on clusters. Although each tool claims to provide bette…
FastFlow tutorial
Marco Aldinucci, Marco Danelutto, Massimo Torquati
FastFlow is a structured parallel programming framework targeting shared memory multicores. Its layered design and the optimized implementation of the communication mechanisms used…
On Designing Multicore-aware Simulators for Biological Systems
Marco Aldinucci, Mario Coppo, Ferruccio Damiani +3
The stochastic simulation of biological systems is an increasingly popular technique in bioinformatics. It often is an enlightening technique, which may however result in being com…
StochKit-FF: Efficient Systems Biology on Multicore Architectures
Marco Aldinucci, Andrea Bracciali, Pietro Liò +2
The stochastic modelling of biological systems is an informative, and in some cases, very adequate technique, which may however result in being more expensive than other modelling…
Porting Decision Tree Algorithms to Multicore using FastFlow
Marco aldinucci, Salvatore Ruggieri, Massimo Torquati
The whole computer hardware industry embraced multicores. For these machines, the extreme optimisation of sequential algorithms is no longer sufficient to squeeze the real machine…
Accelerating sequential programs using FastFlow and self-offloading
Marco Aldinucci, Marco Danelutto, Peter Kilpatrick +2
FastFlow is a programming environment specifically targeting cache-coherent shared-memory multi-cores. FastFlow is implemented as a stack of C++ template libraries built on top of…
Toward a Formal Semantics for Autonomic Components
Marco Aldinucci, Emilio Tuosto
Autonomic management can improve the QoS provided by parallel/ distributed applications. Within the CoreGRID Component Model, the autonomic management is tailored to the automatic…