Global adaptive quadrature for the approximate computation of multidimensional integrals on a distributed-memory multiprocessor. - Marco Lapegna (Concurr. Pract. Exp., 1992)

A Scalabel Parallel Algorithm for the Adaptive Multidimensional Quadrature. - Marco Lapegna; Alessandra D'Alessio (PPSC, 1993)

A parallel row projection solver for large sparse linear systems. - Marco D'Apuzzo; Marco Lapegna (PDP, 1995)

Scalability and Load Balancing in Adaptive Algorithms for Multidimensional Integration. - Marco D'Apuzzo; Marco Lapegna; Almerico Murli (Parallel Comput., 1997)

PAMIHR. A Parallel FORTRAN Program for Multidimensional Quadrature on Distributed Memory Architectures. - Giuliano Laccetti; Marco Lapegna (Euro-Par, 1999)

Advanced environments for parallel and distributed applications: a view of current status. - Pasqua D'Ambra; Marco Danelutto; Daniela di Serafino; Marco Lapegna (Parallel Comput., 2002)

Parallel Components for Multidimensional Quadrature: Some Experiences. - Pasqua D'Ambra; Daniela di Serafino; Marco Lapegna (Parallel Distributed Comput. Pract., 2002)

Integrating MPI-based numerical software into an advanced parallel computing environment. - Pasqua D'Ambra; Marco Danelutto; Daniela di Serafino; Marco Lapegna (PDP, 2003)

A Performance Contract System in a Grid Enabling, Component Based Programming Environment. - Pasquale Caruso; Giuliano Laccetti; Marco Lapegna (EGC, 2005)

Block Matrix Multiplication in a Distributed Computing Environment: Experiments with NetSolve. - Luisa D'Amore; Giuliano Laccetti; Marco Lapegna (PPAM, 2005)

Monitoring and Migration of a PETSc-based Parallel Application for Medical Imaging in a Grid computing PSE. - Almerico Murli; Vania Boccia; Luisa Carracciuolo; Luisa D'Amore; Giuliano Laccetti; Marco Lapegna (Grid-Based Problem Solving Environments, 2006)

Implementing Effective Data Management Policies in Distributed and Grid Computing Environments. - Luisa Carracciuolo; Giuliano Laccetti; Marco Lapegna (PPAM, 2007)

The MedIGrid PSE in an LCG/gLite environment. - Almerico Murli; Vania Boccia; Luisa Carracciuolo; Luisa D'Amore; Giuliano Laccetti; Marco Lapegna (ISPA, 2008)

HADAB: Enabling Fault Tolerance in Parallel Applications Running in Distributed Environments. - Vania Boccia; Luisa Carracciuolo; Giuliano Laccetti; Marco Lapegna; Valeria Mele (PPAM (1), 2011)

A Double Adaptive Algorithm for Multidimensional Integration on Multicore Based HPC Systems. - Giuliano Laccetti; Marco Lapegna; Valeria Mele; Diego Romano; Almerico Murli (Int. J. Parallel Program., 2012)

A Study on Adaptive Algorithms for Numerical Quadrature on Heterogeneous GPU and Multicore Based Systems. - Giuliano Laccetti; Marco Lapegna; Valeria Mele; Diego Romano (PPAM (1), 2013)

Virtualizing CUDA Enabled GPGPUs on ARM Clusters. - Raffaele Montella; Giulio Giunta; Giuliano Laccetti; Marco Lapegna; Carlo Palmieri; Carmine Ferraro; Valentina Pelliccia (PPAM (2), 2015)

A Loosely Coordinated Model for Heap-Based Priority Queues in Multicore Environments. - Giuliano Laccetti; Marco Lapegna; Valeria Mele (Int. J. Parallel Program., 2016)

Relaxing the Correctness Conditions on Concurrent Data Structures for Multicore CPUs. A Numerical Case Study. - Giuliano Laccetti; Marco Lapegna; Valeria Mele; Raffaele Montella (PPAM (2), 2017)

Using GPGPU Accelerated Interpolation Algorithms for Marine Bathymetry Processing with On-Premises and Cloud Based Computational Resources. - Livia Marcellino; Raffaele Montella; Sokol Kosta; Ardelio Galletti; Diana Di Luccio; Vincenzo Santopietro; Mario Ruggieri; Marco Lapegna; Luisa D'Amore; Giuliano Laccetti (PPAM (2), 2017)

Accelerating Linux and Android applications on low-power devices through remote GPGPU offloading. - Raffaele Montella; Sokol Kosta; David Oro; Javier Vera; Carles Fernández; Carlo Palmieri; Diana Di Luccio; Giulio Giunta; Marco Lapegna; Giuliano Laccetti (Concurr. Comput. Pract. Exp., 2017)

An Approach to Forecast Queue Time in Adaptive Scheduling: How to Mediate System Efficiency and Users Satisfaction. - Giovanni Battista Barone; Vania Boccia; Davide Bottalico; Rosanna Campagna; Luisa Carracciuolo; Giuliano Laccetti; Marco Lapegna (Int. J. Parallel Program., 2017)

Guest Editorial for Hybrid Parallelism in New HPC Systems. - Giuliano Laccetti; Ian T. Foster; Marco Lapegna; Paul Messina; Raffaele Montella; Almerico Murli (Int. J. Parallel Program., 2017)

On the Virtualization of CUDA Based GPU Remoting on ARM and X86 Machines in the GVirtuS Framework. - Raffaele Montella; Giulio Giunta; Giuliano Laccetti; Marco Lapegna; Carlo Palmieri; Carmine Ferraro; Valentina Pelliccia; Cheol-Ho Hong; Ivor T. A. Spence; Dimitrios S. Nikolopoulos (Int. J. Parallel Program., 2017)

A Scalable Unified Model for Dynamic Data Structures in Message Passing (Clusters) and Shared Memory (multicore CPUs) Computing environments. - Giuliano Laccetti; Marco Lapegna; Raffaele Montella (CCGrid, 2018)

Implementation of a non-linear solver on heterogeneous architectures. - Luisa Carracciuolo; Marco Lapegna (Concurr. Comput. Pract. Exp., 2018)

Models, algorithms, and tools for highly heterogeneous computing environments. - Giuliano Laccetti; Marco Lapegna; Raffaele Montella; Sokol Kosta (Concurr. Comput. Pract. Exp., 2018)

A High Performance Modified K-Means Algorithm for Dynamic Data Clustering in Multi-core CPUs Based Environments. - Giuliano Laccetti; Marco Lapegna; Valeria Mele; Diego Romano (IDCS, 2019)

An Adaptive Strategy for Dynamic Data Clustering with the K-Means Algorithm. - Marco Lapegna; Valeria Mele; Diego Romano (PPAM (2), 2019)

An adaptive algorithm for high-dimensional integrals on heterogeneous CPU-GPU systems. - Giuliano Laccetti; Marco Lapegna; Valeria Mele; Raffaele Montella (Concurr. Comput. Pract. Exp., 2019)

The Challenge of Onboard SAR Processing: A GPU Opportunity. - Diego Romano; Valeria Mele; Marco Lapegna (ICCS (3), 2020)

Coastal Marine Data Crowdsourcing Using the Internet of Floating Things: Improving the Results of a Water Quality Model. - Diana Di Luccio; Angelo Riccio; Ardelio Galletti; Giuliano Laccetti; Marco Lapegna; Livia Marcellino; Sokol Kosta; Raffaele Montella (IEEE Access, 2020)

Designing a GPU-parallel algorithm for raw SAR data compression: A focus on parallel performance estimation. - Diego Romano; Marco Lapegna; Valeria Mele; Giuliano Laccetti (Future Gener. Comput. Syst., 2020)

Performance enhancement of a dynamic K-means algorithm through a parallel adaptive strategy on multicore CPUs. - Giuliano Laccetti; Marco Lapegna; Valeria Mele; Diego Romano; Lukasz Szustak (J. Parallel Distributed Comput., 2020)

DClu: A Direction-Based Clustering Algorithm for VANETs Management. - Marco Lapegna; Silvia Stranieri (IMIS, 2021)

Dynamic workload prediction and distribution in numerical modeling of solidification on multi-/manycore architectures. - Kamil Halbiniak; Tomasz Olas; Lukasz Szustak; Adam Kulawik; Marco Lapegna (Concurr. Comput. Pract. Exp., 2021)

Special Issue on High-end Heterogeneous Architectures, Methodologies, and Algorithms (HHAMA20). - Sokol Kosta; Giuliano Laccetti; Marco Lapegna; Valeria Mele; Raffaele Montella (Concurr. Comput. Pract. Exp., 2021)

Clustering Algorithms on Low-Power and High-Performance Devices for Edge Computing Environments. - Marco Lapegna; Walter Balzano; Norbert Meyer; Diego Romano (Sensors, 2021)

A GPU-Parallel Image Coregistration Algorithm for InSar Processing at the Edge. - Diego Romano; Marco Lapegna (Sensors, 2021)

Toward a high-performance clustering algorithm for securing edge computing environments. - Giuliano Laccetti; Marco Lapegna; Raffaele Montella (CCGRID, 2022)

Enabling the CUDA Unified Memory model in Edge, Cloud and HPC offloaded GPU kernels. - Raffaele Montella; Diana Di Luccio; Ciro Giuseppe De Vita; Gennaro Mellone; Marco Lapegna; Giuliano Laccetti; Sokol Kosta; Giulio Giunta (CCGRID, 2022)

A hybrid clustering algorithm for high-performance edge computing devices [Short]. - Giuliano Laccetti; Marco Lapegna; Diego Romano (ISPDC, 2022)

A GPU Accelerated Hyperspectral 3D Convolutional Neural Network Classification at the Edge with Principal Component Analysis Preprocessing. - Gianluca De Lucia; Marco Lapegna; Diego Romano (PPAM (2), 2022)

Towards explainable AI for hyperspectral image classification in Edge Computing environments. - Gianluca De Lucia; Marco Lapegna; Diego Romano (Comput. Electr. Eng., 2022)

Competitive-blockchain-based parking system with fairness constraints. - Walter Balzano; Marco Lapegna; Silvia Stranieri; Fabio Vitale (Soft Comput., 2022)

Citizen Science for the Sea with Information Technologies: An Open Platform for Gathering Marine Data and Marine Litter Detection from Leisure Boat Instruments. - Ciro Giuseppe De Vita; Gennaro Mellone; Dante D. Sánchez-Gallegos; Giuseppe Coviello; Diego Romano; Marco Lapegna; Angelo Ciaramella (e-Science, 2023)

Message from the Organizing Committee Chairs: PDP 2023. - Raffaele Montella; Angelo Ciaramella; Marco Lapegna; Marco Danelutto; Dora Blanco Heras (PDP, 2023)

Message from the General Chairs: PDP 2023. - Raffaele Montella; Angelo Ciaramella; Marco Lapegna; Marco Danelutto; Dora Blanco Heras (PDP, 2023)

A highly scalable high-performance Lagrangian transport and diffusion model for marine pollutants assessment. - Raffaele Montella; Diana Di Luccio; Ciro Giuseppe De Vita; Gennaro Mellone; Marco Lapegna; Gloria Ortega López; Livia Marcellino; Enrico Zambianchi; Giulio Giunta (PDP, 2023)

Parallel and hierarchically-distributed Shoreline Alert Model (SAM). - Ciro Giuseppe De Vita; Gennaro Mellone; Aniello Florio; Catherine Alessandra Torres Charles; Diana Di Luccio; Marco Lapegna; Guido Benassai; Giorgio Budillon; Raffaele Montella (PDP, 2023)

A Systematic Mapping Study of Italian Research on Workflows. - Marco Aldinucci; Elena Maria Baralis; Valeria Cardellini; Iacopo Colonnelli; Marco Danelutto; Sergio Decherchi; Giuseppe Di Modica; Luca Ferrucci; Marco Gribaudo; Francesco Iannone; Marco Lapegna; Doriana Medic; et al. (SC Workshops, 2023)

Unlocking the potential of edge computing for hyperspectral image classification: An efficient low-energy strategy. - Gianluca De Lucia; Marco Lapegna; Diego Romano (Future Gener. Comput. Syst., 2023)

Extending a Scientific Workflow Engine with Streaming I/O Capabilities: DAGonStar and CAPIO. - Simone Perrotta; Ciro Giuseppe De Vita; Gennaro Mellone; Marco Edoardo Santimaria; Giuseppe Salvi; Marco Lapegna; Massimo Torquati; Angelo Ciaramella (Euro-Par Workshops (2), 2024)

Striking Trade-off Between High Performance and Energy Efficiency in an Edge Computing Application for Detecting Floating Plastic Debris. - Marco Lapegna; Giuliano Laccetti; Raffaele Montella; Diego Romano (FRAME@HPDC, 2024)

Deploying AI-Based Environmental Monitoring Applications at the Edge: Two Case Studies. - Gianluca De Lucia; Giuliano Laccetti; Marco Lapegna; Raffaele Montella; Diego Romano (PPAM (2), 2024)

Special Issue on the pervasive nature of HPC (PN-HPC). - Marco Lapegna; Valeria Mele; Raffaele Montella; Lukasz Szustak (Concurr. Comput. Pract. Exp., 2024)

Analysis and Mitigation of Soft-errors in GPU-accelerated Hyperspectral Image Classifiers. - Sergiu-Mohamed Abed; Juan-David Guerrero-Balaguera; Josie E. Rodriguez Condia; Gianluca De Lucia; Marco Lapegna; Matteo Sonza Reorda (DDECS, 2025)

Advances in Adapting Memory-Bound CFD Computations to RISC-V Multicore Architecture. - Tomasz Olas; Lukasz Szustak; Roman Wyrzykowski; Mateusz Olas; Marco Lapegna (ICCS (3), 2025)

Detection of Single Scatterers in SAR Tomography using Multi-GPU Platforms. - Massimiliano Russo; Mehwish Nisar; Marco Lapegna; Diego Romano; Antonio Pauciullo; Pasquale Imperatore (JURSE, 2025)

A Massive Open Online Course (MOOC) on High-Performance Parallel Computing for Federica.eu Web-learning Platform. - Giuliano Laccetti; Marco Lapegna; Ilaria Merciai (PDP, 2025)

A Multi-Level Parallel Algorithm for Detection of Single Scatterers in SAR Tomography. - Massimiliano Russo; Mehwish Nisar; Antonio Pauciullo; Pasquale Imperatore; Marco Lapegna; Diego Romano (PDP, 2025)

A deep learning-based method for efficient floating garbage debris recognition on high-performance edge computing platform. - Diego Romano; Carlo Mennella; Marco Lapegna (Future Gener. Comput. Syst., 2026)