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Marco Lapegna
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2020 – today
- 2024
- [j24]Marco Lapegna
, Valeria Mele
Special Issue on the pervasive nature of HPC (PN-HPC). Concurr. Comput. Pract. Exp. 36(10) (2024) - [c30]Marco Lapegna
Striking Trade-off Between High Performance and Energy Efficiency in an Edge Computing Application for Detecting Floating Plastic Debris. FRAME@HPDC 2024 - 2023
- [j23]Gianluca De Lucia
Unlocking the potential of edge computing for hyperspectral image classification: An efficient low-energy strategy. Future Gener. Comput. Syst. 147: 207-218 (2023) - [c29]Ciro Giuseppe De Vita
Citizen Science for the Sea with Information Technologies: An Open Platform for Gathering Marine Data and Marine Litter Detection from Leisure Boat Instruments. e-Science 2023: 1-9 - [c28]Raffaele Montella
A highly scalable high-performance Lagrangian transport and diffusion model for marine pollutants assessment. PDP 2023: 17-26 - [c27]Ciro Giuseppe De Vita
Parallel and hierarchically-distributed Shoreline Alert Model (SAM). PDP 2023: 109-113 - [c26]Raffaele Montella, Angelo Ciaramella, Marco Lapegna, Marco Danelutto, Dora Blanco Heras:
Message from the General Chairs: PDP 2023. PDP 2023: xii-xiii - [c25]Raffaele Montella, Angelo Ciaramella, Marco Lapegna, Marco Danelutto, Dora Blanco Heras:
Message from the Organizing Committee Chairs: PDP 2023. PDP 2023: xiv - [c24]Marco Aldinucci
A Systematic Mapping Study of Italian Research on Workflows. SC Workshops 2023: 2065-2076 - 2022
- [j22]Gianluca De Lucia
Towards explainable AI for hyperspectral image classification in Edge Computing environments. Comput. Electr. Eng. 103: 108381 (2022) - [j21]Walter Balzano
Competitive-blockchain-based parking system with fairness constraints. Soft Comput. 26(9): 4151-4162 (2022) - [c23]Giuliano Laccetti
Toward a high-performance clustering algorithm for securing edge computing environments. CCGRID 2022: 820-825 - [c22]Raffaele Montella, Diana Di Luccio, Ciro Giuseppe De Vita
Enabling the CUDA Unified Memory model in Edge, Cloud and HPC offloaded GPU kernels. CCGRID 2022: 834-841 - [c21]Giuliano Laccetti, Marco Lapegna
A hybrid clustering algorithm for high-performance edge computing devices [Short]. ISPDC 2022: 78-82 - [c20]Gianluca De Lucia
A GPU Accelerated Hyperspectral 3D Convolutional Neural Network Classification at the Edge with Principal Component Analysis Preprocessing. PPAM (2) 2022: 127-138 - 2021
- [j20]Sokol Kosta
Special Issue on High-end Heterogeneous Architectures, Methodologies, and Algorithms (HHAMA20). Concurr. Comput. Pract. Exp. 33(4) (2021) - [j19]Kamil Halbiniak
Dynamic workload prediction and distribution in numerical modeling of solidification on multi-/manycore architectures. Concurr. Comput. Pract. Exp. 33(11) (2021) - [j18]Marco Lapegna
Clustering Algorithms on Low-Power and High-Performance Devices for Edge Computing Environments. Sensors 21(16): 5395 (2021) - [j17]Diego Romano
A GPU-Parallel Image Coregistration Algorithm for InSar Processing at the Edge. Sensors 21(17): 5916 (2021) - [c19]Marco Lapegna
DClu: A Direction-Based Clustering Algorithm for VANETs Management. IMIS 2021: 253-262 - 2020
- [j16]Diana Di Luccio, Angelo Riccio
Coastal Marine Data Crowdsourcing Using the Internet of Floating Things: Improving the Results of a Water Quality Model. IEEE Access 8: 101209-101223 (2020) - [j15]Diego Romano
Designing a GPU-parallel algorithm for raw SAR data compression: A focus on parallel performance estimation. Future Gener. Comput. Syst. 112: 695-708 (2020) - [j14]Giuliano Laccetti, Marco Lapegna
Performance enhancement of a dynamic K-means algorithm through a parallel adaptive strategy on multicore CPUs. J. Parallel Distributed Comput. 145: 34-41 (2020) - [c18]Diego Romano
The Challenge of Onboard SAR Processing: A GPU Opportunity. ICCS (3) 2020: 46-59
2010 – 2019
- 2019
- [j13]Giuliano Laccetti
An adaptive algorithm for high-dimensional integrals on heterogeneous CPU-GPU systems. Concurr. Comput. Pract. Exp. 31(19) (2019) - [c17]Giuliano Laccetti, Marco Lapegna
A High Performance Modified K-Means Algorithm for Dynamic Data Clustering in Multi-core CPUs Based Environments. IDCS 2019: 89-99 - [c16]Marco Lapegna
An Adaptive Strategy for Dynamic Data Clustering with the K-Means Algorithm. PPAM (2) 2019: 101-110 - 2018
- [j12]Luisa Carracciuolo
Implementation of a non-linear solver on heterogeneous architectures. Concurr. Comput. Pract. Exp. 30(24) (2018) - [j11]Giuliano Laccetti
Models, algorithms, and tools for highly heterogeneous computing environments. Concurr. Comput. Pract. Exp. 30(24) (2018) - [c15]Giuliano Laccetti, Marco Lapegna
A Scalable Unified Model for Dynamic Data Structures in Message Passing (Clusters) and Shared Memory (multicore CPUs) Computing environments. CCGrid 2018: 599-608 - 2017
- [j10]Raffaele Montella
Accelerating Linux and Android applications on low-power devices through remote GPGPU offloading. Concurr. Comput. Pract. Exp. 29(24) (2017) - [j9]Giuliano Laccetti
Guest Editorial for Hybrid Parallelism in New HPC Systems. Int. J. Parallel Program. 45(5): 1021-1025 (2017) - [j8]Raffaele Montella
On the Virtualization of CUDA Based GPU Remoting on ARM and X86 Machines in the GVirtuS Framework. Int. J. Parallel Program. 45(5): 1142-1163 (2017) - [j7]Giovanni Battista Barone, Vania Boccia, Davide Bottalico
An Approach to Forecast Queue Time in Adaptive Scheduling: How to Mediate System Efficiency and Users Satisfaction. Int. J. Parallel Program. 45(5): 1164-1193 (2017) - [c14]Livia Marcellino
Using GPGPU Accelerated Interpolation Algorithms for Marine Bathymetry Processing with On-Premises and Cloud Based Computational Resources. PPAM (2) 2017: 14-24 - [c13]Giuliano Laccetti
Relaxing the Correctness Conditions on Concurrent Data Structures for Multicore CPUs. A Numerical Case Study. PPAM (2) 2017: 25-36 - 2016
- [j6]Giuliano Laccetti
A Loosely Coordinated Model for Heap-Based Priority Queues in Multicore Environments. Int. J. Parallel Program. 44(4): 901-921 (2016) - 2015
- [c12]Raffaele Montella
Virtualizing CUDA Enabled GPGPUs on ARM Clusters. PPAM (2) 2015: 3-14 - 2013
- [c11]Giuliano Laccetti
A Study on Adaptive Algorithms for Numerical Quadrature on Heterogeneous GPU and Multicore Based Systems. PPAM (1) 2013: 704-713 - 2012
- [j5]Giuliano Laccetti
A Double Adaptive Algorithm for Multidimensional Integration on Multicore Based HPC Systems. Int. J. Parallel Program. 40(4): 397-409 (2012) - 2011
- [c10]Vania Boccia
HADAB: Enabling Fault Tolerance in Parallel Applications Running in Distributed Environments. PPAM (1) 2011: 700-709
2000 – 2009
- 2008
- [c9]Almerico Murli, Vania Boccia
The MedIGrid PSE in an LCG/gLite environment. ISPA 2008: 829-834 - 2007
- [c8]Luisa Carracciuolo
Implementing Effective Data Management Policies in Distributed and Grid Computing Environments. PPAM 2007: 902-911 - 2006
- [c7]Almerico Murli, Vania Boccia
Monitoring and Migration of a PETSc-based Parallel Application for Medical Imaging in a Grid computing PSE. Grid-Based Problem Solving Environments 2006: 421-432 - 2005
- [c6]Pasquale Caruso, Giuliano Laccetti, Marco Lapegna:
A Performance Contract System in a Grid Enabling, Component Based Programming Environment. EGC 2005: 982-992 - [c5]Luisa D'Amore
Block Matrix Multiplication in a Distributed Computing Environment: Experiments with NetSolve. PPAM 2005: 625-632 - 2003
- [c4]Pasqua D'Ambra
Integrating MPI-based numerical software into an advanced parallel computing environment. PDP 2003: 283-291 - 2002
- [j4]Pasqua D'Ambra
Advanced environments for parallel and distributed applications: a view of current status. Parallel Comput. 28(12): 1637-1662 (2002) - [j3]Pasqua D'Ambra, Daniela di Serafino, Marco Lapegna:
Parallel Components for Multidimensional Quadrature: Some Experiences. Parallel Distributed Comput. Pract. 5(3) (2002)
1990 – 1999
- 1999
- [c3]Giuliano Laccetti, Marco Lapegna
PAMIHR. A Parallel FORTRAN Program for Multidimensional Quadrature on Distributed Memory Architectures. Euro-Par 1999: 1144-1148 - 1997
- [j2]Marco D'Apuzzo, Marco Lapegna
Scalability and Load Balancing in Adaptive Algorithms for Multidimensional Integration. Parallel Comput. 23(8): 1199-1210 (1997) - 1995
- [c2]Marco D'Apuzzo, Marco Lapegna
A parallel row projection solver for large sparse linear systems. PDP 1995: 432-443 - 1993
- [c1]Marco Lapegna, Alessandra D'Alessio:
A Scalabel Parallel Algorithm for the Adaptive Multidimensional Quadrature. PPSC 1993: 933-936 - 1992
- [j1]Marco Lapegna
Global adaptive quadrature for the approximate computation of multidimensional integrals on a distributed-memory multiprocessor. Concurr. Pract. Exp. 4(6): 413-426 (1992)
Coauthor Index
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last updated on 2024-08-03 20:07 CEST by the dblp team
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