Contact Dr Salvatore Filippone
Areas of expertise
- Computing, Simulation & Modelling
Background
Dr. Filippone has an MSc in computer engineering and a PhD in Mathematics, both from the University of Rome "Tor Vergata".
Prior to joining Cranfield he has held positions with IBM Co., where he was a lead developer of the ESSL scientific software products, and at the University of Rome Tor Vergata, where he has taught introductory programming and introductory numerical analysis to engineering undergraduate, and advanced computational methods to graduate students.
Current activities
Dr. Filippone is the Leader of the "Software Engineering for Tchnical Computing" option of the MSc in Computational Software Techniques for Engineering.
He specializes in software to solve complex problems requiring sophisticated numerical algorithms that will stretch the number crunching abilities of a given machine to their utmost capacity.
Numerical Linear Algebra
Algorithms, Library Development, Applications
High Performance Computing
Parallel Computing Programming Environments, Distributed Memory Architectures, Shared Memory Architectures, Software Tools
Engineering Applications
Parallel Computing Techniques in Fluid Dynamics, Structural Analysis, ElectroMagnetism and Antennas, Optimization.
He is a member of SIAM and ACM, and is an associate editor of the ACM Transactions on Mathematical Software; he is also a reviewer and evaluator of EU funded projects.
Publications
Articles In Journals
- Bertaccini D, D'Ambra P, Durastante F & Filippone S. (2024). Why diffusion‐based preconditioning of Richards equation works: Spectral analysis and computational experiments at very large scale. Numerical Linear Algebra with Applications, 31(1)
- Owen H, Lehmkuhl O, D’Ambra P, Durastante F & Filippone S. (2024). Alya toward exascale: algorithmic scalability using PSCToolkit. The Journal of Supercomputing, 80(10)
- D'Ambra P, Durastante F, Filippone S & Zikatanov L. (2023). Automatic coarsening in Algebraic Multigrid utilizing quality measures for matching-based aggregations. Computers & Mathematics with Applications, 144
- D’Ambra P, Durastante F & Filippone S. (2023). Parallel Sparse Computation Toolkit. Software Impacts, 15
- Bisandu DB, Moulitsas I & Filippone S. (2022). Social ski driver conditional autoregressive-based deep learning classifier for flight delay prediction. Neural Computing and Applications, 34(11)
- Alsanousi H, Al Barrak N, Moulitsas I & Filippone S. (2021). Understanding customer behaviours toward the use of electronic banking given customer characteristics and financial portfolios. International Journal of Business and Social Science, 12(1)
- Rasmussen S, Gutmann ED, Moulitsas I & Filippone S. (2021). Fortran coarray implementation of semi-Lagrangian convected air particles within an atmospheric model. ChemEngineering, 5(2)
- D'Ambra P, Durastante F & Filippone S. (2021). AMG Preconditioners for Linear Solvers towards Extreme Scale. SIAM Journal on Scientific Computing, 43(5)
- Abdullahi Hassan A, Cardellini V, D'Ambra P, Di Serafino D & Filippone S. (2019). Efficient algebraic multigrid preconditioners on clusters of GPUs. Parallel Processing Letters, 29(01)
- D’Ambra P, Filippone S & Vassilevski PS. (2018). BootCMatch: A software package for bootstrap AMG based on graph weighted matching. ACM Transactions on Mathematical Software, 44(4)
- Cardellini V, Fanfarillo A & Filippone S. (2017). Coarray-based Load Balancing on Heterogeneous and Many-Core Architectures. Parallel Computing, 68
- Filippone S. (2017). Sparse matrix-vector multiplication on GPGPUs. ACM Transactions on Mathematical Software, 43(4)
- Bertaccini D & Filippone S. (2016). Sparse approximate inverse preconditioners on high performance GPU platforms. Computers & Mathematics with Applications, 71(3)
- Nanthaamornphong A, Carver J, Morris K & Filippone S. (2015). Extracting UML Class Diagrams from Object-Oriented Fortran: ForUML. Scientific Programming, 2015(1)
- D’Ambra P & Filippone S. (2015). A parallel generalized relaxation method for high-performance image segmentation on GPUs. Journal of Computational and Applied Mathematics, 293
- Aprovitola A, D’Ambra P, Denaro FM, di Serafino D & Filippone S. (2015). SParC-LES: Enabling large eddy simulations with parallel sparse matrix computation tools. Computers & Mathematics with Applications, 70(11)
- Cardellini V, Filippone S & Rouson DWI. (2014). Design Patterns for Sparse-Matrix Computations on Hybrid CPU/GPU Platforms. Scientific Programming, 22(1)
- Cardellini V, Filippone S & Rouson DWI. (2014). Design patterns for sparse-matrix computations on hybrid CPU/GPU platforms. Scientific Programming, 22(1)
- D’Ambra P, di Serafino D & Filippone S. (2013). Performance analysis of parallel Schwarz preconditioners in the LES of turbulent channel flows. Computers & Mathematics with Applications, 65(3)
- Morris K, Rouson DWI, Lemaster MN & Filippone S. (2012). Exploring Capabilities within ForTrilinos by Solving the 3D Burgers Equation. Scientific Programming, 20(3)
- Filippone S & Buttari A. (2012). Object-Oriented Techniques for Sparse Matrix Computations in Fortran 2003. ACM Transactions on Mathematical Software, 38(4)
- Morris K, Rouson DWI, Lemaster MN & Filippone S. (2012). Exploring capabilities within ForTrilinos by solving the 3D Burgers equation. Scientific Programming, 20(3)
- Marian VG, Gabriel D, Knoll G & Filippone S. (2011). Theoretical and Experimental Analysis of a Laser Textured Thrust Bearing. Tribology Letters, 44(3)
- D’Ambra P, Serafino DD & Filippone S. (2010). MLD2P4. ACM Transactions on Mathematical Software, 37(3)
- D'Ambra P, di Serafino D & Filippone S. (2007). On the development of PSBLAS-based parallel two-level Schwarz preconditioners. Applied Numerical Mathematics, 57(11-12)
- Filippone S & Colajanni M. (2000). PSBLAS. ACM Transactions on Mathematical Software, 26(4)
- Filippone S, Marrone M & Di Brozolo GR. (1992). Parallel preconditioned conjugate-gradient type algorithms for general sparsity structures. International Journal of Computer Mathematics, 44(1-4)
- Cardellini V, Filippone S & Rouson DWI. Design Patterns for Sparse-matrix Computations on Hybrid CPU/GPU Platforms. Scientific Programming, 22(1)
- Morris K, Rouson DWI, Lemaster MN & Filippone S. Exploring Capabilities within ForTrilinos by Solving the 3D Burgers Equation. Scientific Programming, 20(3)
