### 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
- 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, Albarrak 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. 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, Cardellini V, Barbieri D & Fanfarillo A. (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)
- D’Ambra P & Filippone S. (2016). A parallel generalized relaxation method for high-performance image segmentation on GPUs. Journal of Computational and Applied Mathematics, 293
- Nanthaamornphong A, Carver J, Morris K & Filippone S. (2015). Extracting UML Class Diagrams from Object-Oriented Fortran: ForUML. Scientific Programming, 2015
- 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)

### Conference Papers

- D'Ambra P, Durastante F, Ferdous SM, Filippone S, Halappanavar M, .... (2023). AMG Preconditioners based on Parallel Hybrid Coarsening and Multi-objective Graph Matching
- Albarrak N, Alsanousi H, Moulitsas I & Filippone S. (2022). Using Big Data to Compare Classification Models for Household Credit Rating in Kuwait
- Alsanousi H, Albarrak N, Moulitsas I & Filippone S. (2022). Using client’s Characteristics and Their Financial Products to Predict Their Usage of Banking Electronic Channels
- Bala Bisandu D, Salih Homaid M, Moulitsas I & Filippone S. (2021). A Deep Feedforward Neural Network and Shallow Architectures Effectiveness Comparison: Flight Delays Classification Perspective
- Rasmussen S, Gutmann ED, Friesen B, Rouson D, Filippone S, .... (2018). Development and performance comparison of MPI and Fortran Coarrays within an atmospheric research model
- Abdullahi A, D’Ambra P, di Serafino D & Filippone S. (2018). Parallel Aggregation Based on Compatible Weighted Matching for AMG
- Hassan AA, Cardellini V & Filippone S. (2017). A framework for unit testing with Coarray Fortran
- Cardellini V, Fanfarillo A & Filippone S. (2016). Heterogeneous CAF-Based Load Balancing on Intel Xeon Phi
- Barbieri D, Cardellini V & Filippone S. (2015). SIMPL: A Pattern Language for Writing Efficient Kernels on GPGPU
- Cardellini V, Fanfarillo A & Filippone S. (2014). Sparse matrix computations on clusters with GPGPUs
- Barbieri D, Cardellini V & Filippone S. (2014). Exhaustive Key Search on Clusters of GPUs
- Fanfarillo A, Burnus T, Cardellini V, Filippone S, Nagle D, .... (2014). Coarrays in GNU Fortran
- Fanfarillo A, Burnus T, Cardellini V, Filippone S, Nagle D, .... (2014). OpenCoarrays
- Nanthaamornphong A, Morris K & Filippone S. (2013). Extracting UML class diagrams from object-oriented Fortran
- Barbieri D, Cardellini V, Filippone S & Rouson D. (2012). Design Patterns for Scientific Computations on Sparse Matrices
- Martone M, Paprzycki M & Filippone S. (2012). An Improved Sparse Matrix-Vector Multiply Based on Recursive Sparse Blocks Layout
- Martone M, Filippone S, Paprzycki M & Tucci S. (2010). On the Usage of 16 Bit Indices in Recursively Stored Sparse Matrices
- Filippone S, Simos TE, Psihoyios G & Tsitouras C. (2010). Multilevel Preconditioners, Approximate Inverses and Factorization Updates for Krylov Projection Methods
- Martone M, Filippone S, Tucci S & Paprzycki M. (2010). Assembling recursively stored sparse matrices
- Kontorovich V, Ramos-Alarcon F, Filio RO & Primak S. (2010). Cyclostationary spectrum sensing for Cognitive Radio and multiantenna systems
- Martone M, Filippone S, Paprzycki M & Tucci S. (2010). On BLAS Operations with Recursively Stored Sparse Matrices
- Martone M, Filippone S, Tucci S, Gepner P & Paprzycki M. (2010). Use of hybrid recursive CSR/COO data structures in sparse matrix-vector multiplication
- Aprovitola A, D’Ambra P, di Serafino D & Filippone S. (2010). On the Use of Aggregation-Based Parallel Multilevel Preconditioners in the LES of Wall-Bounded Turbulent Flows
- Aprovitola A, D’Ambra P, Denaro F, di Serafino D & Filippone S. (2010). Scalable algebraic multilevel preconditioners with application to CFD
- Bencivenga B, Mioc F, Foged LJ, Sabbadini M, Filippone S, .... (2009). Computationally efficient tool using UTD on detailed meshed geometries
- Schmidt D, Toninel S, Filippone S & Bianchi GM. (2008). Parallel Computation of Mesh Motion for CFD of IC Engines
- Buttari A, Eijkhout V, Langou J & Filippone S. (2007). Performance Optimization and Modeling of Blocked Sparse Kernels
- Buttari A, D’Ambra P, di Serafino D & Filippone S. (2007). 2LEV-D2P4: a package of high-performance preconditioners for scientific and engineering applications
- Bella G, Bozza F, De Maio A, Del Citto F & Filippone S. (2006). An Enhanced Parallel Version of Kiva–3V, Coupled with a 1D CFD Code, and Its Use in General Purpose Engine Applications
- Buttari A, D’Ambra P, di Serafino D & Filippone S. (2006). Extending PSBLAS to Build Parallel Schwarz Preconditioners
- Bella G, Filippone S, De Maio A & Testa M. (2006). A Simulation Model for Forest Fires
- Bella G, Buttari A, De Maio A, Del Citto F, Filippone S, .... (2005). FAST-EVP: An Engine Simulation Tool
- Filippone S, D'Ambra P & Colajanni M. (2002). Using a Parallel Library of Sparse Linear Algebra in a Fluid Dynamics Application Code on Linux Clusters
- Filippone S, Colajanni M & Pascucci D. (1999). An object-oriented environment for sparse parallel computation on adaptive grids
- Filippone S. (1996). Parallel libraries on distributed memory architectures: The IBM Parallel ESSL
- Filippone S. (1996). The IBM parallel engineering and scientific subroutine library
- Filippone S & Vittoli C. (1996). Some preliminary experiences with sparse BLAS in parallel iterative solvers
- Cerioni F, Colajanni M, Filippone S & Maiolatesi S. (1996). A proposal for parallel sparse BLAS
- Filippone S & Loredana Sales M. (1994). Experiences in numerical software on IBM distributed memory architectures

### Books

- Filippone S & Radicati di Brozolo G. (2020). Vectorized ILU preconditioners for general sparsity patterns In Parallel Computing. CRC Press.
- Abdullahi Hassan A, Cardellini V & Filippone S. (2018). Solving Sparse Linear Systems of Equations Using Fortran Coarrays In Bassini S, Danelutto M, Dazzi P, Joubert GR & Peters F (eds), Advances in Parallel Computing: Volume 32: Parallel Computing is Everywhere: (32). IOS Press.