Publications

Submitted

  1. D. di Serafino, W. Hager, G. Toraldo, M. Viola, On the stationarity for nonlinear optimization problems with polyhedral constraints, 2022.

  2. F. Calabrò, S. Cuomo, D. di Serafino, G. Izzo, E. Messina, The effect of time discretization on the solution of parabolic PDEs with ANNs, 2022, available from arXiv.

  3. D. di Serafino, M. Pragliola, Automatic parameter selection for the TGV regularizer in image restoration under Poisson noise, 2022, available from arXiv.

  4. M. Afraz, R. Khan, A. Ahmad, D. di Serafino, Effects of Nanoparticles on the Flow and Heat Transfer of Polymeric Fluids, 2022.

  5. D. di Serafino, N. Krejić, N. Krklec Jerinkić, M. Viola, LSOS: Line-search Second-Order Stochastic optimization methods for nonconvex finite sums, 2021, available from Optimization Online and arXiv.

Journals

  1. V. De Simone, D. di Serafino, J. Gondzio, S. Pougkakiotis, M. Viola, Sparse Approximations with Interior Point Methods, to appear in SIAM Review, 2022. Accepted in 2021, preprint available from Optimization Online and arXiv.

  2. L. Antonelli, V. De Simone, D. di Serafino, A view of computational models for image segmentation, 2022, available from arXiv, accepted for publication in Annali dell'Università di Ferrara.

  3. D. di Serafino, G. Landi, M. Viola, Directional TGV-based image restoration under Poisson noise, Journal of Imaging, 7 (6), 2021, article 99, doi: 10.3390/jimaging7060099.

  4. D. di Serafino, D. Orban, Constraint-Preconditioned Krylov Solvers for Regularized Saddle-Point Systems, SIAM Journal on Scientific Computing, 43 (2), 2021, pp. A1001-A1026, ISSN: 1064-8275, doi: 10.1137/19M1291753.

  5. D. di Serafino, G. Toraldo, M. Viola, Using gradient directions to get global convergence of Newton-type methods, Applied Mathematics and Computations, 409, article 125612, 2020 (online), 2021 (printed), ISSN: 0096-3003, doi: 10.1016/j.amc.2020.125612.

  6. L. Antonelli, V. De Simone, D. di Serafino, Spatially Adaptive Regularization in Image Segmentation, Algorithms, 13 (9), 2020, article 226, ISSN: 1999-4893, doi: 10.3390/a13090226.

  7. V. De Simone, D. di Serafino, M. Viola, A subspace-accelerated split Bregman method for sparse data recovery with joint l1-type regularizers, Electronic Transactions on Numerical Analysis, 53, 2020, pp. 406-425, ISSN: 10689613, doi: 10.1553/etna_vol53s406.

  8. D. di Serafino, G. Landi, M. Viola, ACQUIRE: an inexact iteratively reweighted norm approach for TV-based Poisson image restoration, Applied Mathematics and Computation, 364, 2020, article 124678, ISSN: ISSN: 0096-3003, published online in 2019, doi: 10.1016/j.amc.2019.124678.

  9. A. Abdullahi Hassan, V. Cardellini, P. D'Ambra, D. di Serafino, S. Filippone, Efficient Algebraic Multigrid Preconditioners on Clusters of GPUs, Parallel Processing Letters, 29 (1), 1950001, 2019, ISSN: 0129-6264, doi: 10.1142/S0129626419500014.

  10. D. di Serafino, G. Toraldo, M. Viola, J. Barlow, A two-phase gradient method for quadratic programming problems with a single linear constraint and bounds on the variables, SIAM Journal on Optimization, 28 (4), 2018, pp. 2809-2838, ISSN: 1052-6234, doi: 10.1137/17M1128538.

  11. L. Bergamaschi, V. De Simone, D. di Serafino, A. Martínez, BFGS-like updates of constraint preconditioners for sequences of KKT linear systems in quadratic programming, Numerical Linear Algebra with Applications, 25 (5), 2018, e2144, ISSN: 1099-1506, doi: 10.1002/nla.2144.

  12. V. De Simone, D. di Serafino, B. Morini, On preconditioner updates for sequences of saddle-point linear systems, Communications in Applied and Industrial Mathematics, 9 (1), 2018, pp. 35-41, ISSN 2038-0909, doi: 10.1515/caim-2018-0003.

  13. D. di Serafino, V. Ruggiero, G. Toraldo, L. Zanni, On the steplength selection in gradient methods for unconstrained optimization, Applied Mathematics and Computation, 318, 2018, pp. 176-195, published online in 2017, ISSN: 0096-3003, doi: 10.1016/j.amc.2017.07.037.

  14. S. Bellavia, V. De Simone, D. di Serafino, B. Morini, On the update of constraint preconditioners for regularized KKT systems, Computational Optimization and Applications, 65 (2), 2016, pp. 339-360 ISSN: 0926-6003, doi: 10.1007/s10589-016-9830-4.

  15. R. De Asmundis, D. di Serafino, G. Landi, On the regularizing behavior of the SDA and SDC gradient methods in the solution of linear ill-posed problems, Journal of Computational and Applied Mathematics, 302, 2016, pp. 81-93, ISSN: 0377-0427, doi: 10.1016/j.cam.2016.01.007.

  16. L. Antonelli, V. De Simone, D. di Serafino, On the application of the spectral projected gradient method in image segmentation, Journal of Mathematical Imaging and Vision, 54 (1), 2016, pp. 106-116, ISSN: 0924-9907, doi: 10.1007/s10851-015-0591-y.

  17. S. Bellavia, V. De Simone, D. di Serafino, B. Morini, Updating constraint preconditioners for KKT systems in quadratic programming via low-rank corrections, SIAM Journal on Optimization, 25 (3), 2015, pp. 1787-1808, ISSN: 1052-6234, doi: 10.1137/130947155.

  18. A. Aprovitola, P. D'Ambra, F.M. Denaro, D. di Serafino, S. Filippone, SParC-LES: enabling large eddy simulations with parallel sparse matrix computation tools, Computers and Mathematics with Applications, 70 (11), 2015, pp. 2688-2700 ISSN: 0898-1221, doi: 10.1016/j.camwa.2015.06.028.

  19. R. De Asmundis, D. di Serafino, W.W. Hager, G. Toraldo, H. Zhang, An efficient gradient method using the Yuan steplength, Computational Optimization and Applications, 59 (3), 2014, pp. 541-563, ISSN: 0926-6003, doi: 10.1007/S10589-014-9669-5.

  20. V. De Simone, D. di Serafino, A matrix-free approach to build band preconditioners for large-scale bound-constrained optimization, Journal of Computational and Applied Mathematics, 268, 2014, pp. 82-92, ISSN: 0377-0427, doi: 10.1016/j.cam.2014.02.035.

  21. A. Borzì, V. De Simone, D. di Serafino, Parallel algebraic multilevel Schwarz preconditioners for a class of elliptic PDE systems, Computing and Visualization in Science, 16 (1), 2013, pp. 1-14, ISSN: 1432-9360, published in 2014, doi: 0.1007/s00791-014-0220-0.

  22. R. De Asmundis, D. di Serafino, F. Riccio, G. Toraldo, On spectral properties of steepest descent methods, IMA Journal of Numerical Analysis, 33, 2013, pp. 1416-1435, ISSN: 0272-4979, doi: 10.1093/imanum/drs056.

  23. P. D'Ambra, D. di Serafino, S. Filippone, Performance analysis of parallel Schwarz preconditioners in the LES of turbulent channel flows, Computers and Mathematics with Applications, 65, 2013, pp. 352-361, ISSN: 0898-122, doi: 10.1016/j.camwa.2012.06.023.

  24. S. Bellavia, V. De Simone, D. di Serafino, B. Morini, A preconditioning framework for sequences of diagonally modified linear systems arising in optimization, SIAM Journal on Numerical Analysis, 50 (6), 2012, pp. 3280-3302, ISSN: 0036-1429, doi: 10.1137/110860707.

  25. S. Bellavia, V. De Simone, D. di Serafino, B. Morini, Efficient Preconditioner Updates for Shifted Linear Systems, SIAM Journal on Scientific Computing, 33 (4), 2011, pp. 1785-1809, ISSN: 1064-8275, doi: 10.1137/100803419.

  26. D. di Serafino, G. Liuzzi, V. Piccialli, F. Riccio, G. Toraldo, A Modified DIviding RECTangles Algorithm for a Problem in Astrophysics, Journal of Optimization Theory and Applications, 151, 2011, pp. 175-190, ISSN: 1573-2878, doi: 10.1007/s10957-011-9856-9.

  27. P. D'Ambra, D. di Serafino, S. Filippone, MLD2P4: a Package of Parallel Algebraic Multilevel Domain Decomposition Preconditioners in Fortran 95, ACM Transactions on Mathematical Software, 37 (3), 2010, art. 30, ISSN: 0098-3500, 10.1145/1824801.1824808.

  28. M. D'Apuzzo, V. De Simone, D. di Serafino, Starting-Point Strategies for an Infeasible Potential Reduction Method, Optimization Letters, 4 (1), 2010, pp. 131-146, ISSN: 1862-4472, published online in 2009, doi: 10.1007/s11590-009-0150-9.

  29. M. D'Apuzzo, V. De Simone, D. di Serafino, On mutual impact of numerical linear algebra and large-scale optimization with focus on interior point methods, Computational Optimization and Applications, 45 (2), 2010, pp. 283-310, ISSN: 0926-6003, published online in 2008, doi: 10.1007/s10589-008-9226-1. Received the COAP 2010 Best Paper Award.

  30. D. di Serafino, S. Gomez, L. Milano, F. Riccio, G. Toraldo, A genetic algorithm for a global optimization problem arising in the detection of gravitational waves, Journal of Global Optimization, 48 (1), 2010, pp. 41-55, ISSN: 1573-2916, doi: 10.1007/s10898-010-9525-9.

  31. A. Mucherino, S. Costantini, D. di Serafino, M. D'Apuzzo, A. Facchiano, G. Colonna, Understanding the role of the topology in protein folding by computational inverse folding experiments, Computational Biology and Chemistry, 32 (4), 2008, pp. 233-239, ISSN: 1476-9271, doi: 10.1016/j.compbiolchem.2008.03.015.

  32. G. Casa, A. Castrillo, G. Galzerano, R. Wehr, A. Merlone, D. di Serafino, P. Laporta, L. Gianfrani, Primary gas thermometry by means of laser absorption spectroscopy: determination of the Boltzmann constant, Physical Review Letters, 100 (20), 2008, paper n. 200801, ISSN: 0031-9007, doi: 10.1103/PhysRevLett.100.200801.

  33. A. Buttari, P. D'Ambra, D. di Serafino, Filippone, 2LEV-D2P4: a package of high-performance preconditioners for scientific and engineering applications, Applicable Algebra in Engineering, Communication and Computing, 18 (3), 2007, pp. 223-239, ISSN: 0938-1279, doi: 10.1007/s00200-007-0035-z.

  34. P. D'Ambra, D. di Serafino, S. Filippone, On the Development of PSBLAS-based Parallel Two-level Schwarz Preconditioners, Applied Numerical Mathematics, 57, 2007, pp. 1181-1196, ISSN: 0168-9274, doi: 10.1016/j.apnum.2007.01.006.

  35. S. Cafieri, M. D'Apuzzo, V. De Simone, D. di Serafino, G. Toraldo, Convergence Analysis of an Inexact Potential Reduction Method for Convex Quadratic Programming, Journal of Optimization Theory and Applications, 135 (3), 2007, pp. 355-366, ISSN: 0022-3239, doi: 10.1007/s10957-007-9264-3.

  36. S. Cafieri, M. D'Apuzzo, V. De Simone, D. di Serafino, On the Iterative Solution of KKT Systems in Potential Reduction Software for Large Scale Quadratic Problems, Computational Optimization and Applications, 38, 2007, pp. 27-45, ISSN: 0926-6003, doi: 10.1007/s10589-007-9035-y.

  37. S. Cafieri, M. D'Apuzzo, V. De Simone, D. di Serafino, Stopping criteria for inner iterations in inexact Potential Reduction methods: a computational study, Computational Optimization and Applications, 36, 2007, pp. 165-193, ISSN: 0926-6003, doi: 10.1007/s10589-006-9007-7.

  38. P. D'Ambra, D. di Serafino, M. Lapegna, Parallel Components for Multidimensional Quadrature: Some Experiences, Parallel and Distributed Computing Practices, 5 (3), 2002, pp. 279-288, ISSN: 1097-2803.

  39. P. D'Ambra, M. Danelutto, D. di Serafino, M. Lapegna, Advanced Environments for Parallel and Distributed Applications: a View of Current Status, Parallel Computing, 28 (12), 2002, pp. 1637-1662, ISSN: 0167-8191, doi: 10.1016/S0167-8191(02)00199-0.

  40. G. Barone, P. D'Ambra, D. di Serafino, G. Giunta, R. Montella, A. Murli, A. Riccio, An Operational mesoscale Air Quality Model for the Campania Region, Annali della Facoltà di Scienze e Tecnologie, Università Parthenope di Napoli, special issue on "Global and Regional Atmospheric Modelling", G. Barone, P.J. Builtjes, G. Giunta eds., 2000, pp. 179-189, ISSN: 1590-9093.

  41. G. Barone, P. D'Ambra, D. di Serafino, G. Giunta, A. Murli, A. Riccio, Application of a Parallel Photochemical Air Quality Model to the Campania Region (Southern Italy), Environmental Modelling & Software, 15 (6-7), 2000, pp. 503-511, ISSN: 1364-8152, doi: 10.1016/S1364-8152(00)00040-2.

  42. D. di Serafino, G. Giunta, A. Murli, A Parallel Software System for the Numerical Simulation of Air Pollution, Annali dell'Università di Ferrara - Sez. 7 - Sc. Mat., supplemento al vol. XLV, 2000, pp. 279-291, ISSN: 0430-3202.

  43. G. Barone, P. D'Ambra, D. di Serafino, G. Giunta, A. Riccio, A Comparison of Numerical Methods for Solving Diffusion-Reaction Equations in Air Quality Models, Computing and Visualization in Science, 2 (1), 1999, pp. 1-13, ISSN: 1432-9360, doi: 10.1007/s007910050022.

  44. G. Barone, P. D'Ambra, D. di Serafino, G. Giunta, A. Murli, A. Riccio, PNAM: Parallel Software for Air Quality Simulations in the Naples Area, Environmental Management and Health, MCB University Press UK, 10 (4), 1999, pp. 209-215, ISSN: 0956-6163, 10.1108/09566169910276021.

  45. G. Barone, P. D’Ambra, D. di Serafino, G. Giunta, A. Riccio, A Comprehensive Atmospheric Chemistry Model for the Description of Dynamics of Reactive Pollutants, Annals of the New York Academy of Sciences, 879, 1999, pp. 383-386, ISSN: 0077-8923, doi: 10.1111/j.1749-6632.1999.tb10441.x.

  46. G. Barone, P. D'Ambra, D. di Serafino, G. Giunta, F. Modestia, A. Murli, A. Riccio, Application of a Photochemical Air Quality Model to the Naples Urban Area and Implications to Local Ozone Control Strategies, Fresenius Environmental Bulletin, 7, 1998, pp. 283-290, ISSN: 1018-4619.

  47. D. di Serafino, A Parallel Implementation of a Multigrid Multiblock Euler Solver on Distributed Memory Machines, Parallel Computing, 23, 1997, pp. 2095-2113, ISSN: 0167-8191, doi: 10.1016/S0167-8191(97)00071-9

Edited special issues of journals and book series

  1. V. De Simone, D. di Serafino, G. Toraldo (eds.), Recent Advances in Nonlinear Optimization and Equilibrium Problems: a Tribute to Marco D'Apuzzo, Quaderni di Matematica, vol. 27, series edited by Dipartimento di Matematica della Seconda Universita' di Napoli, Aracne, 2012, ISBN: 978-88-548-5687-5.

  2. P. D’Ambra, D. di Serafino, M. R. Guarracino, F. Perla (eds.), Parallel and Distributed Processing: an Application Perspective, Scalable Computing: Practice and Experience - special issue, 11 (3), 2010, ISBN: 1097-2803.

  3. P. D'Ambra, M. Danelutto, D. di Serafino (eds.), Advanced Environments for Parallel and Distributed Computing, Parallel Computing - special issue, 28 (12), 2002, ISSN: 0167-8191.

Book chapters & conference proceedings (with peer review)

  1. D. di Serafino, G. Landi, M. Viola, TGV-based restoration of Poissonian images with automatic estimation of the regularization parameter, "2021 21st International Conference on Computational Science and Its Applications (ICCSA)", IEEE, 2021, pp. 139-145, ISBN: 978-1-6654-5843-6, doi: 10.1109/ICCSA54496.2021.00028.

  2. D. di Serafino, G. Toraldo, M. Viola, A Gradient-Based Globalization Strategy for the Newton Method, in "Numerical Computations: Theory and Algorithms. NUMTA 2019", Y.D. Sergeyev and D.E. Kvasov eds., Lecture Notes in Computer Science, vol. 11973, Springer, 2020, pp. 177-185, ISBN: 978-3-030-39080-8, doi: 10.1007/978-3-030-39081-5_16.

  3. L. Antonelli, D. di Serafino, E. Francomano, F. Gregoretti, M. Paliaga, Towards an Efficient Implementation of an Accurate SPH Method, in "Numerical Computations: Theory and Algorithms. NUMTA 2019", Y.D. Sergeyev and D.E. Kvasov eds., Lecture Notes in Computer Science, vol. 11973, Springer, 2020, pp. 3-10, ISBN: 978-3-030-39080-8, doi: 10.1007/978-3-030-39081-5_1.

  4. A. Abdullahi, P. D'Ambra, D. di Serafino, S. Filippone, Parallel Aggregation Based on Compatible Weighted Matching for AMG, in "Large-Scale Scientific Computing", I. Lirkov and S. Margenov eds., Lecture Notes in Computer Science, vol. 10665, Springer, 2018, pp. 563-571, ISBN: 978-3-319-73440-8, doi: 10.1007/978-3-319-73441-5_6.

  5. D. di Serafino, V. Ruggiero, G. Toraldo, L. Zanni, A note on spectral properties of some gradient methods, in "Numerical Computations: Theory and Algorithms (NUMTA-2016)", AIP Conference Proceedings, vol. 1776, 040003, 2016, ISBN: 978-0-7354-1438-9, doi: 10.1063/1.4965315.

  6. S. Bellavia, V. De Simone, D. di Serafino, B. Morini, Building preconditioners for sequences of linear systems arising in optimization, in "Applied Mathematical Optimization and Modelling - APMOD 2012 Extended Abstracts", DS&OR Lab, University of Paderborn, pp. 17-22, 2012, ISBN: 9783844817942.

  7. D. di Serafino, F. Riccio, On the application of multiple-deme parallel genetic algorithms in astrophysics, in "Proceedings of the 18th Euromicro International Conference on Parallel, Distributed and Network-Based Computing", IEEE Conference Publishing Services, pp. 231-237, 2010, ISBN: 978-0-7695-3939-3, doi: 10.1109/PDP.2010.70.

  8. A. Aprovitola, P. D'Ambra, D. di Serafino, S. Filippone, On the use of Aggregation-based Parallel Multilevel Preconditioners in the LES of Wall-bounded Turbulent Flows, in "Large-Scale Scientific Computing", Lecture Notes in Computer Science, vol. 5910, Springer, 2010, pp. 67-75, ISSN: 0302-9743, doi: 10.1007/978-3-642-12535-5.

  9. A. Aprovitola, P. D'Ambra, F. Denaro, D. di Serafino, S. Filippone, Scalable algebraic multilevel preconditioners with application to CFD, invited paper, in "Parallel Computational Fluid Dynamics 2008", D. Tromeur-Dervout, G. Brenner, D. Emerson, J. Erhel eds., Lecture Notes in Computational Science and Engineering, vol. 74, Springer, 2010, pp. 15-27, ISSN: 1439-7358, doi: 10.1007/978-3-642-14438-7.

  10. G. Ceci, A. Mucherino, M. D'Apuzzo, D. di Serafino, S. Costantini, A. Facchiano, G. Colonna, Computational Methods for Protein Fold Prediction: an Ab-initio Topological Approach, in "Data Mining in Biomedicine", P.M. Pardalos, V.L. Boginski and A. Vazacopoulos eds., Springer Optimization and its Applications Series, vol. 7, 2007, pp. 391-430, ISBN: 978-0-387-69318-7, doi: 10.1007/978-0-387-69319-4_21.

  11. S. Cafieri, M. D'Apuzzo, V. De Simone, D. di Serafino, On the Use of an Approximate Constraint Preconditioner in a Potential Reduction Algorithm for Quadratic Programming, in "Applied and Industrial Mathematics in Italy II", V. Cutello, G. Fotia and L. Puccio eds., Series on Advances in Mathematics for Applied Sciences, 75, World Scientific, 2007, pp. 220-230, ISBN: 978-981-270-938-7, doi: 10.1142/9789812709394_0020

  12. A. Buttari, P. D'Ambra, D. di Serafino, S. Filippone, Extending PSBLAS to Build Parallel Schwarz Preconditioners, in "Proceedings of PARA'04. State of the Art in Scientific Computing", J. Dongarra, K. Madsen, J. Wasniewski eds., Lecture Notes in Computer Science, Springer, vol. 3732, 2006, pp. 593-602, ISBN: 978-3-540-29067-4, doi: 10.1007/11558958_71.

  13. S. Cafieri, M. D'Apuzzo, V. De Simone, D. di Serafino, G. Toraldo, On the use of Constraint Preconditioners in Potential Reduction methods, Communications to SIMAI Congress, vol. 1, 2006, ISSN: 1827-9015, doi: 10.1685/CSC06031.

  14. C. Marongiu, P.L. Vitagliano, P. Catalano, V. Tarantino, D. di Serafino, An Improvement of the Dual Time Stepping Technique for Unsteady RANS Computations, European Conference for Aerospace Sciences (EUCASS), Moscow, July 4-7, 2005.

  15. A. Buondonno, E. Coppola, D. di Serafino et al., Analisi dei pedocaratteri come indici di variabilità spaziale dei suoli della piana di Santa Eufemia (Calabria), Bollettino della Società Italiana di Scienza del Suolo, vol. 53, n. 1-2, pp. 267-272, 2004

  16. P. D'Ambra, M. Danelutto, D. di Serafino, M. Lapegna, Integrating MPI-based Numerical Software into an Advanced Parallel Computing Environment, in "Proceedings of the 11th Euromicro Conference on Parallel, Distributed and Network-based Processing", IEEE, 2003, pp. 283-291, ISBN: 0-7695-1875-3, doi: 10.1109/EMPDP.2003.1183601.

  17. A. Buondono, P. Bidello, S. Brenna, E. Coppola, D. di Serafino, C. Glorioso, Valutazione spaziale dei pedocaratteri tramite analisi delle componenti principali. Indagine preliminare su un areale dell'Oltrepo Mantovano, Bollettino della Società Italiana di Scienza del Suolo, vol. 52, n. 1-2, pp. 465-475, 2003.

  18. P. D'Ambra, D. di Serafino, M. Lapegna, Embedding Parallel Quadrature Software into a HPC Environment, in "Parallel Numerics '02", R. Trobec, P. Zinterhof, M. Vaitersic, A. Uhl eds., Jozef Stefan Institute, Ljubljana, and University of Salzburg Publishers, 2002, pp. 15-27, ISBN: 961-6303-39-2.

  19. G. Barone, P. D'Ambra, D. di Serafino, G. Giunta, A. Murli, A. Riccio, Parallel Numerical Simulation of Air Pollution in Southern Italy, in "Large-Scale Computations in Air Pollution Modelling", Z. Zlatev et al. eds., Kluwer, 1999, pp. 39-52, ISBN: 0-7923-5677-2, doi: 10.1007/978-94-011-4570-1_4.

  20. D. di Serafino, L. Maddalena, P. Messina, A. Murli, Some Perspectives on High-Performance Mathematical Software, in "High Performance Algorithms and Software in Nonlinear Optimization", R. De Leone, A. Murli, P.M. Pardalos, G. Toraldo eds., Kluwer, 1998, pp. 1-23, doi: 10.1007/978-1-4613-3279-4_1.

  21. M. Derakhshan, D. di Serafino, A. Murli, The PINEAPL Library: a Parallel Numerical Library for Industrial Applications, 14th GAMM Seminar on "Concepts of Numerical Software", Kiel, January 23-25, 1998.

  22. I. de Bono, D. di Serafino, E. Ducloux, Using a General-Purpose Numerical Library to Parallelize an Industrial Application: Design of High-Performance Lasers, in "Euro-Par'98, Parallel Processing'', D. Pritchard, J. Reeve eds., Lecture Notes in Computer Science, vol. 1470, Springer, 1998, pp. 812-820, ISSN: 0302-9743, doi: 10.1007/BFb0057935.

  23. G. Barone, P. D'Ambra, D. di Serafino, G. Giunta, A. Riccio, Numerical Simulation of Air Pollution Phenomena in the Neapolitan Urban Area (Southern Italy): First Experiences, in "Large-Scale Computations of Engineering and Environmental Problems'', M. Griel, O.P. Iliev, S.D. Margenov, P.S. Vassilevski eds., Notes on Numerical Fluid Mechanics, vol. 62, Vieweg Verlag, 1998, pp. 128-135, ISSN: 0179-9614.

  24. D. di Serafino, L. Maddalena, A. Murli, PINEAPL: A European Project to Develop a Parallel Numerical Library for Industrial Applications, in "Euro-Par'97, Parallel Processing'', C. Lengauer, M. Griebl and S. Gorlatch eds., Lecture Notes in Computer Science, vol. 1300, Springer, 1997, pp. 1333-1339, ISBN: 978-3-540-63440-9, doi: 10.1007/BFb0002891.

  25. P. D'Ambra, D. di Serafino, G. Giunta, A. Riccio, Parallel Numerical Simulation of Reacting Flows in Air Quality Models, in "Parallel Computational Fluid Dynamics. Algorithms and Results Using Advanced Computers", P. Schiano, A. Ecer, J. Periaux, N. Satofuka eds., Elsevier, 1997, pp. 116-123, ISBN:978-0-444-82327-4, doi: 10.1016/B978-044482327-4/50081-4

Unpublished preprints and other

  1. E. Galaris, G. Fabiani, F. Calabrò, D. di Serafino, C. Siettos, Numerical Solution of Stiff ODEs with Physics-Informed Random Projection Neural Networks, 2021, arXiv preprint.

  2. P. Papaioannou, R. Talmon, D. di Serafino, I. Kevrekidis, C. Siettos, Time Series Forecasting Using Manifold Learning, 2021, arXiv preprint.

  3. V. Villani, D. di Serafino, G. Rianna, P. Mercogliano, Stochastic Models for the Disaggregation of Precipitation Time Series on Sub-Daily Scale: Identification of Parameters by Global Optimization, CMCC (Euro-Mediterranean Centre for Climate Change) Research Paper No. RP0256, April 2015, available at SSRN, doi: 10.2139/ssrn.2602889.

  4. P. D'Ambra, A. Buttari, D. di Serafino, S. Filippone, S. Gentile, B. Uçar, A Novel Aggregation Method based on Graph Matching for Algebraic MultiGrid Preconditioning of Sparse Linear Systems, International Conference on Preconditioning Techniques for Scientific and Industrial Applications (Preconditioning 2011), May 2011, Bordeaux, France, HAL-INRIA.

  5. P. D'Ambra, D. di Serafino, S. Filippone, MLD2P4 User's and Reference Guide, software version 2.2, July 2018

  6. A. Aprovitola, P. D'Ambra, F.M. Denaro, D. di Serafino, S. Filippone, Application of parallel algebraic multilevel domain decomposition preconditioners in large eddy simulations of wall-bounded turbulent flows: first experiments, ICAR-CNR Technical Report RT-ICAR-NA-07-02, 2007.

  7. I. de Bono, M.L. De Cesare, D. di Serafino, F.Perla, C06MCFP: a Parallel One-Dimensional Mixed-Radix FFT Routine for MIMD Distributed-Memory Machines, CPS-CNR Tech. Rep. TR-97-17, 1997.

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