Acceleration Scheme for Parallel Projected Aggregation Methods for Solving Large Linear Systems

The Projected Aggregation methods generate the new point xk+1 as the projection of xk onto an "aggregate" hyperplane usually arising from linear combinations of the hyperplanes defined by the blocks. The aim of this paper is to improve the speed of convergence of a particular kind of them...

Descripción completa

Guardado en:
Detalles Bibliográficos
Autor principal: Scolnik, H.
Otros Autores: Echebest, N., Guardarucci, M.T, Vacchino, M.C
Formato: Capítulo de libro
Lenguaje:Inglés
Publicado: 2002
Acceso en línea:Registro en Scopus
DOI
Handle
Registro en la Biblioteca Digital
Aporte de:Registro referencial: Solicitar el recurso aquí
LEADER 05175caa a22005177a 4500
001 PAPER-5183
003 AR-BaUEN
005 20230518203448.0
008 190411s2002 xx ||||fo|||| 00| 0 eng|d
024 7 |2 scopus  |a 2-s2.0-0036959207 
040 |a Scopus  |b spa  |c AR-BaUEN  |d AR-BaUEN 
100 1 |a Scolnik, H. 
245 1 0 |a Acceleration Scheme for Parallel Projected Aggregation Methods for Solving Large Linear Systems 
260 |c 2002 
270 1 0 |m Departamento de Computación, Fac. de Ciencias Exactas y Naturales, Universidad de Buenos AiresArgentina; email: hugo@dc.uba.ar 
506 |2 openaire  |e Política editorial 
504 |a Aharoni, R., Censor, Y., Block-iterative projection methods for parallel computation of solutions to convex feasibility problems (1989) Linear Algebra Appl., 120, pp. 165-175 
504 |a Bramley, R., Sameh, A., Row projection methods for large nonsymmetric linear systems (1992) SIAM J. Sci. Statist. Comput., 13, pp. 168-193 
504 |a Censor, Y., Gordon, D., Gordon, R., (1998) Component Averaging: An Efficient Iterative Parallel Algorithm for Large and Sparce Unstructured Problems, , Technical Report, Department of Mathematics, University of Haifa, Israel (accepted for publication in Parallel Computing) 
504 |a Censor, Y., Zenios, S., (1997) Parallel Optimization: Theory and Applications, , Oxford University Press, New York 
504 |a Cimmino, G., Calcolo approssimato per le soluzioni dei sistemi di equazioni lineari (1938) Ric. Sci., 16, pp. 326-333 
504 |a García-Palomares, U.M., Parallel projected aggregation methods for solving the convex feasibility problem (1993) SIAM J. Optim., 3, pp. 882-900 
504 |a Gubin, L.G., Polyak, B.T., Raik, E.V., The method of projections for finding the common point of convex sets (1967) USSR Comput. Math. and Math. Phys., 7, pp. 1-24 
504 |a Iusem, A., De Pierro, A., Convergence results for an accelerated nonlinear Cimmino algorithm (1986) Numer. Math., 49, pp. 367-378 
504 |a Kaczmarz, S., Angenäherte Auflösung von Systemen linearer Gleichungen (1937) Bull. Intern. Acad. Polonaise Sci. Lett., 35, pp. 355-357 
504 |a Scolnik, H.D., A new method for solving large sparse systems of linear equations using row projections (1998) Proceedings of IMACS International Multiconference Congress Computational Engineering in Systems Applications, pp. 26-30. , Nabeul-Hammamet, Tunisia 
504 |a Scolnik, H.D., (2000) A Class of Optimized Row Projection Methods for Solving Large Non-Symmetric Linear Systems, Report Notas de Matemática-74, , Department of Mathematics, University of La Plata, to appear in Applied Numerical Mathematics 
520 3 |a The Projected Aggregation methods generate the new point xk+1 as the projection of xk onto an "aggregate" hyperplane usually arising from linear combinations of the hyperplanes defined by the blocks. The aim of this paper is to improve the speed of convergence of a particular kind of them by projecting the directions given by the blocks onto the aggregate hyperplane defined in the last iteration. For that purpose we apply the scheme introduced in "A new method for solving large sparse systems of linear equations using row projections" [11], for a given block projection algorithm, to some new methods here introduced whose main features are related to the fact that the projections do not need to be accurately computed. Adaptative splitting schemes are applied which take into account the structure and conditioning of the matrix. It is proved that these new highly parallel algorithms improve the original convergence rate and present numerical results which show their computational efficiency.  |l eng 
536 |a Detalles de la financiación: 11/X243 
536 |a Detalles de la financiación: ∗Work supported by the universities of Buenos Aires and La Plata (Project 11/X243), Argentina. 
593 |a Departamento de Computación, Fac. de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Argentina 
593 |a Departamento de Matemática, Facultad de Ciencias Exactas, Universidad Nacional de La Plata, La Plata, Argentina 
690 1 0 |a PARALLEL ITERATIVE METHODS 
690 1 0 |a PROJECTED AGGREGATION METHODS 
690 1 0 |a ROW PARTITION STRATEGIES 
700 1 |a Echebest, N. 
700 1 |a Guardarucci, M.T. 
700 1 |a Vacchino, M.C. 
773 0 |d 2002  |g v. 117  |h pp. 95-115  |k n. 1-4  |p Ann. Oper. Res.  |x 02545330  |t Annals of Operations Research 
856 4 1 |u https://www.scopus.com/inward/record.uri?eid=2-s2.0-0036959207&doi=10.1023%2fA%3a1021565305371&partnerID=40&md5=11ae9c8b97adaa5c1f69a1b52917737b  |y Registro en Scopus 
856 4 0 |u https://doi.org/10.1023/A:1021565305371  |y DOI 
856 4 0 |u https://hdl.handle.net/20.500.12110/paper_02545330_v117_n1-4_p95_Scolnik  |y Handle 
856 4 0 |u https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_02545330_v117_n1-4_p95_Scolnik  |y Registro en la Biblioteca Digital 
961 |a paper_02545330_v117_n1-4_p95_Scolnik  |b paper  |c PE 
962 |a info:eu-repo/semantics/article  |a info:ar-repo/semantics/artículo  |b info:eu-repo/semantics/publishedVersion 
999 |c 66136