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Tytuł artykułu

A parallel algorithm of icsym forcomplexsymmetric linear systems in quantum chemistry

Treść / Zawartość
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Computational effort is a common issue for solving large-scale complex symmetric linear systems, particularly in quantum chemistry applications. In order to alleviate this problem, we propose a parallel algorithm of improved conjugate gradient-type iterative (ICSYM). Using three-term recurrence relation and or- thogonal properties of residual vectors to replace the tridiagonalization process of classical CSYM, which allows to decrease the degree of the reduce-operator from two to one communication at each iteration and to reduce the amount of vector updates and vector multiplications. Several numerical examples are implemented to show that high performance of proposed improved version is obtained both in convergent rate and in parallel efficiency.
Wydawca
Czasopismo
Rocznik
Strony
385--401
Opis fizyczny
Bibliogr. 21 poz., rys., tab.
Twórcy
autor
  • School of Mechanical Engineering, Northwestern Polytechnical University, Box 552, Xi'an, 710072, Shaanxi, China
autor
  • Department of Applied Mathematics, Northwestern Polytechnical University, Xi'an 710072, Shaanxi, China
autor
  • Department of Applied Mathematics, Northwestern Polytechnical University, Xi'an 710072, Shaanxi, China
autor
  • School of Marine Science and Technology, Northwestern Polytechnical University, Box 24, Xi'an, 710072, Shaanxi, China
autor
  • Sorbonne Universites, Universite de Technologie de Compiegne, Laboratoire Roberval, France
Bibliografia
  • [1] Bai Z., Day D., Demmel J., Dongarra J.: A Test Matrix Collection for Non- -Hermitian Eigenvalue Problems. In: Technical Report CS-97-355, 1997.
  • [2] Bucker H.M., Sauren M.: A parallel version of the Quasi-Minimal Residual method based on coupled two-term recurrences, International Workshop on Applied Parallel Computing, vol. 1184, pp. 157-165, 1996.
  • [3] Bunse-Gerstner A., Stover R.: On a conjugate gradient-type method for solving complex symmetric linear systems, Linear Algebra and its Applications, vol. 287(1-3), pp. 105-123, 1999.
  • [4] Chen G., Hong A., Chen J., Zheng Q., Shan J.L.: The Parallel Algorithm. Higher Education Press, Beijing, 2004.
  • [5] Clemens M., Weiland T., Van Rienen U.: Comparison of Krylov-type methods for complex linear systems applied to high-voltage problems, IEEE Transactions on Magnetics, vol. 34, pp. 3335-3338, 1998.
  • [6] Elman H., OLeary D.: Eigenanalysis of some preconditioned Helmholtz problems, Numerische Mathematik, vol. 83(2), pp. 231-257, 1999.
  • [7] Gu X., Clemens M., Huang T., Li L.: The SCBiCG class of algorithms for complex symmetric linear systems with applications in several electromagnetic model problems, Computer Physics Communication, vol. 191, pp. 52-64, 2015.
  • [8] Hu Q., Yuan L.: A Plane-Wave Least-Squares Method for Time-Harmonic Maxwell's Equations in Absorbing Media, SIAM Journal on Scientic Computing, vol. 36(4), pp. A1937-A1959, 2014.
  • [9] Hu Q., Yuan L.: A Weighted Variational Formulation Based on Plane Wave Basis for Discretization of Helmholtz Equations, International Journal of Numerical Analysis and Modeling, vol. 11(3), pp. 587-607, 2014.
  • [10] Huttunen T., Malinen M., Monk P.: Solving Maxwell's equations using the ultra weak variational formulation, Journal of Computational Physics, vol. 223(2), pp. 731-758, 2007. [11] Kumar V., Rao V.N.: Parallel depth rst search. Part II. Analysis, International Journal of Parallel Programming, vol. 18, pp. 501-509, 1987.
  • [12] Li C., Qiao Z.: A Fast Preconditioned Iterative Algorithm for the Electromagnetic Scattering From a Large Cavity, Journal of Scientic Computing, vol. 53, pp. 435-450, 2012. [13] Sogabe T., Zhang S.-L.: A COCR method for solving complex symmetric linear systems, Journal of Computational and Applied Mathematics, vol. 199, pp. 297-303, 2007.
  • [14] Van der Vorst H.: Iterative Krylov Methods for Large Linear Systems. Cambridge University Press, Cambridge, 2003.
  • [15] Van der Vorst H.A., Melissen J.B.M.: A Petrov-Galerkin type method for solving Ax = b, where A is symmetric complex, IEEE Transactions on Magnetics, vol. 26, pp. 706-708, 1990. [16] Wu J., Wang Z., Li X.: Ecient solution and parallel computation of sparse linear equations. Hunan Science and Technology Press, Changsha, 2004.
  • [17] Xiang T., Liang C.: Iterative solution for dense linear systems arising in computation electromagnetics, Journal of Xidian University, vol. 30, pp. 748-751, 2003.
  • [18] Yang L.T., Brent R.P: The improved BiCG method for large and sparse nonsymmetric linear systems on parallel distributed memory architectures, International Parallel and Distributed Processing Symposium, vol. 3, pp. 1-7, 2002.
  • [19] Yang L.T., Brent R.P.: The improved BiCGStab method for large and sparse nonsymmetric linear systems on parallel distributed memory architectures. In: Proceedings of Fifth International Conference on Algorithms and Architectures for Parallel Processing, pp. 324-328, 2002.
  • [20] Zhag L.-T., Zuo X.-Y., Gu T.-X., Huang T.-Z., Yue J.-H.: Conjugate residual squared method and its improvement for non-symmetric linear systems, International Journal of Computer Mathematics, vol. 87, pp. 1578-1590, 2010.
  • [21] Zuo X., Liu Y., Zhang L., Meng H.: A parallel version of COCR method for solving complex symmetric linear systems, Parallel and Cloud Computing Research, vol. 2(1), pp. 12-18, 2014.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-84e1bc64-c8a5-4827-8a3b-99b86c954d5c
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