The single-grid multilevel method  and its applications

Jinchao Xu

doi:10.3934/ipi.2013.7.987

Previous Article
General convergent expectation maximization (EM)-type algorithms for image reconstruction
IPI Home
This Issue
Next Article
Energy conserving local discontinuous Galerkin methods for wave propagation problems

August 2013, 7(3): 987-1005. doi: 10.3934/ipi.2013.7.987

The single-grid multilevel method and its applications

Jinchao Xu ^1,

1.	Department of Mathematics, The Pennsylvania State Univeristy, University Park, PA 16802, United States

Received October 2012 Revised February 2013 Published September 2013

Abstract
Related Papers

In this paper, we propose the single-grid multilevel (SGML) method for large-scale linear systems discretized from partial differential equations. The SGML method combines the methodologies of both the geometric and the algebraic multigrid methods. It uses the underlying geometric information from the finest grid. A simple and isotropic coarsening strategy is applied to explicitly control the complexity of the hierarchical structure, and smoothers are chosen based on the property of the model problem and the underlying grid information to complement the coarsening and maintain overall efficiency. Additionally, the underlying grid is used to design an efficient parallel algorithm in order to parallelize the SGML method. We apply the SGML method on the Poisson problem and the convection diffusion problem as examples, and we present the numerical results to demonstrate the performance of the SGML method.

Keywords: Large-scale linear system, multigrid method, single-grid multilevel method..

Mathematics Subject Classification: Primary: 65N22, 65N55; Secondary: 65F1.

Citation: Jinchao Xu. The single-grid multilevel method and its applications. Inverse Problems & Imaging, 2013, 7 (3) : 987-1005. doi: 10.3934/ipi.2013.7.987

References:

[1]	D. N. Arnold, R. S. Falk and R. Winther, Multigrid in H(div) and H(curl), Numer. Math., 85 (2000), 197-218. doi: 10.1007/PL00005386. Google Scholar
[2]	R. Blaheta, A multilevel method with correction by aggregation for solving discrete elliptic problems, Apl. Mat., 31 (1986), 365-378. Google Scholar
[3]	D. Braess, Towards algebraic multigrid for elliptic problems of second order, Computing, 55 (1995), 379-393. doi: 10.1007/BF02238488. Google Scholar
[4]	J. H. Bramble, "Multigrid Methods," Pitman Research Notes in Mathematical Sciences, 294, Longman Scientific & Technical, Essex, England, 1993. Google Scholar
[5]	A. Brandt, Multi-level adaptive solutions to boundary-value problems, Math. Comp., 31 (1977), 333-390. doi: 10.1090/S0025-5718-1977-0431719-X. Google Scholar
[6]	A. Brandt, "Multigrid Techniques: 1984 Guide with Applications to Fluid Dynamics," GMD-Studien [GMD Studies], 85, Gesellschaft für Mathematik und Datenverarbeitung mbH, St. Augustin, 1984. Google Scholar
[7]	A. Brandt, General highly accurate algebraic coarsening, Elect. Trans. Numer. Anal., 10 (2000), 1-20. Google Scholar
[8]	A. Brandt, J. Brannick, K. Kahl and I. Livshits, Bootstrap AMG, SIAM J. Sci. Comput., 33 (2011), 612-632. doi: 10.1137/090752973. Google Scholar
[9]	A. Brandt, S. McCormick and J. Ruge, Algebraic multigrid (AMG) for sparse matrix equations, In "Sparsity and its Applications" (Loughborough, 1983), Cambridge Univ. Press, Cambridge, (1985), 257-284. Google Scholar
[10]	A. Brandt, S. F. McCormick and J. W. Ruge, Algebraic multigrid (AMG) for sparse matrix equations, in "Sparsity and its Applications" (ed. D. J. Evans), Cambridge University Press, Cambridge, 1984. Google Scholar
[11]	J. Brannick, Y. Chen, J. Krauss and L. Zikatanov, An algebraic multigrid method based on matching in graphs, in "Domain Decomposition Methods in Science and Engineering XX," Lecture Notes in Computational Science and Engineering, 91, Springer, (2013), 143-150. doi: 10.1007/978-3-642-35275-1_15. Google Scholar
[12]	J. Brannick, Y. Chen and L. Zikatanov, An algebraic multilevel method for anisotropic elliptic equations based on graph partitioning, Numer. Linear Algebra Appl., 19 (2012), 279-295. doi: 10.1002/nla.1804. Google Scholar
[13]	J. Brannick and L. Zikatanov, Algebraic multigrid methods based on compatible relaxation and energy minimization, in "Domain Decomposition Methods in Science and Engineering XVI," Lect. Notes Comput. Sci. Eng., 55, Springer, Berlin, (2007), 15-26. doi: 10.1007/978-3-540-34469-8_2. Google Scholar
[14]	M. Brezina, A. Cleary, R. Falgout, V. Henson, J. Jones, T. Manteuffel, S. McCormick and J. Ruge, Algebraic multigrid based on element interpolation (amge), SIAM Journal on Scientific Computing, 22 (2001), 1570-1592. doi: 10.1137/S1064827598344303. Google Scholar
[15]	M. Brezina, R. Falgout, S. MacLachlan, T. Manteuffel, S. McCormick and J. Ruge, Adaptive smoothed aggregation $(\alpha SA)$ multigrid, SIAM Rev., 47 (2005), 317-346. doi: 10.1137/050626272. Google Scholar
[16]	W. L. Briggs, V. E. Henson and S. F. McCormick, "A Multigrid Tutorial," Second edition, SIAM, Philadelphia, PA, 2000. doi: 10.1137/1.9780898719505. Google Scholar
[17]	V. E. Bulgakov, Multi-level iterative technique and aggregation concept with semi-analytical preconditioning for solving boundary-value problems, Communications in Numerical Methods in Engineering, 9 (1993), 649-657. doi: 10.1002/cnm.1640090804. Google Scholar
[18]	T. Chartier, R. Falgout, V. E. Henson, J. E. Jones, T. A. Manteuffel, S. F. McCormick, J. W. Ruge and P. S. Vassilevski, Spectral element agglomerate AMGe, in "Domain Decomposition Methods in Science and Engineering XVI," Lect. Notes Comput. Sci. Eng., 55, Springer, Berlin, (2007), 513-521. doi: 10.1007/978-3-540-34469-8_64. Google Scholar
[19]	T. Chartier, R. D. Falgout, V. E. Henson, J. Jones, T. Manteuffel, S. McCormick, J. Ruge and P. S. Vassilevski, Spectral AMGe ($\rho$ AMGe), SIAM J. Sci. Comput., 25 (2003), 1-26. doi: 10.1137/S106482750139892X. Google Scholar
[20]	R. Fletcher and C. M. Reeves, Function minimization by conjugate gradients, The Computer Journal, 7 (1964), 149-154. doi: 10.1093/comjnl/7.2.149. Google Scholar
[21]	M. Garland and N. Bell, CUSP: Generic parallel algorithms for sparse matrix and graph computations,, 2010., (). Google Scholar
[22]	L. Grasedyck, J. Xu and L. Wang, Algebraic multigrid methods based on auxiliary grids, preprint, 2013. Google Scholar
[23]	W. Hackbusch, "Multigrid Methods and Applications," Computational Mathematics, 4, Springer-Verlag, Berlin, 1985. Google Scholar
[24]	V. E. Henson and P. S. Vassilevski, Element-free AMGe: General algorithms for computing interpolation weights in AMG, Copper Mountain Conference (2000), SIAM J. Sci. Comput., 23 (2001), 629-650 (electronic). doi: 10.1137/S1064827500372997. Google Scholar
[25]	R. Hiptmair, Multigrid method for Maxwell's equations, SIAM J. Numer. Anal., 36 (1999), 204-225. doi: 10.1137/S0036142997326203. Google Scholar
[26]	X. Hu, P. S. Vasilevski and J. Xu, Comparative convergence analysis of nonlinear AMLI-cycle multigrid, Submitted to SIAM Journal on Numerical Analysis., 51 (2013), 1349-1369. doi: 10.1137/110850049. Google Scholar
[27]	J. E. Jones and P. S. Vassilevski, AMGe based on element agglomeration, SIAM J. Sci. Comput., 23 (2001), 109-133 (electronic). doi: 10.1137/S1064827599361047. Google Scholar
[28]	H. Kim, J. Xu and L. Zikatanov, A multigrid method based on graph matching for convection-diffusion equations, Numer. Linear Algebra Appl., 10 (2003), 181-195. doi: 10.1002/nla.317. Google Scholar
[29]	H. Kim, J. Xu and L. Zikatanov, Uniformly convergent multigrid methods for convection-diffusion problems without any constraint on coarse grids, Adv. Comput. Math., 20 (2004), 385-399. doi: 10.1023/A:1027378015262. Google Scholar
[30]	J. K. Kraus, An algebraic preconditioning method for $M$-matrices: Linear versus non-linear multilevel iteration, Numer. Linear Algebra Appl., 9 (2002), 599-618. doi: 10.1002/nla.281. Google Scholar
[31]	I. Lashuk and P. S. Vassilevski, On some versions of the element agglomeration AMGe method, Numer. Linear Algebra Appl., 15 (2008), 595-620. doi: 10.1002/nla.585. Google Scholar
[32]	O. Livne and A. Brandt, Lean algebraic multigrid (lamg): Fast graph laplacian linear solver, SIAM J. Sci. Comput., 34 (2012), 499-522. doi: 10.1137/110843563. Google Scholar
[33]	J. Mandel, M. Brezina and P. Vaněk, Energy optimization of algebraic multigrid bases, Computing, 62 (1999), 205-228. doi: 10.1007/s006070050022. Google Scholar
[34]	Y. Notay, An aggregation-based algebraic multigrid method, Electronic Transactions on Numerical Analysis, 37 (2010), 123-146. Google Scholar
[35]	Y. Notay and A. Napov, An aggregation-based algebraic multigrid method, Electronic Transactions on Numerical Analysis, 37 (2010), 123-146. Google Scholar
[36]	Y. Notay and P. S. Vassilevski, Recursive Krylov-based multigrid cycles, Numer. Linear Algebra Appl., 15 (2008), 473-487. doi: 10.1002/nla.542. Google Scholar
[37]	J. W. Ruge and K. Stüben, Algebraic multigrid, in "Multigrid Methods" (ed. S. F. McCormick), Frontiers in Applied Mathematics, 3, SIAM, Philadelphia, Pennsylvania, (1987), 73-130. Google Scholar
[38]	Y. Saad, A flexible inner-outer preconditioned gmres algorithm, SIAM Journal on Scientific Computing, 14 (1993), 461-469. doi: 10.1137/0914028. Google Scholar
[39]	K. Stüben, An introduction to algebraic multigrid, in "Multigrid" (eds. U. Trottenberg, C. Oosterlee and A. Schüller), Academic Press, San Diego, CA, (2001), 413-528. Google Scholar
[40]	U. Trottenberg, C. Oosterlee and A. Schüller, "Multigrid," Academic Press, Inc., San Diego, CA, 2001. Google Scholar
[41]	P. Vaněk, J. Mandel and M. Brezina, Algebraic multigrid by smoothed aggregation for second and fourth order elliptic problems, International GAMM-Workshop on Multi-level Methods (Meisdorf, 1994), Computing, 56 (1996), 179-196. doi: 10.1007/BF02238511. Google Scholar
[42]	P. S. Vassilevski, "Multilevel Block Factorization Preconditioners. Matrix-based Analysis and Algorithms for Solving Finite Element Equations," Springer, New York, 2008. Google Scholar
[43]	W. L. Wan, T. F. Chan and B. Smith, An energy-minimizing interpolation for robust multigrid methods, SIAM J. Sci. Comput., 21 (2000), 1632-1649 (electronic). doi: 10.1137/S1064827598334277. Google Scholar
[44]	F. Wang and J. Xu, A crosswind block iterative method for convection-dominated problems, SIAM J. Sci. Comput., 21 (1999), 620-645 (electronic). doi: 10.1137/S106482759631192X. Google Scholar
[45]	L. Wang, X. Hu, J. Cohen and J. Xu, A parallel auxiliary grid AMG method for GPU,, SIAM J. Sci. Comput., 35 (). Google Scholar
[46]	P. Wesseling, "An Introduction to Multigrid Methods," Reprint of the 1992 edition, Cos Cob, CT, 2001. Available from: http://www.MGNet.org. Google Scholar
[47]	J. Xu, Iterative methods by SPD and small subspace solvers for nonsymmetric or indefinite problems, in "Fifth International Symposium on Domain Decomposition Methods for Partial Differential Equations" (Norfolk, VA, 1991), SIAM, Philadelphia, PA, (1992), 106-118. Google Scholar
[48]	J. Xu, The auxiliary space method and optimal multigrid preconditioning techniques for unstructured grids, Computing, 56 (1996), 215-235. doi: 10.1007/BF02238513. Google Scholar
[49]	J. Xu, Fast Poisson-based solvers for linear and nonlinear PDEs, in "Proceedings of the International Congress of Mathematicians. Volume IV," Hindustan Book Agency, New Delhi, (2010), 2886-2912. Google Scholar
[50]	J. Xu and L. Zikatanov, A monotone finite element scheme for convection-diffusion equations, Math. Comp., 68 (1999), 1429-1446. doi: 10.1090/S0025-5718-99-01148-5. Google Scholar
[51]	J. Xu and L. Zikatanov, The method of alternating projections and the method of subspace corrections in Hilbert space, J. Amer. Math. Soc., 15 (2002), 573-597. doi: 10.1090/S0894-0347-02-00398-3. Google Scholar
[52]	J. Xu and L. Zikatanov, On an energy minimizing basis for algebraic multigrid methods, Comput. Vis. Sci., 7 (2004), 121-127. doi: 10.1007/s00791-004-0147-y. Google Scholar
[53]	L. Zikatanov, Two-sided bounds on the convergence rate of two-level methods, Numer. Linear Alg. Appl., 15 (2008), 439-454. doi: 10.1002/nla.556. Google Scholar

show all references

References:

[1]	D. N. Arnold, R. S. Falk and R. Winther, Multigrid in H(div) and H(curl), Numer. Math., 85 (2000), 197-218. doi: 10.1007/PL00005386. Google Scholar
[2]	R. Blaheta, A multilevel method with correction by aggregation for solving discrete elliptic problems, Apl. Mat., 31 (1986), 365-378. Google Scholar
[3]	D. Braess, Towards algebraic multigrid for elliptic problems of second order, Computing, 55 (1995), 379-393. doi: 10.1007/BF02238488. Google Scholar
[4]	J. H. Bramble, "Multigrid Methods," Pitman Research Notes in Mathematical Sciences, 294, Longman Scientific & Technical, Essex, England, 1993. Google Scholar
[5]	A. Brandt, Multi-level adaptive solutions to boundary-value problems, Math. Comp., 31 (1977), 333-390. doi: 10.1090/S0025-5718-1977-0431719-X. Google Scholar
[6]	A. Brandt, "Multigrid Techniques: 1984 Guide with Applications to Fluid Dynamics," GMD-Studien [GMD Studies], 85, Gesellschaft für Mathematik und Datenverarbeitung mbH, St. Augustin, 1984. Google Scholar
[7]	A. Brandt, General highly accurate algebraic coarsening, Elect. Trans. Numer. Anal., 10 (2000), 1-20. Google Scholar
[8]	A. Brandt, J. Brannick, K. Kahl and I. Livshits, Bootstrap AMG, SIAM J. Sci. Comput., 33 (2011), 612-632. doi: 10.1137/090752973. Google Scholar
[9]	A. Brandt, S. McCormick and J. Ruge, Algebraic multigrid (AMG) for sparse matrix equations, In "Sparsity and its Applications" (Loughborough, 1983), Cambridge Univ. Press, Cambridge, (1985), 257-284. Google Scholar
[10]	A. Brandt, S. F. McCormick and J. W. Ruge, Algebraic multigrid (AMG) for sparse matrix equations, in "Sparsity and its Applications" (ed. D. J. Evans), Cambridge University Press, Cambridge, 1984. Google Scholar
[11]	J. Brannick, Y. Chen, J. Krauss and L. Zikatanov, An algebraic multigrid method based on matching in graphs, in "Domain Decomposition Methods in Science and Engineering XX," Lecture Notes in Computational Science and Engineering, 91, Springer, (2013), 143-150. doi: 10.1007/978-3-642-35275-1_15. Google Scholar
[12]	J. Brannick, Y. Chen and L. Zikatanov, An algebraic multilevel method for anisotropic elliptic equations based on graph partitioning, Numer. Linear Algebra Appl., 19 (2012), 279-295. doi: 10.1002/nla.1804. Google Scholar
[13]	J. Brannick and L. Zikatanov, Algebraic multigrid methods based on compatible relaxation and energy minimization, in "Domain Decomposition Methods in Science and Engineering XVI," Lect. Notes Comput. Sci. Eng., 55, Springer, Berlin, (2007), 15-26. doi: 10.1007/978-3-540-34469-8_2. Google Scholar
[14]	M. Brezina, A. Cleary, R. Falgout, V. Henson, J. Jones, T. Manteuffel, S. McCormick and J. Ruge, Algebraic multigrid based on element interpolation (amge), SIAM Journal on Scientific Computing, 22 (2001), 1570-1592. doi: 10.1137/S1064827598344303. Google Scholar
[15]	M. Brezina, R. Falgout, S. MacLachlan, T. Manteuffel, S. McCormick and J. Ruge, Adaptive smoothed aggregation $(\alpha SA)$ multigrid, SIAM Rev., 47 (2005), 317-346. doi: 10.1137/050626272. Google Scholar
[16]	W. L. Briggs, V. E. Henson and S. F. McCormick, "A Multigrid Tutorial," Second edition, SIAM, Philadelphia, PA, 2000. doi: 10.1137/1.9780898719505. Google Scholar
[17]	V. E. Bulgakov, Multi-level iterative technique and aggregation concept with semi-analytical preconditioning for solving boundary-value problems, Communications in Numerical Methods in Engineering, 9 (1993), 649-657. doi: 10.1002/cnm.1640090804. Google Scholar
[18]	T. Chartier, R. Falgout, V. E. Henson, J. E. Jones, T. A. Manteuffel, S. F. McCormick, J. W. Ruge and P. S. Vassilevski, Spectral element agglomerate AMGe, in "Domain Decomposition Methods in Science and Engineering XVI," Lect. Notes Comput. Sci. Eng., 55, Springer, Berlin, (2007), 513-521. doi: 10.1007/978-3-540-34469-8_64. Google Scholar
[19]	T. Chartier, R. D. Falgout, V. E. Henson, J. Jones, T. Manteuffel, S. McCormick, J. Ruge and P. S. Vassilevski, Spectral AMGe ($\rho$ AMGe), SIAM J. Sci. Comput., 25 (2003), 1-26. doi: 10.1137/S106482750139892X. Google Scholar
[20]	R. Fletcher and C. M. Reeves, Function minimization by conjugate gradients, The Computer Journal, 7 (1964), 149-154. doi: 10.1093/comjnl/7.2.149. Google Scholar
[21]	M. Garland and N. Bell, CUSP: Generic parallel algorithms for sparse matrix and graph computations,, 2010., (). Google Scholar
[22]	L. Grasedyck, J. Xu and L. Wang, Algebraic multigrid methods based on auxiliary grids, preprint, 2013. Google Scholar
[23]	W. Hackbusch, "Multigrid Methods and Applications," Computational Mathematics, 4, Springer-Verlag, Berlin, 1985. Google Scholar
[24]	V. E. Henson and P. S. Vassilevski, Element-free AMGe: General algorithms for computing interpolation weights in AMG, Copper Mountain Conference (2000), SIAM J. Sci. Comput., 23 (2001), 629-650 (electronic). doi: 10.1137/S1064827500372997. Google Scholar
[25]	R. Hiptmair, Multigrid method for Maxwell's equations, SIAM J. Numer. Anal., 36 (1999), 204-225. doi: 10.1137/S0036142997326203. Google Scholar
[26]	X. Hu, P. S. Vasilevski and J. Xu, Comparative convergence analysis of nonlinear AMLI-cycle multigrid, Submitted to SIAM Journal on Numerical Analysis., 51 (2013), 1349-1369. doi: 10.1137/110850049. Google Scholar
[27]	J. E. Jones and P. S. Vassilevski, AMGe based on element agglomeration, SIAM J. Sci. Comput., 23 (2001), 109-133 (electronic). doi: 10.1137/S1064827599361047. Google Scholar
[28]	H. Kim, J. Xu and L. Zikatanov, A multigrid method based on graph matching for convection-diffusion equations, Numer. Linear Algebra Appl., 10 (2003), 181-195. doi: 10.1002/nla.317. Google Scholar
[29]	H. Kim, J. Xu and L. Zikatanov, Uniformly convergent multigrid methods for convection-diffusion problems without any constraint on coarse grids, Adv. Comput. Math., 20 (2004), 385-399. doi: 10.1023/A:1027378015262. Google Scholar
[30]	J. K. Kraus, An algebraic preconditioning method for $M$-matrices: Linear versus non-linear multilevel iteration, Numer. Linear Algebra Appl., 9 (2002), 599-618. doi: 10.1002/nla.281. Google Scholar
[31]	I. Lashuk and P. S. Vassilevski, On some versions of the element agglomeration AMGe method, Numer. Linear Algebra Appl., 15 (2008), 595-620. doi: 10.1002/nla.585. Google Scholar
[32]	O. Livne and A. Brandt, Lean algebraic multigrid (lamg): Fast graph laplacian linear solver, SIAM J. Sci. Comput., 34 (2012), 499-522. doi: 10.1137/110843563. Google Scholar
[33]	J. Mandel, M. Brezina and P. Vaněk, Energy optimization of algebraic multigrid bases, Computing, 62 (1999), 205-228. doi: 10.1007/s006070050022. Google Scholar
[34]	Y. Notay, An aggregation-based algebraic multigrid method, Electronic Transactions on Numerical Analysis, 37 (2010), 123-146. Google Scholar
[35]	Y. Notay and A. Napov, An aggregation-based algebraic multigrid method, Electronic Transactions on Numerical Analysis, 37 (2010), 123-146. Google Scholar
[36]	Y. Notay and P. S. Vassilevski, Recursive Krylov-based multigrid cycles, Numer. Linear Algebra Appl., 15 (2008), 473-487. doi: 10.1002/nla.542. Google Scholar
[37]	J. W. Ruge and K. Stüben, Algebraic multigrid, in "Multigrid Methods" (ed. S. F. McCormick), Frontiers in Applied Mathematics, 3, SIAM, Philadelphia, Pennsylvania, (1987), 73-130. Google Scholar
[38]	Y. Saad, A flexible inner-outer preconditioned gmres algorithm, SIAM Journal on Scientific Computing, 14 (1993), 461-469. doi: 10.1137/0914028. Google Scholar
[39]	K. Stüben, An introduction to algebraic multigrid, in "Multigrid" (eds. U. Trottenberg, C. Oosterlee and A. Schüller), Academic Press, San Diego, CA, (2001), 413-528. Google Scholar
[40]	U. Trottenberg, C. Oosterlee and A. Schüller, "Multigrid," Academic Press, Inc., San Diego, CA, 2001. Google Scholar
[41]	P. Vaněk, J. Mandel and M. Brezina, Algebraic multigrid by smoothed aggregation for second and fourth order elliptic problems, International GAMM-Workshop on Multi-level Methods (Meisdorf, 1994), Computing, 56 (1996), 179-196. doi: 10.1007/BF02238511. Google Scholar
[42]	P. S. Vassilevski, "Multilevel Block Factorization Preconditioners. Matrix-based Analysis and Algorithms for Solving Finite Element Equations," Springer, New York, 2008. Google Scholar
[43]	W. L. Wan, T. F. Chan and B. Smith, An energy-minimizing interpolation for robust multigrid methods, SIAM J. Sci. Comput., 21 (2000), 1632-1649 (electronic). doi: 10.1137/S1064827598334277. Google Scholar
[44]	F. Wang and J. Xu, A crosswind block iterative method for convection-dominated problems, SIAM J. Sci. Comput., 21 (1999), 620-645 (electronic). doi: 10.1137/S106482759631192X. Google Scholar
[45]	L. Wang, X. Hu, J. Cohen and J. Xu, A parallel auxiliary grid AMG method for GPU,, SIAM J. Sci. Comput., 35 (). Google Scholar
[46]	P. Wesseling, "An Introduction to Multigrid Methods," Reprint of the 1992 edition, Cos Cob, CT, 2001. Available from: http://www.MGNet.org. Google Scholar
[47]	J. Xu, Iterative methods by SPD and small subspace solvers for nonsymmetric or indefinite problems, in "Fifth International Symposium on Domain Decomposition Methods for Partial Differential Equations" (Norfolk, VA, 1991), SIAM, Philadelphia, PA, (1992), 106-118. Google Scholar
[48]	J. Xu, The auxiliary space method and optimal multigrid preconditioning techniques for unstructured grids, Computing, 56 (1996), 215-235. doi: 10.1007/BF02238513. Google Scholar
[49]	J. Xu, Fast Poisson-based solvers for linear and nonlinear PDEs, in "Proceedings of the International Congress of Mathematicians. Volume IV," Hindustan Book Agency, New Delhi, (2010), 2886-2912. Google Scholar
[50]	J. Xu and L. Zikatanov, A monotone finite element scheme for convection-diffusion equations, Math. Comp., 68 (1999), 1429-1446. doi: 10.1090/S0025-5718-99-01148-5. Google Scholar
[51]	J. Xu and L. Zikatanov, The method of alternating projections and the method of subspace corrections in Hilbert space, J. Amer. Math. Soc., 15 (2002), 573-597. doi: 10.1090/S0894-0347-02-00398-3. Google Scholar
[52]	J. Xu and L. Zikatanov, On an energy minimizing basis for algebraic multigrid methods, Comput. Vis. Sci., 7 (2004), 121-127. doi: 10.1007/s00791-004-0147-y. Google Scholar
[53]	L. Zikatanov, Two-sided bounds on the convergence rate of two-level methods, Numer. Linear Alg. Appl., 15 (2008), 439-454. doi: 10.1002/nla.556. Google Scholar

[1]	Boris Kramer, John R. Singler. A POD projection method for large-scale algebraic Riccati equations. Numerical Algebra, Control & Optimization, 2016, 6 (4) : 413-435. doi: 10.3934/naco.2016018
[2]	Rouhollah Tavakoli, Hongchao Zhang. A nonmonotone spectral projected gradient method for large-scale topology optimization problems. Numerical Algebra, Control & Optimization, 2012, 2 (2) : 395-412. doi: 10.3934/naco.2012.2.395
[3]	Gaohang Yu. A derivative-free method for solving large-scale nonlinear systems of equations. Journal of Industrial & Management Optimization, 2010, 6 (1) : 149-160. doi: 10.3934/jimo.2010.6.149
[4]	Yigui Ou, Wenjie Xu. A unified derivative-free projection method model for large-scale nonlinear equations with convex constraints. Journal of Industrial & Management Optimization, 2021 doi: 10.3934/jimo.2021125
[5]	Hong Seng Sim, Chuei Yee Chen, Wah June Leong, Jiao Li. Nonmonotone spectral gradient method based on memoryless symmetric rank-one update for large-scale unconstrained optimization. Journal of Industrial & Management Optimization, 2021 doi: 10.3934/jimo.2021143
[6]	Hao Li, Hai Bi, Yidu Yang. The two-grid and multigrid discretizations of the $ C^0 $IPG method for biharmonic eigenvalue problem. Discrete & Continuous Dynamical Systems - B, 2020, 25 (5) : 1775-1789. doi: 10.3934/dcdsb.2020002
[7]	Xin-Guo Liu, Kun Wang. A multigrid method for the maximal correlation problem. Numerical Algebra, Control & Optimization, 2012, 2 (4) : 785-796. doi: 10.3934/naco.2012.2.785
[8]	Danuta Gaweł, Krzysztof Fujarewicz. On the sensitivity of feature ranked lists for large-scale biological data. Mathematical Biosciences & Engineering, 2013, 10 (3) : 667-690. doi: 10.3934/mbe.2013.10.667
[9]	Mahmut Çalik, Marcel Oliver. Weak solutions for generalized large-scale semigeostrophic equations. Communications on Pure & Applied Analysis, 2013, 12 (2) : 939-955. doi: 10.3934/cpaa.2013.12.939
[10]	Philippe Bonneton, Nicolas Bruneau, Bruno Castelle, Fabien Marche. Large-scale vorticity generation due to dissipating waves in the surf zone. Discrete & Continuous Dynamical Systems - B, 2010, 13 (4) : 729-738. doi: 10.3934/dcdsb.2010.13.729
[11]	Jingzhi Li, Hongyu Liu, Qi Wang. Fast imaging of electromagnetic scatterers by a two-stage multilevel sampling method. Discrete & Continuous Dynamical Systems - S, 2015, 8 (3) : 547-561. doi: 10.3934/dcdss.2015.8.547
[12]	Hongsong Feng, Shan Zhao. A multigrid based finite difference method for solving parabolic interface problem. Electronic Research Archive, 2021, 29 (5) : 3141-3170. doi: 10.3934/era.2021031
[13]	Tsuguhito Hirai, Hiroyuki Masuyama, Shoji Kasahara, Yutaka Takahashi. Performance analysis of large-scale parallel-distributed processing with backup tasks for cloud computing. Journal of Industrial & Management Optimization, 2014, 10 (1) : 113-129. doi: 10.3934/jimo.2014.10.113
[14]	Suli Zou, Zhongjing Ma, Xiangdong Liu. Auction games for coordination of large-scale elastic loads in deregulated electricity markets. Journal of Industrial & Management Optimization, 2016, 12 (3) : 833-850. doi: 10.3934/jimo.2016.12.833
[15]	Bo You, Chengkui Zhong, Fang Li. Pullback attractors for three dimensional non-autonomous planetary geostrophic viscous equations of large-scale ocean circulation. Discrete & Continuous Dynamical Systems - B, 2014, 19 (4) : 1213-1226. doi: 10.3934/dcdsb.2014.19.1213
[16]	Boling Guo, Guoli Zhou. Finite dimensionality of global attractor for the solutions to 3D viscous primitive equations of large-scale moist atmosphere. Discrete & Continuous Dynamical Systems - B, 2018, 23 (10) : 4305-4327. doi: 10.3934/dcdsb.2018160
[17]	Masataka Kato, Hiroyuki Masuyama, Shoji Kasahara, Yutaka Takahashi. Effect of energy-saving server scheduling on power consumption for large-scale data centers. Journal of Industrial & Management Optimization, 2016, 12 (2) : 667-685. doi: 10.3934/jimo.2016.12.667
[18]	Bo You, Chunxiang Zhao. Approximation of stationary statistical properties of the three dimensional autonomous planetary geostrophic equations of large-scale ocean circulation. Discrete & Continuous Dynamical Systems - B, 2020, 25 (8) : 3183-3198. doi: 10.3934/dcdsb.2020057
[19]	Linfei Wang, Dapeng Tao, Ruonan Wang, Ruxin Wang, Hao Li. Big Map R-CNN for object detection in large-scale remote sensing images. Mathematical Foundations of Computing, 2019, 2 (4) : 299-314. doi: 10.3934/mfc.2019019
[20]	Bo You. Well-posedness for the three dimensional stochastic planetary geostrophic equations of large-scale ocean circulation. Discrete & Continuous Dynamical Systems, 2021, 41 (4) : 1579-1604. doi: 10.3934/dcds.2020332

2020 Impact Factor: 1.639

American Institute of Mathematical Sciences

The single-grid multilevel method and its applications

References:

References:

Tools

Metrics

Other articles
by authors

Tools

Metrics

Other articles
by authors

American Institute of Mathematical Sciences

The single-grid multilevel method and its applications

References:

References:

Tools

Metrics

Other articlesby authors

Tools

Metrics

Other articlesby authors

Other articles
by authors

Other articles
by authors