Fakultät für Mathematik und Naturwissenschaften

Veröffentlichungen

Preprints IMACM

2024
144.
A. Frommer, M. Rinelli and M. Schweitzer, "Analysis of stochastic probing methods for estimating the trace of functions of sparse symmetric matrices", Math. Comp., 2024.
143.
M. Bolten, O. T. Doganay, H. Gottschalk and K. Klamroth, "Non-convex shape optimization by dissipative Hamiltonian flows", Eng. Optim., pp. 1—20, 2024.
142.
V. Vinod and P. Zaspel, "Assessing Non-Nested Configurations of Multifidelity Machine Learning for Quantum-Chemical Properties", Machine Learning: Science and Technology, vol. 5, no. 4, pp. 045005, 2024.
141.
B. Arslan, S. D. Relton and M. Schweitzer, "Structured level-2 condition numbers of matrix functions", Electron. J. Linear Algebra, vol. 40, pp. 28-47, 2024.
140.
D. Palitta, M. Schweitzer and V. Simoncini, "Sketched and truncated polynomial Krylov subspace methods: Matrix Sylvester equations", Math. Comp., 2024.
139.
D. Palitta, M. Schweitzer and V. Simoncini, "Sketched and truncated polynomial Krylov methods: Evaluation of matrix functions", Numer. Linear Algebra Appl., 2024.
138.
V. Vinod, D. Lyu, M. Ruth, U. Kleinekathöfer, P. R. Schreiner and P. Zaspel, "Predicting Molecular Energies of Small Organic Molecules with Multifidelity Methods.", 2024.
137.
A. Frommer, G. Ramirez-Hidalgo, M. Schweitzer and M. Tsolakis, "Polynomial preconditioning for the action of the matrix square root and inverse square root", Electron. Trans. Numer. Anal., vol. 60, pp. 381-404, 2024.
136.
V. Vinod, U. Kleinekathöfer and P. Zaspel, "Optimized multifidelity machine learning for quantum chemistry", Mach. Learn.: Sci. Technol., vol. 5, no. 1, pp. 015054, 2024.
135.
V. Vinod and P. Zaspel, "QeMFi: A Multifidelity Dataset of Quantum Chemical Properties of Diverse Molecules", 2024.
134.
M. Bolten, M. E. Kilmer and S. MacLachlan, "Multigrid preconditioning for regularized least-squares problems", SIAM J. Sci. Comput., vol. 46, no. 5, pp. s271—s295, 2024.
133.
V. Vinod and P. Zaspel, "Investigating Data Hierarchies in Multifidelity Machine Learning for Excitation Energies", 2024.
132.
D. Lyu, M. Holzenkamp, V. Vinod, Y. M. Holtkamp, S. Maity, C. R. Salazar, U. Kleinekathöfer and P. Zaspel, "Excitation Energy Transfer between Porphyrin Dyes on a Clay Surface: A study employing Multifidelity Machine Learning.", 2024.
131.
M. Holzenkamp, D. Lyu, U. Kleinekathöfer and P. Zaspel, "Evaluation of uncertainty estimations for Gaussian process regression based machine learning interatomic potentials.", 2024.
130.
V. Vinod and P. Zaspel, "Benchmarking Data Efficiency in Δ-ML and Multifidelity Models for Quantum Chemistry.", 2024.
129.
P. Zaspel and M. Günther, "Data-driven identification of port-Hamiltonian DAE systems by Gaussian processes.", 2024.
128.
R. Yoda, M. Bolten, K. Nakajima and A. Fujii, "Coarse-grid operator optimization in multigrid reduction in time for time-dependent Stokes and Oseen problems", Jpn. J. Ind. Appl. Math., 2024.
127.
M. Fasi, S. Gaudreault, K. Lund and M. Schweitzer, "Challenges in computing matrix functions" , 2024.
126.
M. A. Botchev, L. A. Knizhnerman and M. Schweitzer, "Krylov subspace residual and restarting for certain second order differential equations", SIAM J. Sci. Comput., vol. 46, no. 2, pp. S223-S253, 2024.
2023
125.
M. Bolten, M. Donatelli, P. Ferrari and I. Furci, "Symbol based convergence analysis in block multigrid methods with applications for Stokes problems", Appl. Numer. Math., vol. 193, pp. 109-130, 2023.
124.
K. Lund and M. Schweitzer, "The Frechet derivative of the tensor t-function", Calcolo, vol. 60, 2023.
123.
M. Bolten, S. Friedhoff and J. Hahne, "Task graph-based performance analysis of parallel-in-time methods", Parallel Comput., vol. 118, pp. 103050, 2023.
122.
M. Bolten, M. Donatelli, P. Ferrari and I. Furci, "Symbol based convergence analysis in multigrid methods for saddle point problems", Linear Algebra Appl., vol. 671, pp. 67--108, 2023.
121.
M. Schweitzer, "Integral representations for higher-order Frechet derivatives of matrix functions: Quadrature algorithms and new results on the level-2 condition number", Linear Algebra Appl., vol. 656, pp. 247-276, 2023.
120.
M. Schweitzer, "Sensitivity of matrix function based network communicability measures: Computational methods and a priori bounds", SIAM J. Matrix Anal. Appl., vol. 44, no. 3, pp. 1321-1348, 2023.
119.
S. Güttel and M. Schweitzer, "Randomized sketching for Krylov approximations of large-scale matrix functions", SIAM J. Matrix Anal. Appl., vol. 44, pp. 1073-1095, 2023.
118.
V. Vinod, S. Maity, P. Zaspel and U. Kleinekathöfer, "Multifidelity Machine Learning for Molecular Excitation Energies", J. Chem. Theory Comput., vol. 19, no. 21, pp. 7658-7670, 2023.
117.
A. Frommer, K. Kahl, M. Schweitzer and M. Tsolakis, "Krylov subspace restarting for matrix Laplace transforms", SIAM J. Matrix Anal. Appl., vol. 44, no. 2, pp. 693-717, 2023.
116.
M. Bolten, S. -. Ekström, I. Furci and S. Serra-Capizzano, "A note on the spectral analysis of matrix sequences via GLT momentary symbols: from all-at-once solution of parabolic problems to distributed fractional order matrices", Electron. Trans. Numer. Anal., vol. 58, pp. 136--163, 2023.
2022
115.
M. Bolten, S. -. Ekström, I. Furci and S. Serra-Capizzano, "Toeplitz Momentary Symbols: definition, results, and limitations in the spectral analysis of structured matrices", Linear Algebra Appl., vol. 651, pp. 51-82, 2022.
114.
D. Maharjan and P. Zaspel, "Toward data-driven filters in paraview", JFV, vol. 29, no. 3, 2022.
113.
M. Bolten, E. D. Sturler and C. Hahn, "Krylov Subspace Recycling for Evolving Structures", Comput. Methods Appl. Mech. Engrg., vol. 391, pp. 114222, 2022.
112.
M. Schweitzer, "Decay bounds for Bernstein functions of Hermitian matrices with applications to the fractional graph Laplacian", Electron. Trans. Numer. Anal., vol. 55, pp. 438-454, 2022.
111.
R. Yoda, M. Bolten, K. Nakajima and A. Fujii, "Assignment of idle processors to spatial redistributed domains on coarse levels in multigrid reduction in time" in Proceedings of the International Conference on High Performance Computing in Asia-Pacific Region, 2022, pp. 41-51.
110.
R. Yoda, M. Bolten, K. Nakajima and A. Fujii, "Acceleration of optimized coarse-grid operators by spatial redistribution for multigrid reduction in time" in Computational Science - ICCS 2022, Groen, Derek and de Mulatier, Clelia and Paszynski, Maciej and Krzhizhanovskaya, Valeria V. and Dongarra, Jack J. and Sloot, Peter M. A., Eds. Cham: Springer International Publishing, 2022, pp. 214-221.
109.
M. Bolten, M. Donatelli, P. Ferrari and I. Furci, "A symbol-based analysis for multigrid methods for block-circulant and block-Toeplitz systems", SIAM J. Matrix Anal. Appl., vol. 43, no. 1, pp. 405-438, 2022.
2021
108.
B. Beckermann, A. Cortinovis, D. Kressner and M. Schweitzer, "Low-rank updates of matrix functions II: Rational Krylov methods", SIAM J. Numer. Anal., vol. 59, no. 3, pp. 1325-1347, 2021.
107.
M. Sugiyama, J. B. Schroder, B. S. Southworth and S. Friedhoff,Weighted Relaxation for Multigrid Reduction in Time, 2021.
106.
M. Bolten, O. T. Doganay, H. Gottschalk and K. Klamroth, "Tracing locally Pareto optimal points by numerical integration", SIAM J. Control Optim., vol. 59, no. 5, pp. 3302-3328, 2021.
105.
N. Haussmann, M. Zang, R. Mease, M. Clemens, B. Schmuelling and M. Bolten, "Towards real-time magnetic dosimetry simulations for inductive charging systems", COMPEL, 2021.
104.
I. Kulchytska-Ruchka, S. Schöps, M. Hinze, S. Friedhoff and S. Ulbrich, "PASIROM: parallel simulation and robust optimization of electro-mechanical energy converters" in German success stories in industrial mathematics, Springer, Cham, 2021, pp. 135-140.
103.
H. De Sterck, R. D. Falgout, S. Friedhoff, O. A. Krzysik and S. P. MacLachlan, "Optimizing multigrid reduction-in-time and parareal coarse-grid operators for linear advection", Numer. Linear Algebra Appl., vol. 28, no. 4, pp. Paper No. e2367, 22, 2021.
102.
S. Friedhoff and B. S. Southworth, "On "optimal" $h$-independent convergence of parareal and multigrid-reduction-in-time using Runge-Kutta time integration", Numer. Linear Algebra Appl., vol. 28, no. 3, pp. Paper No. e2301, 30, 2021.
101.
P. Ferrari, I. Furci and S. Serra-Capizzano, "Multilevel symmetrized Toeplitz structures and spectral distribution results for the related matrix sequences", Electron. J. Linear Algebra, vol. 37, pp. 370-386, 2021.
100.
M. Donatelli, P. Ferrari, I. Furci, S. Serra-Capizzano and D. Sesana, "Multigrid methods for block-Toeplitz linear systems: convergence analysis and applications", Numer. Linear Algebra Appl., vol. 28, no. 4, pp. Paper No. e2356, 20, 2021.
99.
L. Claus and M. Bolten, "Non-overlapping block smoothers for the Stokes equations", Num. Lin. Alg. Appl., vol. 28, no. 6, pp. e2389, 2021.
98.
J. Backhaus, M. Bolten, O. T. Doganay, M. Ehrhardt, B. Engel, C. Frey, H. Gottschalk, M. Günther, C. Hahn, J. Jäschke, P. Jaksch, K. Klamroth, A. Liefke, D. Luft, L. Mäde, V. Marciniak, M. Reese, J. Schultes and V. Schulz, "GivEn - Shape Optimization for Gas Turbines in Volatile Energy Networks" in Mathematical Modeling, Simulation and Optimization for Power Engineering and Management, S. Göttlich and M. Herty and A. Milde, Eds. Cham: Springer, 2021.
97.
J. Stapmanns, J. Hahne, M. Helias, M. Bolten, M. Diesmann and D. Dahmen, "Event-based update of synapses in voltage-based learning rules", Front. Neuroinform., vol. 15, pp. 15, 2021.
96.
S. Güttel and M. Schweitzer, "A comparison of limited-memory Krylov methods for Stieltjes functions of Hermitian matrices", SIAM J. Matrix Anal. Appl., vol. 42, no. 1, pp. 83-107, 2021.
95.
P. Kandolf, A. Koskela, S. D. Relton and M. Schweitzer, "Computing low-rank approximations of the Frechet derivative of a matrix function using Krylov subspace methods", Numer. Linear Algebra Appl., vol. 28, no. 6, pp. e2401, 31, 2021.
94.
H. Harbrecht, J. D. Jakeman and P. Zaspel, "Cholesky-Based Experimental Design for Gaussian Process and Kernel-Based Emulation and Calibration", CiCP, vol. 29, no. 4, pp. 1152-1185, 2021.
93.
J. Hahne, B. S. Southworth and S. Friedhoff,Asynchronous Truncated Multigrid-reduction-in-time (AT-MGRIT), 2021.
92.
P. Ferrari and S. Serra-Capizzano, "Asymptotic spectra of large matrices coming from the symmetrization of Toeplitz structure functions and applications to preconditioning", Numer. Linear Algebra Appl., vol. 28, no. 1, pp. Paper No. e2332, 16, 2021.
91.
A. Frommer, C. Schimmel and M. Schweitzer, "Analysis of probing techniques for sparse approximation and trace estimation of decaying matrix functions", SIAM J. Matrix Anal. Appl., vol. 42, no. 3, pp. 1290-1318, 2021.
90.
J. Hahne, S. Friedhoff and M. Bolten, "Algorithm 1016: PyMGRIT: a Python package for the parallel-in-time method MGRIT", ACM Trans. Math. Software, vol. 47, no. 2, pp. Art. 19, 22, 2021.
89.
P. Ferrari, C. Garoni and S. Serra-Capizzano, "Fast parallel solver for the space-time IgA-DG discretization of the diffusion equation", J. Sci. Comput., vol. 89, no. 1, pp. Paper No. 20, 21, 2021.
2020
88.
M. Bolten, S. Friedhoff, J. Hahne and S. Schöps, "Parallel-in-time simulation of an electrical machine using MGRIT", Comput. Vis. Sci., vol. 23, no. 1-4, pp. Paper No. 14, 14, 2020.
87.
F. Durastante and I. Furci, "Spectral analysis of saddle-point matrices from optimization problems with elliptic PDE constraints", Electron. J. Linear Algebra, vol. 36, pp. 773-798, 2020.
86.
H. De Sterck, S. Friedhoff, A. J. M. Howse and S. P. MacLachlan, "Convergence analysis for parallel-in-time solution of hyperbolic systems", Numer. Linear Algebra Appl., vol. 27, no. 1, pp. e2271, 31, 2020.
85.
M. Kawai, A. Ida, H. Matsuba, K. Nakajima and M. Bolten, "Multiplicative Schwartz-Type Block Multi-Color Gauss-Seidel Smoother for Algebraic Multigrid Methods" in Proceedings of the International Conference on High Performance Computing in Asia-Pacific Region, New York: ACM, 2020, pp. 217-226.
84.
P. Ferrari and S. Serra-Capizzano, "Multigrid for $\mathbb{Q}_{k}$ Finite Element Matrices using a (block) Toeplitz symbol approach", Mathematics, vol. 8, no. 1, pp. Paper No. 5, 2020.
83.
C. Lengauer, S. Apel, M. Bolten, S. Chiba, U. Rüde, J. Teich, A. Größlinger, F. Hannig, H. Köstler, L. Claus, A. Grebhahn, S. Groth, S. Kronawitter, S. Kuckuk, H. Rittich, C. Schmitt and J. Schmitt, "ExaStencils: Advanced Multigrid Solver Generation" in Software for Exascale Computing - SPPEXA 2016-2019, H. J. Bungartz and S. Reiz and B. Uekermann and P. Neumann and W. Nagel, Eds. Cham: Springer, 2020, pp. 405-452.
2019
82.
M. Bolten and C. Hahn, "Using composite finite elements for shape optimization with a stochastic objective functional" in Progress in Industrial Mathematics at ECMI 2018, I. Farago and F. Izsak and P. L. Simon, Eds. Cham: Springer, 2019, pp. 515-520.
81.
M. Bolten and L. Claus, "Local Fourier Analysis of multigrid methods for the Stokes problem", PAMM, vol. 19, pp. e201900394, 2019.
80.
H. Harbrecht and P. Zaspel, "On the Algebraic Construction of Sparse Multilevel Approximations of Elliptic Tensor Product Problems", J. Sci. Comput., vol. 78, no. 2, pp. 1272-1290, 2019.
79.
M. Bolten, H. Gottschalk, C. Hahn and M. Saadi, "Numerical shape optimization to decrease failure probability of ceramic structures", Comput. Vis. Sci., vol. 21, pp. 1-10, 2019.
78.
S. Friedhoff, J. Hahne and S. Schöps, "Multigrid-reduction-in-time for Eddy Current problems", PAMM, vol. 19, no. 1, pp. e201900262, 2019.
77.
P. Ferrari, I. Furci, S. Hon, M. A. Mursaleen and S. Serra-Capizzano, "The eigenvalue distribution of special 2-by-2 block matrix-sequences with applications to the case of symmetrized Toeplitz structures", SIAM J. Matrix Anal. Appl., vol. 40, no. 3, pp. 1066-1086, 2019.
76.
M. Griebel, C. Rieger and P. Zaspel, "Kernel-based stochastic collocation for the random two-phase Navier-Stokes equations", IJUQ, vol. 9, no. 5, 2019.
75.
P. Zaspel, "Ensemble Kalman filters for reliability estimation in perfusion inference", IJUQ, vol. 9, no. 1, 2019.
74.
P. Zaspel, B. Huang, H. Harbrecht and O. A. Lilienfeld, "Boosting Quantum Machine Learning Models with a Multilevel Combination Technique: Pople Diagrams Revisited", J. Chem. Theory Comput., vol. 15, no. 3, pp. 1546-1559, 2019.
73.
M. Bolten and J. Hahne, "An SDE-waveform relaxation method with application in distributed neural network simulations", PAMM, vol. 19, pp. e201900373, 2019.
72.
P. Zaspel, "Algorithmic Patterns for H-Matrices on Many-Core Processors", J. Sci. Comput., vol. 78, no. 2, pp. 1174-1206, 2019.
71.
S. Friedhoff, J. Hahne, I. Kulchytska-Ruchka and S. Schöps, "Exploring Parallel-in-Time Approaches for Eddy Current Problems" in Progress in Industrial Mathematics at ECMI 2018, Farago, Istvan and Izsak, Ferenc and Simon, Peter L., Eds. Springer International Publishing, 2019, pp. 373-379.
2018
70.
M. Bolten and H. Rittich, "Fourier analysis of periodic stencils in multigrid methods", SIAM J. Sci. Comput., vol. 40, no. 3, pp. A1642-A1668, 2018.
69.
A. Frommer, C. Schimmel and M. Schweitzer, "Non-Toeplitz decay bounds for inverses of Hermitian positive definite tridiagonal matrices", Electron. Trans. Numer. Anal., vol. 48, pp. 362-372, 2018.
68.
M. Bolten, K. Kahl, D. Kressner, F. Macedo and S. Sokolović, "Multigrid methods combined with low-rank approximation for tensor-structured Markov chains", Electron. Trans. Numer. Anal., vol. 48, pp. 348-361, 2018.
67.
B. Beckermann, D. Kressner and M. Schweitzer, "Low-rank updates of matrix functions", SIAM J. Matrix Anal. Appl., vol. 39, no. 1, pp. 539-565, 2018.
66.
M. Dumbser, F. Fambri, I. Furci, M. Mazza, S. Serra-Capizzano and M. Tavelli, "Staggered discontinuous Galerkin methods for the incompressible Navier-Stokes equations: spectral analysis and computational results", Numer. Linear Algebra Appl., vol. 25, no. 5, pp. e2151, 31, 2018.
65.
S. Ekström, I. Furci and S. Serra-Capizzano, "Exact formulae and matrix-less eigensolvers for block banded symmetric Toeplitz matrices", BIT, vol. 58, no. 4, pp. 937-968, 2018.
64.
A. Frommer, C. Schimmel and M. Schweitzer, "Bounds for the decay of the entries in inverses and Cauchy-Stieltjes functions of certain sparse, normal matrices", Numer. Linear Algebra Appl., vol. 25, no. 4, pp. e2131, 17, 2018.
63.
M. Bolten, D. Moser and R. Speck, "Asymptotic convergence of the parallel full approximation scheme in space and time for linear problems", Numer. Lin. Alg. Appl., vol. 25, no. 6, pp. e2208, 2018.
62.
S. Ekström, I. Furci, C. Garoni, C. Manni, S. Serra-Capizzano and H. Speleers, "Are the eigenvalues of the B-spline isogeometric analysis approximation of $-\Delta u=\lambda u$ known in almost closed form?", Numer. Linear Algebra Appl., vol. 25, no. 5, pp. e2198, 34, 2018.
61.
F. Ahmad, E. S. Al-Aidarous, D. A. Alrehaili, S. Ekström, I. Furci and S. Serra-Capizzano, "Are the eigenvalues of preconditioned banded symmetric Toeplitz matrices known in almost closed form?", Numer. Algorithms, vol. 78, no. 3, pp. 867-893, 2018.
60.
H. Harbrecht and P. Zaspel, "A scalable H-matrix approach for the solution of boundary integral equations on multi-GPU clusters", 2018.
2017
59.
A. Grebhahn, C. Engwer, M. Bolten and S. Apel, "Variability of stencil computations for porous media applications", CCPE, vol. 29, no. 17, pp. e4119, 2017.
58.
V. Heuveline, M. Schick, C. Webster and P. Zaspel, "Uncertainty Quantification and High Performance Computing (Dagstuhl Seminar 16372)", DROPS-IDN/v2/document/10.4230/DagRep.6.9.59, 2017.
57.
A. Frommer, K. Lund, M. Schweitzer and D. B. Szyld, "The Radau-Lanczos method for matrix functions", SIAM J. Matrix Anal. Appl., vol. 38, no. 3, pp. 710-732, 2017.
56.
S. E. Sayed, M. Bolten and D. Pleiter, "Parallel I/O architecture modelling based on file system counters" in High Performance Computing. ISC High Performance 2016, M. Taufer and B. Mohr and J. Kunkel, Eds. Springer, 2017, pp. 627-637.
55.
J. Hahne, D. Dahmen, J. Schuecker, A. Frommer, M. Bolten, M. Helias and M. Diesmann, "Integration of continuous-time dynamics in a spiking neural network simulator", Front. Neuroinform., vol. 11, pp. 00034, 2017.
54.
R. D. Falgout, S. Friedhoff, T. V. Kolev, S. P. MacLachlan, J. B. Schroder and S. Vandewalle, "Multigrid methods with space-time concurrency", Comput. Vis. Sci., vol. 18, no. 4-5, pp. 123-143, 2017.
53.
P. Zaspel, "Analysis and parallelizationstrategies for Ruge-Stüben AMG on many-core processors", 2017.
52.
M. Bolten, F. Franchetti, P. H. Kelly, C. Lengauer and M. Mohr, "Algebraic description and automatic generation of multigrid methods in SPIRAL", CCPE, vol. 29, no. 17, pp. e4105, 2017.
51.
M. Schweitzer, "A two-sided short-recurrence extended Krylov subspace method for nonsymmetric matrices and its relation to rational moment matching", Numer. Algorithms, vol. 76, no. 1, pp. 1-31, 2017.
50.
M. Bolten, D. Moser and R. Speck, "A multigrid perspective on the parallel full approximation scheme in space and time", Numer. Lin. Alg. Appl., vol. 24, no. 6, pp. e2110, 2017.
2016
49.
M. Bolten, K. Kahl and S. Sokolović, "Multigrid methods for Tensor structured Markov chains with low rank approximation", SIAM J. Sci. Comput., vol. 38, no. 2, pp. A649-A667, 2016.
48.
P. Zaspel, "Subspace correction methods in algebraic multi-level frames", Linear Algebra Appl., vol. 488, pp. 505-521, 2016.
47.
M. Bolten, T. Huckle and C. Kravvaritis, "Sparse matrix approximations and the convergence of multigrid methods", Linear Algebra Appl., vol. 502, pp. 58-76, 2016.
46.
M. Schweitzer, "Restarting and error estimation in polynomial and extended Krylov subspace methods for the approximation of matrix functions", Bergische Universität Wuppertal, Fakultät für Mathematik und Naturwissenschaften, 2016.
45.
S. E. Sayed, M. Bolten, D. Pleiter and W. Frings, "Parallel I/O characterisation based on server- side performance counters" in 2016 1st Joint International Workshop on Parallel Data Storage and data Intensive Scalable Computing Systems (PDSW-DISCS), 2016, pp. 7-12.
44.
S. E. Sayed, M. Bolten and D. Pleiter, "Using file system counters in modelling parallel I/O architectures", ACM SIGOPS OSR, vol. 50, no. 2, pp. 37-46, 2016.
43.
M. Schweitzer, "Monotone convergence of the extended Krylov subspace method for Laplace-Stieltjes functions of Hermitian positive definite matrices", Linear Algebra Appl., vol. 507, pp. 486-498, 2016.
42.
M. Schweitzer, "Any finite convergence curve is possible in the initial iterations of restarted FOM", Electron. Trans. Numer. Anal., vol. 45, pp. 133-145, 2016.
41.
A. Hessenthaler, S. Friedhoff, O. Röhrle and D. A. Nordsletten, "3D Fluid-Structure Interaction Experiment and Benchmark Results", PAMM, vol. 16, no. 1, pp. 451-452, 2016.
40.
M. Bolten and O. Letterer, "Increasing arithmetic intensity in multigrid methods on GPUs using block smoothers" in PPAM 2015, Part I, R. Wyrzykowski and E. Deelman and J. Dongarra and K. Karczewski and J. Kitowski and K. Wiatr, Eds. Springer, 2016, pp. 515-525.
39.
A. Frommer and M. Schweitzer, "Error bounds and estimates for Krylov subspace approximations of Stieltjes matrix functions", BIT, vol. 56, no. 3, pp. 865-892, 2016.
38.
J. Hahne, M. Helias, S. Kunkel, J. Igarashi, I. Kitayama, B. Wylie, M. Bolten, A. Frommer and M. Diesmann, "Including Gap Junctions into Distributed Neuronal Network Simulations" in Brain-Inspired Computing. BrainComp 2015, K. Amunts and L. Grandinetti and T. Lippert and N. Petkov, Eds. Springer, 2016, pp. 43-57.
2015
37.
M. Bolten, M. Donatelli, T. Huckle and C. Kravvaritis, "Generalized grid transfer operators for multigrid methods applied on Toeplitz matrices", BIT, vol. 55, pp. 341-366, 2015.
36.
M. Bolten, H. Gottschalk and S. Schmitz, "Minimal failure probability for ceramic design via shape control", J. Optim. Theory Appl., vol. 166, pp. 983-1001, 2015.
35.
M. L. Minion, R. Speck, M. Bolten, M. Emmett and D. Ruprecht, "Interweaving PFASST and parallel multigrid", SIAM J. Sci. Comput., vol. 37, no. 5, pp. S244-S263, 2015.
34.
M. Bolten, M. Donatelli and T. Huckle, "Analysis of smoothed aggregation multigrid methods based on Toeplitz matrices", Electron. Trans. Numer. Anal., vol. 44, pp. 25-52, 2015.
33.
J. Hahne, M. Helias, S. Kunkel, J. Igarashi, M. Bolten, A. Frommer and M. Diesmann, "A unified framework for spiking and gap-junction interactions in distributed neuronal network simulations", Front. Neuroinform., vol. 9, pp. 00022, 2015.
32.
R. Speck, D. Ruprecht, M. Emmett, M. Minion, M. Bolten and R. Krause, "A multi-level spectral deferred correction method", BIT, vol. 55, pp. 843-867, 2015.
31.
S. Friedhoff and S. MacLachlan, "A generalized predictive analysis tool for multigrid methods", Numer. Linear Algebra Appl., vol. 22, no. 4, pp. 618-647, 2015.
2014
30.
A. Frommer, S. Güttel and M. Schweitzer, "Convergence of restarted Krylov subspace methods for Stieltjes functions of matrices", SIAM J. Matrix Anal. Appl., vol. 35, no. 4, pp. 1602-1624, 2014.
29.
A. Frommer, S. Güttel and M. Schweitzer, "Efficient and stable Arnoldi restarts for matrix functions based on quadrature", SIAM J. Matrix Anal. Appl., vol. 35, no. 2, pp. 661-683, 2014.
28.
M. Bolten, "Evaluation of a multigrid solver for 3-level Toeplitz and circulant matrices on Blue Gene/Q" in Proceedings of the NIC Symposium 2014, K. Binder and G. MÜnster and M. Kremer, Eds. Jülich, 2014, pp. 345-352.
27.
D. Pflüger, H. Bungartz, M. Griebel, F. Jenko, T. Dannert, M. Heene, C. Kowitz, A. P. Hinojosa and P. Zaspel, "EXAHD: An Exa-scalable Two-Level Sparse Grid Approach for Higher-Dimensional Problems in Plasma Physics and Beyond" in Euro-Par 2014: Parallel Processing Workshops, Lopes, Luís and Žilinskas, Julius and Costan, Alexandru and Cascella, Roberto G. and Kecskemeti, Gabor and Jeannot, Emmanuel and Cannataro, Mario and Ricci, Laura and Benkner, Siegfried and Petit, Salvador and Scarano, Vittorio and Gracia, José and Hunold, Sascha and Scott, Stephen L. and Lankes, Stefan and Lengauer, Christian and Carretero, Jesús and Breitbart, Jens and Alexander, Michael, Eds. 2014, pp. 565-576.
26.
C. Lengauer, S. Apel, M. Bolten, A. Größlinger, F. Hannig, U. Rüde, J. Teich, A. Grebhahn, S. Kronawitter, S. Kuckuk, H. Rittich and C. Schmitt, "ExaStencils: Advanced stencil-code engineering" in Euro-Par 2014: Parallel Processing Workshops - Euro-Par 2014 International Workshops, Porto, Portugal, August 25-26, 2014, Revised Selected Papers, Part II, Springer, 2014, pp. 553-564.
25.
R. D. Falgout, S. Friedhoff, T. V. Kolev, S. MacLachlan and J. B. Schroder, "Parallel time integration with multigrid", PAMM, vol. 14, no. 1, pp. 951-952, 2014.
24.
R. Speck, D. Ruprecht, M. Emmett, M. Bolten and R. Krause, "A space-time parallel solver for the three-dimensional heat equation" in Parallel Computing: Accelerating Computational Science and Engineering (CSE), M. Bader and A. Bode and H.-J. Bungartz and M. Gerndt and G.R. Joubert and F. Peters, Eds. IOS Press, 2014, pp. 263-272.
2013
23.
M. Bolten, N. Bozovic and A. Frommer, "Preconditioning of Krylov subspace methods using recycling in Lattice QCD Computations", PAMM, vol. 13, pp. 413-414, 2013.
22.
P. Zaspel and M. Griebel, "Solving incompressible two-phase flows on multi-GPU clusters", Computers & Fluids, vol. 80, pp. 356-364, 2013.
21.
D. Ruprecht, R. Speck, M. Emmett, M. Bolten and R. Krause, "Extreme- scale space-time parallelism" in 2013 International Conference for High Performance Computing, Networking, Storage and Analysis (SC), Denver, CO, USA, 2013.
20.
A. Arnold, M. Bolten, H. Dachsel, F. Fahrenberger, F. Gähler, R. Halver, F. Heber, M. Hofmann, C. Holm, J. Iseringhausen, I. Kabadshow, O. Lenz, M. Pippig, D. Potts and G. Sutmann, "Comparison of Scalable Fast Methods for Long-Range Interactions", Phys. Rev. E, vol. 88, pp. 063308, 2013.
19.
S. Friedhoff, S. MacLachlan and C. Börgers, "Local Fourier analysis of space-time relaxation and multigrid schemes", SIAM J. Sci. Comput., vol. 35, no. 5, pp. S250-S276, 2013.
2012
18.
K. Samiei, B. Peters, M. Bolten and A. Frommer, "Assessment of the potentials of implicit integration methods in discrete element modelling of granular matter", Comput. Chem. Eng., vol. 49, pp. 183-193, 2012.
17.
A. Thiess, R. Zeller, M. Bolten, P. H. Dederichs and S. Blügel, "Massively parallel density functional calculations for thousands of atoms: KKRnano", Phys. Rev. B, vol. 85, pp. 235103, 2012.
16.
M. Bolten and K. Kahl, "Using block smoothers in multigrid methods", PAMM, vol. 12, pp. 645-646, 2012.
2011
15.
M. Bolten, "Multigrid methods for long-range interactions" in Fast methods for long-range interactions in complex systems, G. Sutmann and P. Gibbon and Th. Lippert, Eds. Jülich: Forschungszentrum Jülich, 2011, pp. 115-130.
14.
M. Bolten, A. Thiess, I. Yavneh and R. Zeller, "Preconditioning systems arising from the KKR Green function method using block-circulant matrices", Linear Algebra Appl., vol. 436, no. 2, pp. 436-446, Jan. 2011.
13.
P. Zaspel and M. Griebel, "Photorealistic visualization and fluid animation: coupling of Maya with a two-phase Navier-Stokes fluid solver", Comput. Visual Sci., vol. 14, no. 8, pp. 371-383, 2011.
12.
P. Zaspel and M. Griebel, "Massively Parallel Fluid Simulations on Amazon's HPC Cloud" in 2011 First International Symposium on Network Cloud Computing and Applications, 2011, pp. 73-78.
11.
M. Bolten, D. Brinkers, U. Rüde and M. Stürmer, "Implementation of multigrid on QPACE" in 2011 IEEE International Conference on Cluster Computing (CLUSTER), Los Alamitos, CA, USA: IEEE Computer Society, 2011, pp. 371-377.
10.
M. Bolten, S. Friedhoff, A. Frommer, M. Heming and K. Kahl, "Algebraic multigrid methods for Laplacians of graphs", Linear Algebra Appl., vol. 434, no. 11, pp. 2225-2243, 2011.
9.
M. Bolten, A. Brandt, J. Brannick, A. Frommer, K. Kahl and I. Livshits, "A bootstrap algebraic multilevel method for Markov chains", SIAM J. Sci. Comput., vol. 33, no. 6, pp. 3425-3446, 2011.
2010
8.
M. Griebel and P. Zaspel, "A multi-GPU accelerated solver for the three-dimensional two-phase incompressible Navier-Stokes equations", Comput Sci Res Dev, vol. 25, no. 1, pp. 65-73, 2010.
7.
K. Samiei, B. Peters, M. Bolten and A. Frommer, "An implicit approach to predict the dynamics of granular media", PAMM, vol. 10, no. 1, pp. 55-56, Dez. 2010.
6.
M. Bolten, "Highly scalable multigrid algorithm for particle simulation", PAMM, vol. 10, no. 1, pp. 643-644, Dez. 2010.
5.
G. Sutmann, L. Westphal and M. Bolten, "Particle Based Simulations of Complex Systems with {MP2C}: Hydrodynamics and Electrostatics", AIP Cong. Proc., vol. 1281, pp. 1768-1772, 2010.
2008
4.
M. Bolten, "Hierarchical grid coarsening for the solution of the Poisson equation in free space", Electron. Trans. Numer. Anal., vol. 29, pp. 70-80, 2008.
3.
M. Bolten and G. Sutmann, "NFFT-based extension of a particle simulation method using multigrid", PAMM, vol. 7, no. 1, pp. 2140005-2140006, Dez. 2008.
2006
2.
M. Bolten and G. Sutmann, "A highly accurate and optimal method to calculate long range interactions" in Proceedings of the workshop ``From computational biophysics to systems biology'', J. Meinke and O. Zimmermann and S. Mohanty and U.H.E. Hansmann, Eds. Jülich: John von Neumann Institute for Computing, 2006, pp. 189-192.
2005
1.
M. Bolten, N. Papenberg, B. Fischer, P. Adamidis, R. Rabenseifner and H. Berger, "Parallelisierung eines Nichtlinearen Registrierungsalgorithmus zur Verarbeitung sehr großer Volumen-Daten" in Bildverarbeitung für die Medizin 2005, H. Meinzer and H. Handels and A. Horsch and T. Tolxdorff, Eds. Springer, 2005, pp. 360-364.

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