Preconditioned krylov solvers on gpus H Anzt, M Gates, J Dongarra, M Kreutzer, G Wellein, M Köhler Parallel Computing 68, 32-44, 2017 | 51 | 2017 |
Efficiency of General Krylov Methods on GPUs--An Experimental Study H Anzt, J Dongarra, M Kreutzer, G Wellein, M Köhler 2016 IEEE International Parallel and Distributed Processing Symposium …, 2016 | 19 | 2016 |
On GPU Acceleration of Common Solvers for (Quasi-) Triangular Generalized Lyapunov Equations M Köhler, J Saak Max Plank Institute, Tech. Rep, 2014 | 7 | 2014 |
On BLAS Level-3 Implementations of Common Solvers for (Quasi-) Triangular Generalized Lyapunov Equations M Köhler, J Saak SLICOT Working Note 2014 (1), 2014 | 7 | 2014 |
Sparse-Dense Sylvester Equations in ℋ₂-Model Order Reduction P Benner, M Köhler, J Saak Max Planck Institute Magdeburg, 2011 | 7 | 2011 |
Fast Approximate Solution of the Non-Symmetric Generalized Eigenvalue Problem on Multicore Architectures P Benner, M Köhler, J Saak Parallel Computing: Accelerating Computational Science and Engineering (CSE …, 2014 | 6 | 2014 |
FlexiBLAS - A flexible BLAS library with runtime exchangeable backends M Köhler, J Saak LAPACK Working Note 284, 2013 | 4 | 2013 |
Efficiency improving implementation techniques for large scale matrix equation solvers M Köhler, J Saak | 4 | 2009 |
A Cache‐Aware Implementation of the Spectral Divide‐and‐Conquer Approach for the Non‐Symmetric Generalized Eigenvalue Problem P Benner, M Köhler, J Saak PAMM 14 (1), 819-820, 2014 | 3 | 2014 |
Numerical Solution of Large Scale Sparse Matrix Equations in Python B Baran, M Köhler, N Prasad, J Saak Proceedings in Applied Mathematics and Mechanics, 2014 | 2 | 2014 |
Interfacing C-M.E.S.S. with Python B Baran, M Köhler, N Prasad, J Saak Max Planck Institute Magdeburg, 2013 | 2 | 2013 |
A Shared Memory Parallel Implementation of the IRKA Algorithm for H_2 Model Order Reduction M Köhler, J Saak Applied Parallel and Scientific Computing, 541-544, 2013 | 1 | 2013 |
Iterative Löser für die algebraische Riccatigleichung M Köhler | | 2010 |