Jonas Thies

819 total citations
21 papers, 442 citations indexed

About

Jonas Thies is a scholar working on Computational Theory and Mathematics, Hardware and Architecture and Computational Mechanics. According to data from OpenAlex, Jonas Thies has authored 21 papers receiving a total of 442 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Computational Theory and Mathematics, 7 papers in Hardware and Architecture and 6 papers in Computational Mechanics. Recurrent topics in Jonas Thies's work include Matrix Theory and Algorithms (9 papers), Parallel Computing and Optimization Techniques (7 papers) and Advanced Numerical Methods in Computational Mathematics (4 papers). Jonas Thies is often cited by papers focused on Matrix Theory and Algorithms (9 papers), Parallel Computing and Optimization Techniques (7 papers) and Advanced Numerical Methods in Computational Mathematics (4 papers). Jonas Thies collaborates with scholars based in Germany, Netherlands and Sweden. Jonas Thies's co-authors include Lionel Favier, Juha Ruokolainen, Mika Malinen, Fabien Gillet‐Chaulet, Peter Råback, Martina Schäfer, Ralf Greve, Carlos Martín, M. Sacchettini and G. Durand and has published in prestigious journals such as Journal of Computational Physics, SIAM Journal on Scientific Computing and Atmospheric Research.

In The Last Decade

Jonas Thies

16 papers receiving 436 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Jonas Thies Germany	7	284	127	104	55	39	21	442
Irina Tezaur United States	12	142 0.5×	33 0.3×	38 0.4×	135 2.5×	26 0.7×	38	393
Jie‐Bang Yan United States	15	187 0.7×	33 0.3×	50 0.5×	5 0.1×	6 0.2×	43	803
H. J. Seybold Switzerland	10	36 0.1×	11 0.1×	16 0.2×	86 1.6×	18 0.5×	14	426
Noémi Petra United States	8	131 0.5×	12 0.1×	18 0.2×	26 0.5×	50 1.3×	21	384
G. S. O’Brien Ireland	20	49 0.2×	4 0.0×	70 0.7×	70 1.3×	21 0.5×	52	932
Ding Liang United States	11	304 1.1×	9 0.1×	15 0.1×	12 0.2×	3 0.1×	37	645
Anders Kusk Denmark	12	333 1.2×	122 1.0×	82 0.8×	17 0.3×	1 0.0×	39	686
Kara Peterson United States	10	70 0.2×	3 0.0×	7 0.1×	147 2.7×	36 0.9×	34	276
A. McD. Mercer Canada	14	70 0.2×	6 0.0×	6 0.1×	176 3.2×	55 1.4×	55	632
Bernd Dachwald Germany	22	84 0.3×	24 0.2×	2 0.0×	17 0.3×	9 0.2×	71	1.2k

Countries citing papers authored by Jonas Thies

Since Specialization

Citations

This map shows the geographic impact of Jonas Thies's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Jonas Thies with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jonas Thies more than expected).

Fields of papers citing papers by Jonas Thies

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jonas Thies. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Jonas Thies. The network helps show where Jonas Thies may publish in the future.

Co-authorship network of co-authors of Jonas Thies

This figure shows the co-authorship network connecting the top 25 collaborators of Jonas Thies. A scholar is included among the top collaborators of Jonas Thies based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Jonas Thies. Jonas Thies is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Bendix, Jörg, et al.. (2025). Evaluating station, satellite, & combined data for XGBoost-based visibility forecast. Atmospheric Research. 328. 108395–108395.

Thies, Jonas, et al.. (2025). Performance of linear solvers in tensor-train format on current multicore architectures. The International Journal of High Performance Computing Applications. 39(3). 443–461.

Thies, Jonas, et al.. (2024). Algebraic temporal blocking for sparse iterative solvers on multi-core CPUs. The International Journal of High Performance Computing Applications. 39(2). 230–250.

Thies, Jonas, et al.. (2023). SIMD vectorization for simultaneous solution of locally varying linear systems with multiple right-hand sides. The Journal of Supercomputing. 79(13). 14684–14706. 3 indexed citations

Thies, Jonas, et al.. (2022). Performance of the Low-Rank TT-SVD for Large Dense Tensors on Modern MultiCore CPUs. SIAM Journal on Scientific Computing. 44(4). C287–C309. 3 indexed citations

Hager, Georg, et al.. (2020). Performance engineering for real and complex tall & skinny matrix multiplication kernels on GPUs. The International Journal of High Performance Computing Applications. 35(1). 5–19. 10 indexed citations

Thies, Jonas, et al.. (2020). PHIST. ACM Transactions on Mathematical Software. 46(4). 1–26. 3 indexed citations

Basermann, Achim, A. R. Bishop, Holger Fehske, et al.. (2020). A Recursive Algebraic Coloring Technique for Hardware-efficient Symmetric Sparse Matrix-vector Multiplication. elib (German Aerospace Center). 7(3). 1–37. 81 indexed citations

Wellein, Gerhard, Moritz Kreutzer, Jonas Thies, et al.. (2020). Equipping Sparse Solvers for Exascale. elib (German Aerospace Center).

10.

Hager, Georg, et al.. (2019). Performance Engineering for a Tall & Skinny Matrix Multiplication Kernel on GPUs. arXiv (Cornell University).

11.

Wubs, Fred W., et al.. (2018). Numerical bifurcation analysis of a 3D turing-type reaction–diffusion model. Communications in Nonlinear Science and Numerical Simulation. 60. 145–164. 3 indexed citations

12.

Thies, Jonas, Moritz Kreutzer, Andreas Alvermann, et al.. (2015). Increasing the Performance of the Jacobi--Davidson Method by Blocking. SIAM Journal on Scientific Computing. 37(6). C697–C722. 12 indexed citations

13.

Krämer, Lukas, et al.. (2015). On the parallel iterative solution of linear systems arising in the FEAST algorithm for computing inner eigenvalues. Parallel Computing. 49. 153–163. 9 indexed citations

14.

Gagliardini, Olivier, Thomas Zwinger, Fabien Gillet‐Chaulet, et al.. (2013). Capabilities and performance of Elmer/Ice, a new-generation ice sheet model. Geoscientific model development. 6(4). 1299–1318. 280 indexed citations

15.

Gagliardini, Olivier, Thomas Zwinger, G. Durand, et al.. (2012). Capabilities and performance of the new generation ice-sheet model Elmer/Ice. AGUFM. 2012. 1 indexed citations

16.

Wubs, Fred W. & Jonas Thies. (2011). A Robust Two-Level Incomplete Factorization for (Navier–)Stokes Saddle Point Matrices. SIAM Journal on Matrix Analysis and Applications. 32(4). 1475–1499. 4 indexed citations

17.

Thies, Jonas & Fred W. Wubs. (2011). Design of a Parallel Hybrid Direct/Iterative Solver for CFD Problems. 23. 387–394. 3 indexed citations

18.

Thies, Jonas, et al.. (2011). Determining (seasonal) periodic orbits in global ocean models using continuation methods. University of Groningen research database (University of Groningen / Centre for Information Technology). 2 indexed citations

19.

Dijkstra, Henk A., et al.. (2010). The application of Jacobian-free Newton–Krylov methods to reduce the spin-up time of ocean general circulation models. Journal of Computational Physics. 229(21). 8167–8179. 15 indexed citations

20.

Thies, Jonas, Fred W. Wubs, & Henk A. Dijkstra. (2009). Bifurcation analysis of 3D ocean flows using a parallel fully-implicit ocean model. Ocean Modelling. 30(4). 287–297. 12 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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