Karl Rupp

3.9k total citations
49 papers, 653 citations indexed

About

Karl Rupp is a scholar working on Hardware and Architecture, Computer Networks and Communications and Electrical and Electronic Engineering. According to data from OpenAlex, Karl Rupp has authored 49 papers receiving a total of 653 indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Hardware and Architecture, 17 papers in Computer Networks and Communications and 16 papers in Electrical and Electronic Engineering. Recurrent topics in Karl Rupp's work include Parallel Computing and Optimization Techniques (22 papers), Advancements in Semiconductor Devices and Circuit Design (15 papers) and Matrix Theory and Algorithms (14 papers). Karl Rupp is often cited by papers focused on Parallel Computing and Optimization Techniques (22 papers), Advancements in Semiconductor Devices and Circuit Design (15 papers) and Matrix Theory and Algorithms (14 papers). Karl Rupp collaborates with scholars based in Austria, United States and Russia. Karl Rupp's co-authors include Tibor Grasser, S. Selberherr, Ansgar Jüngel, M. Bina, Josef Weinbub, Stanislav Tyaginov, Yannick Wimmer, Philippe Tillet, Barry Smith and B. Kaczer and has published in prestigious journals such as Proceedings of the IEEE, Journal of Computational Physics and IEEE Transactions on Electron Devices.

In The Last Decade

Karl Rupp

47 papers receiving 624 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Karl Rupp Austria 14 314 131 103 99 93 49 653
Rahul S. Sampath United States 10 112 0.4× 87 0.7× 76 0.7× 51 0.5× 161 1.7× 17 494
Maxim Naumov United States 11 181 0.6× 154 1.2× 154 1.5× 149 1.5× 107 1.2× 26 678
Takeshi Iwashita Japan 15 305 1.0× 71 0.5× 59 0.6× 171 1.7× 128 1.4× 89 583
Ilya Lashuk United States 9 103 0.3× 61 0.5× 51 0.5× 71 0.7× 121 1.3× 11 359
Chaofeng Hou China 11 106 0.3× 157 1.2× 174 1.7× 28 0.3× 73 0.8× 33 566
Aparna Chandramowlishwaran United States 13 147 0.5× 255 1.9× 240 2.3× 36 0.4× 85 0.9× 38 617
Paul Messina United States 15 127 0.4× 277 2.1× 389 3.8× 50 0.5× 64 0.7× 39 708
Josef Weinbub Austria 12 230 0.7× 46 0.4× 51 0.5× 43 0.4× 59 0.6× 78 598
Eiichi Takahashi Japan 15 507 1.6× 118 0.9× 158 1.5× 28 0.3× 59 0.6× 126 963
Robert Hesse United States 12 212 0.7× 53 0.4× 80 0.8× 87 0.9× 107 1.2× 30 461

Countries citing papers authored by Karl Rupp

Since Specialization
Citations

This map shows the geographic impact of Karl Rupp'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 Karl Rupp with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Karl Rupp more than expected).

Fields of papers citing papers by Karl Rupp

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Karl Rupp. 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 Karl Rupp. The network helps show where Karl Rupp may publish in the future.

Co-authorship network of co-authors of Karl Rupp

This figure shows the co-authorship network connecting the top 25 collaborators of Karl Rupp. A scholar is included among the top collaborators of Karl Rupp 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 Karl Rupp. Karl Rupp is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Anzt, Hartwig, Erik G. Boman, Robert D. Falgout, et al.. (2020). Preparing sparse solvers for exascale computing. Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences. 378(2166). 20190053–20190053. 16 indexed citations
2.
Hong, Zhang, et al.. (2018). Vectorized Parallel Sparse Matrix-Vector Multiplication in PETSc Using AVX-512. 1–10. 2 indexed citations
3.
Mills, Richard T., et al.. (2018). Vectorized Parallel Sparse Matrix-Vector Multiplication in PETSc Using AVX-512. 1–10. 13 indexed citations
4.
Rupp, Karl, Christoph Jungemann, Sung‐Min Hong, et al.. (2016). A review of recent advances in the spherical harmonics expansion method for semiconductor device simulation. Journal of Computational Electronics. 15(3). 939–958. 20 indexed citations
5.
Tyaginov, Stanislav, Yannick Wimmer, Karl Rupp, et al.. (2015). Comparison of analytic distribution function models for hot-carrier degradation modeling in nLDMOSFETs. Microelectronics Reliability. 55(9-10). 1427–1432. 1 indexed citations
6.
Rupp, Karl, et al.. (2015). Transformation invariant local element size specification. Applied Mathematics and Computation. 267. 195–206. 2 indexed citations
7.
Weinbub, Josef, et al.. (2014). The meshing framework ViennaMesh for finite element applications. Journal of Computational and Applied Mathematics. 270. 166–177. 7 indexed citations
8.
Tillet, Philippe, Karl Rupp, S. Selberherr, & Chin‐Teng Lin. (2013). Towards performance-portable, scalable, and convenient linear algebra. 13 indexed citations
9.
Weinbub, Josef, Karl Rupp, & S. Selberherr. (2013). Highly flexible and reusable finite element simulations with ViennaX. Journal of Computational and Applied Mathematics. 270. 484–495. 1 indexed citations
10.
Ahnert, Karsten, et al.. (2013). Programming CUDA and OpenCL: A Case Study Using Modern C++ Libraries. SIAM Journal on Scientific Computing. 35(5). C453–C472. 28 indexed citations
11.
Rupp, Karl, et al.. (2012). Sparse approximate inverse preconditioners for iterative solvers on GPUs. IEEE International Conference on High Performance Computing, Data, and Analytics. 13. 10 indexed citations
12.
Wagner, Markus, Karl Rupp, & Josef Weinbub. (2012). A comparison of algebraic multigrid preconditioners using graphics processing units and multi-core central processing units. IEEE International Conference on High Performance Computing, Data, and Analytics. 2. 9 indexed citations
13.
Tillet, Philippe, Karl Rupp, & S. Selberherr. (2012). An automatic OpenCL compute kernel generator for basic linear algebra operations. IEEE International Conference on High Performance Computing, Data, and Analytics. 4. 9 indexed citations
14.
Rupp, Karl, et al.. (2012). Bipolar Spherical Harmonics Expansions of the Boltzmann Transport Equation. RWTH Publications (RWTH Aachen). 6 indexed citations
15.
Weinbub, Josef, Karl Rupp, Lado Filipovic, Alexander Makarov, & S. Selberherr. (2012). Towards a free open source process and device simulation framework. 1–4. 1 indexed citations
16.
Rupp, Karl, Tibor Grasser, & Ansgar Jüngel. (2011). Parallel preconditioning for spherical harmonics expansions of the Boltzmann transport equation. 147–150. 6 indexed citations
17.
Rupp, Karl, Tibor Grasser, & Ansgar Jüngel. (2011). On the feasibility of spherical harmonics expansions of the Boltzmann transport equation for three-dimensional device geometries. 34.1.1–34.1.4. 29 indexed citations
18.
Rupp, Karl & S. Selberherr. (2010). The Economic Limit to Moore's Law [Point of View. Proceedings of the IEEE. 98(3). 351–353. 9 indexed citations
19.
Rupp, Karl. (2010). Symbolic integration at compile time in finite element methods. 347–354. 1 indexed citations
20.
Bartsch, Annett, Wolfgang Wagner, Karl Rupp, & Richard Kidd. (2007). Application of C and Ku-Band scatterometer data for catchment hydrology in northern latitudes. 3702–3705. 3 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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2026