Tomasz Piontek

567 total citations
18 papers, 243 citations indexed

About

Tomasz Piontek is a scholar working on Computer Networks and Communications, Hardware and Architecture and Information Systems. According to data from OpenAlex, Tomasz Piontek has authored 18 papers receiving a total of 243 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Computer Networks and Communications, 8 papers in Hardware and Architecture and 7 papers in Information Systems. Recurrent topics in Tomasz Piontek's work include Distributed and Parallel Computing Systems (13 papers), Parallel Computing and Optimization Techniques (8 papers) and Cloud Computing and Resource Management (7 papers). Tomasz Piontek is often cited by papers focused on Distributed and Parallel Computing Systems (13 papers), Parallel Computing and Optimization Techniques (8 papers) and Cloud Computing and Resource Management (7 papers). Tomasz Piontek collaborates with scholars based in Poland, Germany and United Kingdom. Tomasz Piontek's co-authors include Jan Węglarz, Ariel Oleksiak, Krzysztof Kurowski, Bartosz Bosak, Wojciech Piątek, Derek Groen, Peter V. Coveney, Alfons G. Hoekstra, O. Hoenen and Joris Borgdorff and has published in prestigious journals such as Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences, Future Generation Computer Systems and Simulation Modelling Practice and Theory.

In The Last Decade

Tomasz Piontek

17 papers receiving 230 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Tomasz Piontek Poland 10 148 108 77 46 38 18 243
Arthur S Buddy Bland United States 6 178 1.2× 46 0.4× 110 1.4× 111 2.4× 16 0.4× 9 272
Douglas W. Doerfler United States 11 217 1.5× 57 0.5× 195 2.5× 46 1.0× 15 0.4× 37 292
Sunita Chandrasekaran United States 9 143 1.0× 55 0.5× 138 1.8× 34 0.7× 12 0.3× 49 249
Michael Showerman United States 6 300 2.0× 142 1.3× 206 2.7× 54 1.2× 41 1.1× 12 403
Jeremy Enos United States 8 309 2.1× 152 1.4× 207 2.7× 55 1.2× 41 1.1× 16 417
G Kumfert United States 8 117 0.8× 44 0.4× 71 0.9× 23 0.5× 58 1.5× 12 212
Iréa Touche France 4 185 1.3× 101 0.9× 62 0.8× 11 0.2× 21 0.6× 4 237
Ruymán Reyes Spain 9 110 0.7× 45 0.4× 124 1.6× 22 0.5× 12 0.3× 20 192
Christian Terboven Germany 9 179 1.2× 90 0.8× 155 2.0× 27 0.6× 6 0.2× 41 300
R. D. Williams United States 2 83 0.6× 21 0.2× 58 0.8× 15 0.3× 16 0.4× 5 165

Countries citing papers authored by Tomasz Piontek

Since Specialization
Citations

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

Fields of papers citing papers by Tomasz Piontek

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Tomasz Piontek

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

All Works

18 of 18 papers shown
1.
Wright, David W., Robin A. Richardson, Wouter Edeling, et al.. (2020). Building Confidence in Simulation: Applications of EasyVVUQ. Advanced Theory and Simulations. 3(8). 21 indexed citations
2.
Piontek, Tomasz, et al.. (2019). Predicting queue wait time probabilities for multi-scale computing. Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences. 377(2142). 20180151–20180151. 7 indexed citations
3.
Hoenen, O., Tomasz Piontek, Bartosz Bosak, et al.. (2019). Application of the extreme scaling computing pattern on multiscale fusion plasma modelling. Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences. 377(2142). 20180152–20180152. 5 indexed citations
4.
Alowayyed, Saad, Tomasz Piontek, James L. Suter, et al.. (2018). Patterns for High Performance Multiscale Computing. Future Generation Computer Systems. 91. 335–346. 17 indexed citations
5.
Swain, Martin, et al.. (2016). MultiGrain/MAPPER: A distributed multiscale computing approach to modeling and simulating gene regulation networks. Future Generation Computer Systems. 63. 1–14. 3 indexed citations
6.
Piontek, Tomasz, et al.. (2016). Development of Science Gateways Using QCG — Lessons Learned from the Deployment on Large Scale Distributed and HPC Infrastructures. Journal of Grid Computing. 14(4). 559–573. 11 indexed citations
7.
Bosak, Bartosz, et al.. (2014). Preprocessing and Storing High-Throughput Sequencing Data. Computational Methods in Science and Technology. 9–20. 2 indexed citations
8.
Grabowski, Piotr, et al.. (2013). NEW SCIENCE GATEWAYS FOR ADVANCED COMPUTING SIMULATIONS AND VISUALIZATION USING VINE TOOLKIT IN PL-GRID. Computing and Informatics / Computers and Artificial Intelligence. 32(5). 1100–1115.
9.
Oleksiak, Ariel, et al.. (2013). Runtime power usage estimation of HPC servers for various classes of real-life applications. Future Generation Computer Systems. 36. 299–310. 27 indexed citations
10.
Kurowski, Krzysztof, et al.. (2013). DCworms – A tool for simulation of energy efficiency in distributed computing infrastructures. Simulation Modelling Practice and Theory. 39. 135–151. 33 indexed citations
11.
Borgdorff, Joris, Carles Bona-Casas, Krzysztof Kurowski, et al.. (2012). A Distributed Multiscale Computation of a Tightly Coupled Model Using the Multiscale Modeling Language. Procedia Computer Science. 9. 596–605. 20 indexed citations
12.
Oleksiak, Ariel, et al.. (2012). Practical power consumption estimation for real life HPC applications. Future Generation Computer Systems. 29(1). 208–217. 47 indexed citations
13.
Wesner, Stefan, et al.. (2012). CoolEmAll - Models and tools for optimization of data center energy-efficiency. 1–5. 6 indexed citations
14.
Zasada, Stefan J., Derek Groen, Joris Borgdorff, et al.. (2012). Distributed Infrastructure for Multiscale Computing. UvA-DARE (University of Amsterdam). 3. 65–74. 11 indexed citations
15.
Kurowski, Krzysztof, et al.. (2011). Parallel application benchmarks and performance evaluation of the Intel Xeon 7500 family processors. Procedia Computer Science. 4. 372–381. 11 indexed citations
16.
Kurowski, Krzysztof, et al.. (2010). VINE TOOLKIT—TOWARDS PORTAL BASED PRODUCTION SOLUTIONS FOR SCIENTIFIC AND ENGINEERING COMMUNITIES WITH GRID-ENABLED RESOURCES SUPPORT. Scalable Computing Practice and Experience. 11(2). 161–172. 6 indexed citations
17.
Kurowski, Krzysztof, et al.. (2010). Parallel Large Scale Simulations in the PL-Grid Environment. Computational Methods in Science and Technology. Special Issue(1). 47–56. 4 indexed citations
18.
Pukacki, Juliusz, Marcin Adamski, Piotr Grabowski, et al.. (2006). Programming Grid Applications with Gridge. Computational Methods in Science and Technology. 12(1). 47–68. 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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