Prof. Dr. Gudula Rünger
Address
Technische Universität Chemnitz
Department of Computer Science
Str. der Nationen 62
09111 Chemnitz
Technische Universität Chemnitz
Department of Computer Science
Str. der Nationen 62
09111 Chemnitz
Contact
Research Interests
- Parallel programming and parallel Programming models for Scientific Computing
- Transformation approaches in software development
- Software tools for parallel and distributed programming
- Tools and libraries for mixed programming models
- Programming languages and programming language concepts
- Algorithmic and parallel adaptivity
- Energy efficiency
- Parallel applications
Textbooks
- Parallel Programming for Multicore and Cluster Systems (2nd Edition), 2013
- Parallele Programmierung, 2012
- Parallel Programming for Multicore and Cluster Systems, 2010
- Multicore: Parallele Programmierung, 2008
- Parallele und verteilte Programmierung, 2000
Research Focus: Parallel, distributed Systems
Prof. Rünger is the speaker of the research focus Parallel, distributed Systems of the Department of Computer Science at Technische Universität Chemnitz. This research focus combines several areas of computer science to investigate new ways of programming and software development for emerging parallel and distributed systems.Professional Activities
- Program Committee, Workshop on Education for High-Performance Computing (EduHPC-17), November 13, 2017
- Steering Committee, 18th IEEE International Workshop on Parallel and Distributed Scientific and Engineering Computing (PDSEC 2017), June 2, 2017
- Program Committee: Posters and Research Demos, 17th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGrid 2017), May 14–17, 2017
- Program Committee: Applications of Parallel and Distributed Computing (Track Chair), 16th International Conference on Algorithms and Architectures for Parallel Processing (ICA3PP 2016), December 14–16, 2016
- Program Committee, 15th International Conference on Ubiquitous Computing and Communications (IUCC-2016), December 14–16, 2016
- Program Committee, Workshop on Education for High-Performance Computing (EduHPC-16), November 14, 2016
- Program Committee, 8th International Conference on Internet Computing for Science and Engineering (ICICSE|16), August 13–14, 2016
- Steering Committee, 17th IEEE International Workshop on Parallel and Distributed Scientific and Engineering Computing (PDSEC 2016), May 27, 2016
- Program Committee, 24th High Performance Computing Symposium (HPC 2016), April 3–6, 2016
Aktuelle Veröffentlichungen
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Jakobs, T.; Klöckner, O.; Rünger, G.: Parallelization with load balancing of the weather scheme WSM7 for heterogeneous CPU-GPU platforms. In: The Journal of Supercomputing. Springer, 2024. DOI: 10.1007/s11227-024-06009-9 Online resource available
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Rauber, T.; Rünger, G.: Pareto-Optimal Execution of Parallel Applications with Respect to Time and Energy. In: Proceedings of the 13th International Conference on Smart Cities and Green ICT Systems (SMARTGREENS 2024).: pp. 65-72. SciTePress – ISBN 978-989-758-702-3. Angers, France, 2024. DOI: 10.5220/0012627100003714 Online resource available
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Jakobs, T.; Kratzsch, S.; Rünger, G.: Analyzing Data Reordering of a combined MPI and AVX execution of a Jacobi Method. In: 2023 31st Euromicro International Conference on Parallel, Distributed and Network-Based Processing (PDP): pp. 159-163. Neaples, Italy, 2023. DOI: 10.1109/PDP59025.2023.00032 Online resource available
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Rauber, T.; Rünger, G.: Performance and Energy Evaluation for Solving a Schrödinger-Poisson System on Multicore Processors. In: Computer Performance Engineering and Stochastic Modelling: pp. 18-33. Springer Nature Switzerland – ISBN 978-3-031-43185-2. Florence, Italy, 2023. DOI: 10.1007/978-3-031-43185-2_2 Online resource available
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Rauber, T.; Rünger, G.: Parallel Programming for Multicore and Cluster Systems, Third Edition. Springer Verlag – ISBN 978-3-031-28923-1 (Print), 978-3-031-28924-8 (Online), 2023. DOI: 10.1007/978-3-031-28924-8 Online resource available
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Hofmann, M.; Kiesel, R.; Kramer, R.; Rünger, G.; Schaller, T.: Performance Comparison of Parallel Sorting Algorithms for Data-intensive Particle Simulations using OpenCL. To appear in: International Conference on High Performance Computing & Simulation (HPCS 2020): pp. . IEEE – ISSN . Barcelona, Spain, 2021.
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Kramer, R.; Rünger, G.: A Workflow-based Support for the Automatic Creation and Selection of Energy-efficient Task-Schedules on DVFS Processors. In: Proceedings of Sixth International Congress on Information and Communication Technology (vol. 236): pp. 44-61. Springer Singapore – ISBN 978-981-16-2380-6, 2021. DOI: 10.1007/978-981-16-2380-6_23 Online resource available
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Rauber, T.; Rünger, G.: Modeling the effect of application-specific program transformations on energy and performance improvements of parallel ODE solvers. In: Journal of Computational Science, vol. 51. Elsevier – ISSN 1877-7503, 2021. DOI: 10.1016/j.jocs.2021.101356 Online resource available
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Dietze, R.; Rünger, G.: The Search-based Scheduling Algorithm HP* for Parallel Tasks on Heterogeneous Platforms. In: Concurrency and Computation: Practice and Experience. Wiley, 2020. DOI: 10.1002/cpe.5898 Online resource available
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Jakobs, T.; Reinhardt, L.; Rünger, G.: Performance and energy consumption of a Gram–Schmidt process for vector orthogonalization on a processor integrated GPU. In: Sustainable Computing: Informatics and Systems. Elsevier – ISSN 2210-5379, September 2020. DOI: 10.1016/j.suscom.2020.100456 Online resource available
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Kalinnik, N.; Kiesel, R.; Rauber, T.; Richter, M.; Rünger, G.: A performance- and energy-oriented extended tuning process for time-step-based scientific applications. In: The Journal of Supercomputing, vol. 76. Springer, August 2020. DOI: 10.1007/s11227-020-03402-y Online resource available
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Kramer, R.; Rünger, G.: A Web-Based Support for the Management and Evaluation of Measurement Data from Stress-Strain and Continuous-Cooling-Transformation Experiments. In: Information Systems Architecture and Technology: Proceedings of 40th Anniversary International Conference on Information Systems Architecture and Technology -- ISAT 2019: pp. 150--159. Springer International Publishing – ISBN 978-3-030-30440-9. Cham, 2020. DOI: 10.1007/978-3-030-30440-9_15 Online resource available
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Kramer, R.; Rünger, G.: Performance and efficiency investigations of SIMD programs of Coulomb solvers on multi- and many-core systems with vector units. In: 2020 28th Euromicro International Conference on Parallel, Distributed and Network-Based Processing -- PDP 2020. IEEE Computer Society Conference Publishing Services (CPS) – ISBN 978-1-7281-6582-0, 2020. DOI: 10.1109/PDP50117.2020.00044 Online resource available
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Rauber, T.; Rünger, G.: A Parameter Selection Process by Data Analysis for Tuning Multi-threaded Time-Stepping Algorithms. In: 2020 Seventh International Conference on Software Defined Systems (SDS): pp. 43--50. IEEE. Paris, Frankreich, 2020. DOI: 10.1109/SDS49854.2020.9143911 Online resource available
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Dietze, R.; Rünger, G.: Search-based Scheduling for Parallel Tasks on Heterogenous Platforms. In: Euro-Par 2019: Parallel Processing Workshops: pp. 333-344. Springer – ISBN 978-3-030-48340-1. Göttingen, Germany, August 2019. DOI: 10.1007/978-3-030-48340-1_26 Online resource available
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Jakobs, T.; Naumann, B.; Rünger, G.: Performance and energy consumption of the SIMD Gram–Schmidt process for vector orthogonalization. In: The Journal of Supercomputing. Springer – ISSN 1573-0484, 2019. DOI: 10.1007/s11227-019-02839-0 Online resource available
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Kiesel, R.; Rünger, G.: Performance and Energy Evaluation of Parallel Particle Simulation Algorithms for Different Input Particle Data. In: Position Papers of the 2019 Federated Conference on Computer Science and Information Systems (FedCSIS 2019), 12th Workshop on Computer Aspects of Numerical Algorithms (CANA'19) (vol. 19): pp. 31-37. Leipzig, Germany, September 2019. DOI: 10.15439/2019F344 Online resource available
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Margenov, S.; Rauber, T.; Atanassov, E.; Almeida, F.; Blanco, V.; Ciegis, R.; Cabrera, A.; Frasheri, N.; Harizanov, S.; Kriauzien, R.; Rünger, G.; Segundo, P. S.; Starikovicius, A.; Szabo, S.; Zavalnij, B.: Applications for ultrascale systems. In: Ultrascale Computing Systems, no. 24: pp. 89-244. The Institution of Engineering and Technology – ISBN 978-1-78561-833-8, 2019.
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Rauber, T.; Rünger, G.: Multiprocessor Task Programming and Flexible Load Balancing for Time-stepping Methods on Heterogeneous Cloud Infrastructures. In: 2019 IEEE SmartWorld, Ubiquitous Intelligence & Computing, Advanced & Trusted Computing, Scalable Computing & Communications, Cloud & Big Data Computing, Internet of People and Smart City Innovation (SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI) : pp. 1537-1544. IEEE – ISBN 978-1-7281-4034-6. Leicester, UK, August 2019. DOI: 10.1109/SmartWorld-UIC-ATC-SCALCOM-IOP-SCI.2019.00277 Online resource available
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Rauber, T.; Rünger, G.: On the Energy Consumption and Accuracy of Multithreaded Embedded Runge-Kutta Methods. In: Proceedings of the The International Conference on High Performance Computing & Simulation (HPCS 2019) (vol. 15): pp. 382-389. IEEE – ISBN 978-1-7281-4485-6. Dublin, Ireland, July 2019. DOI: 10.1109/HPCS48598.2019.9188214 Online resource available
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Rauber, T.; Rünger, G.: Enabling Scalability, Adaptivity, and Resilience in Cloud Applications by Software-defined M-Task-based Programming. In: Proceedings of the 6th International Conference on Software Defined Systems (SDS 2019): pp. 88-95. IEEE – ISBN 978-1-7281-0722-6. Rome, Italy, June 2019. DOI: 10.1109/sds.2019.8768599 Online resource available
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Rauber, T.; Rünger, G.: DVFS RK: Performance and Energy Modeling of Frequency-Scaled Multithreaded Runge-Kutta Methods. In: Proceedings of the 27th Euromicro International Conference on Parallel, Distributed and Network-based Processing (PDP 2019): pp. 392-399. IEEE – ISBN 978-1-7281-1644-0. Pavia, Italy, February 2019. DOI: 10.1109/empdp.2019.8671593 Online resource available
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Rauber, T.; Rünger, G.: A Scheduling Selection Process for Energy-efficient Task Execution on DVFS Processors. In: Concurrency and Computation: Practice and Experience, vol. 31. Wiley – ISSN 1532-0626, Juni 2019. DOI: 10.1002/cpe.5043 Online resource available
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Rauber, T.; Rünger, G.; Stachowski, M.: Model-based optimization of the energy efficiency of multi-threaded applications. In: Sustainable Computing: Informatics and Systems, vol. 22: pp. 44-61. Elsevier – ISSN 2210-5379, 2019. DOI: 10.1016/j.suscom.2019.01.022 Online resource available
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Dietze, R.; Hofmann, M.; Rünger, G.: Analysis and Modeling of Resource Contention Effects based on Benchmark Applications. In: International Conference on High Performance Computing & Simulation (HPCS 2018), Special Session on High Performance Computing Benchmarking and Optimization (HPBench 2018): pp. 330-337. IEEE – ISBN 978-1-5386-7879-4. Orléans, France, July 2018. DOI: 10.1109/HPCS.2018.00062 Online resource available
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Hofmann, M.; Kiesel, R.; Leichsenring, D.; Rünger, G.: A Hybrid CPU/GPU Implementation of Computationally Intensive Particle Simulations Using OpenCL. In: Proceedings of the 17th IEEE International Symposium On Parallel And Distributed Computing (ISPDC 2018): pp. 9-16. IEEE – ISBN 978-1-5386-5330-2. Geneva, Switzerland, June 2018. DOI: 10.1109/ISPDC2018.2018.00011 Online resource available
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Hofmann, M.; Kiesel, R.; Rünger, G.: Energy and Performance Analysis of Parallel Particle Solvers from the ScaFaCoS Library. In: Proceedings of the 2018 ACM/SPEC International Conference on Performance Engineering (ICPE 2018): pp. 88-95. ACM – ISBN 978-1-4503-5095-2. Berlin, Germany, April 2018. DOI: 10.1145/3184407.3184409 Online resource available
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Hofmann, M.; Rünger, G.: Flexible all-to-all data redistribution methods for grid-based particle codes. In: Concurrency and Computation: Practice and Experience, vol. 30, no. 18: pp. e4421. Wiley – ISSN 1532-0634, 2018. DOI: 10.1002/cpe.4421 Online resource available
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Jakobs, T.; Rünger, G.: On the energy consumption of Load/Store AVX instructions. In: Proceedings of the 2018 Federated Conference on Computer Science and Information Systems (FedCSIS 2018), 11th Workshop on Computer Aspects of Numerical Algorithms (CANA'18): pp. 319-327. IEEE. Poznan, Poland, September 2018. DOI: 10.15439/2018F28 Online resource available
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Jakobs, T.; Rünger, G.: Examining Energy Efficiency of Vectorization Techniques Using a Gaussian Elimination. In: International Conference on High Performance Computing & Simulation (HPCS 2018): pp. 268-275. IEEE – ISBN 978-1-5386-7879-4. Orléans, France, July 2018. DOI: 10.1109/HPCS.2018.00054 Online resource available
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Kalinnik, N.; Kiesel, R.; Rauber, T.; Richter, M.; Rünger, G.: Exploring Self-Adaptivity towards Performance and Energy for Time-stepping Methods. In: Proceedings of the 2018 30th International Symposium on Computer Architecture and High Performance Computing (SBAC-PAD 2018): pp. 115-123. IEEE – ISSN 1550-6533. Lyon, France, September 2018. DOI: 10.1109/CAHPC.2018.8645887 Online resource available
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Kalinnik, N.; Kiesel, R.; Rauber, T.; Richter, M.; Rünger, G.: On the Autotuning Potential of Time-stepping methods from Scientific Computing. In: Proceedings of the 2018 Federated Conference on Computer Science and Information Systems (FedCSIS 2018), 11th Workshop on Computer Aspects of Numerical Algorithms (CANA'18) (vol. 15): pp. 329-338. ACSIS – ISSN 2300-596. Poznań, Poland, September 2018. DOI: 10.15439/2018F169 Online resource available
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Rauber, T.; Rünger, G.: Energy and Performance Improvement of Parallel ODE Solvers by Application-specific Program Transformations. In: Proceedings of the 19th IEEE International Workshop on Parallel and Distributed Scientific and Engineering Computing (PDSEC-18), IEEE International Parallel and Distributed Processing Symposium Workshops: pp. 967-976. IEEE – ISBN 978-1-5386-5555-9. Vancouver, Canada, May 2018. DOI: 10.1109/IPDPSW.2018.00151 Online resource available
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Rauber, T.; Rünger, G.: How do loop transformations affect the energy consumption of Runge-Kutta methods?. In: Proceedings of the 26th Euromicro International Conference on Parallel, Distributed, and Network-based Processing (PDP 2018): pp. 499-507. IEEE – ISBN 978-1-5386-4975-6. Cambridge, United Kingdom, March 2018. DOI: 10.1109/PDP2018.2018.00085 Online resource available
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Richter, M.; Rünger, G.: Symbolic matrix multiplication for multi-threaded sparse GEMM utilizing sparse matrix formats. In: International Conference on High Performance Computing & Simulation (HPCS 2018): pp. 523-530. IEEE – ISBN 978-1-5386-7879-4. Orléans, France, July 2018. DOI: 10.1109/HPCS.2018.00088 Online resource available
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Dietze, R.; Goldberg, N.; Herzog, R.; Hofmann, M.; Ihlemann, J.; Meyer, A.; Ospald, F.; Rünger, G.; Springer, R.: Integrating models for fiber reinforced materials into Finite Element simulations. In: Proceedings of the 3rd International MERGE Technologies Conference for Lightweight Structures (IMTC 2017). Verlag Wissenschaftliche Scripten – ISBN 978-3-95735-066-4, September 2017.
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Dietze, R.; Hofmann, M.; Rünger, G.: Resource contention aware execution of multiprocessor tasks on heterogeneous platforms. In: Proceedings of the 15th International Workshop on Algorithms, Models and Tools for Parallel Computing on Heterogeneous Platforms (Heteropar'2017): pp. 390-402. Springer – ISBN 978-3-319-75178-8. Santiago de Compostela, Spain, August 2017 (published 2018). DOI: 10.1007/978-3-319-75178-8_32 Online resource available
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Dietze, R.; Hofmann, M.; Rünger, G.: Resource Contention Aware Scheduling of Multiprocessor Tasks on Heterogeneous Platforms. Poster presented at PhD Forum, International Supercomputing Conference: High Performance (ISC 2017). Frankfurt, Germany, June 2017. DOI: 10.13140/RG.2.2.32630.91200 Online resource available
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Dietze, R.; Hofmann, M.; Rünger, G.: Integrating generic FEM simulations into complex simulation applications. In: Scalable Computing: Practice and Experience, Special issue on High Performance Computing Solutions for Complex Problems, vol. 18, no. 2: pp. 133-144. Universitatea de Vest din Timisoara – ISSN 1895-1767, 2017. DOI: 10.12694/scpe.v18i2.1285 Online resource available
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Jakobs, T.; Lang, J.; Rünger, G.; Stöcker, P.: Tuning linear algebra for energy efficiency on multicore machines by adapting the ATLAS library. In: Future Generation Computer Systems, vol. 82: pp. 555-564. Elsevier – ISSN 0167-739X, 2017 (published May 2018). DOI: 10.1016/j.future.2017.03.009 Online resource available
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Jakobs, T.; Rünger, G.: Improving Energy Efficiency through Vectorization. Poster presented at PhD Forum, International Supercomputing Conference: High Performance (ISC 2017). Frankfurt, Germany, June 2017. DOI: 10.13140/RG.2.2.28017.17767 Online resource available
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Rünger, G.; Dietze, R.; Hofmann, M.; Jakobs, T.: Ökologische und ökonomische Nachhaltigkeit in rechenintensiven Anwendungsprogrammen. Poster presented at "Go Next!" - Tag der Nachhaltigkeit an der TU Chemnitz. In: Ökologische, ökonomische und soziale Nachhaltigkeit an der TU Chemnitz, Posterband mit Beiträgen aus Lehre, Forschung, Administration und von universitären Interessensgruppen: pp. 43-45 – ISBN 978-3-96100-037-1. Chemnitz, Germany, June 2017. URN: urn:nbn:de:bsz:ch1-qucosa-229689 Online resource available
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Rauber, T.; Rünger, G.: Comparison of Time and Energy Oriented Scheduling for Task-based programs. In: Proceedings of the 12th International Conference on Parallel Processing and Applied Mathematics (PPAM 2017) (Lecture Notes in Computer Science, vol. 10777): pp. 185-196. Springer – ISBN 978-3-319-78024-5. Lublin, Poland, September 2017 (published March 2018). DOI: 10.1007/978-3-319-78024-5_17 Online resource available
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Rauber, T.; Rünger, G.: Tuning Energy Effort and Execution Time of Application Software. In: Proceedings of the 38th International Conference on Information Systems Architecture and Technology (ISAT 2017) (Advances in Intelligent Systems and Computing, vol. 656): pp. 239-251. Springer – ISBN 978-3-319-67228-1. Szklarska Poręba, Poland, September 2017. DOI: 10.1007/978-3-319-67229-8_22 Online resource available
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Rauber, T.; Rünger, G.; Stachowski, M.: Performance and Energy Metrics for Multi-threaded Applications on DVFS Processors. In: Sustainable Computing: Informatics and Systems, vol. 17: pp. 55-68. Elsevier – ISSN 2210-5379, 2017 (published March 2018). DOI: 10.1016/j.suscom.2017.10.015 Online resource available
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Rauber, T.; Rünger, G.; Stachowski, M.: Model-based Optimization of the Energy Efficiency of Multi-threaded Applications. In: Proceedings of the 8th International Green and Sustainable Computing Conference (IGSC 2017): pp. 1-6. IEEE – ISBN 978-1-5386-3470-7. Orlando, USA, October 2017 (published 2018). DOI: 10.1109/IGCC.2017.8323578 Online resource available
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Rauber, T.; Rünger, G.; Stachowski, M.: Towards New Metrics for Appraising Performance and Energy Efficiency of Parallel Scientific Programs. In: Proceedings of the 13th IEEE International Conference on Green Computing and Communication (GreenCom-2017): pp. 466-474. IEEE – ISBN 978-1-5386-3066-2. Exeter, United Kingdom, June 2017 (published 2018). DOI: 10.1109/iThings-GreenCom-CPSCom-SmartData.2017.75 Online resource available
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Strazdins, P. E.; Teranishi, K.; Couturier, R.; Antony, J.; Rauber, T.; Rünger, G.; Yang, L. T.: Introduction to PDSEC Workshop. In: 2017 IEEE International Parallel and Distributed Processing Symposium Workshops: pp. 1115-1116. IEEE – ISBN 978-1-5386-3408-0. Orlando, USA, May 2017. DOI: 10.1109/IPDPSW.2017.210 Online resource available
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Dietze, R.; Hofmann, M.; Rünger, G.: Water-Level scheduling for parallel tasks in compute-intensive application components. In: The Journal of Supercomputing, Special Issue on Sustainability on Ultrascale Computing Systems and Applications, vol. 72, no. 11: pp. 4047-4068. Springer – ISSN 1573-0484, 2016. DOI: 10.1007/s11227-016-1711-1 Online resource available
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Hofmann, M.; Rünger, G.; Seifert, T.: Transparent redirection of file-based data accesses for distributed scientific applications. In: Proceedings of the 19th IEEE International Conference on Computational Science and Engineering (CSE 2016): pp. 1-8. IEEE – ISBN 978-1-5090-3593-9. Paris, France, August 2016. DOI: 10.1109/CSE-EUC-DCABES.2016.236 Online resource available
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Jakobs, T.; Hofmann, M.; Rünger, G.: Reducing the Power Consumption of Matrix Multiplications by Vectorization. In: Proceedings of the 19th IEEE International Conference on Computational Science and Engineering (CSE 2016): pp. 1-8. IEEE – ISBN 978-1-5090-3593-9. Paris, France, August 2016. DOI: 10.1109/CSE-EUC-DCABES.2016.187 Online resource available
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Bongo, L. A.; Ciegis, R.; Frasheri, N.; Gong, J.; Kimovski, D.; Kropf, P.; Margenov, S.; Mihajlovic, M.; Neytcheva, M.; Rauber, T.; Rünger, G.; Trobec, R.; Wuyts, R.; Wyrzykowski, R.: Applications for Ultrascale Computing. In: Supercomputing Frontiers and Innovations, vol. 2, no. 1: pp. 19-48 – ISSN 2313-8734, 2015. DOI: 10.14529/jsfi150102 Online resource available
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Carretero, J.; Distefano, S.; Petcu, D.; Pop, D.; Rauber, T.; Rünger, G.; Singh, D. E.: Energy-efficient Algorithms for Ultrascale Systems. In: Supercomputing Frontiers and Innovations, vol. 2, no. 2: pp. 77-104 – ISSN 2313-8734, 2015. DOI: 10.14529/jsfi150205 Online resource available
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Dietze, R.; Hofmann, M.; Rünger, G.: Exploiting Heterogeneous Compute Resources for Optimizing Lightweight Structures. In: Blas, J. G.; Carretero, J.; Jeannot, E.; Wyrzykowski, R. (Eds.): Proceedings of the 2nd International Workshop on Sustainable Ultrascale Computing Systems (NESUS 2015): pp. 127-134 – ISBN 978-84-608-2581-4. Krakow, Poland, September 2015. Online resource available
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Hannusch, S.; Herzog, R.; Hofmann, M.; Ihlemann, J.; Kroll, L.; Meyer, A.; Ospald, F.; Rünger, G.; Springer, R.; Stockmann, M.; Ulke-Winter, L.: Efficient Simulation, Optimization, and Validation of Lightweight Structures. In: Proceedings of the 2nd International MERGE Technologies Conference for Lightweight Structures (IMTC 2015): pp. 219-227. Verlag Wissenschaftliche Scripten. Best Paper Award – ISBN 978-3-95735-025-1. Chemnitz, Germany, Oktober 2015.
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Hofmann, M.; Rünger, G.: Sustainability through flexibility: Building complex simulation programs for distributed computing systems. In: Simulation Modelling Practice and Theory, Special Issue on Techniques and Applications for Sustainable Ultrascale Computing Systems, vol. 58, no. 1: pp. 65-78. Elsevier – ISSN 1569-190X, 2015. DOI: 10.1016/j.simpat.2015.05.007 Online resource available
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Lang, J.; Rünger, G.; Stöcker, P.: Towards energy-efficient linear algebra with an ATLAS library tuned for energy consumption. In: 2015 International Conference on High Performance Computing & Simulation (HPCS 2015): pp. 63-70. IEEE, 2015. DOI: 10.1109/HPCSim.2015.7237022 Online resource available
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Rauber, T.; Rünger, G.: Modeling and Analyzing the Energy Consumption of Fork-Join-based Task Parallel Programs. In: Concurrency and Computation: Practice and Experience, vol. 27, no. 1: pp. 211-236. John Wiley & Sons, Ltd. – ISSN 1532-0634, 2015. DOI: 10.1002/cpe.3219 Online resource available
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Dümmler, J.; Gehre, S.; Rünger, G.: Modeling and Verification of Production Process Chains. In: International Journal of Computer Theory and Engineering, vol. 6, no. 4: pp. 346-352. IACSIT Press – ISSN 1793-8201, 2014. DOI: 10.7763/IJCTE.2014.V6.887 Online resource available
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Dümmler, J.; Gehre, S.; Rünger, G.: Modellierung und Verifikation von Prozessketten. In: 3. Methodenband der Querschnittsarbeitsgruppe 1 “Energetisch-wirtschaftliche Bilanzierung” des Spitzentechnologieclusters eniPROD: pp. 33-42. Verlag Wissenschaftliche Scripten – ISBN 978-3-95735-003-9, 2014. Online resource available
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Dümmler, J.; Rünger, G.: Execution Schemes for the NPB-MZ Benchmarks on Hybrid Architectures: A Comparative Study. In: Bader, M.; Bode, A.; Bungartz, H.-J.; Gerndt, M.; Joubert, G. R.; Peters, F. (Eds.): Parallel Computing: Accelerating Computational Science and Engineering (Advances in Parallel Computing, vol. 25): pp. 733 - 742. IOS Press – ISBN 978-1-61499-380-3, 2014. DOI: 10.3233/978-1-61499-381-0-733 Online resource available
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Lang, J.; Rünger, G.: An execution time and energy model for an energy-aware execution of a conjugate gradient method with CPU/GPU collaboration. In: Journal of Parallel and Distributed Computing, vol. 74, no. 9: pp. 2884-2897. Elsevier – ISSN 0743-7315, 2014. DOI: 10.1016/j.jpdc.2014.06.001 Online resource available
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Lang, J.; Rünger, G.: Measuring and modelling energy consumption for a CPU/GPU conjugate gradient method in an adaptive FEM. In: Proc. of the High-Level Programming for Heterogeneous and Hierarchical Parallel Systems workshop at HiPEAC conference 2014. Wien, Österreich, 2014.
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Lang, J.; Rünger, G.; Stöcker, P.: Simulation Coupling for Simulink Models with the Functional Mock-up Interface. In: 3rd International Colloquium of the Cluster of Excellence eniPROD 2014. Posterbeitrag. Chemnitz, Deutschland, 2014.
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Rauber, T.; Rünger, G.; Schwind, M.: Energy Measurement and Prediction for Multi-Threaded Programs. In: 22nd High Performance Computing Symposium 2014 (HPC 2014), Part of the SCS Spring Simulation Conference. Tampa, USA, 2014. Online resource available
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Rauber, T.; Rünger, G.; Schwind, M.; Xu, H.; Melzner, S.: Energy Measurement, Modeling, and Prediction for Processors with Frequency Scaling. In: The Journal of Supercomputing, vol. 70, no. 3: pp. 1451-1476. Springer – ISSN 0920-8542, 2014. DOI: 10.1007/s11227-014-1236-4 Online resource available
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Reichel, T.; Rünger, G.: SP-AHP: An IT system for collaborative multi-criteria decision-making. In: Benghozi, P.-J.; Krob, D.; Lonjon, A.; Panetto, H. (Eds.): Digital Enterprise Design & Management. Proceedings of the Second International Conference on Digital Enterprise Design and Management DED&M 2014 (Advances in Intelligent Systems and Computing, vol. 261): pp. 59-70. Springer. Paris La Defense, Frankreich, 2014. DOI: 10.1007/978-3-319-04313-5_6 Online resource available
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Reichel, T.; Rünger, G.; Meynerts, L.; Götze, U.: Environment-oriented multi-criteria decision support for the assessment of manufacturing process chains. In: 3. Methodenband der Querschnittsarbeitsgruppe 1 “Energetisch-wirtschaftliche Bilanzierung” des Spitzentechnologieclusters eniPROD: pp. 33-42. Verlag Wissenschaftliche Scripten – ISBN 978-3-95735-003-9, 2014. Online resource available
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Schubert, M.; Rünger, G.: Smartphone-App-System zur mobilen Visualisierung von Energiemessdaten. In: 3. Methodenband der Querschnittsarbeitsgruppe 1 “Energetisch-wirtschaftliche Bilanzierung” des Spitzentechnologieclusters eniPROD: pp. 33-42. Verlag Wissenschaftliche Scripten – ISBN 978-3-95735-003-9, 2014. Online resource available