Dr. Jens Lang

Consultation hour

Publications

• 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
• Lang, J.: Data-aware tuning of scientific applications with model-based autotuning. In: Concurrency and Computation: Practice and Experience, vol. 29, no. 4: pp. 1-15. John Wiley and Sons, Ltd  –  ISSN 1532-0634, 2017. DOI: 10.1002/cpe.3885 Online resource available

• Lang, J.: Energie- und Ausführungszeitmodelle zur effizienten Ausführung wissenschaftlicher Simulationen, TU Chemnitz, Fakultät für Informatik, Doctoral thesis, 2015. Online resource available
• 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

• Lang, J.: Grüner verschlüsseln – Messung des Energieverbrauchs von Verschlüsselungsalgorithmen. In: Team der Chemnitzer Linux-Tage, (Eds.): Chemnitzer Linux-Tage 2014 – Tagungsband: pp. 25–32. Universitätsverlag Chemnitz  –  ISBN 978-3-944640-08-2. Chemnitz, 2014. Online resource available
• 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
• 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.
• 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.

• Balg, M.; Lang, J.; Meyer, A.; Rünger, G.: Array-based reduction operations for a parallel adaptive FEM. In: Keller, R.; Kramer, D.; Weiß, J.-P. (Eds.): Facing the Multicore Challenge Ⅲ (LNCS, vol. 7686): pp. 25-36. Springer  –  ISBN 978-3-642-35892-0, 2013. DOI: 10.1007/978-3-642-35893-7_3 Online resource available
• Lang, J.; Rünger, G.: High-Resolution Power Profiling of GPU Functions Using Low-Resolution Measurement. In: Wolf, F.; Mohr, B.; an Mey, D. (Eds.): Euro-Par 2013 Parallel Processing (LNCS, vol. 8097): pp. 801–812. Springer  –  ISBN 978-3-642-40046-9, 2013. DOI: 10.1007/978-3-642-40047-6_80 Online resource available
• Lang, J.; Rünger, G.: Dynamic distribution of workload between CPU and GPU for a parallel conjugate gradient method in an adaptive FEM. In: Procedia Computer Science, vol. 18: pp. 299-308. Elsevier. International Conference on Computational Science (ICCS 2013), 2013. DOI: 10.1016/j.procs.2013.05.193 Online resource available
• Lang, J.; Rünger, G.; Stöcker, P.: Dynamische Simulationskopplung von Simulink-Modellen durch einen Functional-Mock-up-Interface-Exportfilter / TU Chemnitz. (Chemnitzer Informatik-Berichte CSR-13-05)  –  ISSN 0947-5125, 2013. Online resource available

• Dachsel, H.; Hofmann, M.; Lang, J.; Rünger, G.: Automatic Tuning of the Fast Multipole Method Based on Integrated Performance Prediction. In: Proceedings of the 14th IEEE International Conference on High Performance Computing and Communications (HPCC-2012): pp. 617-624. IEEE  –  ISBN 978-1-4673-2164-8. Liverpool, United Kingdom, Juni 2012. DOI: 10.1109/HPCC.2012.88 Online resource available
• Lang, J.: MapReduce – Parallelität im Großen und im Kleinen. In: Team der Chemnitzer Linux-Tage, (Eds.): Chemnitzer Linux-Tage 2012 – Tagungsband: pp. 69-76. Universitätsverlag Chemnitz  –  ISBN 978-3-941003-52-1. Chemnitz, 2012. Online resource available

• Hoffmann, K. H.; Hofmann, M.; Lang, J.; Rünger, G.; Seeger, S.: Accelerating Physical Simulations Using Graphics Processing Units. In: it - Information Technology, vol. 53, no. 2: pp. 49-59. Oldenbourg Wissenschaftsverlag GmbH  –  ISSN 1611-2776, 2011. DOI: 10.1524/itit.2011.0625 Online resource available

• Hoffmann, K. H.; Hofmann, M.; Lang, J.; Rünger, G.; Seeger, S.: Simulating Anomalous Diffusion on Graphics Processing Units. In: Proceedings of the 11th IEEE International Workshop on Parallel and Distributed Scientific and Engineering Computing (PDSEC-10): pp. 1-8. IEEE  –  ISBN 978-1-4244-6534-7. Atlanta, USA, April 2010. DOI: 10.1109/IPDPSW.2010.5470767 Online resource available

Theses

• Student research thesis: Performanzanalyse paralleler Algorithmen auf NUMA-Architekturen (Performance analysis of parallel algorithms on NUMA architectures)
  Department of Computer Science, TU Chemnitz, 2008.
• Diploma thesis: Verwendung von Grafikprozessoren zur Simulation von Diffusionsprozessen mit zufälligen Sierpiński-Teppichen (Application of graphics processing units for simulation of diffusion processes with random Sierpiński carpets)
  Department of Computer Science, TU Chemnitz, 2008. (available online)
• Doctoral thesis: Energie- und Ausführungszeitmodelle zur effizienten Ausführung wissenschaftlicher Simulationen (Energy and execution time models for an efficient execution of scientific simulations)
  Department of Computer Science, TU Chemnitz, 2014. (available online)