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

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

Jakobs, T.: Optimierung der Energie-Effizienz für Algorithmen der Linearen Algebra durch SIMD-Programmierung und AVX-Vektorisierung, TU Chemnitz, Fakultät für Informatik, Doctoral thesis, 2022. Online resource available

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

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

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

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

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

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

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

Jakobs, T.: Nicht-blockierende Implementierung von verketteten Listen mit Hilfe der Intel Transactional Synchronization Extension. In: Studierendensymposium Informatik 2016 der TU Chemnitz: pp. 27-38. Universitätsverlag Chemnitz  –  ISBN 978-3-944640-85-3, 2016. URN: urn:nbn:de:bsz:ch1-qucosa-201104 Online resource available

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