Publication list
2023
Understanding Scalable Perovskite Solar Cell Manufacturing with Explainable AI
Klein, L.; Ziegler, S.; Laufer, F.; Debus, C.; Götz, M.; Maier-Hein, K.; Paetzold, U.; Isensee, F.; Jaeger, P.
2023
Klein, L.; Ziegler, S.; Laufer, F.; Debus, C.; Götz, M.; Maier-Hein, K.; Paetzold, U.; Isensee, F.; Jaeger, P.
2023
Precise Energy Consumption Measurements of Heterogeneous Artificial Intelligence Workloads
Caspart, R.; Ziegler, S.; Weyrauch, A.; Obermaier, H.; Raffeiner, S.; Schuhmacher, L. P.; Scholtyssek, J.; Trofimova, D.; Nolden, M.; Reinartz, I.; Isensee, F.; Götz, M.; Debus, C.
2023. High Performance Computing. ISC High Performance 2022 International Workshops – Hamburg, Germany, May 29 – June 2, 2022, Revised Selected Papers. Ed.: H. Anzt, 108–121, Springer International Publishing. doi:10.1007/978-3-031-23220-6_8
Caspart, R.; Ziegler, S.; Weyrauch, A.; Obermaier, H.; Raffeiner, S.; Schuhmacher, L. P.; Scholtyssek, J.; Trofimova, D.; Nolden, M.; Reinartz, I.; Isensee, F.; Götz, M.; Debus, C.
2023. High Performance Computing. ISC High Performance 2022 International Workshops – Hamburg, Germany, May 29 – June 2, 2022, Revised Selected Papers. Ed.: H. Anzt, 108–121, Springer International Publishing. doi:10.1007/978-3-031-23220-6_8
D6.1 : Analysis of user applications, collection of requirements
Lisana Berberi; Heredia, I.; Kozlov, V.; Vollmer, E.; Sainz-Pardo, J.; Bartok, J.; Fojud, A.; Blaszczak, M.; Rausch, A.; Alibabaei, K. F.
2023. Zenodo. doi:10.5281/zenodo.7635453
Lisana Berberi; Heredia, I.; Kozlov, V.; Vollmer, E.; Sainz-Pardo, J.; Bartok, J.; Fojud, A.; Blaszczak, M.; Rausch, A.; Alibabaei, K. F.
2023. Zenodo. doi:10.5281/zenodo.7635453
D1.2 : AI4EOSC Data Management Plan
Aguilar, F.; Kozlov, V.; Heredia, I.
2023. Zenodo. doi:10.5281/zenodo.7649075
Aguilar, F.; Kozlov, V.; Heredia, I.
2023. Zenodo. doi:10.5281/zenodo.7649075
D3.1 : State of the art landscaping and initial platform requirements specification
Moltó, G.; Calatrava, A.; Nguyen, G.; Díaz, J. S.-P.; Lisana Berberi; Kozlov, V.; Cruz, M. S.
2023. Zenodo. doi:10.5281/zenodo.7635430
Moltó, G.; Calatrava, A.; Nguyen, G.; Díaz, J. S.-P.; Lisana Berberi; Kozlov, V.; Cruz, M. S.
2023. Zenodo. doi:10.5281/zenodo.7635430
D3.2 : Initial High Level Architecture
García, Á. L.; Lisana Berberi; Kozlov, V.; Antonacci, M.; Calatrava, A.; Langarita, S.; Moltó, G.
2023. Zenodo. doi:10.5281/zenodo.7728882
García, Á. L.; Lisana Berberi; Kozlov, V.; Antonacci, M.; Calatrava, A.; Langarita, S.; Moltó, G.
2023. Zenodo. doi:10.5281/zenodo.7728882
Massively Parallel Genetic Optimization Through Asynchronous Propagation of Populations
Taubert, O.; Weiel, M.; Coquelin, D.; Farshian, A.; Debus, C.; Schug, A.; Streit, A.; Götz, M.
2023. doi:10.48550/arXiv.2301.08713
Taubert, O.; Weiel, M.; Coquelin, D.; Farshian, A.; Debus, C.; Schug, A.; Streit, A.; Götz, M.
2023. doi:10.48550/arXiv.2301.08713
Massively Parallel Genetic Optimization Through Asynchronous Propagation of Populations
Taubert, O.; Weiel, M.; Coquelin, D.; Farshian, A.; Debus, C.; Schug, A.; Streit, A.; Götz, M.
2023. High Performance Computing – 38th International Conference, ISC High Performance 2023, Hamburg, Germany, May 21–25, 2023, Proceedings. Ed.: A. Bhatele, 106 – 124, Springer Nature Switzerland. doi:10.1007/978-3-031-32041-5_6
Taubert, O.; Weiel, M.; Coquelin, D.; Farshian, A.; Debus, C.; Schug, A.; Streit, A.; Götz, M.
2023. High Performance Computing – 38th International Conference, ISC High Performance 2023, Hamburg, Germany, May 21–25, 2023, Proceedings. Ed.: A. Bhatele, 106 – 124, Springer Nature Switzerland. doi:10.1007/978-3-031-32041-5_6
Training Parameterized Quantum Circuits with Triplet Loss
Wendenius, C.; Kuehn, E.; Streit, A.
2023. Machine Learning and Knowledge Discovery in Databases : European Conference, ECML PKDD 2022, Grenoble, France, September 19–23, 2022, Proceedings. Part V. Ed.: M.-R. Amini, 515–530, Springer Nature Switzerland. doi:10.1007/978-3-031-26419-1_31
Wendenius, C.; Kuehn, E.; Streit, A.
2023. Machine Learning and Knowledge Discovery in Databases : European Conference, ECML PKDD 2022, Grenoble, France, September 19–23, 2022, Proceedings. Part V. Ed.: M.-R. Amini, 515–530, Springer Nature Switzerland. doi:10.1007/978-3-031-26419-1_31
2022
A Computational Workflow for Interdisciplinary Deep Learning Projects utilizing bwHPC Infrastructure
Schilling, M.; Neumann, O.; Scherr, T.; Cui, H.; Popova, A. A.; Levkin, P. A.; Götz, M.; Reischl, M.
2022. Proceedings of the 7th bwHPC Symposium, 69–74, Kommunikations- und Informationszentrum (kiz). doi:10.18725/OPARU-46069
Schilling, M.; Neumann, O.; Scherr, T.; Cui, H.; Popova, A. A.; Levkin, P. A.; Götz, M.; Reischl, M.
2022. Proceedings of the 7th bwHPC Symposium, 69–74, Kommunikations- und Informationszentrum (kiz). doi:10.18725/OPARU-46069
Hyde: The First Open-Source, Python-Based, Gpu-Accelerated Hyperspectral Denoising Package
Coquelin, D.; Rasti, B.; Gotz, M.; Ghamisi, P.; Gloaguen, R.; Streit, A.
2022. 2022 12th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS), Rome, Italy, 13-16 September 2022, 1–5, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/WHISPERS56178.2022.9955088
Coquelin, D.; Rasti, B.; Gotz, M.; Ghamisi, P.; Gloaguen, R.; Streit, A.
2022. 2022 12th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS), Rome, Italy, 13-16 September 2022, 1–5, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/WHISPERS56178.2022.9955088
iMagine D4.1 : Best practices and guideline for developers and providers of AI-based image analytics services
Heredia, I.; Kozlov, V.
2022. Zenodo. doi:10.5281/zenodo.7372358
Heredia, I.; Kozlov, V.
2022. Zenodo. doi:10.5281/zenodo.7372358
Prediction of Optimal Solvers for Sparse Linear Systems Using Deep Learning
Funk, Y.; Götz, M.; Anzt, H.
2022. Proceedings of the 2022 SIAM Conference on Parallel Processing for Scientific Computing (PP). Ed.: X. Li, 14–24, Society for Industrial and Applied Mathematics (SIAM). doi:10.1137/1.9781611977141.2
Funk, Y.; Götz, M.; Anzt, H.
2022. Proceedings of the 2022 SIAM Conference on Parallel Processing for Scientific Computing (PP). Ed.: X. Li, 14–24, Society for Industrial and Applied Mathematics (SIAM). doi:10.1137/1.9781611977141.2
A survey of the European Open Science Cloud services for expanding the capacity and capabilities of multidisciplinary scientific applications
Calatrava, A.; Asorey, H.; Astalos, J.; Azevedo, A.; Benincasa, F.; Blanquer, I.; Bobak, M.; Brasileiro, F.; Codó, L.; Cano, L. del; Esteban, B.; Ferret, M.; Handl, J.; Kerzenmacher, T.; Kozlov, V.; et al.
2022. arxiv. doi:10.48550/ARXIV.2211.07738
Calatrava, A.; Asorey, H.; Astalos, J.; Azevedo, A.; Benincasa, F.; Blanquer, I.; Bobak, M.; Brasileiro, F.; Codó, L.; Cano, L. del; Esteban, B.; Ferret, M.; Handl, J.; Kerzenmacher, T.; Kozlov, V.; et al.
2022. arxiv. doi:10.48550/ARXIV.2211.07738
A container-based workflow for distributed training of deep learning algorithms in HPC clusters
González-Abad, J.; López García, Á.; Kozlov, V. Y.
2022. doi:10.5445/IR/1000152892
González-Abad, J.; López García, Á.; Kozlov, V. Y.
2022. doi:10.5445/IR/1000152892
2021
Evolutionary Optimization of Neural Architectures in Remote Sensing Classification Problems
Coquelin, D.; Sedona, R.; Riedel, M.; Götz, M.
2021. 2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS, 12-16 July 2021, 1587–1590, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/IGARSS47720.2021.9554309
Coquelin, D.; Sedona, R.; Riedel, M.; Götz, M.
2021. 2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS, 12-16 July 2021, 1587–1590, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/IGARSS47720.2021.9554309
Accelerating Neural Network Training with Distributed Asynchronous and Selective Optimization (DASO)
Coquelin, D.; Debus, C.; Götz, M.; Lehr, F. von der; Kahn, J.; Siggel, M.; Streit, A.
2021. Springer. doi:10.21203/rs.3.rs-832355/v1
Coquelin, D.; Debus, C.; Götz, M.; Lehr, F. von der; Kahn, J.; Siggel, M.; Streit, A.
2021. Springer. doi:10.21203/rs.3.rs-832355/v1
2020
HeAT – a Distributed and GPU-accelerated Tensor Framework for Data Analytics
Götz, M.; Coquelin, D.; Debus, C.; Krajsek, K.; Comito, C.; Knechtges, P.; Hagemeier, B.; Tarnawa, M.; Hanselmann, S.; Siggel, M.; Basermann, A.; Streit, A.
2020. doi:10.5445/IR/1000123473
Götz, M.; Coquelin, D.; Debus, C.; Krajsek, K.; Comito, C.; Knechtges, P.; Hagemeier, B.; Tarnawa, M.; Hanselmann, S.; Siggel, M.; Basermann, A.; Streit, A.
2020. doi:10.5445/IR/1000123473
High-performance data analytics of hybrid rocket fuel combustion data using different machine learning approaches
Debus, C.; Ruettgers, A.; Petrarolo, A.; Kobald, M.; Siggel, M.
2020. AIAA Scitech 2020 Forum, American Institute of Aeronautics and Astronautics. doi:10.2514/6.2020-1161
Debus, C.; Ruettgers, A.; Petrarolo, A.; Kobald, M.; Siggel, M.
2020. AIAA Scitech 2020 Forum, American Institute of Aeronautics and Astronautics. doi:10.2514/6.2020-1161
HeAT - A Distributed and GPU-accelerated Tensor Framework for Data Analytics
Götz, M.; Debus, C.; Coquelin, D.; Krajsek, K.; Comito, C.; Knechtges, P.; Hagemeier, B.; Tarnawa, M.; Hanselmann, S.; Siggel, M.; Basermann, A.; Streit, A.
2020. 2020 IEEE International Conference on Big Data (Big Data): 10-13 December 2020, online, 276–287, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/BigData50022.2020.9378050
Götz, M.; Debus, C.; Coquelin, D.; Krajsek, K.; Comito, C.; Knechtges, P.; Hagemeier, B.; Tarnawa, M.; Hanselmann, S.; Siggel, M.; Basermann, A.; Streit, A.
2020. 2020 IEEE International Conference on Big Data (Big Data): 10-13 December 2020, online, 276–287, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/BigData50022.2020.9378050
Loss Scheduling for Class-Imbalanced Segmentation Problems
Taubert, O.; Götz, M.; Schug, A.; Streit, A.
2020. 19th IEEE International Conference on Machine Learning and Applications (ICMLA), 422–427, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/ICMLA51294.2020.00073
Taubert, O.; Götz, M.; Schug, A.; Streit, A.
2020. 19th IEEE International Conference on Machine Learning and Applications (ICMLA), 422–427, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/ICMLA51294.2020.00073
HeAT – a Distributed and GPU-accelerated TensorFramework for Data Analytics
Götz, M.; Debus, C.; Coquelin, D.; Krajsek, K.; Comito, C.; Knechtges, P.; Hagemeier, B.; Tarnawa, M.; Hanselmann, S.; Siggel, M.; Basermann, A.; Streit, A.
2020. 2020 IEEE International Conference on Big Data (Big Data), 276–287, Institute of Electrical and Electronics Engineers (IEEE)
Götz, M.; Debus, C.; Coquelin, D.; Krajsek, K.; Comito, C.; Knechtges, P.; Hagemeier, B.; Tarnawa, M.; Hanselmann, S.; Siggel, M.; Basermann, A.; Streit, A.
2020. 2020 IEEE International Conference on Big Data (Big Data), 276–287, Institute of Electrical and Electronics Engineers (IEEE)
2019
Benchmarking Deep Learning Infrastructures by Means of TensorFlow and Containers
Grupp, A.; Kozlov, V.; Campos, I.; David, M.; Gomes, J.; López García, Á.
2019. High Performance Computing : ISC High Performance 2019 International Workshops, Frankfurt, Germany, June 16-20, 2019. Ed.: M. Weiland, 478–489, Springer International Publishing. doi:10.1007/978-3-030-34356-9_36
Grupp, A.; Kozlov, V.; Campos, I.; David, M.; Gomes, J.; López García, Á.
2019. High Performance Computing : ISC High Performance 2019 International Workshops, Frankfurt, Germany, June 16-20, 2019. Ed.: M. Weiland, 478–489, Springer International Publishing. doi:10.1007/978-3-030-34356-9_36
Machine learning-aided numerical linear Algebra: Convolutional neural networks for the efficient preconditioner generation
Götz, M.; Anzt, H.
2019. Proceedings of ScalA 2018: 9th Workshop on Latest Advances in Scalable Algorithms for Large-Scale Systems, 49–56, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/ScalA.2018.00010
Götz, M.; Anzt, H.
2019. Proceedings of ScalA 2018: 9th Workshop on Latest Advances in Scalable Algorithms for Large-Scale Systems, 49–56, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/ScalA.2018.00010
Remote Sensing Data Analytics with the Udocker Container Tool using Multi-GPU Deep Learning Systems
Cavallaro, G.; Kozlov, V.; Götz, M.; Riedel, M.
2019. Proceedings of 2019 Big Data from Space (BiDS’19). Ed.: S. Pierre, 177–180. doi:10.2760/848593
Cavallaro, G.; Kozlov, V.; Götz, M.; Riedel, M.
2019. Proceedings of 2019 Big Data from Space (BiDS’19). Ed.: S. Pierre, 177–180. doi:10.2760/848593
2018
The Helmholtz Analytics Toolkit (HEAT): A scientific Big Data Library for HPC
Krajsek, K.; Comito, C.; Götz, M.; Hagemeier, B.; Knechtges, P.; Siggel, M.
2018. Proceedings of the Extreme Data Workshop 2018
Krajsek, K.; Comito, C.; Götz, M.; Hagemeier, B.; Knechtges, P.; Siggel, M.
2018. Proceedings of the Extreme Data Workshop 2018
2016
Online Distance Measurement for Tree Data Event Streams
Kuehn, E.; Streit, A.
2016. 2016 IEEE 14th Intl Conf on Dependable, Autonomic and Secure Computing, 14th Intl Conf on Pervasive Intelligence and Computing, 2nd Intl Conf on Big Data Intelligence and Computing and Cyber Science and Technology Congress(DASC/PiCom/DataCom/CyberSciTech), Auckland, New Zealand, 8–12 August 2016. Ed. : Q. Jin, 681–688, IEEE Computer Society. doi:10.1109/DASC-PICom-DataCom-CyberSciTec.2016.122
Kuehn, E.; Streit, A.
2016. 2016 IEEE 14th Intl Conf on Dependable, Autonomic and Secure Computing, 14th Intl Conf on Pervasive Intelligence and Computing, 2nd Intl Conf on Big Data Intelligence and Computing and Cyber Science and Technology Congress(DASC/PiCom/DataCom/CyberSciTech), Auckland, New Zealand, 8–12 August 2016. Ed. : Q. Jin, 681–688, IEEE Computer Society. doi:10.1109/DASC-PICom-DataCom-CyberSciTec.2016.122
Data locality via coordinated caching for distributed processing
Fischer, M.; Kuehn, E.
2016. 7th International Conference on Cloud Computing, GRIDs, and Virtualization, Roma, I, March 20-24, 2016. Ed.: C. Becker Westphall, 113–118, International Academy, Research, and Industry Association (IARIA)
Fischer, M.; Kuehn, E.
2016. 7th International Conference on Cloud Computing, GRIDs, and Virtualization, Roma, I, March 20-24, 2016. Ed.: C. Becker Westphall, 113–118, International Academy, Research, and Industry Association (IARIA)
2015
Clustering evolving batch system jobs for online anomaly detection
Kuehn, E.
2015. 15th IEEE International Conference on Data Mining, Atlantic City, NJ, November 14-17, 2015. Ed.: P. Cui, 1534–1535, IEEE Computer Society. doi:10.1109/ICDMW.2015.219
Kuehn, E.
2015. 15th IEEE International Conference on Data Mining, Atlantic City, NJ, November 14-17, 2015. Ed.: P. Cui, 1534–1535, IEEE Computer Society. doi:10.1109/ICDMW.2015.219
2014
Monitoring data streams at process level in scientific big data batch clusters
Kuehn, E.; Fischer, M.; Jung, C.; Petzold, A.; Streit, A.
2014. Proceedings of the International Symposium on Big Data Computing (BDC 2014), London, UK, December 8-9, 2014, 90–952, IEEE Computer Society. doi:10.1109/BDC.2014.21
Kuehn, E.; Fischer, M.; Jung, C.; Petzold, A.; Streit, A.
2014. Proceedings of the International Symposium on Big Data Computing (BDC 2014), London, UK, December 8-9, 2014, 90–952, IEEE Computer Society. doi:10.1109/BDC.2014.21