Morris Riedel Service 0

Service – Overview

Organisation of International Scientific Conferences Chair 1st International Icelandic High Performance Computing (IHPC) Community Workshop, August 11, 2021, Reykjavik, Iceland [ Web Page ] Topic Chair Data Management, Analytics and Deep Learning 26th Euro-Par Conference, August 24-28, 2020, Warsaw, Poland [ Web Page ] Program Committee Member 2020 IEEE International Symposium on Parallel and Distributed Processing with Applications (ISPA 2020), December 17-19, 2020, Exeter, UK [ Web Page ] Program Committee Member 10th IEEE International Conference on Big Data and Cloud Computing (BDCloud 2020), December 17-19, 2020, Exeter, UK [ Web Page ] Program Committee Member The 22nd IEEE International...

Morris Riedel Media 0

Media – Overview

2022 RAISE CoE Training: LSTM and GRU Morris Riedel, Reza Hassanian 2022-10-31, Public YouTube Online Training and Teaching Seminar Abstract The RAISE CoE EU project works on nine different engineering use cases (see: https://www.coe-raise.eu/use-cases) that bring researchers and experts from the industry together to co-design intertwined AI and HPC methodologies for the Exascale era. These methodologies’ goal is to be usable by various scientific and engineering applications to enable AI at Exascale (see: https://www.coe-raise.eu/ai-exascale). While several of these applications adopt deep learning methods for image processing, such as Convolutional Neural Networks (CNNs), many other use cases require sequence analysis methods...

Morris Riedel Publications

Publications – Overview

Academic Articles Articles published in ISI Journal with a High Impact Factor Hassanian, R., Riedel, M., Yeganeh, N., Unnthorsson, R.: A Practical Approach for Estimating the Optimum Tilt Angle of a Photovoltaic Panel for a Long Period—Experimental Recorded Data, Journal of MDPI Solar, vol. 1, no 1, 2021[ JOURNAL ] [ DOI ] [ JUSER ] [ GOOGLE SCHOLAR ] [ RESEARCHGATE ] Maassen, O., Fritsch, S., Palm, J., Deffge, S., Kunze, J., Marx, G., Riedel, M., Schuppert, A., Bickenbach, J.: Future Medical Artificial Intelligence Application Requirements and Expectations of Physicians in German University Hospitals: Web-Based Survey, Journal of Medical...

Morris Riedel Teaching 0

Teaching – Overview

Teaching Experience Adjunct Lecturer, Lecturer, Senior Lecturer or Professor University Course: High Performance Computing – Advanced Scientific Computing, REI204M, School of Engineering and Natural Sciences, University of Iceland, Iceland, Spring 2022 [ MORE ] University Course: Cloud Computing and Big Data – Parallel and Scalable Machine Learning and Deep Learning, REI504M, School of Engineering and Natural Sciences, University of Iceland, Iceland, Spring 2021 [ MORE ] University Course: High Performance Computing – Advanced Scientific Computing, REI204M, School of Engineering and Natural Sciences, University of Iceland, Iceland, Spring 2021 [ MORE ] University Course: Cloud Computing and Big Data – Parallel...

Morris Riedel Theses 0

Theses – Overview

Theses Proposals I’m always open to proposals for bachelor, master, or doctoral thesis topics that are along the lines of my research interests. Feel free to contact me for details. Doctoral Theses in Progress [In Progress] Deep Learning Application Co-Design on Innovative HPC Architectures Ernir Erlingsson, Doctoral Thesis University of Iceland, School of Engineering and Natural Sciences (SENS), Iceland [ MORE ] [In Progress] Design and Evaluation of a Joint Model of Service Access including Service Discovery and Federated Identity Management in e-infrastructures Ahmed Shiraz Memon, Doctoral Thesis University of Iceland, School of Engineering and Natural Sciences (SENS), Iceland [...

Morris Riedel Biography 0

Biography

Biography Executive Summary Prof. Dr. – Ing. Morris Riedel received his PhD from the Karlsruhe Institute of Technology (KIT) and worked in data-intensive parallel and distributed systems since 2004. He is currently a Full Professor of High-Performance Computing with an emphasis on Parallel and Scalable Machine Learning at the School of Natural Sciences and Engineering of the University of Iceland. Since 2004, Prof. Dr. – Ing. Morris Riedel held various positions at the Juelich Supercomputing Centre of Forschungszentrum Juelich in Germany. In addition, he is the Head of the joint High Productivity Data Processing research group between the Juelich Supercomputing...

Morris Riedel Research 0

Research – Overview

Research Areas Research of the high productivity data processing research group at Forschungszentrum Juelich – Juelich Supercomputing Centre and University of Iceland focuses on application-driven parallel and scalable machine learning methods including related areas such as feature engineering, statistical data mining, and innovative deep learning techniques. In our projects we are cooperating with academic research groups worldside as well as with selected industry companies including the support of start-ups. Additional funding sources are the European Union or the German Federal Ministry of Education and Research. If you are interested in one of these research topics please contact me by email...

2021-05-17 Practice and Experience in Using Parallel and Scalable Machine Learning with Heterogenous Modular Supercomputing Architectures Morris Riedel 0

Practice and Experience in Using Parallel and Scalable Machine Learning with Heterogenous Modular Supercomputing Architectures

Practice and Experience in Using Parallel and Scalable Machine Learning with Heterogenous Modular Supercomputing Architectures Heterogenity in Computing Workshop (HCW) held in conjunction of the 35th IEEE International Parallel and Distributed Processing Symposium (IPDPS) Portland, Virtual Conference, 2021-05-17 – 2020-05-21 [ EVENT ] [ Slides ~21.3 MB (pdf) ] Practice and Experience in Using Parallel and Scalable Machine Learning with Heterogenous Modular Supercomputing Architectures Thanks for a great conference workshop @IPDPS 2021 HCW Workshop 👉slides: https://t.co/SHaiOm3w6R… 👉talk recording: https://t.co/Ze00JSAd1q@Haskoli_Islands @uni_iceland @fzj_jsc @fz_juelich @helmholtz_ai @helmholtz_en @EuroHPC_JU @EuroHpc @CoeRaise @DEEPprojects @EOSC_Nordic — Morris Riedel (@MorrisRiedel) May 18, 2021

Eric Michael Sumner 0

Eric Michael Sumner

Lecture at a Domestic Conference Simulation and Data Lab – Accoustic and Tacticle Engineering (ACUTE), 2nd Icelandic HPC Community Workshop, October 28, 2021, University of Iceland, Groska, Room Ada, Reykjavik, Iceland [ Slides ~1.09 MB (pdf) ] Lecture at an Academic Symposium, Seminar or Forum for Academic Groups Sound Engineering, RAISE CoE All Hands Meeting (AHM), November 24, 2021, virtual conference [ Slides ~1.19 MB (pdf) ]

2022 High Performance Computing 2022 Course Outline 0

HPC – Course Spring 2022

High Performance Computing – Course Spring 2022 Advanced Scientific Computing 16 university lectures with additional practical lectures for hands-on exercises in context The University of Iceland, School of Engineering and Natural Sciences Faculty of Industrial Engineering, Mechanical Engineering and Computer Science Spring 2022 TBD

2021 Cloud Computing and Big Data Course Outline 0

Cloud Computing and Big Data – Course Fall 2021

Cloud Computing and Big Data – Course Fall 2021 Parallel & Scalable Machine Learning & Deep Learning 16 university lectures with additional practical lectures for hands-on exercises in context The University of Iceland, School of Engineering and Natural Sciences Faculty of Industrial Engineering, Mechanical Engineering and Computer Science Fall 2021 More information about lecture materials will follow soon.

2021 HPC Course Spring 2021 Course Outline 0

HPC – Course Spring 2021

High Performance Computing – Course Spring 2021 Advanced Scientific Computing 16 university lectures with additional practical lectures for hands-on exercises in context The University of Iceland, School of Engineering and Natural Sciences Faculty of Industrial Engineering, Mechanical Engineering and Computer Science Spring 2021 More information about slide materials will follow soon.

THE INFLUENCE OF SAMPLING METHODS ON PIXEL-WISE HYPERSPECTRAL IMAGE CLASSIFICATION WITH 3D CONVOLUTIONAL NEURAL NETWORKS-MORRIS RIEDEL 0

The Influence of Sampling Methods on Pixel-Wise Hyperspectral Image Classification with 3D Convolutional Neural Networks

The Influence of Sampling Methods on Pixel-Wise Hyperspectral Image Classification with 3D Convolutional Neural Networks Lange, J., Cavallaro, G., Goetz, M., Erlingsson, E., Riedel, M.: The Influence of Sampling Methods on Pixel-Wise Hyperspectral Image Classification with 3D Convolutional Neural Networks, in conference proceedings of the IEEE International Geoscience and Remote Sensing Symposium (IGARSS 2018), July 22-27, 2018, Valencia, Spain [ EVENT ] [ DOI ] [ JUSER ] [ GOOGLE SCHOLAR ] [ RESEARCHGATE ] Abstract: Supervised image classification is one of the essential techniques for generating semantic maps from remotely sensed images. The lack of labeled ground truth datasets,...