Prof. Dr. - Ing. Morris Riedel

Morris Riedel Research 0

Research

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...

Ahmed Shiraz Memon 0

Theses

Ahmed Shiraz Memon

Doctoral Student Ahmed Shiraz Memon [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 Final Lecture 16 – Epilogue of Big Data & Cloud Computing course at @Haskoli_Islands @uni_iceland @uisens @fzj_jsc @fz_juelich & job review & invited lecture of phd student Shiraz Memon on European Open Science Cloud @EOSC_eu @eoscpilot @EoscPortal slides: https://t.co/NM29spbtaV pic.twitter.com/eVil8RCAgn — Morris Riedel (@MorrisRiedel) December 2, 2018 Lectures (from Sep 2015 – today) Plenary Lecture or Keynote Address...

Ernir Erlingsson 0

Theses

Ernir Erlingsson

Doctoral Student Ernir Erlingsson [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 [ PERSONAL WEB PAGE ] Phd student @ernire Ernir Erlingsson of @Haskoli_Islands alongside other data-driven & HPC application specialists explain technology experts at the @DEEPprojects F2F meeting how to take advantage of the modular supercomputing concept implemented by @fzj_jsc pic.twitter.com/aby8UE95l9 — Morris Riedel (@MorrisRiedel) May 8, 2018 Today I’ll be presenting how we’ll use the @DEEPprojects modular supercomputing architecture to enhance deep learning #EASC18 @MorrisRiedel pic.twitter.com/JfveJWHV9l — Ernir Erlingsson (@ernire) April...

2020 Cloud Computing and Big Data Course Outline 0

Teaching

Cloud Computing and Big Data – Course Fall 2020

Cloud Computing and Big Data – Course Fall 2020 Parallel & Scalable Machine Learning & Deep Learning 16 university lectures with additional practical lectures for hands-on exercises in context University of Iceland, School of Engineering and Natural Sciences Faculty of Industrial Engineering, Mechanical Engineering and Computer Science Fall 2020 Lecture 0 – Prologue Slides PDF (9,90 MB) Lecture 0 – Prologue – Recording Part 1 Lecture 0 – Prologue – Recording Part 2 Teaching Lecture 0 – Prologue of #CloudComputing & #BigData – Parallel & Scalable #MachineLearning & #DeepLearning Course @Haskoli_Islands @uni_iceland @uisens . slides: https://t.co/gCCeXpZM0v@DEEPprojects @fzj_jsc @fz_juelich @helmholtz_ai @EOSC_Nordic...

2020-07-02 ON4OFF Demo Collaborative Filtering Singular Value Decomposition (SVD) Example Morris Riedel 0

Talks

ON4OFF Demo Collaborative Filtering – Singular Value Decomposition (SVD) Example

ON4OFF Demo Collaborative Filtering – Singular Value Decomposition (SVD) Example Online Webinar ON4OFF Project Meeting 2020-07-02 [ Slides ~2.95 MB (pdf) ] [ Jupyter Notebook and Movie Rental Demo Datasets ~3.82 KB (zip) ] Talk & Live demo of recommender systems & collaborative filtering @ProjectJupyter @fzj_jsc @fz_juelich – #ON4OFF online meeting @PieperBeauty @adesso_SE @DEEPprojects @Haskoli_Islands @uni_iceland @uisens @helmholtz_ai . slides & Jupyter notebook & data: https://t.co/Ui3V4ex8VN . pic.twitter.com/89860BJjN8 — Morris Riedel (@MorrisRiedel) July 3, 2020 Talk & Live demo of recommender systems & collaborative filtering Jupyter Jülich Supercomputing Centre Forschungszentrum… Posted by Morris Riedel on Friday, July 3, 2020 Sieh dir...

Morris Riedel ISC High Performance 2020 Digital Conference 0

Biography

ISC High Performance 2020 Digital Conference

ISC High Performance 2020 Digital Conference 2020 June 22–25, 2020 Virtual Conference [ EVENT ] Description Welcome to ISC 2020 Digital, the inaugural online event that focuses on bringing the most critical developments and trends in high performance computing, machine learning and data analytics for the benefit of the global HPC community. Virtual Participation Impressions and Social Media As program committee member I would like to thank chairs & speakers of a great CFD-ML Workshop @ISChpc #ISC20 Digital Conference #ISChpc #HPC #ISC20_SCC @DEEPprojects @fzj_jsc @fz_juelich @Haskoli_Islands @uni_iceland @uisens @helmholtz_ai . recordings: https://t.co/nqffmJseXF pic.twitter.com/u2cIKVfzdO — Morris Riedel (@MorrisRiedel) June 25, 2020...

Extending the Collaborative Online Visualization and Steering Framework for Computational Grids with Attribute-based Authorization 0

Publications

Extending the Collaborative Online Visualization and Steering Framework for Computational Grids with Attribute-based Authorization

Extending the Collaborative Online Visualization and Steering Framework for Computational Grids with Attribute-based Authorization Riedel, M., Frings, W., Habbinga, S., Eickermann, Th., Mallmann, D., Streit, A., Wolf, F., Lippert, Th., Ernst, A., Spurzem, R., in Proceedings of the 9th IEEE/ACM International Conference on Grid Computing (Grid 2008), September 29 – October 1, 2008, Tsukuba, Japan [ EVENT ] [ DOI ] [ JUSER ] [ RESEARCHGATE ] Abstract: Especially within Grid infrastructures driven by high-performance computing (HPC), collaborative online visualization and steering (COVS) has become an important technique to dynamically steer the parameters of a parallel simulation or to just...

Classification of Different Approaches for e-Science Applications in Next Generation Computing Infrastructures 0

Publications

Classification of Different Approaches for e-Science Applications in Next Generation Computing Infrastructures

Classification of Different Approaches for e-Science Applications in Next Generation Computing Infrastructures Riedel, M., Streit, A., Wolf, F., Lippert, Th., Kranzlmueller, D., in conference proceedings of 4th IEEE Conference on e-Science (e-Science 2008), December 7-12, 2008, Indianapolis, USA [ EVENT ] [ DOI ] [ JUSER ] [ RESEARCHGATE ] Abstract: Simulation and thus scientific computing is the third pillar alongside theory and experiment in todays science and engineering. The term e-science evolved as a new Research field that focuses on collaboration in key areas of science using next generation infrastructures to extend the powers of scientific computing. This paper...