Hands-on workshops

Getting more Python Performance with Intel® optimized Distribution for Python
Jim Cownie

The slides used during the workshops can be downloaded from RSE18_Intel_Python_Workshop.

The K-Means example used is pretty close to the one available from the scikit-learn examples at http://ogrisel.github.io/scikit-learn.org/sklearn-tutorial/auto_examples/cluster/plot_color_quantization.html.

A complex version of the Black Scholes demo is available from Intel’s Python TCEs at https://github.com/triskadecaepyon/ep2017_tutorial_tune_performance

 

Using Singularity for High Performance Computing
Mihai Duta, Diamond Light Source
Andrew Gittings, University of Oxford

The materials for the workshop have been made available at https://github.com/mcduta/RSE-2018

 

Data vizualisation with Shiny
David Mawdsley, University of Manchester
Louise Lever, University of Manchester

The workshop materials are available at https://uomresearchit.github.io/RSE18-shiny-workshop/. A snapshot of the workshop is available at DOI 10.5281/zenodo.1409659

 

Make testing easy with pytest
Matt Williams, University of Bristol

The slides used during the workshops can be downloaded from pytest_rse18. The materials for the workshops have been made available at https://github.com/milliams/python_testing

 

A tried-and-tested workflow for software quality assurance
Mark Woodbridge, Research Computing Service, Imperial College London
Mayeul d’Avezac, Research Computing Service, Imperial College London

The materials for the workshop have been made available at https://doi.org/10.5281/zenodo.1409199

 

Talks Slides

The first year in the life of a Research Software Group
Andrew Edmondson (Advanced Research Computing, University of Birmingham)
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The Research Software Engineer Culture Shock
Andrew Williams (University of Bristol)
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Building Nordic-RSE: why and how?
Radovan Bast, Anne Fouilloux, Bjørn Lindi, Radek Lonka, Sri Harsha Vathsavayi, Thor Wikfeldt (University of Oslo, Department of Geosciences)
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RSE Trainings at DLR 2.0 – What we’ve learned from 1.0
Carina Haupt, Michael Meinel (German Aerospace Center (DLR))
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Be prepared to be unpopular: tips on shutting services down
Catherine Jones (Science and technology Facilities Council)
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Easy, fast, and robust data analysis with modern C++
Corentin Schreiber (University of Oxford)
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Maximising the value of research software – a research funder perspective
David Carr (Wellcome Trust)
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Nammu and Oracc: digital humanities software in the sustainable development of Iraqi history and heritage
Eleanor Robson (University College London)
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Robot Routing with a Quantum Processor
James Clark (STFC Hartree Centre)
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Dealing with research software: recommendations for best practices
Kaja Scheliga (Helmholtz Association)
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The Knowledge Makers
Matteo Cancellieri (Open University)
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Harnessing AI for Research
Matthew Johnson (Microsoft Research, Cambridge)
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Surviving as an Apprentice Developer
Matthew Richards (STFC)
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Interactive Research Data Visualisation by Drag-and-Drop
Matthew Walker (University of Southampton)
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UiOHive: a local Hub-node organization for building competence in IoT
John F. Burkhart, Ana Costa Conrado, Simom Filhol, Anne Fouilloux (University of Oslo, Department of Geosciences)
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Fast code with just enough effort
Pashmina Cameron (Microsoft Research)
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“YOU HAVE 0 CREDIT – PLEASE INSERT C̶O̶I̶N̶ FILE”: The Citation File Format
Stephan Druskat (Humboldt-Universität zu Berlin, Department of German Studies and Linguistics)
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Surviving the vacuum: A strategy for sustaining software in the absence of RSE teams
Stephan Druskat, Thomas Krause (Humboldt-Universität zu Berlin, Department of German Studies and Linguistics)
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The challenges of creating an interactive big data visualisation platform for meteorology
Stephen Haddad (Met Office)
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Software in the brave new world of UKRI
Susan Morrell, Eddie Clarke (EPSRC)
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Software Engineering Guidelines – From Theory to Practice
Tobias Schlauch, Carina Haupt (German Aerospace Center (DLR))
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Code is Science: a manifesto for open source code in science
Yo Yehudi (University of Cambridge)
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SIP: Prototyping the Science Data processing for the worlds largest radio telescope.
Benjamin Mort (The University of Oxford’s e-Research Centre)
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Measuring the financial return on investment of the ARCHER eCSE Programme
Lorna Smith, Chris Johnson, Xu Guo, Neelofer Banglawala, Alan Simpson (EPCC, The University of Edinburgh)
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“So, we can toss the cluster in a skip, right?”: Experiences of computational biology in the clouds
Matthew Hartley (The John Innes Centre)
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Challenges and pathways to sustainability in scientific software ecosystems
James Howison (University of Texas at Austin)
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Lessons learnt from building the RSE community in Cardiff University
Ian Harvey, Unai Lopez-Novoa (Cardiff University)
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Poster Downloads

Parsl: Scripting Scalable Workflows in Python
Yadu Babuji, Kyle Chard, Ian Foster, Daniel S. Katz, Mike Wilde, Anna E. Woodard, Justin M. Wozniak (University of Illinois Urbana-Champaign, University of Chicago, Argonne National Laboratory)
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Defining Policies to Turn a Team and Project Around
Jason M. Gates (Sandia National Laboratories)
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Leveraging graph databases for big data management
Mike Gavrielides, Wei Xing (The Francis Crick Institute)
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Testing and Auto-Tuning GPU code with Kernel Tuner
Ben van Werkhoven (Netherlands eScience Center)
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Implementation and performance of an AVX512 extension to OpenQCD
Jarno Rantaharju (Swansea Academy of Advanced Computing)
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Supporting community of GAP developers and package authors
Alexander Konovalov (University of St Andrews)
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Improving Performance and Scalability of NISMOD: National Infrastructure Systems Model
Roald Schoenmakers (University of Oxford)
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