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Supported by the German Research Foundation (DFG) as part of the priority programme 1648 "Software for Exascale Computing"

GROMACS 2016 developer workshop

GROMACS on highly parallel and heterogeneous platforms

On May 19–20, a group of >50 GROMACS developers and users gathered at the Max Planck Institute for biophysical Chemistry in Göttingen to discuss various aspects of software development and future directions for GROMACS.

The agenda contained talks and discussions about

  • the history and design principles of GROMACS,
  • how to do code development,
  • constant pH and lambda dynamics,
  • scalable electrostatics methods,
  • QM/MM,
  • external potentials,

and many more. Most of the talks were recorded (some weren't due to technical issues—sorry for that!) and can be found below. Due to legal regulations we can only make the talks public where we have an explicit agreement of the speakers, which also means that the discussion is not part of the following videos.

Erik Lindahl: Workshop Introduction

GROMACS history, design principles, new and coming in GROMACS 2016

Christian Blau: Scientific Code Development

How to do code development for GROMACS, best practices.

Berk Hess: Developing and contributing to GROMACS

How to get your code into GROMACS, or how to become a GROMACS developer.

Mark Abraham: GROMACS development, practices & problems

Gerrit Groenhof: Molecular dynamics at constant pH

Thomas Ullmann: A lambda-dynamics module for GROMACS

Ivo Kabadschow: Towards GROMACS with lambda-dynamics. FMM-based electrostatics.

Bartosz Kohnke: FMM - GPU implementation and lambda-dynamics

Berk Hess: FMM regularization

Carsten Kutzner: Compute power optimization by cluster & simulation setup

David van der Spoel, Jochen Hub: Structural changes of proteins in solution using SAXS/WAXS data

Christian Blau: External potentials from experimental data

Gerrit Groenhof: The road ahead for QM/MM in GROMACS

Thomas Kubar: QM/MM with DFTB3 in GROMACS

Katra Kolsek, Vedran Miletic: Reactive MD

Berk Hess: Accelerated Weight Histogram Method

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