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| What | Who | Details | ||
|---|---|---|---|---|
| Conference | Ant | Some of us should go to this: Dear Stefan, I would like to invite you and colleagues of the Twente Centre for Scientific Computing to participate in the ACOS symposium on 30 October at DIFFER Eindhoven. Could you share this invitation with your TCSC colleagues? ACOS is the only multidisciplinary computational sciences symposium in the Netherlands. Attention will be given to different computational methods, machine learning, molecular dynamics, multiscale modeling and many more topics. In addition to academic and industrial participants, the Netherlands eScience Center, SURFsara and CWI will be present. We have formed an interesting program with various keynote speakers, a poster session and contributed talks. Best regards, Stephan van Duren List of conference and call for mini-symposia ASCE Durham UK: https://sites.durham.ac.uk/emi2020-ic/accepted-minisymposiums/ | ||
| Release | Coming | |||
| Docker | Hao | No news, no h.shi-1 only Linux version is tested, need to compile all the settings before move to other systems. Hao needs to talk to Han this week on the docker before he leaves. Hao added the MercuryDPM-Trunk docker image for both Ubuntu and Mac. The windows version will be tested later on. Update: Docker does not work on Windows home, even if HyperV is installed. Need to test on Windows Professional & Enterprise. | ||
| Courses | Thomas | Basic C++ will be given by Thomas Oct 28-30. C++ for Developers be given by Anthony Oct 30 - Nov 1. Juan, Hong, Juan, Mitchel, Hao, Yousef are interested. A MercuryDPM course is not planned, although Julius would be interested. There are two UTstudents that will take teh Basic and Developers version. | ||
| Oomphlib coupling | Mitchel | 1-way coupled code is approx 4000 faster but does not work for non-refinables elements as it needs the extra data Hao did the test on 4000 particles with new code, the Oomph-part is indeed much faster than the older version, this reduces the total simulation time by approx. 20%. However, it seems somewhere else is getting heavier and the new run compare to the old run is actually longer. Hao checked with Mitchel on both old and new implementations and found out the time cost difference on the locate_zeta function in pressure gradient. Think of updating coupling force not every Mercury Timestep to reduce the run time.
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| Jinja or Jinja2 | Hao | Do we want to add a python interface to MercuryDPM in the future? Would be useful to use in combination with GrainLearning. We also have the Mercury command line interface, but that cannot pass functions. There is a student from Erlangen (attanded DEM8) who might be interested in writing this interface in the MercuryMonth | ||
| MercuryMonth | Starts April 20; first week we give the MercuryDPM course;
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