VI-SEEM National dissemination event: Hands on workshop on MD biomolecular simulations / modeling

24 April 2018

Purpose of the course

The purpose of this course is to present to existing and potential users of Molecular Dynamics packages the method, the necessary steps for a successful simulation, common practices, common mistakes. The steps for a complete simulation workflow i.e. system setup up to final properties evaluation will be presented using popular software packages.

Outcomes

After the course the participants should be able to efficiently use their prefered MD application (i.e. NAMD, GROMACS, LAMMPS, CP2K), for molecular modelling and molecular dynamics simulations, how to create configuration files based on their needs, tuning the models, how to efficiently use the resources based on the simulation details, avoid common mistakes.

Prerequisites

Background in Physics/Chemistry/Biology. Programming skills, aware of Parallel environments. Bring your own laptop in order to be able to participate in the training hands on. Hands on work will be done in pairs so if you don’t have a laptop you might work with a colleague. Course language is English.

Registration

Registrations will be evaluated on a first-come, first-served basis. GRNET is responsible for the selection of the participants on the basis of the training requirements and the technical skills of the candidates. GRNET will also seek to guarantee the maximum possible geographical coverage with the participation of candidates from many countries.

Venue

GRNET headquarters

Address: 2nd  Floor, 7, Kifisias Av. GR 115 23 Athens

Information on how to reach GRNET headquarters ia available on GRNET website: https://grnet.gr/en/contact-us/  

Accommodation options near GRNET can be found at: https://grnet.gr/wp-content/uploads/sites/13/2015/11/Hotels-near-GRNET-en.pdf

ARIS - System Information

ARIS is the name of the Greek supercomputer, deployed and operated by GRNET (Greek Research and Technology Network) in Athens. ARIS consists of 532 computational nodes seperated in four “islands” as listed here:

• 426 thin nodes: Regular compute nodes without accelerator.

• 44 gpu nodes: “2 x NVIDIA Tesla k40m” accelerated nodes.

• 18 phi nodes: “2 x INTEL Xeon Phi 7120p” accelerated nodes.

• 44 fat nodes: Fat compute nodes have larger number of cores and memory per core than a thin node.

All the nodes are connected via Infiniband network and share 2PB GPFS storage.The infrastructure also has an IBM TS3500 library of maximum storage capacity of about 6 PB. Access to the system is provided by two login nodes.

About Tutors

Dr. Zoe Cournia (female) is a Researcher – Assistant Professor level at the Biomedical Research Foundation, Academy of Athens, where she works on anticancer drug design, design of drug delivery systems and biomolecular modeling using computational techniques. She graduated from the Chemistry Department, University of Athens in 2001 and completed her PhD at the University of Heidelberg in Germany in 2006. She then worked as a postdoctoral researcher at the Chemistry Department, Yale University, USA, on computer-aided drug design and in 2009 she became a lecturer at Yale College. She has been awarded the American Association for Cancer Research Angiogenesis Fellowship (2008), the "Woman of Innovation 2009" Award from the Connecticut Technology Council, USA, the Marie Curie Fellowship from the European Union (2010), the "Outstanding Junior Faculty Award" from the American Chemical Society (2014) and the first "Ada Lovelace Award" from the "Partnership for Advanced Computing in Europe" (2016). She is currently teaching at the Master’s program “Information Technologies in Technology and Medicine” at the Department of Informatics and Telecommunications, National University of Athens.
 

Dr. Dimitris Tsalikis (male) is a Research Associate at the Department of Chemical Engineering in the University of Patras. His research focuses on the physicochemical characterization and the rheology of polymers, polymer nanocomposites, nanofluidics and formulations via atomistic and mesoscopic simulations and to this he develops novel parallel computational methodologies. He received his Diploma in Chemical Engineering from the University of Patras in 2004 and his Ph.D. (titled: “Computational study of structural relaxation and plastic deformation of glassy polymers”) from the National Technical University of Athens in 2009 under the advisement of Prof. Doros N. Theodorou. In 2011 he joined the research team of Prof. Vlasis Mavrantzas in Patras as a Research Associate. Dr. Tsalikis has a solid experience with high performance computing since 2007 being an active user of Tier1 and Tier0 HPC systems available to scientific community under the frameworks of HPC-Europa, PRACE and LinkSCEEM projects. He is currently teaching at the Master’s program “Polymer Science and Technology” at University of Patras.

Dr. Dellis (Male) holds a B.Sc. in Chemistry (1990) and PhD in Computational Chemistry (1995) from the National and Kapodistrian University of Athens, Greece. He has extensive HPC and grid computing experience. He was using HPC systems in computational chemistry research projects on fz-juelich machines (2003-2005). He received an HPC-Europa grant on BSC (2009). In EGEE/EGI projects he acted as application support and VO software manager for SEE VO, grid sites administrator (HG-02, GR-06), NGI_GRNET support staff (2008-2014). In PRACE 1IP/2IP/3IP/4IP/5IP he was involved in benchmarking tasks either as group member or as BCO (2010-2017). Currently he holds the position of “Senior HPC Applications Support Engineer” at GRNET S.A. where he is responsible for activities related to user consultations, porting, optimization and running HPC applications at national and international resources.

About GRNET

GRNET provides Internet connectivity, high-quality e-Infrastructures and advanced services to the Greek Educational, Academic and Research community.

Through its high-speed, high-capacity infrastructure that spans across the entire country, GRNET interconnects more than 150 institutions, including all universities and technological institutions, as well as many research institutes and the public Greek School Network.

GRNET operates the National High Performance Computing system (a Tier-1 in the European HPC ecosystem) and offers user and application support services, that provide Greek scientists with the computing infrastructure and expertise they need for their research enabling them to perform large scale simulations.

GRNET offers innovative IaaS cloud computing services to the Greek and global research & education communities: “ ~okeanos” and “okeanos global” allow users to create multi-layer virtual infrastructure and instantiate virtual computing machines, local networks to interconnect them, and a reliable storage space within seconds, with few, simple mouse clicks.

GRNET aims at contributing towards Greece’s Digital Convergence with the EU, by supporting the development and encouraging the use of e-Infrastructures and services. The right and timely planning strategies, together with the long experience and know-how of its people, guarantee the continuation and enhancement of GRNET’s successful course.

Greek Research and Technology Network – Networking Reserach and Education:

www.grnet.gr, hpc.grnet.gr