Efficient Use of HPC Systems
11 - 12 December 2019
The purpose of this course is to present to existing and potential users of PRACE HPC systems an introduction on how to efficiently use these systems,their typical tools, software environment, compilers, libraries, MPI/OpenMP, batch system, etc.
The trainees will learn what the HPC systems offer, how they work and how to apply for access to these infrastructures - both PRACE Tier-1 and Tier-0.
The course addresses to any potential user of an HPC infrastructure. Background in modules, compilers, MPI/OpenMP/Cuda, batch systems, running time consuming applications is desirable.
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.
The maximum number of participants is 25.
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.
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.
1 ml node: Machine Learning node consisting of 1 server, containing 2 Intel E5-2698v4 processors, 512 GB of central memory and 8 NVIDIA V100 GPU card
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.
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 (2010-2018). Currently he is leader of the HPC team at GRNET S.A.
Kyriakos Ginis received his Diploma in Electrical and Computer Engineering in 2003 from the National Technical University of Athens, Greece. Between 2004 and 2014 he participated in the european projects EGEE I/II/III and EGI as a grid site administrator of the HellasGrid sites HG-01-GRNET, HG-06-EKT and HG-08-Okeanos. Since 2014 he works at GRNET as a system administrator of the ARIS HPC system, primarily responsible for hardware, operating systems and file/storage systems. He continues maintaining the HellasGrid sites HG-06 and HG-08, and supports other GRNET services such as the unique and persistent identifiers (PID)
service, also part of the EUDAT project.
Nikoloutsakos Nikolaos holds a diploma of Engineering in Computer Engineering and Informatics (2014) from the University of Patras, Greece. From 2015 he works as software engineer at GRNET S.A. where he is part of the user application support team for the ARIS HPC system. He has been involved in major national and European projects, such as PRACE and EUDAT. His main research interests include parallel programming models, co-processor programming using GPUs and Intel Xeon Phis.
GRNET – National Infrastructures for Research and Technology, is the national network, cloud computing and IT e-Infrastructure and services provider. It supports hundreds of thousands of users in the key areas of Research, Education, Health and Culture.
GRNET provides an integrated environment of cutting-edge technologies integrating a country-wide dark fiber network, data centers, a high performance computing system and Internet, cloud computing, high-performance computing, authentication and authorization services, security services, as well as audio, voice and video services.
GRNET scientific and advisory duties address the areas of information technology, digital technologies, communications, e-government, new technologies and their applications, research and development, education, as well as the promotion of Digital Transformation.
Through international partnerships and the coordination of EC co-funded projects, it creates opportunities for know-how development and exploitation, and contributes, in a decisive manner, to the development of Research and Science in Greece and abroad.
National Infrastructures for Research and Technology – Networking Research and Education