• PRACE Training Centres (PTCs)
  • !!
  • PRACE operates ten PRACE Training Centres (PTCs) and they have established a state-of-the-art curriculum for training in HPC and scientific computing. PTCs carry out and coordinate training and education activities that enable both European academic researchers and European industry to utilise the computational infrastructure available through PRACE and provide top-class education and training opportunities for computational scientists in Europe.
    With approximately 100 training events each year, the ten PRACE Training Centres (PTCs) are based at:

    PTC training events are advertised on the following pages. Registration is free and open to all (pending availability):
    https://events.prace-ri.eu/category/2/

    The following figure depicts the location of the PTC centers throughout Europe.
    PATC, PTC location

    PATC events this month:

    December 2018
    Mon Tue Wed Thu Fri Sat Sun
     
    1
     
    2
     
    The aim of this workshop is to present the HPC numerical methods used in the fields of Computational Fluid Dynamics (CFD) and Numerical Astrophysics. The workshop aims to share the methodologies, numerical methods and their implementation used by the state-of-the-art codes in the HPC environment. 
    Key-note lectures will present the challenges of numerically solving Partial Differential Equations (PDE) in problems related to fluid/hydrodynamics, using massively parallel clusters. The workshop will focus on state-of the art of the different HPC architectures and the related numerical methods. Lecture topics will highlight major areas of Numerical Astrophysics and CFD including N-body dynamics, hydrodynamics/magnetohydrodynamics, relativistic hydrodynamics and magnetohydrodynamics, compressible and incompressible flows, turbulence, multi-phase flows and computational tools (visualization and parallel computing), etc...
    For each thematic area, state-of-the-art codes used by the community/research group will be described. The key-note lectures will be based on the forefront numerical techniques within the aforementioned areas, and a follow-up will be partially devoted to hands-on experiences, where the participants will be invited to share their knowledge, by opened discussion. Further information will be available later for participants upon confirmations of the speakers.

    Skills:
    At the end of the course, the student will possess and know how to use the following skills:

    Numerical analysis
    Algorithms for PDE Solution
    Parallel computing (MPI, OpenMP, GPGPUs) 
    HPC architecture
    Strategies for massively parallelization of numerical methods
    Numerical Libraries for HPC
    Target audience:
    Academic and industrial researchers, software developer  which use / are planning to use / develop a code for CFD or plasma physics.
    Pre-requisites:
    Basic knowledge on parallel computing, numerical analysis and algorithms for p.d.e. solution.

    The course is FREE of charge

     

    events.prace-ri.eu/event/790/
    Dec 3 8:00 to Dec 5 18:00
    This training will present basic elements first to enable developpers to understand when and how to use a debugger, and second to optimize the performance of their codes.

    Debugging :

    A short introduction to debugging with examples
    Optimization :

     Basics (stripping, IOs, getting the calculations out of the loops, changing the algorithm, ...)
     Compiler options 
     Vectorization - Data access (cache usage maximization)
     OpenMP parallelization strategies
     Theory to upper-bound the expected performance benefit (speedup, efficiency, peak, memory bandwidth, ...)
    Half of the course will be made of hands-on sessions. The hands-on will use the https://github.com/aff3ct/MIPP library

    Trainers

    Bertrand Cirou
    Mathieu Cloirec
    Cédric Jourdain
    Learning outcomes 
    Ability to understand the main issues for code optimization, knowledge of the main tools and techniques for basic debugging.Prerequisites 
    Basic knowledge of Unix, programming experience in C++, OpenMP

    events.prace-ri.eu/event/799/
    Dec 3 9:00 to Dec 6 17:00
    A number of manufacturers have recently started to produce high performance, multicore CPUs based on the ARM64 architecture. This hands-on workshop is aimed at helping users to port HPC codes to ARM64 processors.

    Although ARM64 is already supported by a number of compiler suites including GNU, ARM and Cray, many users may only have experience in compiling for the Intel x86
    architecture so some changes to the build procedure may be required. In particular, the compilation options required for best performance may be different.

    This 2-day hands-on workshop, delivered by staff from ARM and EPCC, will cover the ARM64 architecture, compilers and libraries. Access will be provided to the Tier2 GW4 Isambard system, based on Cavium ThunderX2 CPUs, for all practical exercises.

    Although test codes will be provided for the hands-on exercises, all attendees are encouraged to bring their own applications to work on during the practical sessions.

     

    Outline timetable

    Monday 3rd December

    09:30 - Registration
    10:00 - Welcome and Introduction
    10:10 - Introduction to the Arm architecture
    10:30 - Arm in HPC - Hardware and Ecosystem
    11:00 - The Catalyst project
    11:30 - Break
    11:45 - Compilers and Tools
    12:30 - Hands on - Getting started
    13:00 - Lunch (not provided)
    14:00 - Hands on: Part 1
    16:00 - Close
    Tuesday 4th December

    10:00 - Optimisation for Arm
    11:00 - Vectorisation
    11:30 - Looking forward - SVE
    12:00 - Hands on: Part 2
    13:00 - Lunch (not provided)
    14:00 - Hands on: Part 2 continued
    16:00 - Close
     

     

    events.prace-ri.eu/event/804/
    Dec 3 11:00 to Dec 4 17:00
    This training will present basic elements first to enable developpers to understand when and how to use a debugger, and second to optimize the performance of their codes.

    Debugging :

    A short introduction to debugging with examples
    Optimization :

     Basics (stripping, IOs, getting the calculations out of the loops, changing the algorithm, ...)
     Compiler options 
     Vectorization - Data access (cache usage maximization)
     OpenMP parallelization strategies
     Theory to upper-bound the expected performance benefit (speedup, efficiency, peak, memory bandwidth, ...)
    Half of the course will be made of hands-on sessions. The hands-on will use the https://github.com/aff3ct/MIPP library

    Trainers

    Bertrand Cirou
    Mathieu Cloirec
    Cédric Jourdain
    Learning outcomes 
    Ability to understand the main issues for code optimization, knowledge of the main tools and techniques for basic debugging.Prerequisites 
    Basic knowledge of Unix, programming experience in C++, OpenMP

    events.prace-ri.eu/event/799/
    Dec 3 9:00 to Dec 6 17:00
    The aim of this workshop is to present the HPC numerical methods used in the fields of Computational Fluid Dynamics (CFD) and Numerical Astrophysics. The workshop aims to share the methodologies, numerical methods and their implementation used by the state-of-the-art codes in the HPC environment. 
    Key-note lectures will present the challenges of numerically solving Partial Differential Equations (PDE) in problems related to fluid/hydrodynamics, using massively parallel clusters. The workshop will focus on state-of the art of the different HPC architectures and the related numerical methods. Lecture topics will highlight major areas of Numerical Astrophysics and CFD including N-body dynamics, hydrodynamics/magnetohydrodynamics, relativistic hydrodynamics and magnetohydrodynamics, compressible and incompressible flows, turbulence, multi-phase flows and computational tools (visualization and parallel computing), etc...
    For each thematic area, state-of-the-art codes used by the community/research group will be described. The key-note lectures will be based on the forefront numerical techniques within the aforementioned areas, and a follow-up will be partially devoted to hands-on experiences, where the participants will be invited to share their knowledge, by opened discussion. Further information will be available later for participants upon confirmations of the speakers.

    Skills:
    At the end of the course, the student will possess and know how to use the following skills:

    Numerical analysis
    Algorithms for PDE Solution
    Parallel computing (MPI, OpenMP, GPGPUs) 
    HPC architecture
    Strategies for massively parallelization of numerical methods
    Numerical Libraries for HPC
    Target audience:
    Academic and industrial researchers, software developer  which use / are planning to use / develop a code for CFD or plasma physics.
    Pre-requisites:
    Basic knowledge on parallel computing, numerical analysis and algorithms for p.d.e. solution.

    The course is FREE of charge

     

    events.prace-ri.eu/event/790/
    Dec 3 8:00 to Dec 5 18:00
    A number of manufacturers have recently started to produce high performance, multicore CPUs based on the ARM64 architecture. This hands-on workshop is aimed at helping users to port HPC codes to ARM64 processors.

    Although ARM64 is already supported by a number of compiler suites including GNU, ARM and Cray, many users may only have experience in compiling for the Intel x86
    architecture so some changes to the build procedure may be required. In particular, the compilation options required for best performance may be different.

    This 2-day hands-on workshop, delivered by staff from ARM and EPCC, will cover the ARM64 architecture, compilers and libraries. Access will be provided to the Tier2 GW4 Isambard system, based on Cavium ThunderX2 CPUs, for all practical exercises.

    Although test codes will be provided for the hands-on exercises, all attendees are encouraged to bring their own applications to work on during the practical sessions.

     

    Outline timetable

    Monday 3rd December

    09:30 - Registration
    10:00 - Welcome and Introduction
    10:10 - Introduction to the Arm architecture
    10:30 - Arm in HPC - Hardware and Ecosystem
    11:00 - The Catalyst project
    11:30 - Break
    11:45 - Compilers and Tools
    12:30 - Hands on - Getting started
    13:00 - Lunch (not provided)
    14:00 - Hands on: Part 1
    16:00 - Close
    Tuesday 4th December

    10:00 - Optimisation for Arm
    11:00 - Vectorisation
    11:30 - Looking forward - SVE
    12:00 - Hands on: Part 2
    13:00 - Lunch (not provided)
    14:00 - Hands on: Part 2 continued
    16:00 - Close
     

     

    events.prace-ri.eu/event/804/
    Dec 3 11:00 to Dec 4 17:00
    This training will present basic elements first to enable developpers to understand when and how to use a debugger, and second to optimize the performance of their codes.

    Debugging :

    A short introduction to debugging with examples
    Optimization :

     Basics (stripping, IOs, getting the calculations out of the loops, changing the algorithm, ...)
     Compiler options 
     Vectorization - Data access (cache usage maximization)
     OpenMP parallelization strategies
     Theory to upper-bound the expected performance benefit (speedup, efficiency, peak, memory bandwidth, ...)
    Half of the course will be made of hands-on sessions. The hands-on will use the https://github.com/aff3ct/MIPP library

    Trainers

    Bertrand Cirou
    Mathieu Cloirec
    Cédric Jourdain
    Learning outcomes 
    Ability to understand the main issues for code optimization, knowledge of the main tools and techniques for basic debugging.Prerequisites 
    Basic knowledge of Unix, programming experience in C++, OpenMP

    events.prace-ri.eu/event/799/
    Dec 3 9:00 to Dec 6 17:00
    The aim of this workshop is to present the HPC numerical methods used in the fields of Computational Fluid Dynamics (CFD) and Numerical Astrophysics. The workshop aims to share the methodologies, numerical methods and their implementation used by the state-of-the-art codes in the HPC environment. 
    Key-note lectures will present the challenges of numerically solving Partial Differential Equations (PDE) in problems related to fluid/hydrodynamics, using massively parallel clusters. The workshop will focus on state-of the art of the different HPC architectures and the related numerical methods. Lecture topics will highlight major areas of Numerical Astrophysics and CFD including N-body dynamics, hydrodynamics/magnetohydrodynamics, relativistic hydrodynamics and magnetohydrodynamics, compressible and incompressible flows, turbulence, multi-phase flows and computational tools (visualization and parallel computing), etc...
    For each thematic area, state-of-the-art codes used by the community/research group will be described. The key-note lectures will be based on the forefront numerical techniques within the aforementioned areas, and a follow-up will be partially devoted to hands-on experiences, where the participants will be invited to share their knowledge, by opened discussion. Further information will be available later for participants upon confirmations of the speakers.

    Skills:
    At the end of the course, the student will possess and know how to use the following skills:

    Numerical analysis
    Algorithms for PDE Solution
    Parallel computing (MPI, OpenMP, GPGPUs) 
    HPC architecture
    Strategies for massively parallelization of numerical methods
    Numerical Libraries for HPC
    Target audience:
    Academic and industrial researchers, software developer  which use / are planning to use / develop a code for CFD or plasma physics.
    Pre-requisites:
    Basic knowledge on parallel computing, numerical analysis and algorithms for p.d.e. solution.

    The course is FREE of charge

     

    events.prace-ri.eu/event/790/
    Dec 3 8:00 to Dec 5 18:00
    This training will present basic elements first to enable developpers to understand when and how to use a debugger, and second to optimize the performance of their codes.

    Debugging :

    A short introduction to debugging with examples
    Optimization :

     Basics (stripping, IOs, getting the calculations out of the loops, changing the algorithm, ...)
     Compiler options 
     Vectorization - Data access (cache usage maximization)
     OpenMP parallelization strategies
     Theory to upper-bound the expected performance benefit (speedup, efficiency, peak, memory bandwidth, ...)
    Half of the course will be made of hands-on sessions. The hands-on will use the https://github.com/aff3ct/MIPP library

    Trainers

    Bertrand Cirou
    Mathieu Cloirec
    Cédric Jourdain
    Learning outcomes 
    Ability to understand the main issues for code optimization, knowledge of the main tools and techniques for basic debugging.Prerequisites 
    Basic knowledge of Unix, programming experience in C++, OpenMP

    events.prace-ri.eu/event/799/
    Dec 3 9:00 to Dec 6 17:00
    7
     
    8
     
    9
     
    Description:
    This course focuses on the development and execution of bioinformatics pipelines and on their optimization with regards to computing time and disk space. In an era where the data produced per-analysis is in the order of terabytes, simple serial bioinformatic pipelines are no longer feasible. Hence the need for scalable, high-performance parallelization and analysis tools which can easily cope with large-scale datasets. To this end we will study the common performance bottlenecks emerging from everyday bioinformatic pipelines and see how to strike down the execution times for effective data analysis on current and future supercomputers.
    As a case study, two different bioinformatics pipelines (whole-exome and transcriptome analysis) will be presented and re-implemented on the supercomputers of Cineca thanks to ad-hoc hands-on sessions aimed at applying the concepts explained in the course.

    Skills:
    By the end of the course each student should be able to:

    Manage the transfer of big data files and/or large number of files from the local computer to the Cineca platforms and vice versa
    Prepare the environment to analyse big amount of biological data on a supercomputer
    Run single parallel bioinformatic programs on a supercomputer
    Combine bioinformatics applications into pipelines on a supercomputer
    Target audience:
    Biologists, bioinformaticians and computer scientists interested in approaching large-scale NGS-data analysis for the first time.
    Pre-requisites:
    Basic knowledge of python and shell command line. A very basic knowledge of biology is recommended but not required.

    Grant
    The course is FREE of charge.
    The lunch for the three days will be offered to all the participants and some grants are available. The only requirement to be eligible is to be not funded by your institution to attend the course and to work or live in an institute outside the Roma area. The grant  will be 300 euros for students working and living outside Italy and 150 euros for students working and living in Italy (except Rome area). Some documentation will be required and the grant will be paid only after a certified presence of minimum 80% of the lectures.

    Further information about how to request the grant, will be provided at the confirmation of the course: about 3 weeks before the starting date.

    events.prace-ri.eu/event/791/
    Dec 10 9:00 to Dec 12 17:00
    Scope of the course

    The Python programming language has become more and more popular among researchers for its simplicity and the availability of specific programming libraries, and at the same time the correct exploitation of heterogeneous architectures presents challenges for the development of parallel applications. In order to bring these two topics together, this course is focused on the use of Python on CPU and GPU platforms for scientific computing in general.

     

    General description

    The basic concepts of good programming practices in Python and general parallel programming will be introduced, and then GPU computing will be explained combining the essential theory concepts with hands-on sessions. The proposed exercises will be tested in the supercomputing facilities provided by SURFsara using Python with different programming libraries:

    numba
    PyCUDA
    mpi4py
     

    IMPORTANT INFORMATION: WAITING LIST

    If the course gets fully booked, no more registrations are accepted through this website. However, you can be included in the waiting list: for that, please send an email to training@surfsara.nl and you'll be informed when a place becomes available.

    events.prace-ri.eu/event/783/
    Dec 10 9:00 to Dec 11 17:30
    Description:
    This course focuses on the development and execution of bioinformatics pipelines and on their optimization with regards to computing time and disk space. In an era where the data produced per-analysis is in the order of terabytes, simple serial bioinformatic pipelines are no longer feasible. Hence the need for scalable, high-performance parallelization and analysis tools which can easily cope with large-scale datasets. To this end we will study the common performance bottlenecks emerging from everyday bioinformatic pipelines and see how to strike down the execution times for effective data analysis on current and future supercomputers.
    As a case study, two different bioinformatics pipelines (whole-exome and transcriptome analysis) will be presented and re-implemented on the supercomputers of Cineca thanks to ad-hoc hands-on sessions aimed at applying the concepts explained in the course.

    Skills:
    By the end of the course each student should be able to:

    Manage the transfer of big data files and/or large number of files from the local computer to the Cineca platforms and vice versa
    Prepare the environment to analyse big amount of biological data on a supercomputer
    Run single parallel bioinformatic programs on a supercomputer
    Combine bioinformatics applications into pipelines on a supercomputer
    Target audience:
    Biologists, bioinformaticians and computer scientists interested in approaching large-scale NGS-data analysis for the first time.
    Pre-requisites:
    Basic knowledge of python and shell command line. A very basic knowledge of biology is recommended but not required.

    Grant
    The course is FREE of charge.
    The lunch for the three days will be offered to all the participants and some grants are available. The only requirement to be eligible is to be not funded by your institution to attend the course and to work or live in an institute outside the Roma area. The grant  will be 300 euros for students working and living outside Italy and 150 euros for students working and living in Italy (except Rome area). Some documentation will be required and the grant will be paid only after a certified presence of minimum 80% of the lectures.

    Further information about how to request the grant, will be provided at the confirmation of the course: about 3 weeks before the starting date.

    events.prace-ri.eu/event/791/
    Dec 10 9:00 to Dec 12 17:00
    Scope of the course

    The Python programming language has become more and more popular among researchers for its simplicity and the availability of specific programming libraries, and at the same time the correct exploitation of heterogeneous architectures presents challenges for the development of parallel applications. In order to bring these two topics together, this course is focused on the use of Python on CPU and GPU platforms for scientific computing in general.

     

    General description

    The basic concepts of good programming practices in Python and general parallel programming will be introduced, and then GPU computing will be explained combining the essential theory concepts with hands-on sessions. The proposed exercises will be tested in the supercomputing facilities provided by SURFsara using Python with different programming libraries:

    numba
    PyCUDA
    mpi4py
     

    IMPORTANT INFORMATION: WAITING LIST

    If the course gets fully booked, no more registrations are accepted through this website. However, you can be included in the waiting list: for that, please send an email to training@surfsara.nl and you'll be informed when a place becomes available.

    events.prace-ri.eu/event/783/
    Dec 10 9:00 to Dec 11 17:30
    Efficient Use of HPC Systems

    11 - 12 December 2018

    Description

    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.

    Prerequisites

    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.

    Registration

    The maximum number of participants is 30.

    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: grnet.gr/en/contact-us/  

    Accommodation options near GRNET can be found at: grnet.gr/wp-content/up.....n.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. 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.

    Dr Aristeidis Sotiropoulos received his BSc in Computer Science in 1998 from the University of Crete, Greece and his PhD in Parallel Processing and Cluster Computing in 2004 from the National Technical University of Athens, Greece. His interests mainly focus on the fields of Large Scale Computing & Storage Systems, System Software for Scalable High Speed Interconnects for Computer Clusters and Advanced Microprocessor Architectures. He has published several scientific papers in international journals and conference proceedings. He has received the IEEE IPDPS 2001 best paper award for the paper "Minimizing Completion Time for Loop Tiling with Computation and Communication Overlapping". He has worked in several European and National R&D programs in the field of High Performance Computing, Grid Computing, Cloud Computing and Storage. In 2013, he was appointed as the Head of Operations and Financial Management Services, in charge of 15 people. Currently, he is managing EC projects at GRNET SA, the Greek NREN responsible for the provision of advanced e-infrastructure services to the Greek Academic and Research Community.

    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

    events.prace-ri.eu/event/794/
    Dec 11 9:00 to Dec 12 16:00
    Description:
    This course focuses on the development and execution of bioinformatics pipelines and on their optimization with regards to computing time and disk space. In an era where the data produced per-analysis is in the order of terabytes, simple serial bioinformatic pipelines are no longer feasible. Hence the need for scalable, high-performance parallelization and analysis tools which can easily cope with large-scale datasets. To this end we will study the common performance bottlenecks emerging from everyday bioinformatic pipelines and see how to strike down the execution times for effective data analysis on current and future supercomputers.
    As a case study, two different bioinformatics pipelines (whole-exome and transcriptome analysis) will be presented and re-implemented on the supercomputers of Cineca thanks to ad-hoc hands-on sessions aimed at applying the concepts explained in the course.

    Skills:
    By the end of the course each student should be able to:

    Manage the transfer of big data files and/or large number of files from the local computer to the Cineca platforms and vice versa
    Prepare the environment to analyse big amount of biological data on a supercomputer
    Run single parallel bioinformatic programs on a supercomputer
    Combine bioinformatics applications into pipelines on a supercomputer
    Target audience:
    Biologists, bioinformaticians and computer scientists interested in approaching large-scale NGS-data analysis for the first time.
    Pre-requisites:
    Basic knowledge of python and shell command line. A very basic knowledge of biology is recommended but not required.

    Grant
    The course is FREE of charge.
    The lunch for the three days will be offered to all the participants and some grants are available. The only requirement to be eligible is to be not funded by your institution to attend the course and to work or live in an institute outside the Roma area. The grant  will be 300 euros for students working and living outside Italy and 150 euros for students working and living in Italy (except Rome area). Some documentation will be required and the grant will be paid only after a certified presence of minimum 80% of the lectures.

    Further information about how to request the grant, will be provided at the confirmation of the course: about 3 weeks before the starting date.

    events.prace-ri.eu/event/791/
    Dec 10 9:00 to Dec 12 17:00
    Efficient Use of HPC Systems

    11 - 12 December 2018

    Description

    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.

    Prerequisites

    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.

    Registration

    The maximum number of participants is 30.

    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: grnet.gr/en/contact-us/  

    Accommodation options near GRNET can be found at: grnet.gr/wp-content/up.....n.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. 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.

    Dr Aristeidis Sotiropoulos received his BSc in Computer Science in 1998 from the University of Crete, Greece and his PhD in Parallel Processing and Cluster Computing in 2004 from the National Technical University of Athens, Greece. His interests mainly focus on the fields of Large Scale Computing & Storage Systems, System Software for Scalable High Speed Interconnects for Computer Clusters and Advanced Microprocessor Architectures. He has published several scientific papers in international journals and conference proceedings. He has received the IEEE IPDPS 2001 best paper award for the paper "Minimizing Completion Time for Loop Tiling with Computation and Communication Overlapping". He has worked in several European and National R&D programs in the field of High Performance Computing, Grid Computing, Cloud Computing and Storage. In 2013, he was appointed as the Head of Operations and Financial Management Services, in charge of 15 people. Currently, he is managing EC projects at GRNET SA, the Greek NREN responsible for the provision of advanced e-infrastructure services to the Greek Academic and Research Community.

    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

    events.prace-ri.eu/event/794/
    Dec 11 9:00 to Dec 12 16:00
    The Flemish Supercomputing Center (VSC) organizes an OpenMP course at Heverlee (Belgium). This course is offered with PRACE support by SURFsara (The Netherlands) and it is based on a PATC course developed by Dr. Rolf Rabenseifner (HLRS, Stuttgart).

    For registration and more information, please visit the following page:

    www.vscentrum.be/en/ed.....22018

    events.prace-ri.eu/event/802/
    Dec 13 9:00 17:00
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    PTC events this month:

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    Scope of the course

    The Python programming language has become more and more popular among researchers for its simplicity and the availability of specific programming libraries, and at the same time the correct exploitation of heterogeneous architectures presents challenges for the development of parallel applications. In order to bring these two topics together, this course is focused on the use of Python on CPU and GPU platforms for scientific computing in general.

     

    General description

    The basic concepts of good programming practices in Python and general parallel programming will be introduced, and then GPU computing will be explained combining the essential theory concepts with hands-on sessions. The proposed exercises will be tested in the supercomputing facilities provided by SURFsara using Python with different programming libraries:

    numba
    PyCUDA
    mpi4py


    events.prace-ri.eu/event/783/
    Dec 10 9:00 to Dec 11 17:30
    Scope of the course

    The Python programming language has become more and more popular among researchers for its simplicity and the availability of specific programming libraries, and at the same time the correct exploitation of heterogeneous architectures presents challenges for the development of parallel applications. In order to bring these two topics together, this course is focused on the use of Python on CPU and GPU platforms for scientific computing in general.

     

    General description

    The basic concepts of good programming practices in Python and general parallel programming will be introduced, and then GPU computing will be explained combining the essential theory concepts with hands-on sessions. The proposed exercises will be tested in the supercomputing facilities provided by SURFsara using Python with different programming libraries:

    numba
    PyCUDA
    mpi4py


    events.prace-ri.eu/event/783/
    Dec 10 9:00 to Dec 11 17:30
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