Dear users of LRZ, We are happy to announce that LRZ and PRACE will offer several online training events. There are still some places available. Please mind that registration is necessary since the details to access the online courses will be provided to registered attendees only. OpenCL Programming for Intel FPGAs Date: Thursday, April 23 15:00 - Friday, April 24, 2020, 19:00 Webpage: https://www.lrz.de/services/compute/courses/2020-04-23_hfpg1s20/ Registration Deadline: April 20, 2020 (extended!) Lecturer: Marlon Price (Intel) Content: This course offered by Intel in cooperation with LRZ gives a high-level overview of FPGAs, what they are, why they are so important as accelerators, and how they can be programmed using OpenCL. This course contains both lectures and lab exercises to help gain familiarity with OpenCL Programming for Intel FPGAs. PRACE Workshop: HPC code optimisation workshop Date: Monday, June 8 - Wednesday, June 10, 2020, 09:00-17:00 Webpage: https://events.prace-ri.eu/event/1003/ Registration Deadline: May 25, 2020 Lecturers: Momme Allalen (LRZ), Fabio Baruffa (Intel), Gennady Fedorov (Intel), Mathias Gerald (LRZ), Carla Guillen (LRZ), Michael Steyer (Intel), Igor Vorobtsov (Intel) Content: We will begin with a description of the latest micro-processor architectures and how the developers can efficiently use modern HPC hardware, in particular the vector units via SIMD programming and AVX-512 optimization and the memory hierarchy. The attendees are then conducted along the optimization process by means of hands-on exercises and learn how to enable vectorization using simple pragmas and more effective techniques, like changing data layout and alignment. The work is guided by the hints from the Intel® compiler reports, and using Intel® Advisor. Besides Intel® Advisor, the participants will also be guided to the use of Intel® VTune(tm) Amplifier, Intel® Application Performance Snapshot and LIKWID as tools for investigating and improving the performance of a HPC application. We further cover the Intel® Math Kernel Library (MKL), in order to show how to gain performance through the use of libraries. PRACE Course: Introduction to hybrid programming in HPC Date: Wednesday, June 17 08:45 - Friday, June 19, 2020 16:00 Webpage: https://events.prace-ri.eu/event/1009/ Registration Deadline: June 2, 2020 Lecturers: Dr. habil. Georg Hager (RRZE, Uni. Erlangen), Dr. Rolf Rabenseifner (HLRS, Uni. Stuttgart), Dr. Claudia Blaas-Schenner, Dr. Irene Reichl (VSC Research Center, TU Wien) Content: Most HPC systems are clusters of shared memory nodes. To use such systems efficiently both memory consumption and communication time has to be optimized. Therefore, hybrid programming may combine the distributed memory parallelization on the node interconnect (e.g., with MPI) with the shared memory parallelization inside of each node (e.g., with OpenMP or MPI-3.0 shared memory). This course analyses the strengths and weaknesses of several parallel programming models on clusters of SMP nodes. LRZ has joined forces with VSC Vienna and HLRS Stuttgart and will offer this course online as a replacement for the course originally scheduled in April at LRZ. We also want to inform you about the following 2 MOOCS (Massive Open Online Courses) offered by PRACE: PRACE MOOC: MPI: A Short Introduction to One-sided Communication Date: Starting on April 20, 2020 Webpage: https://www.futurelearn.com/courses/mpi-one-sided Content: Learn the details of one-sided communication in MPI programming. Discover the advantages to one-sided communication in parallel programming. Message Passing Interface (MPI) is a key standard for parallel computing architectures. On this course, you'll learn the essential concepts of one-sided communication in MPI, as well as the advantages of the MPI communication model. You'll learn the details of how exactly MPI works, as well how to use Remote Memory Access (RMA) routines. Examples, exercises, and tests will be used to help you learn and explore. PRACE MOOC: Python in High Performance Computing Date: Starting on April 27, 2020 Webpage: https://www.futurelearn.com/courses/python-in-hpc Content: The Python programming language is popular in scientific computing because of the benefits it offers for fast code development. The performance of pure Python programs is often suboptimal, but there are ways to make them faster and more efficient. On this course, you'll find out how to identify performance bottlenecks, perform numerical computations efficiently, and extend Python with compiled code. You'll learn various ways to optimise and parallelise Python programs, particularly in the context of scientific and high performance computing. For upcoming ONLINE courses by HLRS see https://www.hlrs.de/training/ Information on further HPC courses: * by LRZ: http://www.lrz.de/services/compute/courses/ * by the Gauss Centre of Supercomputing (GCS): http://www.gauss-centre.eu/training * by German Centres (collected by the Gauß-Allianz): https://hpc-calendar.gauss-allianz.de/ * by the Partnership for Advanced Computing in Europe (PRACE): http://www.training.prace-ri.eu/ Please also forward this announcement to other interested colleagues. Kind regards, Volker Weinberg -- Dr. Volker Weinberg HPC Training and Education Coordinator Leibniz Supercomputing Centre of the Bavarian Academy of Sciences and Humanities email: weinberg@lrz.de<mailto:weinberg@lrz.de> address: Boltzmannstr. 1 - D-85748 Garching bei Muenchen room: E.1.016 phone: +49 (89) 35831-8863