ONLINE – PRACE Training Centre: Introduction to Parallel Programming

11 – 13 November 2020

Purpose of the course

The focus is to understand the basics of parallel programming with the message-passing interface (MPI) and OpenMP parallel programming paradigms. MPI is the dominant parallelization paradigm in high performance computing and enables one to write programs that run on distributed memory machines, such as the ARIS Greek supercomputer and other systems of the PRACE infrastructure. OpenMP is a threading based approach which enables one to parallelize a program over a single shared memory machine, such as a single node in ARIS. The course also contains performance and best practice considerations, e.g., hybrid MPI+OpenMP parallelization. The course ends with a section presenting profiling and code optimizations to understand the behavior and performance of parallelized codes.

The 3 day course consist of lectures and hands-on exercises on parallel programming. Hands-on sessions (in C and Fortran) will allow users to immediately test and understand the taught constructs of the Message Passing  Interface (MPI) and the shared memory directives of OpenMP. The course ends with a section presenting profiling and code optimizations to understand the behavior and performance of parallelized codes.

ONLINE – PRACE Training Centre: Introduction to Parallel Programming

11 – 13 November 2020

Purpose of the course

The focus is to understand the basics of parallel programming with the message-passing interface (MPI) and OpenMP parallel programming paradigms. MPI is the dominant parallelization paradigm in high performance computing and enables one to write programs that run on distributed memory machines, such as the ARIS Greek supercomputer and other systems of the PRACE infrastructure. OpenMP is a threading based approach which enables one to parallelize a program over a single shared memory machine, such as a single node in ARIS. The course also contains performance and best practice considerations, e.g., hybrid MPI+OpenMP parallelization. The course ends with a section presenting profiling and code optimizations to understand the behavior and performance of parallelized codes.

The 3 day course consist of lectures and hands-on exercises on parallel programming. Hands-on sessions (in C and Fortran) will allow users to immediately test and understand the taught constructs of the Message Passing  Interface (MPI) and the shared memory directives of OpenMP. The course ends with a section presenting profiling and code optimizations to understand the behavior and performance of parallelized codes.

Introduction to Biomolecular modeling and Molecular dynamics in HPC

(Classical and Quantum)

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

GRNET HPC resources for research against COVID-19 pandemic

With a sense of responsibility for Public Health and for the Scientific communities that perform exhaustive research to tackle the COVID-19 epidemic, GRNET opens its HPC infrastructure for directly related Research, via high priority – fast track review process.

GRNET provides computing and storage resources for modeling and running simulations, as well as for data processing and Artificial Intelligence.

If you are a researcher and / or member of a research team in Greece, interested and ready to immediately use GRNET national HPC System ARIS https://hpc.grnet.gr  in the COVID-19 directly related Research, please contact us at: hpc-info [at] lists.grnet.gr

RESCHEDULED, ONLINE – PRACE Training Centre: Machine Learning in HPC, 11-12 June 2020.

Machine Learning in HPC

RESCHEDULED, ONLINE

11-12 June 2020

Description

After the course the participants should be able to understand basic principles in Machine Learning and apply basic machine learning methods.

Learn how to efficiently use HPC infrastructures to get
the best performance out of different machine learning tools. How to use these machine learning frameworks like: Tensorflow, PyTorch, Keras, Horovood with hands-on sessions.

Learn using multiple GPUs to significantly shorten the time required to train lots of data, making solving complex problems feasible.

Learn best-practices to avoid common mistakes to efficiently use the HPC infrastracture and overcome the scalability challenges when using parallel computing techniques

PRACE Training Centre: Accelerator Programming, 10-11 Feb.

Accelerator Programming
GPU programming using CUDA

10 – 11 Febryary 2020

Description

The focus is to understand the basics of accelerator programming with the CUDA parallel computing platform model.

CUDA is a parallel computing platform and application programming interface (API) model created by NVIDIA. It allows software developers to use a CUDA-enabled graphics processing unit (GPU) for general purpose processing – an approach known as GPGPU. The CUDA platform is a software layer that gives direct access to the GPU’s virtual instruction set and parallel computational elements, for the execution of compute kernels.

The course also contains performance and best practice considerations, e.g., gpu libraries, performance optimizations, tools for debugging and profiling.

After the course the participants should have the basic skills needed for utilizing CUDA and OpenACC in new, or existing (own code) programs.