Annotation
This training is designed to equip participants with essential knowledge and skills to utilize the IT4Innovations (IT4I) supercomputing infrastructure effectively. Covering a spectrum of topics ranging from HPC system architecture to performance analysis basics, participants will gain insights into accessing, utilizing, and optimizing their computational workflows on high-performance clusters. Experienced instructors will facilitate each session, offering theoretical insights and hands-on exercises. Participants are encouraged to engage actively to maximize their learning experience. Registered participants will receive access to the HPC infrastructure.
Target Audience and Purpose of the Course:
This course is primarily crafted for application users with prior experience on smaller platforms, such as desktops, who now seek to leverage HPC capabilities to address problems surpassing the capabilities of their current resources. These users, often scientists from diverse fields, may not be developers of the applications they employ but require a deeper understanding of the underlying processes, particularly parallelization.
The course aims to offer participants an introduction to the key aspects of HPC, with a specific focus on the practices at IT4I, addressing their pertinent queries along the way.
Level
beginner
Language
English
Agenda
1. HPC systems architecture and IT4I architecture introduction
Brief introduction to the High-Performance Computing (HPC) in the world and in the Czech Republic. Presenting hardware architecture of the contemporary HPC systems, and basics every HPC user should know, such as scalability, top500, path to exascale, or EPI.
2. Accessing and using IT4I clusters
First login.
How to get your data to the cluster.
How to log in to the cluster and prepare a computation environment.
How to submit computational jobs.
3. Code development on the cluster
Remote development on the cluster.
Compiling and building software tools and custom code.
4. Parallel Programming Basics
This section briefly describes how to run parallel applications that use threads and MPI. And, how to set the environment variables for a hybrid run to utilize the provided hardware efficiently.
5. Leveraging accelerated hardware (GPUs)
In the GPU section of the course, attendees will understand the place of today’s GPUs in HPC. Their architecture will be introduced and compared with CPUs. Several GPU programming models will be briefly introduced, focusing on CUDA, and including a few hands-on exercises.
6. Performance Analysis Basics
Why should we care about performance? This section will answer the question, introduce you to the basic concepts of a performance analysis, provide an overview of performance tools, and show how to start using them.
Tutors
Filip Vaverka holds a PhD degree in Computer Science from Brno University of Technology, Czech Republic. He is currently a member of the Infrastructure Research Lab at IT4Innovations National Supercomputing Center. His research focuses on highly scalable pseudo-spectral methods, accelerated and heterogeneous parallel computing.
Ondřej Meca holds a PhD degree in Computer Science from VSB—Technical University of Ostrava, Czech Republic. He is currently a member of the Infrastructure Research Lab at IT4Innovations National Supercomputing Center. His research interests include verifying parallel algorithms, developing pre/post-processing algorithms for large-scale engineering problems, and developing highly scalable linear solvers.
Jakub Homola is a PhD. student of Computational Science and a Research Assistant at IT4Innovations, VSB-TUO. He graduated in Computational and Applied Mathematics at VSB - Technical University of Ostrava, specializing in Computational Methods and HPC. His research and professional interests are FETI methods and GPU programming in CUDA, HIP and SYCL. He is partially involved in the EUPEX project, where he is working with the ESPRESO library to optimize it for future supercomputers with European processors.
Radim Vavřík is a researcher in the Infrastructure Research Lab at IT4Innovations. He is interested in parallel computing, scalable algorithms design, GPU acceleration, code optimization, and performance analysis. He worked on a hydrological and flood modelling software, a high-performance heterogeneous platform for energy-efficient computing, a GPU acceleration of a highly parallel FEM library, and as a performance analyst in several EU CoEs and projects, including POP2, POP3, SPACE, and SCALABLE.
