FIRE: Industrial Users FPGAs seminar
2023-11-01 09:30 - 17:30 UTC | SURF Utrecht, Moreelsepark 48, Utrecht, 3511 EP, Netherlands
This “Industrial users of FPGAs” seminar aims to bring together professionals working and applying FPGAs in the Netherlands. It is a knowledge-sharing event created for and by the FPGA engineer. FIRE is short for:
FPGA Innovation Research Exchange.

You are most welcome!
This is the second of a series of five seminars bringing together FPGA practitioners, computer science and engineering experts, scientific computing experts, application owners and HPC providers. We will attempt to build a community through which we discuss and evaluate the need and usability of FPGAs in HPC and Scientific Computing. Curious about the first FIRE seminar? Check the blog of SURF.
The series is part of the FIRE symposia and is jointly organised by QBayLogic, SURF and the Hardware Accelleration Network NL.
Program
10:00-10:05 – Opening
10:05-10:30 – Design rules and automation for FPGA development at Technolution
Speakers: Edwin Hakkennes, Technical Architect and Tom van Leeuwen, Designer at Technolution
10:35-11:00 – SOCs/FPGAs: Beyond programmable functionality
Speaker: Dirk van den Heuvel, Principal Consultant at TOPIC embedded systems
11:00-11:30 – Coffee break
11:30-11:55 – Realtime FPGA processing for measurement and control applications
Speaker: Ronald Grootelaar, Consulting Engineer at Kendrion
12:00-12:25 – Efinix Titanium series of FPGAs
Speaker: not yet known, will follow later
12:30-14:00 – Lunch
14:00-14:25 – Complex Timing Constraints
Speaker: Frank de Bont, Consultant at Core|Vision
14:30-14:55 – Lattice Nexus family of FPGAs
Speaker: Etienne Janssen, Regional Sales Manager at Lattice Semiconductor
15:00-15:30 – Coffee break
15:30-15:55 – Hardware verification with Clash HDL and automated counter-example shrinking
Speaker: Martijn Bastiaan, Compiler Engineer at QBayLogic
16:00-16:25 – Using the AMD Dynamic Function eXchange (DFX) flow to achieve timing closure
Speaker: Gert-Jan Lahpor, Senior FPGA designer at Aimvalley
16:30-17:30 – drinks
Sign up
You can sign up here, until the event sells out!
Location
The event will take place at the SURF office in Utrecht, Moreelsepark 48, 3511 EP Utrecht.

Introduction To Supercomputing part 1
2023-11-08 09:00 - 12:30 | VU Boelelaan, De Boelelaan 1081, Amsterdam, Netherlands
What will you learn in this training?
In this training you will do practical exercises to learn how to use the national supercomputer Snellius effectively and how to complete your tasks with minimal effort in the shortest possible time.
Sign up
For whom
Anyone who wants to know how to perform huge computing tasks.
The language of instruction is English.
Location
This training takes place at the VU Campus
De Boelelaan 1081, Amsterdam – Room WN-C203/C255
View the floor plan here

Advanced course SURF Research Cloud
2023-11-08 14:00 - 17:00 | Tilburg University, Warandelaan 2, Tilburg, 5037 AB, Netherlands
Want to improve your skills in cloud computing to get the most out of our cloud services? Join this free advanced SURF Research Cloud course and discover the advanced capabilities with SURF Research Cloud. This is a continuation of the course Introduction to SURF Research Cloud.
Sign up
In this training we cover the following topics:

Creating your own catalogue items (custom configuration) and components (configuration building blocks)
Explanation of the basic configuration of MS Windows for SURF Research Cloud
Demo of a highly secure environment
Creating a component to install an application

This is a continuation of the Introduction to SURF Research Cloud training course.
For whom.
Research engineers, PhD students, professors.
The working language is English.
Requirements

Bring your own laptop
A browser (Chrome or Firefox will do)
Experience with Powershell is recommended
Experience with version control (git)

Location
The training will be held in Tilburg.
Tilburg University
Warandelaan 2
5037 AB Tilburg
Building K, 1203.

Introduction Training Supercomputing Part II
2023-11-09 09:00 - 13:00 | VU Boelelaan, De Boelelaan 1081, Amsterdam, Netherlands
If you need to perform many calculations, or analyses that are too big for your own system, clusters and supercomputers provide the computing power you need. In this course, you will learn to work with the national supercomputer Snellius.

Sign Up
What will you learn in this course?
This course is a continuation of the first introduction course to Supercomputing, where you can take a deeper dive in the use of supercomputers with some particular focus in efficiency and good practices and an eminently practical approach.
The outline of this sesión includes the following modules:

Fundamentals of performance analysis. This technical introductory presentation introduces hybrid high-performance systems, abstractly covering the system’s architecture and configuration. Our goal is to enhance the understanding of HPC complexity before delving into the importance of performance analysis models. Special focus will be given to the Roofline model.

Abstract modeling of hybrid supercomputers. To present an abstract modeling approach for hybrid supercomputers, condensing their complexity into three core parameters: peak performance, memory, and network bandwidth.
Performance analysis. To explore performance analysis, starting with an overview of various models and delving into the specifics of the roofline model.
The Roofline model. To describe the roofline model and present its practical application through clear explanations and demonstrations.

File systems. This practical session covers the correct usage of file systems on HPC systems, especially on Snellius.
Slurm hybrid jobs. Slurm, a prevalent job scheduler for High-Performance Computing (HPC) systems, has been introduced in previous sections for fundamental understanding. This module advances the specifics of resource allocation parameters for hybrid shared- and distributed-memory jobs.

Nodes, cores, and tasks. This segment will delve into the fundamental concepts of nodes, cores, and tasks, shedding light on their roles within the context of HPC systems.
Bindings. The concept of bindings will be explored, providing insights into how tasks are linked to specific resources enhancing participants’ understanding of resource allocation mechanisms.
Hands on. We will execute the vector addition kernel with multiple configurations using a set of scripts.

QCG Pilotjob. In some cases, users have to execute a large amount of lightweight cases. However, supercomputer’s nodes are too powerful and allow only relatively big partitions. For instance, the smallest allocation possible on Snellius is 1/4 of a node: 32 cores and 64 GB. Job concurrency is a common strategy to efficiently launch multiple light jobs on such big partitions.

Fundamentals of job concurrency. This segment delves into the foundational principles underlying job concurrency. Job concurrency is a methodological approach that enables the simultaneous execution of multiple smaller jobs within a larger allocated partition. The objective is to optimize resource utilization and enhance efficiency in scenarios where lighter tasks are executed on nodes designed for heavier workloads.
Hands on QCG PilotJob. This practical session provides participants with hands-on experience working with the QCG Pilotjob framework. Participants will gain practical insights into the strategies and techniques of utilizing job concurrency to launch and manage multiple lightweight jobs within the context of sizable node partitions.

Prerequisites
Participation in the course Introduction to Supercomputing, Part I
The language of instruction is English
Location
This course takes place at the VU Campus
De Boelelaan 1081, Amsterdam – Room WN-C203/C255
View the floor plan here

Parallel Progamming with Python, CPU part
2023-11-15 10:00 - 15:00 | SURF Amsterdam, Science Park 140, Amsterdam, 1098 XG, Netherlands
In this course, you will learn about parallel programming with Python, a language that is becoming increasingly popular among researchers because of its simplicity and the availability of dedicated programming libraries. In large computing systems, it is essential to properly exploit heterogeneous architectures, and here you will understand the different challenges and how to overcome them with different Python functions for CPU and GPU platforms that are directly applicable to scientific computing.
Sign up
What.
In this course, you will

Understand the limitations and benefits of parallel programming and its use with Python
Implement code using different libraries for parallel programming on CPU and GPU, including PyCUDA or mpi4py.
Experience how to achieve high performance with Python using the supercomputing facilities at SURF.

For whom.
Anyone interested in learning how to achieve high performance with Python codes.
Prerequisites:

Basic knowledge of Linux
Basic knowledge of Python and use of Jupyter notebooks

You must have:

Your own laptop with an up-to-date browser and a terminal emulator. Using the operating systems Linux and macOS is preferred but not mandatory. For Windows users, we recommend downloading MobaXterm (portable version) as a terminal emulator.

Schedule
Day 1 (CPU):
10:00 to 11:00: Introduction to Python and Parallel Computing
11:00 to 11:15: Coffee break
11:15 to 12:30: Hands-on: Introduction to Python and parallel programming (threading/multiprocess)
12:30 to 13:00: Lunch
13:30 to 15:00: Parallel programming with Python (Profiling, Numba)

Parallel programming course with Python, GPU part
2023-11-16 09:00 - 15:00 | SURF Amsterdam, Science Park 140, Amsterdam, 1098 XG, Netherlands
In this course, you will learn about parallel programming with Python, a language that is becoming increasingly popular among researchers because of its simplicity and the availability of dedicated programming libraries. In large computing systems, it is essential to properly exploit heterogeneous architectures, and here you will understand the different challenges and how to overcome them with different Python functions for CPU and GPU platforms that are directly applicable to scientific computing.
Sign up
What.
In this course, you will

Understand the limitations and benefits of parallel programming and its use with Python
Implement code using different libraries for parallel programming on CPU and GPU, including PyCUDA or mpi4py.
Experience how to achieve high performance with Python using the supercomputing facilities at SURF.

For whom.
Anyone interested in learning how to achieve high performance with Python codes.
Prerequisites:

Basic knowledge of Linux
Basic knowledge of Python and use of Jupyter notebooks

You must have:

Your own laptop with an up-to-date browser and a terminal emulator. Using the operating systems Linux and macOS is preferred but not mandatory. For Windows users, we recommend downloading MobaXterm (portable version) as a terminal emulator.

Schedule
Day 2 (GPU):
10:00 to 10:15: Welcome and introduction to the course
10:15 to 10:30: Coffee break
10:45 to 12:00: Introduction to PyCUDA
12:00 to 13:00: Lunch
13:00 to 15:00: Hands-on: PyCUDA examples

Introduction SURF Research Cloud
2023-11-22 09:00 - 12:00 | SURF Amsterdam, Science Park 140, Amsterdam, 1098 XG, Netherlands
This webinar will explain cloud computing in general. The accompanying hands-on approach will introduce you to (some of the) multiple features of the SURF Research Cloud. You will learn how create and operate your own virtual compute environment(s). At the end, you will feel comfortable to install your own applications and profit from the power of Cloud computing.
Sign up
For whom?
Anyone interested to use a flexible and tailor-made environment to execute powerful applications. It is also a useful kickstarter for current HPC Cloud users.
The working language is English.
Requirements

A browser (Chrome or Firefox will do nicely)
Prior experience with Linux commands will help, but not a prerequisite.

Introduction to Deep Learning
2023-11-24 09:00 - 17:00 | SURF Amsterdam, Science Park 140, Amsterdam, 1098 XG, Netherlands
In the course, you’ll learn how deep neural networks work and how they are optimized. During our hands-on sessions you will have the opportunity to work on our high-performance systems and train neural networks to solve an image classification problem. We’ll cover various neural network architectures: from a basic fully connected network, to a convolutional neural network and variational auto-encoders (time permitting).
Sign up
What will you learn?
In this course you will learn to

Understand how a neuron and neural network works
Understand how a neural network is trained
Explore the effect of hyperparameters on neural network performance
Work with a high-level machine learning API (Keras)

For whom?
Everyone interested in deep learning, but with no (or little) current experience & knowledge.
Prerequisites

Python
Basics of linear algebra
Basic statistics

Topics

Neural network: basics

How does a neuron work?
Fully connected networks
Training/optimizing a neural network

Convolutional neural networks (CNNs)
(Variational) Auto-Encoders

Introduction Scientific Visualisation with Blender: Data, Lights, Camera, Action!
2023-12-04 10:00 - 2023-12-18 17:00 | Online
What.
In this course, we introduce Blender from the basics, starting with the user interface and basic functionality. We cover the 3D scene, cameras, lighting and materials, and some basic mesh editing and animation. It helps to have some familiarity with basic 3D graphics concepts, such as 3D geometry, transformations and rendering, but it will be easy to pick up this knowledge quickly during the course.
Sign up
Online
This is an online self-study course, where we will have a number of weekly synchronisation meetings and there will be many suggested exercises guided by the instructors via permanent consultation in a dedicated Discord channel.
Being an online self-study course, the course will start on 4 December at 10:00 am and close on 18 December at 5:00 pm.
For specific details about the course, please visit the visualisation team’s course page at SURF: https://surf-visualization.github.io/blender-course/overview/introducti…

Introduction training supercomputing part I
2024-01-15 09:00 - 13:00 | SURF Amsterdam, Science Park 140, Amsterdam, 1098 XG, Netherlands
What will you learn in this training?
In this training you will do practical exercises to learn how to use the national supercomputer Snellius effectively and how to complete your tasks with minimal effort in the shortest possible time.
Sign up

For whom.
Anyone who wants to know how to perform huge computing tasks.
The language of instruction is English.
Prerequisites
Basic knowledge of Unix shell is useful.

Sign in

Introduction training supercomputing part II
2024-01-15 13:30 - 17:00 | SURF Amsterdam, Science Park 140, Amsterdam, 1098 XG, Netherlands
What will you learn in this course?
This course is a follow-up to the first introductory Supercomputing course, where you can take a deeper dive into the use of supercomputers with a special focus on efficiency and good practices and a very practical approach.
Sign up

The format of this course includes the following modules:

Fundamentals of performance analysis. This introductory technical presentation introduces high-performance hybrid systems, abstractly covering the architecture and configuration of the system. Our aim is to enhance the understanding of HPC complexity before delving deeper into the importance of performance analysis models. Special attention is paid to the Roofline model.

Abstract Modelling hybrid supercomputers. Presenting an abstract modelling approach for hybrid supercomputers, condensing their complexity into three key parameters: peak performance, memory and network bandwidth.
Performance analysis. Explore performance analysis, starting with an overview of different models and going deeper into the specifics of the roofline model.
The roofline model. Describing the roofline model and presenting its practical application through clear explanations and demonstrations.

File systems. This practical session covers the proper use of file systems on HPC systems, especially on Snellius.
Slurm hybrid tasks. Slurm, a widely used job scheduler for high-performance computing (HPC) systems, has been introduced in earlier sections for a basic understanding. This module covers the specific resource allocation parameters for hybrid jobs with shared and distributed memory.

Nodes, cores and tasks. This segment covers the fundamental concepts of nodes, cores and tasks, and highlights their role within the context of HPC systems.
Bindings. The concept of bindings is explored, providing insight into how tasks are associated with specific resources, improving participants’ understanding of resource allocation mechanisms.
Hands on. We will run the vector optics kernel with multiple configurations using a set of scripts.

QCG pilot job. In some cases, users need to run a large number of lightweight cases. However, the nodes of supercomputers are too powerful and only allow relatively large partitions. For example, the smallest possible allocation on Snellius is 1/4 of a node: 32 cores and 64 GB. Job concurrency is a common strategy for efficiently launching multiple lightweight jobs on such large partitions.

Fundamentals of job concurrency. This segment discusses the basic principles underlying job concurrency. Job concurrency is a methodological approach that enables the simultaneous execution of multiple smaller jobs within a larger allocated partition. The goal is to optimise resource utilisation and improve efficiency in scenarios where lighter tasks are executed on nodes designed for heavier workloads.
Hands-on QCG PilotJob. This hands-on session provides participants with hands-on experience of the QCG Pilotjob framework. Participants will gain practical insights into the strategies and techniques of using job concurrency to launch and manage multiple lightweight jobs within the context of bulky node partitions.

Prerequisites
Participation in the course Introduction to Supercomputing, Part I
The language of instruction is English
Location
This training course takes place at the VU Campus
De Boelelaan 1081, Amsterdam – Room WN-C203/C255
View the floor plan here

Sign in

Introduction SURF Research Cloud
2024-01-22 09:00 - 13:00 | UvA campus (Science Park) A1.16, Amsterdam, 1012 WP, Netherlands
This training course explains cloud computing in general. The accompanying hands-on approach introduces you to (some of) the many possibilities of SURF Research Cloud. You will learn how to create and manage your own virtual computing environment(s). At the end, you will feel comfortable enough to install your own applications, and benefit from the power of cloud computing.
Sign up

For whom?
Anyone who wants to use a flexible and customised environment to run powerful applications. It is also a useful kickstarter for current HPC Cloud users.
The working language is English.
Requirements

A browser (Chrome or Firefox is good enough)
Experience with Linux commands helps, but is not a requirement.

This training is a collaboration between SURF and the UvA, sponsored by EuroCC.
Sign in

Training TRANSITS 1
2024-01-24 09:00 - 2024-01-26 17:00 | SURF Utrecht, Moreelsepark 48, Utrecht, 3511 EP, Netherlands
Responding to current situation
The TRANSITS 1 course is the basic and among others developed by SURF in a European context for CSIRTs, and is the basic training. It dates from 2001 and has been in great demand worldwide ever since. In the process, the teaching material has been constantly updated.
Sign up

Getting started with Transits 1
The following components are covered:

organisational aspects
operational aspects
technical background
legal and regulatory aspects

Attention to own input
The TRANSITS training is a full 3-day programme for 2 groups of up to 14 participants each. This gives you room for a lot of personal input and you can ask all your questions. Thanks to the cooperation with NCSC-NL, you will meet participants from all types of CSIRTs in the Netherlands; so you will get even more out of the training.
Lunch is included – you pay for any overnight stay yourself.
For whom?
Are you (or will you be) a member of the local CSIRT within your own institution? Then you are very welcome to participate. In addition, the training is excellent for security officers and ICT managers who want to know what a CSIRT entails. If you participate, we expect you to have basic knowledge of internet technology and security.

Programme
We start all training days at 9am with coffee. On days 1 and 2, we will work from 9.30 to 17.30! We conclude day 1 with a communal dinner. On day 3, we hand out certificates to all participants at the end of the day’s programme, at 16.00.

Cost
Cost for this training course:

SURF members: 350 euro (excluding VAT)
Non-members of SURF: 1,050 euro (excluding VAT)

Registration and cancellation

Registration is not optional; please read the cancellation conditions for SURFacademy meetings.

Introduction to Deep Learning
2024-01-29 09:00 - 13:00 | UvA campus (Science Park) A1.16, Amsterdam, 1012 WP, Netherlands
You will learn how deep neural networks work and how they are optimised. During our hands-on sessions, you will get the chance to work on our high-performance systems and train neural networks to solve an image classification problem. We cover different neural network architectures: from a basic fully connected network, to a convolutional neural network and variational auto-encoders (time permitting).
The language of instruction is English.
Sign up

What will you learn in this course?

Understand how a neuron and neural network work
Understand how a neural network is trained
Investigate the effect of hyperparameters on the performance of neural networks
Working with a high-level machine learning API (Keras)

For whom.
Anyone who is interested in deep learning, but has no (or little) current experience & knowledge.
Prerequisites

Python
Basic linear algebra
Basic statistics

Topics

Neural network: basic principles

How does a neuron work?
Fully connected networks
Training/optimising a neural network

Convolutional neural networks (CNNs)
(Variational) Auto-encoders

This training is a collaboration between SURF and the UvA, sponsored by EuroCC.

Sign in

Essentials 4 Data Support
2024-02-08 - 2024-03-21 | DANS, Anna van Saksenlaan 51, Den Haag, Zuid-Holland, 2593 HW, Netherlands
About the course
This course teaches data supporters basic knowledge and skills (essentials) to take the first steps in supporting researchers in storing, managing, archiving and sharing research data. After the course, you will have an overview of the different phases of scientific research data. For each phase, you will get tools to advise researchers on adding value to their research data.
Sign up

Course structure
Besides acquiring knowledge, practising and sharing knowledge are central. You can follow the course in two ways:

Online only (free of charge)
Full course: online + meetings + certificate (895 euro excl. VAT)

Time investment
Besides attending two course days, the average online study load is four to six hours per week (fifty hours in total).
For whom
The course is aimed at anyone who wants to support researchers in storing, managing, archiving and sharing research data: a data supporter. For example, (data) librarians, IT staff and researchers with data management tasks.
Organisation
Research Data Netherlands (RDNL) is a partnership for sustainable data archiving. Parties involved:

4TU.ResearchData
Data Archiving and Networked Services (DANS)
Dutch Techcentre for Life Sciences (DTL)
SURF

More information and registration
Visit the Research Data Netherlands site for more information on the full programme and how to register.

Sign in

Introduction to Supercomputing, part I
2024-02-13 09:00 - 12:30 | Online
What will you learn in this training?
In this training you will:
• understand what is high-performance computing (HPC)
• learn basic details on clusters and supercomputers
• do practical exercises on the national supercomputer Snellius effectively
• apply the essential best practices on how to work effectively with large HPC systems
Sign upFor whom?

Anyone who wants to know how to perform very large computing tasks.
Prerequisites
Basic knowledge of Unix shell is useful.
Language
This webinar will be in English

Sign up

Workshop Linux Basics
2024-02-15 12:30 - 17:00 | Wageningen University & Research, Droevendaalsesteeg 4, Wageningen, 6708 PB, Netherlands
Linux Basics for HPC
Are you interested in using the High Performance Computing Cluster (HPC) but lack the basic Linux knowledge? Join the course on the basics of Linux for working on the HPC clusters. You will learn the Linux commands and skills needed to create repetitive tasks.

Location
Wageningen University & Research – Forum B0432
Costs

For WUR HPC group members: free
For externals: 250 euro

Registration and cancellation

Registration is mandatory via email at: it-workshops@wur.nl

Cluster computing for social scientists with R - CANCELLED
2024-02-16 09:00 - 17:00 | SURF Amsterdam, Science Park 140, Amsterdam, 1098 XG, Netherlands
CANCELLEDIn this course, you will learn the basics of supercomputing. The day starts with an introduction to supercomputer architecture, including a hands-on session focused on running jobs on a supercomputer.
The second half of the programme focuses on translating your R workflow from a GUI (Rstudio) workflow on your desktop to a scripting/batch environment on the supercomputer. Topics covered here include: efficient programming, parallel computing, and using the SLURM job manager to send your job/analysis to the supercomputer.
Sign upIn this course you will:

Do practical exercises to learn how to effectively use the Lisa national computing cluster and the national supercomputer, and how to complete your tasks with minimal effort in the shortest possible time.
Experience how to achieve high performance with R by using SURF’s supercomputing facilities.

Prerequisites:

Basic knowledge of Linux (Unix shell) is useful
Basic knowledge of R is useful

You must have:
A personal laptop with an up-to-date browser and a terminal emulator (Putty for users of the OSSC/CBS RA environment). Using the operating systems Linux and macOS is preferred but not mandatory. For Windows users, we recommend downloading MobaXterm (portable version) as a terminal emulator. If you are limited in your choice, Putty also works.
Acknowledgements
This course has been sponsored by the EuroCC project.

Introduction to Supercomputing, part I
2024-03-12 09:00 - 12:30 | Online
What will you learn in this training?
In this training you will

understand what is high-performance computing (HPC)
learn basic details on clusters and supercomputers
do practical exercises on the national supercomputer Snellius effectively
apply the essential best practices on how to work effectively with large HPC systems

Sign up

For whom?
Anyone who wants to know how to perform very large computing tasks.
Basic knowledge of Unix shell is useful.

Sign up

Introduction to SURF Research Cloud
2024-03-12 13:00 - 17:00 | Erasmus University Rotterdam, Burgemeester Oudlaan 50, Rotterdam, 3062PA, Netherlands
This training explains cloud computing in general. The accompanying hands-on approach introduces you to (some of) the many features of SURF Research Cloud. You will learn how to create and manage your own virtual computing environment(s). By the end, you will feel comfortable enough to install your own applications, and benefit from the power of cloud computing.
Sign up

For whom?
Anyone who wants to use a flexible and customized environment to run powerful applications.
The language of instruction is English.
Requirements
Bring your own laptop.
A browser (Chrome or Firefox is good enough).
Experience with Linux commands helps, but is not a requirement.

Sign up

Spring HPC School: Introduction to Advanced Computing
2024-04-08 09:00 - 2024-04-12 14:00 | Eindhoven University of Technology, De Zaale 32, Eindhoven, Netherlands
For whom?
This introductory course is aimed at first-time and novice users of high-performance computing facilities. Many researchers can benefit from using a such supercomputing facilities to speed up their research or enable them to solve bigger problems.
Sign up

What to expect?
Day 1 & 2
In the first two half-day sessions (primer course) you will learn how to use (remote) Linux machines, demystify the Linux terminal, upload & edit files, automating tasks etc. We will cover the basics of file version control using Git. In addition, we will talk about the “supercomputing staircase” and how you as a TU/e researcher can gain access to suitable computing facilities, both local & national. The knowledge in this course is also a prerequisite for other sessions in the Spring HPC School.
Day 3
The third day will be an introduction to spuercomputing with hands-on. If you need to perform many calculations, or analyses that are too big for your own system, clusters and supercomputers will provide the computing power you need. You will learn how to work with these large computing systems!
During this do you will:

understand what is high-performance computing (HPC)
learn basic details on clusters and supercomputers
do practical exercises on the national supercomputer Snellius effectively
apply the essential best practices on how to work effectively with large HPC systems

Day 4
Finally, the fourth day will be dedicated to cloud computing. Do you want to create and manage your own work environment and run powerful applications on it? SURF Research Cloud opens the door to cloud computing on different platforms. During this day, your workload runs on the SURF HPC Cloud platform in Amsterdam.
Prerequisites

Basic knowledge of Unix shell is useful.
Bring your own laptop.
A browser (Chrome or Firefox is good enough).
Experience with Linux commands helps, but is not a requirement.

Sign up

Training TRANSITS 2
2024-04-10 09:00 - 2024-04-12 17:00 | SURF Amsterdam, Science Park 140, Amsterdam, 1098 XG, Netherlands
Network monitoring, forensic analysis and more
TRANSITS II training is aimed at more experienced members of already functioning CSIRTs. We focus in this training on techniques for network monitoring and forensic analysis. We also provide a number of tools to improve (human) communication – which is so essential precisely in CSIRT work. Practical exercises are part of every topic covered.
Subscribe

Attention to personal input
The TRANSITS training is a full three-day programme for a group of up to 18 participants. Much attention is paid to the participants’ own input and questions. Moreover, due to the cooperation with NCSC-NL, participants from all types of CSIRTs in the Netherlands are expected, which increases the learning effect. Training and lunches cost 500 euro for members of SURF and 1000 euro for non-members of SURF. The joint dinner is included.
For whom?
Are you a member of the local CSIRT at your institution? And do you already have some CSIRT work experience? Then you are welcome to participate in this training. The training is three-quarters (computer/network) technical in nature.
Programme
We start all training days at 09.00 with coffee and on days 1 and 2 we get to work from 09.30 to 17.30! We conclude the first 2 days with a communal dinner.
On day 3, we hand out certificates to all participants at the end of the day’s programme at 16.00 hrs.
Costs

For SURF members: 550 euro excluding VAT.
For non-SURF member institutions: 1,050 euro excl. vat.

Registration and cancellation

Registration is not optional; please read the cancellation policy for SURFacademy meetings.

End-to-end Data Management for Data Supporters
2024-04-11 10:00 - 16:30 | SURF Amsterdam, Science Park 140, Amsterdam, 1098 XG, Netherlands
Do you want to know more about the tools and facilities for compute and data to better support researchers in Research Data Management (RDM)? Then please join us for this in-person training!
Sign up

Calling all data supporters!
We will be covering the whole research data lifecycle with discussions and demos of available tools – think of RDM platforms, compute and data infrastructure facilities, publication workflows, etc. Note that the focus is not on the technical details of the tools/facilities but on what these can do for your RDM needs! However, for those participants who do want to follow-along the practical steps in these demos, we are happy to facilitate this.
We are particularly interested in tackling some of the big challenges data stewards and other data professionals are facing in the realm of RDM. Expect lively discussion, opportunities to consider your own use cases, and a good lunch!
For whom?
Data supporters with non-technical and/or technical interests

Sign up

Introduction to Supercomputing, part II
2024-04-15 09:00 - 14:00 | Eindhoven University of Technology, De Zaale 32, Eindhoven, Netherlands
If you need to perform many calculations, or analyses that are too big for your own system, clusters and supercomputers provide the computing power you need. In this course, you will learn to work with the national supercomputer Snellius.
Sign up

What will you learn in this course?
This course is a follow-up to the first introductory Supercomputing course, where you can take a deeper dive into the use of supercomputers with a special focus on efficiency and good practices and a very practical approach.
The format of this course includes the following modules:

Fundamentals of performance analysis. This introductory technical presentation introduces high-performance hybrid systems, abstractly covering the architecture and configuration of the system. Our aim is to enhance the understanding of HPC complexity before delving deeper into the importance of performance analysis models. Special attention is paid to the Roofline model.

Abstract Modelling hybrid supercomputers. Presenting an abstract modelling approach for hybrid supercomputers, condensing their complexity into three key parameters: peak performance, memory and network bandwidth.
Performance analysis. Explore performance analysis, starting with an overview of different models and going deeper into the specifics of the roofline model.
The roofline model. Describing the roofline model and presenting its practical application through clear explanations and demonstrations.

File systems. This practical session covers the proper use of file systems on HPC systems, especially on Snellius.
Slurm hybrid tasks. Slurm, a widely used job scheduler for high-performance computing (HPC) systems, has been introduced in earlier sections for a basic understanding. This module covers the specific resource allocation parameters for hybrid jobs with shared and distributed memory.

Nodes, cores and tasks. This segment covers the fundamental concepts of nodes, cores and tasks, and highlights their role within the context of HPC systems.
Bindings. The concept of bindings is explored, providing insight into how tasks are associated with specific resources, improving participants’ understanding of resource allocation mechanisms.
Hands on. We will run the vector optics kernel with multiple configurations using a set of scripts.

QCG pilot job. In some cases, users need to run a large number of lightweight cases. However, the nodes of supercomputers are too powerful and only allow relatively large partitions. For example, the smallest possible allocation on Snellius is 1/4 of a node: 32 cores and 64 GB. Job concurrency is a common strategy to efficiently launch multiple lightweight jobs on such large partitions.

Fundamentals of job concurrency. This segment discusses the basic principles underlying job concurrency. Job concurrency is a methodological approach that allows the simultaneous execution of multiple smaller jobs within a larger allocated partition. The goal is to optimise resource utilisation and improve efficiency in scenarios where lighter tasks are executed on nodes designed for heavier workloads.
Hands-on QCG PilotJob. This hands-on session provides participants with hands-on experience of the QCG Pilotjob framework. Participants will gain practical insights into the strategies and techniques of using job concurrency to launch and manage multiple lightweight jobs within the context of bulky node partitions.

Prerequisites
Participation in the course Introduction to Supercomputing, Part I
The language of instruction is English
Location
TU/e Eindhoven

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High-Performance Deep Learning
2024-04-16 09:00 - 2024-04-17 14:00
Would you like to learn the basics about Deep Learning?

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What?
On day 1 of this course you will:

Understand the fundamental theories of machine learning and the intuitions/ideas behind the algorithms
Work with a high-level machine learning API (Keras)
Explore hyperparameter space to improve a neural network
Understand the pitfalls of classic machine learning algorithms

On day 2 of this course you will learn:

How to set up your software environment
About the technical capabilities of modern day CPUs and GPUs
How to identify bottlenecks in your code

Who?
Everyone interested in getting familiar with machine learning at scale, from the beginning up to more advanced topics
Prerequisites

Basic knowledge on statistics
Basic knowledge on linear algebra
Basic knowledge on Python programming. Some experience with the use of Jupyter Notebooks is desirable, but not essential.

* Basic knowledge on parallel computing is helpful, but not required.

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Introduction to Scientific Visualisation with ParaView
2024-04-17 09:00 - 13:00 | Online
Annotation
NCC Netherlands and NCC Czechia are inviting you to the course Introduction to Scientific Visualisation with ParaView.
Read moreThis foundational course introduces participants to the fundamentals of scientific visualisation using ParaView, an accessible and powerful open-source tool widely utilised in academic and professional settings. Attendees will embark on a structured exploration, starting with a clear distinction between scientific visualisation and information visualisation, setting the stage for understanding their respective roles and applications.
Through guided instruction, participants will acquire a solid grasp of the ParaView data model and pipelines, learning how to navigate and manipulate data effectively. Practical exercises will enable attendees to apply these concepts hands-on, gaining confidence in performing basic visualisation tasks and experimenting with various data types.
By the conclusion of this introductory course, participants will have developed a foundational skill set in leveraging ParaView for scientific visualisation. Equipped with this knowledge, attendees will be poised to explore advanced techniques and applications further, laying a solid groundwork for continued growth and proficiency in the field.
Benefits for the attendees, what will they learn

An overview of scientific visualization versus information visualization
The basics of the ParaView data model and pipelines
Performing basic visualization tasks with ParaView, including hands-on experience with a number of different types of data and visualization aspects.

Level
beginner
Language
English
Prerequisites
None in terms of experience, but a laptop with ParaView installed is required.
Tutors
Paul Melis, Casper van Leeuwen
Paul Melis has been with SURF since 2009 and works on scientific visualization and eXtended Reality Innovation. Casper van Leeuwen joined SURF in 2014 and focuses, amongst other things, on interactive (web-based) visualization. They both have an MSc in Computer Science, Paul from the University of Twente, Casper from the University of Delft. They have a range of visualization support and development experience regarding 3D graphics, interactive 3D visualization and remote visualization. They work within the High-Performance Computing & Visualization group at SURF, where they support the users of the Dutch Supercomputer Snellius with visualization-related tasks. They also regularly demo XR devices and applications, develop demos, or get involved in producing visualizations for PR purposes.
Starts 17 Apr 2024, 09:00
Ends 17 Apr 2024, 13:00
Europe/Prague
ONLINE
Registration
Registration is obligatory. Only registered participants will receive the Zoom link.
After the number of registrations has reached its maximum or the registration form has been closed, you may want to send us an email stating that you are interested to be put on the waiting list. (Vacancies may occur due to cancellations, etc.) E-mail to training@it4i.cz.
Practicalities
This training will be an online event. Technical details about joining will be sent to the accepted registrants before the event.
Please note that the training is held using Zoom. We advise all participants to download the Zoom application to enjoy full functionality.
Capacity and Fees
The capacity is limited to 30 participants.
Please note that the course is open and free of charge for participants from the Member States (MS) of the European Union (EU) and Associated/Other Countries to the Horizon 2020 programme.

Energy Aware Simulations
2024-04-18 09:00 - 14:00 | Eindhoven University of Technology, De Zaale 32, Eindhoven, Netherlands
Did you know that an optimal use of applications or code development can have an impact in the environment? The energy usage of computing infrastructure is becoming an increasingly prominent topic for computing systems design and usage. In this course you will learn about the basics behind energy efficient computing.
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What?
This course will present some tools and technologies that allow a user/software-developer to understand their energy usage in terms of energy analysis of the software that is being deployed on the system. You will get an overview on how to optimize the use of computing systems and application development for the purpose of energy efficiency, rather than keeping a focus on performance or memory usage. You will learn how to do green coding and work with applications in a sustainable way. Some of the main topics will include:

Overview of the data center energy footprint
Energy usage and energy-aware computing on HPC systems

Who?

Everyone interested in learning how to understand energy usage of their software.

Requirements:

Basic knowledge of Linux
Basic programming experience is recommended

You should have:
Your own laptop with an up-to-date browser and a terminal emulator. The use of the operating systems Linux and macOS is preferred, but not mandatory. For Windows users we recommend to download MobaXterm (portable version) as terminal emulator.

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ParaView for (remote) visualizations
2024-04-19 09:00 - 14:00 | Eindhoven University of Technology, De Zaale 32, Eindhoven, Netherlands
In this course you will get to know the fundamentals of scientific visualisation using ParaView. The main topics will cover the 3D data manipulation model and pipelines, learning how to work with simulation data effectively. Practical exercises with different scientific examples will help you to apply these concepts.
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Prerequisites

You will need to have your own laptop with ParaView installed (https://www.paraview.org/)

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Introduction Scientific Visualisation with Blender: Data, Lights, Camera, Action!
2024-04-23 09:00 - 17:00 | SURF Amsterdam, Science Park 140, Amsterdam, 1098 XG, Netherlands
Would you like to make 3D visualizations that are visually more attractive than what ParaView or VisIt can provide? Do you need an image for a grant application that needs to look spectacular? Would you like to create a cool animation of your simulation data? Then this course may be for you!
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Goal
The goal of this course is to provide you with hands-on knowledge to produce great images and basic animations from 3D scientific data. We will be using the open-source package Blender (http://www.blender.org), which provides good basic functionality, while also being usable for advanced usage and general editing of 3D data. It is also a lot of fun to work with (once you get used to its graphical interface).
Example types of relevant scientific data are 3D cell-based simulations, 3D models from photogrammetry, (isosurfaces of) 3D medical scans, molecular models and earth sciences data. Note that we don’t focus on information visualization of abstract data, such as graphs (although you could convert those into a 3D model first and then use them in Blender).
We like to encourage participants to bring along the data they normally work with, or a sample thereof, and would like to apply the course knowledge to.
For whom?
Anyone interesting in learning how to design attractive visualizations. We assume the context to be an academic setting, but it is not make many assumptions on use cases for Blender, and we are happy to help to how we can use Blender to make attractive visuals of the data.
Prerequisites:
It helps to have some familiarity with basic 3D graphics concepts (transformations, rendering), but it is not mandatory.
You will need to have a laptop, preferably with an acceptable GPU, where you can install Blender during the course.

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Advanced Topics in Scientific Visualization with Blender: Geometry, Scripts, Animation, Action!
2024-04-25 10:00 - 2024-05-03 12:00 | Online
This course is a follow-up to our introductory Blender course. We assume you are familiar with working with Blender and have some experience with topics such as the Blender UI, 3D meshes, materials, lighting and cameras.
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Course Setup
In this course you will learn a number of advanced Blender topics:
* The basics of the Python API that is available in Blender. You will learn how the API is structured and eventually start making some simple geometry with code. This can be used, for example, for writing custom import scripts or to perform operations that you would otherwise do manually.
* The node-based shader editor that is used to create and edit materials. In our introductory Blender course we did go into detail on materials, but without describing the node-based shader networks that are the basis of materials. Here, we go deeper into these node network and how to edit them.
* More advanced animation topics, such as shape keys.
Another important part of the course is that you will work on a visualization based on your own research or other endeavors.
The basis of the course is self-paced training during 10 days, using course materials that we provide (videos and exercises) and with some short online sessions. During the course period you can work on the materials in your own pace. We provide a Discord communication channel with the course teachers that you can use for questions and feedback during the course. We use a small number of online plenary sessions spread over the indicated two-week period, beginning with an introductory webinar of two hours and follow-up feedback sessions. These are used to discuss your projects and make sure you are able to make progress.
Prerequisites

Basic knowledge of Blender: getting around the interface, making and adding geometry, some basics on materials
Basic knowledge of Python
An idea and/or some data for your own project to work on during the course.
You will need to have your own laptop with Blender installed (http://www.blender.org)

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