CERN School of Computing 2024

8 Sept 2024, 15:00 → 21 Sept 2024, 11:00 Europe/Zurich

DESY

Alberto Pace (CERN), Kristina Gunne (CERN), Andrzej Nowicki (CERN), Judith Katzy (DESY, HAMBURG)

Welcome to the 45^th CERN School of Computing (CSC 2024)

The school will take place between the 8^th-21^st September 2024 in Hamburg, Germany. This year’s School is organized in collaboration with the Deutches Elektronen-Synchroton (DESY) and the event will be hosted at the DESY campus in Hamburg.

Academic Programme

The two-week programme will consist around 50 hours of lectures and hands-on exercises, covering three main themes: physics computing, software engineering, and data technologies. Students who pass the final optional exam will receive a diploma from the CSC, as well as ECTS credits.

Other activities

However, it's not all study; the social and sport programme is also a vital part of the School. We will have ample opportunities to explore and experience some of the great cultural, historical and natural attractions of Hamburg and its surroundings.

The application for this school is now closed!

Important dates

• Wednesday 14th of February - applications open
• Monday 15 April (midnight UTC+2 / CEST) - extended deadline for applications
• Monday 29 April - invitations sent to the selected participants
• Wednesday 29 May - registration fee payment deadline
• Sunday 8 September (afternoon/evening) - student arrivals at DESY, Hamburg
• Saturday 21 September (morning) - departure

Who can apply?

The School is aimed at postgraduate (ie. minimum of Bachelor degree or equivalent) students, engineers and scientists with a few years' experience in particle physics, in computing, or in related fields. We welcome applications from all countries and nationalities. Applicants are responsible for ensuring that their registration fee and travel cost is covered by their home institute or employer, or, failing this, themselves. 

 

Sunday, 8 September

15:30 → 19:30 Arrival and registration at DESY

19:30 → 20:30 Dinner DESY

Monday, 9 September

09:30 → 10:30 Opening Ceremony

Speaker: Alberto Pace (CERN)

10:30 → 10:45 Announcements

10:45 → 11:15 Break

11:15 → 11:30 Spare

11:30 → 12:30 Introduction to Physics Computing L1: Hadron Collider Physics

Here we will focus on the physics of particle collisions, theoretical aspects of the standard model of particle physics, its predictive power as well as its shortcomings. Experimental aspects such as collider facilities and modern particle physics experiments as well as example physics questions and corresponding data analyses will be discussed. Furthermore, the compute models with the resulting amount of recorded data and simulated Monte Carlo events will be described.

Speaker: Arnulf Quadt (Georg August Universitaet Goettingen (DE))

12:30 → 13:30 Tools and Techniques L1: Introduction

First, we discuss some of the characteristics of software projects for high energy physics, and some of the issues that arise when people want to contribute to them. We then continue with a brief introduction to software engineering from the perspective of the individual contributor, both as a formal process and how it actually affects what you do. We discuss the examples of unit testing and memory access problems.

Speaker: Prof. Bob Jacobsen

13:30 → 14:30 Lunch

14:30 → 15:30 Tools and Techniques L2: Tools for Collaboration, Software Engineering Across the Project

We continue the track with a discussion of system performance, and what you can (and can't) to affect it. We examine tools to help with that, discussing how they work and how they can mislead. We then discuss source control as a tool for collaboration. Using examples from basic to large and advanced, we show how individual choices can affect the building of large systems.

Speaker: Prof. Bob Jacobsen

15:30 → 16:30 Exercise 1: Tools and Techniques

The exercises provide some direct experience with the tools and techniques described in the Lectures. Teams of two students will work together on examples designed to show the strengths and weaknesses of various tools and approaches. Basic and advanced exercises are available so that students can work at their own level.

The very first step is find somebody to work with and sit down together. The two of you will be working together on these exercises. These have been designed to work best two people (or occasionally three), not with one!
To start the exercises, open the instructions URL (below) in your favorite web browser and follow those instructions.
Please read that index page’s instructions all the way through. We’ve put some general info at the top that you should know, and put some reference links at the bottom that you might later discover you need.

Speakers: Prof. Bob Jacobsen, Giulio Eulisse (CERN)

16:30 → 17:00 Coffee break

17:00 → 18:00 Exercise 2: Tools and Techniques

This is a continuation of the Tools and Techniques exercises

Speakers: Prof. Bob Jacobsen, Giulio Eulisse (CERN)

18:00 → 18:30 Transport to dinner venue (bus)

18:30 → 19:30 Self-presentation: 1 minute per person

19:30 → 21:30 Welcome dinner

21:30 → 21:50 Transport back to DESY

Tuesday, 10 September

08:45 → 09:45 Introduction to Physics Computing L2: Digital Data, Simulation and Reconstruction in Modern Particle Physics Experiments

Here, a focus will be placed on specific detector sub-components and their data readout concepts as well as data reconstruction techniques, simulation techniques and analysis techniques.

Speaker: Arnulf Quadt (Georg August Universitaet Goettingen (DE))

09:45 → 10:45 Software Security L1: Introduction

The first lecture starts with a definition of computer security and an explanation of why it is so difficult to achieve. The lecture highlights the importance of proper threat modelling and risk assessment. It then presents three complementary methods of mitigating threats: protection, detection, reaction; and tries to prove that security through obscurity is not a good choice.

Speaker: Sebastian Lopienski (CERN)

10:45 → 11:00 Announcements

11:00 → 11:30 Coffee break

11:30 → 12:30 Software Design L1: Parallelism in a Modern HEP Data Processing Framework

Even though the miniaturization of transistors on chips continues like predicted by Moore's law, computer hardware starts to face scaling issues, so-called performance 'walls'. Probably, the best known is the 'power wall', which limits clock frequencies. Amongst others, a way of increasing processor performance remains now to integrate many cores in the same chip. At the same time, the upcoming LHC upgrade will increase the required CPU power drastically. Both problems challenge the current way of software design in high energy physics (HEP). Developers in high energy physics are forced to re-think their ways of software design and need to move to massively parallel applications. This lecture will explain the current HEP software design, the hardware and physics issues that need to be tackled, and possible approaches to achieve the required level of parallelization.

Speakers: Andrei Gheata (CERN), Stephan Hageboeck (CERN)

12:30 → 13:30 Software Security L2: Security in different phases of software development

The second lecture addresses the following question: how to create secure software? It introduces the main security principles (like least privilege, or defense in depth) and discusses security in different phases of the software development cycle. The emphasis is put on the implementation part: most common pitfalls and security bugs are listed, followed by advice on best practice for security development.

Speaker: Sebastian Lopienski (CERN)

13:30 → 14:30 Lunch

14:30 → 16:00 Study or sports time

16:00 → 16:30 Coffee break

16:30 → 16:45 Student presentation

16:45 → 17:45 Exercises 1: Software Security

In the practice session, a range of typical security vulnerabilities will be presented. The goal is to learn how they can be exploited (for privilege escalation, data confidentiality compromise etc.), how to correct them, and how to avoid them in the first place! Students will be given small pieces of source code in different programming languages, and will be asked to find vulnerabilities and fix them. The online course documentation will gradually reveal more and more information to help students in this task. Additionally, students will have a chance to try several source code analysis tools, and see how such tools can help them find functionality bugs and security vulnerabilities.

Speaker: Sebastian Lopienski (CERN)

17:45 → 18:45 Exercises 2: Software Security

In the practice session, a range of typical security vulnerabilities will be presented. The goal is to learn how they can be exploited (for privilege escalation, data confidentiality compromise etc.), how to correct them, and how to avoid them in the first place! Students will be given small pieces of source code in different programming languages, and will be asked to find vulnerabilities and fix them. The online course documentation will gradually reveal more and more information to help students in this task. Additionally, students will have a chance to try several source code analysis tools, and see how such tools can help them find functionality bugs and security vulnerabilities.

Speaker: Sebastian Lopienski (CERN)

19:30 → 21:30 Pub Quiz Dinner

Wednesday, 11 September

08:45 → 09:45 Data Science L1: Tools for interactive data exploration

High energy physics has a rich history of interactive exploration of physics data, starting with tools like PAW and ROOT. The explosion of Data Science has created new tools for interactive exploration of large and ad-hoc datasets. This lecture introduces some of these, and shows how they can be used to find new and useful features starting with available data.

Speakers: Prof. Bob Jacobsen, Giulio Eulisse (CERN)

09:45 → 10:45 Software Design L2: Base Concepts of Parallel Programming: A Pragmatic Approach

This and the following lecture will explain the concepts behind various parallelization methodologies. First, a theoretical introduction to threads, thread-safety and concurrent data access will be given. As the recent C++ standards (starting from C++11) provide build-in support for parallel programming, their most commonly used concurrency features will be shown. Finally, concrete solutions for problems specific to concurrent programming will be discussed.

Speakers: Andrei Gheata (CERN), Stephan Hageboeck (CERN)

10:45 → 11:00 Announcements

11:00 → 11:30 Coffee break

11:30 → 12:30 Software Design L3: Understanding, Debugging and Profiling a Complex Multithreaded Application

Dealing with a parallel application is complex. We need to use procedures to rise fences to protect against mistakes, like static analysis tools allowing to find bugs in an automatic way. We also need to use tools to inspect and manipulate the behavior of programs at runtime, like the GDB debugger. Finally, profilers such as igprof can help us understand the performance bottlenecks of an application and get more insight on its efficiency. The objective of this lecture is to become familiar with these tools and be able to apply them in multithreaded programs.

Speakers: Andrei Gheata (CERN), Stephan Hageboeck (CERN)

12:30 → 13:30 Data Science L2: Interactive exploration of non-numeric data

This lecture continues the exploration of interactive tools, using a learn-by-doing approach. It covers approaches for statistical simulation, geographical analysis, and textual data.

Speakers: Prof. Bob Jacobsen, Giulio Eulisse (CERN)

13:30 → 14:30 Lunch

14:30 → 16:00 Study or sports time

16:00 → 16:30 Coffee break

16:30 → 16:45 Student presentation

16:45 → 17:45 Exercise 3: Tools and Techniques

The exercises provide some direct experience with the tools and techniques described in the Lectures. Teams of two students will work together on examples designed to show the strengths and weaknesses of various tools and approaches. Basic and advanced exercises are available so that students can work at their own level.

Speakers: Prof. Bob Jacobsen, Giulio Eulisse (CERN)

17:45 → 18:45 Exercise 3: Software Security

In the practice session, a range of typical security vulnerabilities will be presented. The goal is to learn how they can be exploited (for privilege escalation, data confidentiality compromise etc.), how to correct them, and how to avoid them in the first place! Students will be given small pieces of source code in different programming languages, and will be asked to find vulnerabilities and fix them. The online course documentation will gradually reveal more and more information to help students in this task. Additionally, students will have a chance to try several source code analysis tools, and see how such tools can help them find functionality bugs and security vulnerabilities.

Speaker: Sebastian Lopienski (CERN)

19:30 → 20:30 Dinner DESY

20:45 → 21:45 Quantum Intro Evening Lecture

Thursday, 12 September

08:45 → 09:45 Data Management L1: Setting the scene: Storage technologies, Storage reliability

The lecture presents the various Storage Models, and the supporting management techniques.

The lecture will then go in details on techniques to deliver arbitrary reliability and performance and discuss the solutions for long data preservation and trading between reliability, performances and costs.

Speaker: Alberto Pace (CERN)

09:45 → 10:45 Software Security L3: Web application security, exercise debriefing

This third hour consists of a debriefing of the exercises, and in particular those web-related. Various vulnerabilities typical to web applications (such as Cross-site scripting, SQL injection, cross-site request forgery etc.) are introduced and discussed.

Speaker: Sebastian Lopienski (CERN)

10:45 → 11:00 Announcements

11:00 → 11:30 Coffee break

11:30 → 12:30 Data Management L2: Cryptography, authentication, authorization and accounting 1

This lectures give elements of computer security that are relevant to data management. The lectures address the various cryptographic technologies used in data storage systems to ensure data encryption, integrity, confidentiality and access control. The Public Key infrastructure standard will be described as an example.

Speaker: Alberto Pace (CERN)

12:30 → 13:30 Exercise 4:

Speakers: Prof. Bob Jacobsen, Giulio Eulisse (CERN)

13:30 → 14:30 Lunch

14:30 → 14:45 Photo

14:45 → 15:45 Transport to Hamburg

15:45 → 19:00 Hamburg hafenrundfart visit excursion

19:00 → 19:30 Transport to restaurant by train

19:30 → 21:30 Pizza Dinner

21:30 → 21:50 Return to DESY or evening out...

Friday, 13 September

08:45 → 09:45 Software Design L4: Patterns for Parallel Software Development

This lecture will present a set of common patterns in parallel programming. The sequential origin of these patterns will be discussed, as well as the restrictions that they impose. A particularly successful combination of patterns, Map-Reduce, will be described in detail and examples of its everyday use at large scale will be given. On the other hand, it will be shown how high-level features like C++ lambdas, the TBB library or the Spark framework can help get started with the aforementioned parallel patterns.

Speakers: Andrei Gheata (CERN), Stephan Hageboeck (CERN)

09:45 → 10:45 Data Management L3: Cryptography, authentication, authorization and accounting 2

This lecture will continue the discussion on various authentication technologies and then move to authorization. Accounting will also be addressed.

Speaker: Alberto Pace (CERN)

10:45 → 11:00 Announcements

11:00 → 11:30 Coffee break

11:30 → 12:30 Exercises 1: Software Design

The exercises will cover the topics of lectures 1 to 4 at a hands-on basis, based on C++11, TBB and Spark. It covers examples for the new C++11 functionality related to threads and thread safety. In addition, there will be examples for concurrent access to data, lock and lock-free data structures, and task based programming.  Finally, there will be an exercise to practise the Map-Reduce pattern by using the Spark parallel data processing framework.

Speakers: Andrei Gheata (CERN), Stephan Hageboeck (CERN)

12:30 → 13:30 Exercises 2: Software Design

The exercises will cover the topics of lectures 1 to 4 at a hands-on basis, based on C++11, TBB and Spark. It covers examples for the new C++11 functionality related to threads and thread safety. In addition, there will be examples for concurrent access to data, lock and lock-free data structures, and task based programming.  Finally, there will be an exercise to practise the Map-Reduce pattern by using the Spark parallel data processing framework.

Speakers: Andrei Gheata (CERN), Stephan Hageboeck (CERN)

13:30 → 14:30 Lunch

14:30 → 16:00 Study or sports time

16:00 → 16:30 Coffee break

16:30 → 16:45 Student presentation

16:45 → 17:45 Exercise 3: Software Design

This is a continuation of the Software Design exercises.

Speakers: Andrei Gheata (CERN), Stephan Hageboeck (CERN)

17:45 → 18:45 Exercise 4: Software Design

This is a continuation of the Software Design exercises.

Speakers: Andrei Gheata (CERN), Stephan Hageboeck (CERN)

19:30 → 20:30 Dinner DESY

Saturday, 14 September

08:45 → 12:45 Airbus Visit or free time

12:45 → 13:30 Lunch

13:30 → 17:30 Airbus Visit or free time

17:30 → 19:30 Free time

19:30 → 20:30 Dinner DESY

Sunday, 15 September

10:00 → 10:15 Announcements

10:15 → 11:15 Data Analysis L1: Introduction

In this lecture we will explain what are the main goals of data analysis. We will introduce statistics as the powerful mathematical tool for data analysis. We will define probability and random variables as key concepts in statistics for data analysis.

Speaker: Toni Sculac (University of Split Faculty of Science (HR))

11:15 → 12:15 Data Analysis L2: Probability density functions and Monte Carlo methods

In this lecture we will discuss what probability density functions (PDFs) are, and what are their main properties. We will mention the most important PDFs and their properties both for discrete and continuous random variables. The importance of the Gaussian distribution lies in the Central Limit Theorem that will be discussed. Finally, we will discuss the concept of Monte Carlo methods and their usage in High Energy Physics and Data Analysis.

Speaker: Toni Sculac (University of Split Faculty of Science (HR))

12:15 → 18:15 Sunday Excursion (incl lunch)

19:30 → 20:30 Dinner DESY

Monday, 16 September

08:45 → 09:45 Data Analysis L3: Parameter estimation and confidence intervals

In this lecture we will introduce the concept of test statistics and estimators. We will explain what are the key properties of a good estimator and how to obtain it using the Maximum Likelihood and Least Squares methods. We will define confidence intervals and make a strong statement on their statistical interpretation when discussing scientific results. Finally, we will learn how to derive confidence intervals for the Maximum likelihood and Least Squares methods.

Speaker: Toni Sculac (University of Split Faculty of Science (HR))

09:45 → 10:45 Introduction to Machine Learning 1

Speaker: Judith Katzy (DESY, HAMBURG)

10:45 → 11:00 Announcements

11:00 → 11:30 Coffee break

11:30 → 12:30 Introduction to machine learning 2

Speaker: Judith Katzy (DESY, HAMBURG)

12:30 → 13:30 Sustainable computing

Speaker: Ana Lucia Varbanescu (University of Twente)

13:30 → 14:30 Lunch

14:30 → 16:00 Study or sports time

16:00 → 16:30 Coffee break

16:30 → 16:45 Student presentation

16:45 → 17:45 Exercises 1: Data Analysis

There will be 3 sets of exercises covering basic properties of PDFs and Monte Carlo generators, Maximum Likelihood fit, and Hypothesis testing. Students will be given realistic but simplified problems where key concepts from statistics need to be applied in order to provide scientific interpretation of data. Each set of exercises consists of 5 problems that will help guide the student. Data is provided in a simple text file and can be analysed with any programming language that offers libraries for statistical analysis (Python or C++ are recommended).

Speaker: Toni Sculac (University of Split Faculty of Science (HR))

17:45 → 18:45 Exercises 2: Data Analysis

There will be 3 sets of exercises covering basic properties of PDFs and Monte Carlo generators, Maximum Likelihood fit, and Hypothesis testing. Students will be given realistic but simplified problems where key concepts from statistics need to be applied in order to provide scientific interpretation of data. Each set of exercises consists of 5 problems that will help guide the student. Data is provided in a simple text file and can be analysed with any programming language that offers libraries for statistical analysis (Python or C++ are recommended).

Speaker: Toni Sculac (University of Split Faculty of Science (HR))

19:30 → 20:30 Dinner DESY

Tuesday, 17 September

08:45 → 09:45 Introduction to Machine Learning 3

Speaker: Judith Katzy (DESY, HAMBURG)

09:45 → 10:45 Data Analysis L4: Hypothesis testing and p-value

We will learn about the hypothesis testing procedure and all of its key concepts. We will discuss how to choose a critical region and learn about errors of first and second kind. We will learn the importance of a blinded analysis and understand all the needed steps before looking at the data. Finally, we will discuss when can we announce a discovery in science and the concept of a p-value.

Speaker: Toni Sculac (University of Split Faculty of Science (HR))

10:45 → 11:00 Announcements

11:00 → 11:30 Coffee break

11:30 → 12:30 Sustainable computing 2

Speaker: Ana Lucia Varbanescu (University of Twente)

12:30 → 13:30 Data Management L4: Distributed Hash Tables, Data Replication, Caching, Monitoring, Alarms and Quota 1

This lecture describes the various possible technologies used to implement distributed hash tables, data workflows and complex data transfer processes. It also discusses problems with data caching and Garbage Collection to conclude on monitoring and quota enforcement.

Speaker: Alberto Pace (CERN)

13:30 → 14:30 Lunch

14:30 → 16:00 Study or sports time

16:00 → 16:30 Coffee break

16:30 → 16:45 Student presentation

16:45 → 17:45 Exercice 1: Data Technologies

The first part of hands-on exercises aims to improve understanding of basic parameters in IO systems:
• network and media latency
• access patterns
• OS caching
• bottlenecks and optimization strategies for local and remote data access.
Few essential Linux tools will be introduced to monitor and measure IO performance avoiding bias introduced by OS caching. Students will experience and measure the impact of latency and access patterns on IO performance.
The second part covers the concept of parallelism and redundancy in storage system. We will apply the technology of Cloud storage systems to store and retrieve files in our local desktop cluster using a distributed hash table to locate files or file fragments and a REST interface to do GET, PUT or DELETE operations on these.
The exercises conclude with the implementation and performance tuning of a RAID verification algorithm.

Speaker: Andreas Joachim Peters (CERN)

17:45 → 18:45 Exercises 2: Data Technologies

The first part of hands-on exercises aims to improve understanding of basic parameters in IO systems:
• network and media latency
• access patterns
• OS caching
• bottlenecks and optimization strategies for local and remote data access.
Few essential Linux tools will be introduced to monitor and measure IO performance avoiding bias introduced by OS caching. Students will experience and measure the impact of latency and access patterns on IO performance.
The second part covers the concept of parallelism and redundancy in storage system. We will apply the technology of Cloud storage systems to store and retrieve files in our local desktop cluster using a distributed hash table to locate files or file fragments and a REST interface to do GET, PUT or DELETE operations on these.
The exercises conclude with the implementation and performance tuning of a RAID verification algorithm.

Speaker: Andreas Joachim Peters (CERN)

19:30 → 20:30 Dinner DESY

Wednesday, 18 September

08:45 → 09:45 Introduction to Machine Learning 4

Speaker: Judith Katzy (DESY, HAMBURG)

09:45 → 10:45 Data Analysis L5

Speaker: Toni Sculac (University of Split Faculty of Science (HR))

10:45 → 11:00 Announcements

11:00 → 11:30 Coffee break

11:30 → 12:30 Exercises 3: Data Technologies

This is a continuation of the Data Technologies exercises.

Speaker: Andreas Joachim Peters (CERN)

12:30 → 13:30 Exercises 4: Data Technologies

This is a continuation of the Data Technologies exercises.

Speaker: Andreas Joachim Peters (CERN)

13:30 → 14:30 Lunch

14:30 → 16:00 Study or sports time

16:00 → 16:30 Coffee break

16:30 → 16:45 Student presentation

16:45 → 17:45 Machine Learning exercise 1

Speaker: Peter Steinbach

17:45 → 18:45 Machine Learning exercises 2

Speaker: Peter Steinbach

19:00 → 21:00 CERN, Computing and talent aquisition

https://indico.cern.ch/event/1417998/overview

Speakers: Barbara Binder (CERN), Heather Gray (UC Berkeley/LBNL)

21:00 → 22:00 Networking dinner

Thursday, 19 September

08:45 → 09:45 Introduction to Machine Learning 5

Speaker: Judith Katzy (DESY, HAMBURG)

09:45 → 10:45 Machine Learning exercise 3

Speaker: Peter Steinbach

10:45 → 11:00 Announcements

11:00 → 11:30 Coffee break

11:30 → 12:30 Exercise 3: Data Analysis

This is a continuation of the Data Analysis exercises

Speaker: Toni Sculac (University of Split Faculty of Science (HR))

12:30 → 13:30 Exercise 4: Data Analysis

This is a continuation of the Data Analysis exercises.

Speaker: Toni Sculac (University of Split Faculty of Science (HR))

13:30 → 14:30 Lunch

14:30 → 16:00 Study or sports time

16:00 → 16:30 Coffee break

16:30 → 17:30 Machine Learning exercise 4

Speaker: Peter Steinbach

17:30 → 19:00 Spare / DESY visit

19:30 → 20:30 Dinner DESY

Friday, 20 September

09:30 → 11:00 Exam

11:00 → 11:30 Coffee break

11:30 → 13:30 Traditional football match

13:30 → 14:30 Lunch

14:30 → 16:00 Graduation ceremony

16:00 → 18:30 Free time

18:30 → 19:30 Transport to dinner venue

19:30 → 22:30 Closing Dinner Party

Saturday, 21 September

08:00 → 11:00 Breakfast and check out