Introduction to Physics Computing L1: Hadron Collider Physics (Physics Computing)

• Arnulf Quadt (University of Göttingen)

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.

Tools and Techniques L1: Introduction (Physics Computing)

• Bob Jacobsen (LBNL)

To start, 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. This forms the framework for the Software Technologies Track. 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. The lecture discusses several categories of tools & techniques you can use to make yourself more productive and effective. Continuous testing and documentation has proven to be important in producing high quality work, but it's often difficult to do; we discuss some available approaches. Many problems require specific tools and techniques to solve them effectively: We discuss the examples of performance tuning and memory access problems.

Tools and Techniques L2: Tools for Collaboration, Software Engineering Across the Project (Physics Computing)

• Bob Jacobsen (LBNL)

HEP software is built by huge teams. How can this be done effectively, while still giving people satisfying tasks to perform? Large systems are a hard problem, and this lecture focuses on the current techniques for dealing with it. Use of central source control (e.g. SVN) has become routine, so we build on that understanding to discuss distributed systems like Git. We then discuss the larger area of release & distributing via a package versioning system (e.g. SVN and CMT) vs. a distributed build system (e.g. Git and CMake). Now that we've covered both individual and group work, we go back to the software engineering topics of the first lecture to see how these fit together. How does our individual work affect the ability of the entire project to proceed? What are tools and techniques that will improve both our individual work, and out contributions to the whole? We close with a summary of observations.

Updates

Tools and Techniques E1 (Physics Computing)

• Bob Jacobsen (LBNL)

The first three exercises provide some direct experience with the tools and techniques described in Lectures 1 and 2. Teams of two students will work together on through examples designed to show the strengths and weaknesses of various tools and approaches. This will be followed by small projects for additional development experience.

Tools and Techniques E2 (Physics Computing)

• Bob Jacobsen (LBNL)

The first three exercises provide some direct experience with the tools and techniques described in Lectures 1 and 2. Teams of two students will work together on through examples designed to show the strengths and weaknesses of various tools and approaches. This will be followed by small projects for additional development experience.

Introduction to Physics Computing L2: Digital Data, Simulation and Reconstruction in Modern Particle Physics Experiments (Physics Computing)

• Arnulf Quadt (University of Göttingen)

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.

Updates

Software Security L1: Introduction (Base Technologies)

• Sebastian Lopienski (CERN)

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.

Computer Architecture & Performance Tuning L1: Hardware vs. software vs. you – who’s the boss? (Base Technologies)

• Andrzej Nowak

Considering the rise of complex many-core processors, a sufficient understanding of their architecture and of the applicable performance tuning opportunities has become an indispensable element of software development. In this lecture, the anatomy of a modern PC (x86) server is discussed, with a particular focus on the CPU. Multiple resources and strategies to achieve optimal performance exist, both in hardware and in software – but how to take control of them? Non-x86 architectures of growing importance, such as ARM and NVIDIA, will also be briefly covered. The lecture will be supported by relevant examples from the physics domain.

Tools and Techniques E3 (Physics Computing)

• Bob Jacobsen (LBNL)

The first three exercises provide some direct experience with the tools and techniques described in Lectures 1 and 2. Teams of two students will work together on through examples designed to show the strengths and weaknesses of various tools and approaches. This will be followed by small projects for additional development experience.

Tools and Techniques E4 (Physics Computing)

• Bob Jacobsen (LBNL)

After the two-person teams acquire some experience with the development and release tools, we will group projects to demonstrate some of the real-world issues discussed in the lecture. Groups of two teams will first work together to create a functional release from individual sub-projects at various stages of completion to show the strengths and weaknesses of test and release tools. This is followed by a larger scale exercise with groups of teams.

Tools and Techniques E5 (Physics Computing)

• Bob Jacobsen (LBNL)

After the two-person teams acquire some experience with the development and release tools, we will group projects to demonstrate some of the real-world issues discussed in the lecture. Groups of two teams will first work together to create a functional release from individual sub-projects at various stages of completion to show the strengths and weaknesses of test and release tools. This is followed by a larger scale exercise with groups of teams.

Data Technologies L1: Setting the scene: Storage technologies (Data Technologies)

• Alberto Pace (CERN)

The lecture presents the various Storage Models, and the supporting management techniques including Name Servers and interfaces for Data Management. Storage Reliability and performance The lecture will also discuss the various solution to ensure long data preservation and reliability with the consequences on performance, including when using Peer to Peer Storage and data transfers.

Updates

Computer Architecture & Performance Tuning L2: Architectural Details and Performance Studies (Base Technologies)

• Andrzej Nowak

Although by using various tools we are often able to get a generous peek both inside hardware and software, drawing meaningful high-level conclusions is not always straightforward. More challenges come from accelerators and co-processors, where different computing paradigms take precedence, such as extreme data parallelism, different math capabilities, the importance of special languages as well as memory size and topology changes. The objective of this lecture is to bring the audience closer to "where it matters" in modern computing systems, and to identify important paths for high performance.

Software Security L2: Security in different phases of software development (Base Technologies)

• Sebastian Lopienski (CERN)

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.

Software Security E1 (Base Technologies)

• Sebastian Lopienski (CERN)

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.

Software Security E2 (Base Technologies)

• Sebastian Lopienski (CERN)

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.

Software Security E3 (Base Technologies)

• Sebastian Lopienski (CERN)

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.

Data Technologies L2: Cryptography, authentication authorization and accounting 1 (Data Technologies)

• Alberto Pace (CERN)

These lectures give elements of computer security that are relevant to data management. The lectures address the various technologies used in data storage systems to ensure data encryption, integrity, confidentiality and access control

Updates

Data Technologies L3: Cryptography, authentication authorization and accounting 2 (Data Technologies)

• Alberto Pace (CERN)

These lectures give elements of computer security that are relevant to data management. The lectures address the various technologies used in data storage systems to ensure data encryption, integrity, confidentiality and access control.

Software Design L1: Physics and Computing Challenges to Experiment Software (Base Technologies)

• Enric Tejedor (CERN)

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.

Data Technologies L4: Additional component for Data Replication, Caching, Monitoring, Alarms and Quota 1 (Data Technologies)

• Alberto Pace (CERN)

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

Updates

Data Technologies L5: Additional component for Data Replication, Caching, Monitoring, Alarms and Quota 2 (Data Technologies)

• Alberto Pace (CERN)

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

Software Design L2: Concurrent Programming in Action 1 (Base Technologies)

• Danilo Piparo (CERN)

This and the following lecture will explain the concepts behind various parallelization methodologies. First, a theoretical introduction into threads, thread-safety and concurrent data access will be given. As the new C++ standard (C++11) now provides build-in support for parallel programming, the new features of this standard will be shown. Finally, concrete solutions for the theoretical problems will be discussed.

Computer Architecture & Performance Tuning E1 (Base Technologies)

• Andrzej Nowak

The aim of the exercises in this series is to give the attendees a practical introduction to performance oriented programming on Linux. Advanced tools will be used during the course, enabling the participants to discover how the interaction of the code and the hardware influences performance. The participants will also be given the task of correlating performance figures with certain programming decisions. In addition, the participants will understand the limits of performance optimization and the ways to establish at which point inside those limits their workload is placed. The exercises will be supported by demonstrating real world problems in production environments, including multi-threaded examples.

Computer Architecture & Performance Tuning E2 (Base Technologies)

• Andrzej Nowak

The aim of the exercises in this series is to give the attendees a practical introduction to performance oriented programming on Linux. Advanced tools will be used during the course, enabling the participants to discover how the interaction of the code and the hardware influences performance. The participants will also be given the task of correlating performance figures with certain programming decisions. In addition, the participants will understand the limits of performance optimization and the ways to establish at which point inside those limits their workload is placed. The exercises will be supported by demonstrating real world problems in production environments, including multi-threaded examples.

Computer Architecture & Performance Tuning E3 (Base Technologies)

• Andrzej Nowak

Data Visualizations L1

• Eamonn Maguire

Data Visualizations L2

• Eamonn Maguire

Updates

Data Visualizations E1

• Eamonn Maguire

Data Analysis L1: Introduction to data analysis and Monte Carlo method (Physics Computing)

• Ivica Puljak (FESB)

First lecture in Data Analysis series discuss graphical techniques used in exploratory data analysis, gives an introduction to concept of probability, and descriptive statistics summarizing the basic features of the data gathered from experiments. Monte Carlo method is introduced and explained with examples from engineering and high energy physics.

Updates

Software Design L3: Concurrent Programming in Action 2 (Base Technologies)

• Danilo Piparo (CERN)

The focus of this lecture lies in concurrent programming based on the 'task model', using TBB as implementation library. There will be a deeper look into concurrent data access and lock and lock-free data formats. Using the learned concepts, we will look again at the data challenges from lecture 1 and see, how a future-proof software design might look like.

Software Design L4: Patterns for Parallel Software Development (Base Technologies)

• Enric Tejedor (CERN)

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.

Software Design E1 (Base Technologies)

• Enric Tejedor (CERN)
• Danilo Piparo (CERN)

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.

Software Design E2 (Base Technologies)

• Enric Tejedor (CERN)
• Danilo Piparo (CERN)

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.

Software Design E3 (Base Technologies)

• Danilo Piparo (CERN)
• Enric Tejedor (CERN)

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.

Data Analysis L2: Distributions and estimators (Physics Computing)

• Ivica Puljak (FESB)

In this lecture commonly used probability distributions are introduced with basic properties and few examples. Parameter estimation with maximum likelihood and least-squared methods is explained.

Updates

Networking Performance L1: Internet Quality of Service options (Base Technologies)

• Francois Fluckiger

This first topic discusses the status and the option to master and improve on the Quality of Service of the Internet. Indeed, modern scientific applications require fast transfers high-bit rate connections, as well as network predictability and high availability. On the other hand, the Internet historical technology is not naturally best suited to deterministic behaviour. This lecture explains the technical challenges and the range of options available to improve QoS guarantees in Internet-based networks.

Data Analysis L3: Confidence intervals (Physics Computing)

• Ivica Puljak (FESB)

Determining the errors on the parameters, which is equivalent to the confidence interval estimation is shown with specific examples on maximum likelihood and least-squared methods in one and more than one dimension. Uncertainties in physics and error propagation are also discussed.

Data Analysis E1: Monte Carlo method and Fitting with Root (Physics Computing)

• Ivica Puljak (FESB)

• Generating random numbers • Monte-Carlo toy experiments • Modeling signal and background.  • Fitting with ROOT packages (finding peaks).

Data Analysis E2: Confidence interval (Physics Computing)

• Ivica Puljak (FESB)

• Finding errors on fit parameters  • Extracting confidence intervals

Data Analysis E3: Hypothesis testing (Physics Computing)

• Ivica Puljak (FESB)

• Finding p-value • Converting p-values to significance • Low count experiments and hypothesis testing

Special evening talk

• Francois Fluckiger

Multivariate Classification L1: Traditional Techniques (Physics Computing)

• Thomas Keck (KIT)

The aim of this lecture is to make the audience aware of multivariate classification (MVC) methods. Commonly used classification methods are introduced and the fundamental concepts behind them are explained. In particular boosted decision trees and artificial neural networks are discussed in detail.

Updates

Multivariate Classification L2: Deep Learning (Physics Computing)

• Thomas Keck (KIT)

The aim of this lecture is to make the audience aware of multivariate classification (MVC) methods. Commonly used classification methods are introduced and the fundamental concepts behind them are explained. In particular boosted decision trees and artificial neural networks are discussed in detail.

Networking Performance L2: Multimedia over the Internet (Base Technologies)

• Francois Fluckiger

The Internet is not only a network of computer resources but also a network of people cooperating to use these resources, in particular in professional scientific environment. Part of the collaborative tools scientists are increasingly using include audio and video systems. They place new challenging requirements on the networking systems. The class discusses these requirements and their consequences on the end-systems as well as within the underlying network.

Data Technologies E1 (Data Technologies)

• Andreas Peters (CERN)

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.

Data Technologies E2 (Data Technologies)

• Andreas Peters (CERN)

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.

Data Technologies E3 (Data Technologies)

• Andreas Peters (CERN)

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.

Data Analysis L4: Statistical tests (Physics Computing)

• Ivica Puljak (FESB)

Hypothesis testing is introduced with examples of goodness-of-fit tests and the most recent examples from high energy physics. Particular emphasis is given on the p-values and when we claim the discoveries.

Updates

Multivariate Classification E1 (Physics Computing)

• Thomas Keck (KIT)

Multivariate Classification E2 (Physics Computing)

• Thomas Keck (KIT)

Data Technologies E4 (Data Technologies)

• Andreas Peters (CERN)

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.

Data Technologies E5 (Data Technologies)

• Andreas Peters (CERN)

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.

Guest lecture: Software testing and its automation

• Alessandra Gorla (IMDEA)

Software testing is a core activity of any project involving software development. The goal of testing is to detect as many faults as possible during the development process such that they could be fixed before deployment. This lecture will cover some of the basic concepts of software testing and its automation: how to properly use a testing infrastructure on a continuous integration environment, how to write test cases using black and white box techniques, how to effectively maintain a test suite in a rapidly evolving project, and how to make test suites effective at catching real faults.

Updates

Guest lecture: Codes, shuffles and cards

• Fernando Blasco (UPM)

There are a lot of card magic tricks that are based in mathematical properties. There are several tricks related to binary system of numbering but it's not the only example relating computing and magic: even there is a PhD Thesis that studied the relationship between shuffles and dynamic computer memories. Error detecting codes, divisibility properties, algorithms and Gilbreath's principle are just some examples that underlie in some magic tricks. In this talk we present some of those effects as well as the mathematics they are based on. We also give clues for the people who like a deeper knowledge on this subject. The talk is intended as an interactive talk where attendees participate in "the show".

Guest lecture: Space environment and space mission design

• Gustavo Alonso (UPM)

How the environment in outer space and in different extra-terrestrial bodies influences and conditions the design of space missions, with some practical examples of actual missions.

Presentations by Students

• Wojciech Ziolek (CERN)
• Ulf Bobson Severin Tigerstedt (Helsinki Institute of Physics (FI))
• Davide Pedretti (Universita e INFN, Legnaro (IT))
• Antoni Shtipliyski (University of Manchester (GB))
• Alexei Sytov (Universita di Ferrara & INFN (IT))
• Marzieh Bahmani (Polish Academy of Sciences (PL))
• Christian Bourjau (University of Copenhagen (DK))
• Stefan-Gabriel Chitic (CERN)
• Vojtech Simetka (CERN)
• Lennaert Bel (Nikhef National institute for subatomic physics (NL))

Graduation ceremony

• Sebastian Lopienski (CERN)

Closing session