Opening Ceremony

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.

Announcements

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.

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.

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.

Announcements

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.

Guest lecture: Start Up Nation Karin Gattegno is the VP of Strategic Partnerships at Start-Up Nation Central, building links between Israel – the Start-up Nation, and companies, countries, governments, and entrepreneurs worldwide, connecting them to the Israeli innovation and tech ecosystem. Karin has over 10 years of experience working with High-Tech companies. Prior to joining Start-Up Nation Central, she headed up the Hi-Tech business development in PwC Israel, working with hundreds of start-ups and advising them on various issues including fundraising and M&A's. Before this, Karin worked at Tamir Fishman, a local investment house, as an investment banker in the Corporate Finance department and then as the head of operations and investor relations of DFJ-Tamir Fishman, the local affiliation of Draper Fisher Jurvetson.

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.

Multivariate Classification L1: An Introduction to Machine 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.

Multivariate Classification L2: Deep Learning - Selected Ideas and Concepts (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.

Announcements

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.

Student presentations

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.

Multivariate Classification E1 (Physics Computing)

• Thomas Keck (KIT)

Multivariate Classification E2 (Physics Computing)

• Thomas Keck (KIT)

Announcements

Software Security L3: Web application security, exercise debriefing (Base Technologies)

• Sebastian Lopienski (CERN)

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.

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.

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.

Announcements

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.

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

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.

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.

Announcements

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)

• 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.

Announcements

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 Visualization L1 (Data Technologies)

• Eamonn Maguire

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.

Data Visualization L2 (Data Technologies)

• Eamonn Maguire

Special evening talk

• Ivica Puljak (U.Split)

Books mentioned during the special evening talk by Ivica: **Sean Carroll - “The Big Picture: On the Origins of Life, Meaning, and the Universe Itself”**, OneWorld Publications, 2016 **Steven Pinker - “Enlightenment Now: The Case for Reason, Science, Humanism, and Progress”**, Penguin Books, 2018 **Hans Rosling, Anna, Rosling Roennlund, Ola Rosling - “Factfulness: Ten Reasons We're Wrong About the World-and Why Things Are Better Than You Think”**, Flatiron Books, 2018 **Yuval Noah Harari - “Homo Deus: a Brief History of Tomorrow”**, Harvill Secker, 2015 **Yuval Noah Harari - “21 Lessons for the 21st Century”**, Jonathan Cape, 2018 **Max Tegmark - “Life 3.0: Being Human in the Age of Artificial Intelligence”**, Knoph, 2017 **Thomas L. Friedman - “Thank You for Being Late: An Optimist's Guide to Thriving in the Age of Accelerations”** Macmillan Publisher, 2016

Data Visualization E1 (Data Technologies)

• Eamonn Maguire

Data Visualization E2 (Data Technologies)

• Eamonn Maguire

Announcements

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 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.

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

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.

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.

Announcements

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.

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 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.

Special evening talk

• Francois Fluckiger

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.

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.

Announcements

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.

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).

Guest lecture: FLSH, Innovation and stupidity Speaker: Dov Moran Dov Moran is an Israeli entrepreneur, inventor and investor, best known as the inventor of the USB memory stick, and one of the most prominent Israeli hi-tech leaders in the world. [From Wikipedia]

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

CSC examination

Announcements

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.

Guest lecture: The Israeli cyber landscape dr David Primor is ex CERN PhD student (ATLAS); currently cyber advisor and entrepreneur with extensive cyber governmental background

Guest lecture: Sequence Alignment for Ride Sharing As researchers and developers, we constantly face new problems, and challenge existing solutions to old problems. On beautiful circumstances, solved problems from one domain shed light on new problems from totally different domains. This happened to me while I was researching a Ride Sharing problem of optimally grouping multiple riders on a single taxi - a DNA Sequence Alignment algorithm gave inspiration for a hybrid solution, that turned out to be significantly more efficient than the original one. By sharing with you this story and its resulting algorithm, I hope to entertain your curiosity, spark your creativity, and encourage you to venture into unexpected solution spaces. Speaker: Dalya Gartzman - Algorithms Researcher (Via - On Demand Transit) A mathematician at heart, an algorithmatician in practice. After receiving my MSc. in math from TAU I ventured into data science and algorithms domains, glad to discover that the real world is at least as exciting as the abstract. Currently algorithms researcher at Via - On Demand Transit, applying both my theoretical and practical passions. Founder of Algorithms Israel and co-organizer of PyData Tel Aviv MeetUps.

Graduation and closing ceremony