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CERN School of Computing 2014

24 August 2014 to 6 September 2014
University of Minho and LIP
Europe/Lisbon timezone

Contribution List

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  1. 55. Intervention of the Rector of University of Minho
    Antonio Cunha
    25/08/2014, 09:15
  2. 59. Intervention of the President of LIP (Laboratorio Experimental de Fisica de Particulas)
    Jose Mariano Gago
    25/08/2014, 09:25
  3. 61. Intervention of the Portuguese National Science Foundation, FCT (on behalf of the Ministry of Education and Science),
    Miguel Seabra
    25/08/2014, 09:35
  4. 62. CERN, 60 years of Science for Peace
    Rolf Heuer (CERN General Director)
    25/08/2014, 09:45
  5. 63. Challenges of the Computing Infrastructures for Scientific Research of the Coming Years
    Frederic Hemmer (CERN, IT Department Head)
    25/08/2014, 11:00
  6. 56. The Cern School of Computing
    Alberto Pace (CERN, Director of CSC)
    25/08/2014, 11:15
  7. 60. Introduction to Physics computing
    Arnulf Quadt (Georg-August-Universitaet Goettingen (DE))
    25/08/2014, 11:30
  8. 4. Tools and Techniques - Lecture 1
    Robert Jacobsen (Lawrence Berkeley National Laboratory (LBNL))
    25/08/2014, 14:00
    Introduction to the Track; Tools You Can Use 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 discuss several categories of tools & techniques you can use to make yourself more productive and effective. Continuous...
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  9. 5. Tools and Techniques - Lecture 2
    Robert Jacobsen (Lawrence Berkeley National Laboratory (LBNL))
    25/08/2014, 15:00
    Tools for Collaboration HEP software is built by huge teams. How can this be done effectively, while still giving people satisfying tasks to perform? This lecture discusses some of the technical approaches used. Source control (e.g. SVN, Git) tools are becoming common. We discuss the different ways they can be used with their advantages and disadvantages. We then address the larger area of...
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  10. 1. Presentation of the School
    Alberto Pace (CERN)
    25/08/2014, 16:00
  11. 0. Tools and Techniques - Exercise 1
    Robert Jacobsen (Lawrence Berkeley National Laboratory (LBNL))
    25/08/2014, 16:50
    The first exercises provide some direct experience with the individual tools and techniques described in Lectures 1 and 2. Teams of two students will work together to update existing applications, working 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. Exercise 3...
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  12. 6. Tools and Techniques - Exercise 2
    Robert Jacobsen (Lawrence Berkeley National Laboratory (LBNL))
    25/08/2014, 17:50
    The first exercises provide some direct experience with the individual tools and techniques described in Lectures 1 and 2. Teams of two students will work together to update existing applications, working 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. Exercise 3...
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  13. 8. Introduction to Physics Computing - Lecture 2
    Arnulf Quadt (Georg-August-Universitaet Goettingen (DE))
    26/08/2014, 08:45
  14. 9. Computer Architecture & Perf. Tuning - Lecture 1
    Mr Sverre Jarp (CERN)
    26/08/2014, 09:45
    Understanding scalable hardware The lecture describes the hardware architecture of a modern x86_64 PC server. Architectures from other companies, such as Nvidia and ARM, will also be mentioned. Acceleration opportunities (but also bottlenecks) in the architecture will be covered in detail with an aim to give the students a good understanding of what resources are available from a hardware...
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  15. 10. Computer Architecture & Perf. Tuning - Lecture 2
    Andrzej Nowak (CERN)
    26/08/2014, 11:30
    "Architectural Details and Performance Studies" Considering the rise of complex many-core processors, a sufficient understanding of their architecture and of the relevant performance tuning opportunities has become an indispensable element of software development. Although by using various tools we are often able to get a generous peek both inside the hardware and software, drawing high-level...
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  16. 7. Tools and Techniques - Exercise 3
    Robert Jacobsen (Lawrence Berkeley National Laboratory (LBNL))
    26/08/2014, 16:15
    The first exercises provide some direct experience with the individual tools and techniques described in Lectures 1 and 2. Teams of two students will work together to update existing applications, working 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. Exercise 3...
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  17. 11. Tools and Techniques - Exercise 4
    Robert Jacobsen (Lawrence Berkeley National Laboratory (LBNL))
    26/08/2014, 17:15
    After the two-person teams acquire additional experience with the code management and release tools in exercise 4 and 5, in exercise 6 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...
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  18. 12. Tools and Techniques - Exercise 5
    Robert Jacobsen (Lawrence Berkeley National Laboratory (LBNL))
    26/08/2014, 18:15
    After the two-person teams acquire additional experience with the code management and release tools in exercise 4 and 5, in exercise 6 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...
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  19. 13. Tools and Techniques - Exercise 6
    Robert Jacobsen (Lawrence Berkeley National Laboratory (LBNL))
    26/08/2014, 19:15
    After the two-person teams acquire additional experience with the code management and release tools in exercise 4 and 5, in exercise 6 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...
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  20. 14. Software Design in the Many-Cores era - Lecture 1
    Benedikt Hegner (CERN), Danilo Piparo (CERN)
    27/08/2014, 08:45
    Outfitting a Modern HEP Data Processing Framework for Concurrency 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...
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  21. 15. Secure Software - Lecture 1
    Sebastian Lopienski (CERN)
    27/08/2014, 09:45
  22. 16. Secure Software - Lecture 2
    Sebastian Lopienski (CERN)
    27/08/2014, 11:30
  23. 17. Secure Software - Exercise 1
    Dr Giuseppe Lo Presti (CERN), Sebastian Lopienski (CERN)
    27/08/2014, 16:30
  24. 18. Secure Software - Exercise 2
    Dr Giuseppe Lo Presti (CERN), Sebastian Lopienski (CERN)
    27/08/2014, 17:35
  25. 19. Secure Software - Exercise 3
    Dr Giuseppe Lo Presti (CERN), Sebastian Lopienski (CERN)
    27/08/2014, 18:40
  26. 20. Software Design in the Many-Cores era - Lecture 2
    Benedikt Hegner (CERN), Danilo Piparo (CERN)
    28/08/2014, 08:45
    Base Concepts of Parallel Programming: A Pragmatic Approach This lecture will explain the main concepts behind concurrent programming. First, a theoretical introduction into threads will be given. As the new C++ standard (C++11) now provides built-in support for parallel programming, the new features of this standard will be shown. The second part of this lecture builds thread-safety and...
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  27. 21. Software Design in the Many-Cores era - Lecture 3
    Benedikt Hegner (CERN), Danilo Piparo (CERN)
    28/08/2014, 09:45
    Development Patterns for Parallel Software Development The focus of this lecture lies on repeating a few design patterns of sequential software. It then discusses under which conditions these can be transformed into parallel design patterns. It discusses how different level of constrains affect the scaling of the parallel patterns shown.
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  28. 22. Secure Software - Lecture 3
    Sebastian Lopienski (CERN)
    28/08/2014, 11:30
    Web App. Security Debriefing
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  29. 23. Software Design in the Many-Cores era - Lecture 4
    Benedikt Hegner (CERN), Danilo Piparo (CERN)
    29/08/2014, 08:45
    Understanding, Debugging and Profiling a Complex Multithreaded Application Writing thread-safe code is a complex problem and difficult to master. This lecture explains basic tools and techniques assisting you in parallel software development. Firstly, we will show basic examples and tools for static code analysis. Then we will have a look at how to understand and debug a multithreaded...
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  30. 24. Software Design in Many-core area - Exercise 2
    Benedikt Hegner (CERN), Danilo Piparo (CERN)
    29/08/2014, 09:45
  31. 25. Software Design in Many-core area - Exercise 3
    Benedikt Hegner (CERN), Danilo Piparo (CERN)
    29/08/2014, 11:30
  32. 26. Software Design in Many-core area - Exercise 3
    Benedikt Hegner (DESY), Danilo Piparo (CERN)
    29/08/2014, 16:30
  33. 27. Computer Architecture & Perf. Tuning - Exercise 1
    Andrzej Nowak (CERN), Mr Sverre Jarp (CERN)
    29/08/2014, 17:35
  34. 28. Computer Architecture & Perf. Tuning - Exercise 2
    Andrzej Nowak (CERN), Mr Sverre Jarp (CERN)
    29/08/2014, 18:40
  35. 29. Data Analysis - Lecture 1
    Ivica Puljak (University of Split (HR))
    30/08/2014, 08:45
  36. 30. Data Analysis - Lecture 2
    Ivica Puljak (Technical University of Split FESB)
    30/08/2014, 09:45
  37. 31. Data Analysis - Lecture 3
    Ivica Puljak (Technical University of Split FESB)
    30/08/2014, 11:30
  38. 32. Data Technologies - Lecture 1
    Alberto Pace (CERN)
    01/09/2014, 08:45
  39. 33. Data Technologies - Lecture 2
    Alberto Pace (CERN)
    01/09/2014, 09:45
  40. 64. Data Analysis - Lecture 4
    Ivica Puljak (Technical University of Split FESB)
    01/09/2014, 11:30
  41. 35. Data Analysis - Exercise 1
    Ivica Puljak (Technical University of Split FESB)
    01/09/2014, 16:30
  42. 36. Data Analysis - Exercise 2
    Ivica Puljak (Technical University of Split FESB)
    01/09/2014, 17:35
  43. 37. Data Analysis - Exercise 3
    Ivica Puljak (Technical University of Split FESB)
    01/09/2014, 18:40
  44. 38. Data Technologies - Lecture 3
    Alberto Pace (CERN)
    02/09/2014, 08:45
  45. 39. Data Technologies - Lecture 4
    Alberto Pace (CERN)
    02/09/2014, 09:45
  46. 65. Spotlight on Big Data/Technologies -... inspired by nature, society, physics and mathematics
    Mr Andreas Joachim Peters (CERN)
    02/09/2014, 11:30
    A look behind Big Data and Cloud technology and into the future of money and civilization archiving tools.
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  47. 41. Data Technologies - Exercise 1
    Alberto Pace (CERN), Mr Andreas Joachim Peters (CERN)
    02/09/2014, 16:30
  48. 42. Data Technologies - Exercise 2
    Alberto Pace (CERN), Mr Andreas Joachim Peters (CERN)
    02/09/2014, 17:35
  49. 43. Data Technologies - Exercise 3
    Alberto Pace (CERN), Mr Andreas Joachim Peters (CERN)
    02/09/2014, 18:40
  50. 44. Data Analysis - Lecture 5
    Ivica Puljak (Technical University of Split FESB)
    03/09/2014, 08:45
  51. 45. Data Analysis - Lecture 6
    Ivica Puljak (Technical University of Split FESB)
    03/09/2014, 09:45
  52. 46. Data Technologies - Lecture 5
    Alberto Pace (CERN)
    03/09/2014, 11:30
  53. 47. Multivariate Visualisation - Lecture 1
    Benjamin Radburn-Smith (Purdue University (US))
    03/09/2014, 13:30
  54. 48. Data Technologies - Exercise 4
    Alberto Pace (CERN), Mr Andreas Joachim Peters (CERN)
    04/09/2014, 08:45
  55. 49. Data Technologies - Exercise 5
    Alberto Pace (CERN), Mr Andreas Joachim Peters (CERN)
    04/09/2014, 09:45
  56. 50. Data Analysis - Exercise 4
    Ivica Puljak (Technical University of Split FESB)
    04/09/2014, 11:30
  57. 51. Data Analysis - Exercise 5
    Ivica Puljak (Technical University of Split FESB)
    04/09/2014, 13:30
  58. 66. Calculability and comlexity
    Stefano Martina (Universita e INFN (IT))
    05/09/2014, 09:45
    Brief introduction of the analisys of calculability and complexity, and introduction of theoretical computer science. Turing machine, complexity hierarchy, etc...
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  59. 67. Challenges in the CERN Accelerator Complex
    Helga Timko (CERN)
    05/09/2014, 09:59
    Beam instabilities and loss of Landau damping are major limiting factors for the HL-LHC era. A short introduction to how the beam is produced and what the major challenges are.
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  60. 68. Clustering
    Vincent Alexander Croft (Radboud University Nijmegen (NL))
    05/09/2014, 10:13
    In the era before 'Big data' LHC physicists used clustering algorithms to join 3 dimensional objects together inside their detectors. Now similar algorithms, working in N dimensions, are revolutionising the way that people choose which TV to watch, how the business world makes transactions and even how geeks find love. Clustering can be used to create structures that isolate nuances in the...
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  61. 69. Modern HEP Data Analysis - How to handle the growing complexity
    Raphael Marius Friese (KIT - Karlsruhe Institute of Technology (DE))
    05/09/2014, 10:27
    In the era before 'Big data' LHC physicists used clustering algorithms to join 3 dimensional objects together inside their detectors. Now similar algorithms, working in N dimensions, are revolutionising the way that people choose which TV to watch, how the business world makes transactions and even how geeks find love. Clustering can be used to create structures that isolate nuances in the...
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  62. 70. Non-parametric density estimation
    Lucio Anderlini (Laboratoire d'Annecy de Physique de Particules)
    05/09/2014, 10:41
    Fitting is often used to model data distributions of different categories in order to identify, or unfold, these components in regions of the parameter space where they are mixed. The traditional use of high-order polynomial functions is now being replaced by non-parametric techniques as the Kernel Density Estimation (KDE) and Density Estimation Trees (DETs). Among the advantages of these...
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  63. 71. Parallelism for free with Haskell
    Janos Daniel Pek (CERN)
    05/09/2014, 10:54
    Haskell is a standardised, general-purpose purely functional programming language with non-strict semantics and strong static typing. In this talk some of these properties will be demonstrated by working through a very simple example. Having these properties, it is possible to build safe and highly parallel applications running on multi-core architectures or GPUs without significant effort...
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  64. 72. Performance of RAID arrays
    Michael Sokolov (SRV24)
    05/09/2014, 11:30
    1) interfaces 2) low productivity RAID 5 3) SSD 4) Inefficiency of the classic RAID with SSD
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  65. 73. Profiling code in Python
    Pawel Szostek (CERN)
    05/09/2014, 11:43
    Python code is much easier to write than C, yet much less efficient. It's often assumed that Python is not performance-oriented and therefore making effort to optimize it doesn't pay off. However, if there arises a need to profile the code and find bottlenecks we are not completely lost. In this talk I will tell why perf(_deluxe.py) is not suitable for this purpose and which tools can we take instead
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  66. 74. Puppet is so awesome it sucks
    Hristo Mohamed (University of Sofia (BG))
    05/09/2014, 11:56
    Puppet is IT automation software that defines and enforces the state of your infrastructure throughout your software development cycle. From provisioning and configuration to orchestration and reporting, from initial code development through production release and updates, Puppet frees sysadmins from writing one-off, fragile scripts and other manual tasks. At the same time, Puppet ensures...
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  67. 75. Software Defined Networking - programming your network
    Stefan Nicolae Stancu (CERN)
    05/09/2014, 12:07
    Software Defined Networking is a new model for managing and controlling networks that emerged from the need to make the network more agile in virtualized datacentre environments. Given the short time of the presentation I will present the concept of SDN (and OpenFlow, the main underlying protocol), by analogy to traditional networking, highlighting the main advantages (centralized control,...
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  68. 76. Toward construction of neutron diffractometer for protein crystal
    Tomoyori Katsuaki (KEK)
    05/09/2014, 12:20
    We performed a time-of-flight (TOF) single crystal neutron diffraction experiment with a diffractometer (the IBARAKI Biological Crystal Diffractometer (iBIX)) installed at a coupled moderator (CM) pulsed neutron source in J-PARC using single crystal silicon, and we determined several candidates for fundamental fitting functions to faithfully reproduce the TOF Bragg reflection profile...
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  69. 58. CERN, 60 years of Science for Peace
    Rolf Heuer (CERN Director General)
  70. 34. Data Analysis - Lecture 4
    Ivica Puljak (Technical University of Split FESB)
  71. 3. Introduction to Physics Computing - Lecture 1
    Arnulf Quadt (Georg-August-Universitaet Goettingen (DE))
  72. 40. Networking Performance - Lecture 2
    Mr Francois Fluckiger (CERN - IT/DI)
  73. 2. Opening Session
  74. 54. Opening session
  75. 57. Presentation of the School and Opening declaration
    Alberto Pace (CERN)
  76. 52. Presentations by students
  77. 53. Presentations by students