Introduction to High-Performance Computing

Europe/Stockholm
KTH main campus

KTH main campus

KTH main campus Valhallavägen 79
Description

The PDC- Center for High-Performance Computing and the KTH School of Computer Science and Communication (CSC) welcome you to our summer school introductory course on high-performance computing. This course is part of the Swedish e-Science Education .

Interested students and researchers (with academic or industrial backgrounds) from all over the world are invited to apply to attend the course, which will be held at the KTH main campus in Stockholm during late August. (Please note that for KTH Masters students, the summer school is available as course number DN2258.)

This course provides the skills needed to utilize high-performance computing (HPC) resources, and includes an introduction to a range of important topics, such as:

  • HPC programming languages, libraries and tools,
  • modern computer architectures,
  • parallel algorithms, and
  • optimizing serial and parallel programs.
Case studies in various scientific disciplines will be used to help illustrate these topics. The course consists of both lectures and guided hands-on lab sessions. Participants who successfully complete the course (including the associated programming project) will be awarded 7.5 ECTS (European Credit Transfer and Accumulation System).

The course is suitable for scientists and graduate students who are interested in high-performance computing. Applicants must be able to communicate in English, and have previous programming experience.

The PDC Summer School receives considerable funding from SeSE, the Swedish e-Science education. The two leading e-Science Centres in Sweden, SeRC (www.e-science.se) and eSSENCE (http://essenceofescience.se) have taken the initiative to establish a Graduate School SeSE, to fund, develop and offer basic training in fields where the use of e-Science is emerging and where education can have an immense impact on the research, but also advanced training for students in fields that are already computer-intensive. The school is open to all graduate students in Sweden, and is built upon the previous successful school NGSSC and KCSE. SeSE will be a meeting place for graduate students using e-Science tools and techniques.

2014 will be the 19th year that the course has been held – participants will become part of the long tradition of the PDC Summer School, which you can read about in the course pages for all the previous years.

Please note that there are a limited number of places available in the summer school, so be sure to register early! Course registration opens on March 15, and closes on June 1, 2014.

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Slides
    • 08:30 09:15
      Registration 45m
      E3 - Osquarsbacke 14 - KTH Main Campus
    • 09:15 10:15
      Welcome to PDC and the Summer School 1h
      Speaker: Erwin Laure (PDC-HPC)
      Slides
    • 10:15 10:30
      Coffee Break 15m
    • 10:30 12:15
      High-Performance Computer Architecture 1h 45m
      Speaker: ERIK HAGERSTEN
      Slides
    • 12:15 14:00
      Picnic - KTH garden close to E3 room 1h 45m
    • 14:00 15:00
      High-Performance Computer Architecture 1h
      Speaker: Erik Hagersten
      Slides
    • 15:00 15:15
      Coffee break 15m
    • 15:15 17:00
      High-Performance Computer Architecture 1h 45m
      Speaker: Erik Hagersten
      Slides
    • 09:15 10:00
      Concepts and Algorithms for Scientific Computing 45m
      Speaker: Björn Engqvist
      Slides
    • 10:00 10:15
      Coffee break 15m
    • 10:15 11:15
      Concepts and Algorithms for Scientific Computing 1h
      Speaker: Björn ENGQUIST
    • 11:15 12:15
      Interconnection Networks 1h
      Speaker: Michael Schliephake (KTH)
      Slides
    • 12:15 13:30
      Individual Lunch 1h 15m
    • 13:30 14:30
      Introduction to PDC's Environment 1h
      Speaker: Radovan Bast (PDC - KTH)
      Slides
    • 14:30 14:45
      Coffee break 15m
    • 14:45 16:45
      Lab: Introduction to PDC's Environment 2h
    • 14:45 16:45
      PDC Machine Room Tour 2h
    • 09:15 10:00
      Shared memory programming, OpenMP 45m
      Speaker: Mats BRORSSON
      Slides
    • 10:00 10:15
      Coffee Break 15m
    • 10:15 12:00
      Shared memory programming, OpenMP 1h 45m
      Speaker: Mats BRORSSON
      Slides
    • 12:00 13:00
      Individual Lunch 1h
    • 13:15 14:00
      Shared memory programming, OpenMP 45m
      Speaker: Mats BRORSSON
      Slides
    • 14:15 15:00
      Lab: Programming Exercises on OpenMP 45m
      Speaker: Stefano MARKIDIS
    • 15:00 15:15
      Coffee Break 15m
    • 15:15 17:00
      Lab: Programming Exercises on OpenMP 1h 45m
      Speaker: Stefano MARKIDIS
    • 09:15 10:00
      Shared memory programming, OpenMP 45m
      Speaker: Mats BRORSSON
    • 10:00 10:15
      Coffee Break 15m
    • 10:15 12:00
      Shared memory programming, OpenMP 1h 45m
      Speaker: Mats BRORSSON
    • 12:00 13:00
      Individual Lunch 1h
    • 13:15 15:00
      Lab: OpenMP Advanced Project 1h 45m
      Speaker: Stefano MARKIDIS
    • 15:00 15:15
      Coffee Break 15m
    • 15:15 17:00
      Lab: OpenMP Advanced Project 1h 45m
      Speaker: Stefano MARKIDIS
    • 09:15 10:00
      GPU Architectures for Non-Graphics People 45m
      Speaker: David BLACK-SCHAFFER
      Slides
    • 10:00 10:15
      Coffee Break 15m
    • 10:15 11:00
      GPUs: The Hype, The Reality, and The Future 45m
      Speaker: David BLACK-SCHAFFER
      Slides
    • 11:15 12:00
      Introduction to CUDA 45m
      Speaker: Michael Schliephake (KTH)
      Slides
    • 12:00 13:00
      Individual Lunch 1h
    • 13:00 13:45
      Introduction to CUDA 45m
      Speaker: Michael Schliephake (KTH)
      Slides
    • 14:00 15:00
      Lab: CUDA 1h
      Speaker: Mr Michael Schliephake (KTH)
    • 15:00 15:15
      Coffee Break 15m
    • 15:15 16:15
      Lab: CUDA 1h
      Speaker: Mr Michael Schliephake (KTH)
    • 09:15 10:00
      Introduction to CUDA 45m
      Speaker: Michael Schliephake (KTH)
      Slides
    • 10:00 10:15
      Coffee break 15m
    • 10:15 12:00
      MPI: Introduction, Basic Concepts, Point-to-Point Communication 1h 45m
      Speaker: Erwin Laure (PDC-HPC)
    • 12:00 13:00
      Individual Lunch 1h
    • 13:15 15:00
      Lab: CUDA 1h 45m
    • 15:00 15:15
      Coffee break 15m
    • 15:15 17:00
      Lab: MPI Part 1/CUDA 1h 45m
    • 09:15 10:00
      MPI - Point-to-Point Communication 45m
      Speaker: Erwin Laure (PDC-HPC)
      Slides
    • 10:00 10:15
      Coffee Break 15m
    • 10:15 11:00
      MPI - Collective Communication 45m
      Speaker: Erwin Laure (PDC-HPC)
      Slides
    • 11:15 12:00
      MPI - Intermediate MPI 45m
      Speaker: Erwin Laure (PDC-HPC)
      Slides
    • 12:00 13:00
      Individual Lunch 1h
    • 13:00 13:45
      MPI: Intermediate MPI 45m
      Speaker: Erwin Laure (PDC-HPC)
    • 14:00 15:00
      Lab: MPI Part 2 1h
    • 15:00 15:15
      Coffee Break 15m
    • 15:15 17:00
      Lab: MPI Part 2 1h 45m
    • 15:15 17:00
      Project Work 1h 45m
    • 09:15 10:00
      Performance Engineering 45m
      Speaker: Pekka Manninen
      Slides
    • 10:00 10:15
      Coffee Break 15m
    • 10:15 12:00
      Performance Engineering 1h 45m
      Speaker: Pekka Manninen
      Slides
    • 12:00 13:00
      Individual Lunch 1h
    • 13:00 13:45
      Parallel Performance Engineering 45m
      Speaker: Pekka Manninen
    • 14:00 15:00
      Lab: Parallel Performance Engineering 1h
      Speaker: Pekka Manninen
    • 15:00 15:15
      Coffee Break 15m
    • 15:15 17:00
      Lab: Performance Engineering 1h 45m
      Speaker: Pekka Manninen
    • 08:30 09:00
      Wrap up: Performance Engineering 30m
      Speaker: Pekka Manninen
    • 09:15 10:00
      MPI: Advanced Concepts 45m
      Speaker: Erwin Laure (PDC-HPC)
      Slides
    • 10:00 10:15
      Coffee Break 15m
    • 10:15 11:00
      MPI: Advanced Concepts 45m
      Speaker: Erwin Laure (PDC-HPC)
    • 11:15 12:00
      Gyrokinetic modelling for fusion plasmas 45m
      Thermonuclear fusion energy is one of the most attractive future energy sources because of the widespread and abundant distribution and low cost of its fuel supplies, and because of its inherent safety and environmental features. A positive energy balance in a magnetic fusion device requires heating a Deuterium and Tritium mixture to around 100 million degrees and maintaining the hot plasma in magnetic confinement for sufficiently long time. Understanding and controlling the processes and instabilities inherent in a fusion energy grade plasma is therefore key to achieving a sustained nuclear fusion. Understanding the interaction between the macroscopic instabilities and the microscopic plasma perturbations is always a challenging issue due to the intrinsic multi-scale and nonlinear nature of the problem. It is, on the other hand, an almost unavoidable step towards realistic simulations of high temperature fusion plasmas. Microscopic instabilities have gained much attention over the last few decades mainly because they tend to define size of a viable fusion reactor. Hence a lot can be gained from a detailed understanding of the underlying physics - unfortunately this is a very hard problem and has only recently become tractable due to the rapid development of computing systems and more importantly theoretical developments. In this presentation: a) A brief general introduction to fusion b) A discussion on the theoretical model(s9 and technical implementations c) Overview of results from the Chalmers gropu using the GENE code
      Speaker: Prof. Pär Strand
    • 12:00 13:00
      Individual Lunch 1h
    • 13:15 15:00
      Lab: MPI Part 3 1h 45m
    • 15:00 15:15
      Coffee Break 15m
    • 15:15 17:00
      Lab: MPI Part 3 1h 45m
    • 15:15 17:00
      Project Work 1h 45m
    • 18:00 21:00
      Dinner at Jakthornet restaurant 3h
    • 09:15 10:00
      Future Programming Languages 45m
      Speaker: Dr Stefano Markidis (PDC - KTH)
      Slides
    • 10:00 10:15
      Coffee Break 15m
    • 10:15 11:00
      Future Programming Languages 45m
      Speaker: Dr Stefano Markidis (PDC - KTH)
    • 11:15 12:00
      Abstractions for processing large data sets 45m
      At Google there is often a need to process very large data sets across many machines. Building efficient parallel processing programs is not trivial and to avoid the overhead of each engineer reinventing the wheel, Google has created several programming models to abstract away the complexities of parallelism and have the programmer concentrate on the core of his processing problem instead. I will talk mainly about the MapReduce model, the conceptual model the programmer get to work with and how it is implemented under the hood. I will also mention a few other models in use at Google, like Pregel, Dremel and Flume.
      Speaker: Jonas Yngvesson (Google Inc.)
    • 12:00 13:00
      Individual Lunch 1h
    • 13:00 17:00
      Open Lab and Project Work 4h