Masterpraktikum Scientific Computing - High Performance Computing - Winter 12

Term

Winter 12

Lecturer

Michael Bader,
Alexander Heinecke

Time and Place

preliminary meeting: July 11 2012, 12:30pm - 1:15pm, 02.07.023

Audience

Masterpraktikum (Modul IN2106), Wahlpflichtpraktikum im Bereich theoretische Informatik (Modul IN8904)
Studierende im Masterstudiengang Informatik, Studierende der Informatik im Hauptstudium, Studierende der Techno-, Diplom- und Finanz-Mathematik

Language: English

Tutorials

-

Exam

-

Semesterwochenstunden / ECTS Credits

6 SWS / 10 Credits

TUMonline

https://campus.tum.de/tumonline/lv.detail?clvnr=950070504

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News

The course will take place on

• Tuesday, 16.10.2012, 15:00 - 16:30, room 02.07.023
• Tuesday, 30.10.2012, 15:00 - 16:30, room 02.07.023
• Tuesday, 13.11.2012, 15:00 - 16:30, room 02.07.023
• Tuesday, 27.11.2012, 15:00 - 16:30, room 02.07.023
• Tuesday, 11.12.2012, 15:00 - 16:30, room 02.07.023
• Tuesday, 29.01.2013, 15:00 - 16:30, room 02.07.023

Content

High Performance Computing has become a critical success factor in research and industry. Even the computational power of commodity parts like desktop systems increased rapidly due to vectorization, EPIC, multi-core. This lab course uncovers the principles behind these buzzwords and highlights programming concepts, software design and coding styles which are mandatory to unleash the power of modern chips.

We focus on developing datastructers and algorithms with respect to their performance, for both single and parallel executions. We deep-dive into different platforms like CPUs, GPUs and multi-node clusters. Furthermore, we cover several programming concepts like auto-vectorization, explicit vectorization, OpenMP, MPI and OpenCL. The platform differences are evaluated through detailed runtime experiments.

Topics:

• Performance-Optimization of sequential applications
  • Pipelining
    • Loop unrolling
    • Data dependencies
  • Caches
    • Cache blocking
  • Performance-Measurement
• State-of-the-Art Hardware
  • CPUs
  • Memory Subsystems
  • Supercomputer
  • GPUs
• Parallele Programming
  • OpenMP
  • MPI
  • OpenCL

The course is held in two parts. The first one introduces basics, concepts and programming models through theoretical and practical exercises. You work on these exercise in small teams. The second part is a real-life task: each team has to optimize a given scientific application with respect to the underlying hardware architecture.

C-Programming and Linux Know-How are helpful!

Slides

• 16.10.2011: Introduction, Vectorization
• 30.10.2011: OpenMP
• 13.11.2011: MPI and CG method
• 27.11.2011: Cilk and OpenCL

Exercise Sheets

• 16.10.2011: Exercise Sheet 1 | Code (hand in on 30.10.2011)
• 30.10.2011: Exercise Sheet 2 | Code (hand in on 13.11.2011)
• 13.11.2011: Exercise Sheet 3 | Code (hand in on 27.11.2011)
• 27.11.2011: Exercise Sheet 4 ] (hand in on 11.12.2011)

Material

• MPI 2.2 Standard: http://www.mpi-forum.org/docs/mpi-2.2/mpi22-report.pdf
• OpenMP Tutorial: https://computing.llnl.gov/tutorials/openMP/
• Intel C++ Compiler Referenz: http://software.intel.com/sites/products/documentation/hpc/compilerpro/en-us/cpp/lin/main_cls_lin.pdf
• Intel Architecture Manuals: http://www.intel.com/products/processor/manuals/index.htm