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HPC - Algorithms and Applications - Winter 16

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Term
Winter 16/17
Lecturer
Prof. Dr. Michael Bader
Time and Place
lecture: Mon, 14-16 in room MI 02.07.023 (intro lecture on Wed, Oct 19, in the tutorial slot)
tutorial: Wed, 12-14, in room MI 02.07.023 (roughly every other week)
Audience
Elective topic in Informatics Bachelor/Master: students in mathematics or in any science or engineering discipline are welcome!
Tutorials
Alexander Pöppl, Valeriy Khakhutskyy
Exam
Fri, Feb 24, 13.30 in Interim 2
Semesterwochenstunden / ECTS Credits
3 SWS (2V + 1Ü) / 4 ECTS
TUMonline
TUMOnline



Contents

Announcements

  • A Q&A session concerning the exam (lectures and tutorials) will take place on Feb 15, 2017 (Wed), 12:15-13:45, in seminar room MI 02.07.023 (tutorial slot)
  • there will be no lecture on Mon, Oct 17 (opening day)
  • the intro lecture is moved to Wed, Oct 19 (tutorial slot)

Content

The lecture will have a focus on parallel algorithms and implementation techniques in the field of numerical simulation and high performance computing, such as:

  • linear algebra problems on dense and sparse matrices
  • simulation on structured and unstructured meshes
  • particle-based simulations (with long-range and short-range interactions)
  • spectral methods (parallel FFT and related algorithms)
  • Monte Carlo and statistical methods

(a.k.a. the seven dwarfs of HPC).

The accompanying tutorials will include practical assignments, and will concentrate on the programming of GPU and accelerator platforms.

Lecture Material

Lecture slides will be published/updated here after the lessons. See also the lecture from winter term 2015/16.

Tutorials

Roughly every second week a two hour tutorial will take place (details at page top; days and time will be announced in TUMonline and in the lectures). The assignments and their solutions will be gradually posted here.


Date Slides Worksheet Source Source (solution)
Oct 24th Organizational remarks Introduction to CUDA - - -
Nov 11th Introduction to CUDA Worksheet 1 Exercise 1 included in Exercise 2
Nov 23rd Dense LA in CUDA (part 2) Worksheet 2 Template (Lecture) Template (Homework) Solution 2
Nov 30th Sparse LA in CUDA Worksheet 3 Template (Lecture) Template (Homework) Memory Accesses; Solution included in Exercise 4
Dec 14th Solving the heat equation with CUDA Worksheet 4 Template (Task 1.1a) Template (Task 1.1b) Template (Homework) Solution 4
Jan 11th The Shallow Water Equations and CUDA Worksheet 5 Exercise 5 included in Exercise 6
Jan 25th Further topics on SWE and CUDA Worksheet 6 Exercise 6 -

Exam

End-Term Exam

  • Written Exam on Feb 24th, 13:30-15:15 in Interim 2 (black building in front of Informatics building)
    • please be in the lecture room in time (by 13:15); the exam will start on 13:30, at the latest, and there will be announcements before the start!
  • Helping material: One sheet of A4 paper (two-sided) with hand-written notes on it.
  • The exam will extend over all topics discussed in the lectures and tutorials:
    • approx. 30% of the questions will deal with questions related to the tutorials; basic knowledge about GPU programming with CUDA is thus necessary


Repeat Exam

  • Exam Review: on appointment in the week from Apr 24; please contact Alexander Pöppl
  • The same rules as for the written exam will apply (see below)
  • Written exam on Mon, Apr 10th, 2017, from 10:30 (MI Lecture Hall 2)
    • Please try to be in front of the room by 10:15 as the working time will start at 10.30. Announcements will be made prior to 10:30.
  • Helping material: One sheet of A4 paper (two-sided) with hand-written notes on it.
  • The exam will extend over all topics discussed in the lectures and tutorials:
    • approx. 30% of the questions will deal with questions related to the tutorials; basic knowledge about GPU programming with CUDA is thus required


Exam Preparation

  • the following worksheet contains some example questions (with solutions) from previous exams:
    • exam questions with example solutions
    • note that this collection of exercises does not reflect the extent of assignments in the exam
    • note that the contents of the lecture may have slightly changed compared to previous years, such that exercises can have a slightly different focus

Literature and Online Material

(all available as ebooks from TUM library)

Books on CUDA

(both available as ebooks from TUM library)

Prerequisites

Helpful, but not strictly required is knowledge in:

  • basics of numerical methods (e.g.: lecture IN0019 Numerical Programming or similar)
  • basics of parallel programming (lecture Parallel Programming, HPC - Programming Paradigms and Scalability, or similar)

Most important is a certain interest in problems from scientific computing and numerical simulation!