Parallel and High Performance Computing

(Parallel Computing: Grundlagen und Anwendungen)

Vorlesung mit Übung im Wintersemester 2016/2017
Prof. Dr. D. Kranzlmüller, Dr. K. Fürlinger, R. Kowalewski M.Sc.

This course will be held in English!

Welcome to the course webpage for Parallel and High Performance Computing for winter-term 2016/17 at LMU Munich. Here you will be able to find details on the lecture and the accompanying practical lab exercises.

News

Content

Parallel computing is concerned with using multiple compute units to solve a problem faster or with higher accuracy. Historically, the main application area for parallel machines is found in engineering and scientific computing, where high performance computing (HPC) systems today employ tens- or even hundreds of thousand compute cores.

The application area for parallel computing has, however, expanded recently to essentially include all areas of information technology. Virtually all servers, desktop, and notebook systems, and even smartphones and tables are today equipped with CPUs that contain multiple compute cores. In each case, the potential for these systems can only be fully realized by explicit parallel programming. As such understanding the benefits, challenges, and limits of parallel computing is increasingly becoming a "must have" qualification for IT professionals.

This course addresses the increasing importance of parallel and high performance computing and is covering three interwoven areas: Parallel hardware architectures, parallel algorithm design, and parallel programming. The successful student will be able to identify potentials for parallel computing in various application areas, judge the suitability of contemporary hardware architectures for a parallel computing problem and understand efficient implementation strategies using modern parallel programming approaches.

The lecture is partially based on material that has been developed at UC Berkeley and which has been funded by the US National Science Foundation. The course slides will be made available for download by the date of the lecture and will be in English.

Audience

The course is intended for both bachelor and master students of computer science and related fields. More formally, in German: Die Vorlesung richtet sich an Studenten der Informatik bzw. Medieninformatik (Diplom) nach dem Vordiplom sowie an Studenten der Informatik, Bioinformatik bzw. Medieninformatik (Bachelor, Master) im Rahmen der vertiefenden Themen der Informatik. Für Vorlesung und Übung werden 6 ECTS-Punkte vergeben.

Important Dates

Please note that the dates and locations for lecture and lab exercises listed below are provisional and may change prior to the start of the course!

• Lecture: Friday 9 - 12, Oettingenstr. 67, Room B001. First lecture: October 21, 2016.
• Lab exercise: Thursday 14 - 16, Amalienstr. 73A, Room 112. First lab: October 27, 2016.
• Please keep an eye on News for any short-term changes and announcements.
• Friday December 12, 11:00am: Guest lecture by Prof. Jesper Larsson Traeff, TU Wien
  Title: The Power of Structured Data in MPI
  Abstract: The ability to communicate arbitrarily (statically) structured data via the derived datatype mechanism is a unique feature of MPI (the Message-Passing Interface). We believe that the power of derived datatypes, in particular in combination with the collective communication operations is still not fully explored, neither with respect to descriptive advantages nor their potential for improved performance. This talk will describe recent applications of MPI derived datatypes to improve complex algorithms for collective communication operations, and discuss open issues in the specification and implementation of efficient, derived datatype mechanisms.
• The written exam (duration: 90 min.) for the lecture will take place on Friday, Feb. 24 2017, at 15:15pm, in Room M 218, Geschwister-Scholl-Platz 1.
  
• The written repeat exam (duration: 90 min.) will take place on Thursday, April 13, 2017, at 14:15pm, in Room B 051, Theresienstr. 39.

Lab Exercises

The lecture is accompanied by a lab exercises to deepen the understanding of topics covered in the lecture. High performance computing systems hosted at the Leibniz Supercomputing Center will be made available to the students. Worksheets for the lab exercises will be made available on UniWorX.

Downloads

Lecture slides will be made available chapter-by-chapter through this webpage.

Further Reading

	Paul E. McKenney (Ed.): Is Parallel Programming Hard, And, If So, What Can You Do About It? (online)
	Ananth Grama et al.: Introduction to Parallel Computing (2nd Ed.)
	David Culler and Jaswinder Pal Singh: Parallel Computer Architecture, A Hardware/Software Approach
	John Hennessy and David Patterson: Computer Architecture a Quantitative Approach (5th Ed.)
	Georg Hager and Gerhard Wellein: Introduction to High Performance Computing for Scientist and Engineers
	Barbara Chapman et al.: Using OpenMP
	William Gropp, Ewing Lusk, Anthony Skjellum: Using MPI
	William Gropp, Torsten Hoefler, Ewing Lusk: Using Advanced MPI

Registration

Please register for the course on UniWorX.

Contact

Via email and/or after the lecture and lab exercises.