1. Parallel Programming Henri Bal (bal@cs.vu.nl)bal@cs.vu.nl Vrije Universiteit Faculty of Sciences Amsterdam

2. Overview What is parallel programming? Why do we need parallel programming? Organization of this course Practicum Parallel Programming

3. ICWall A large display suitable for: – Education (classroom) – Modern scientific applications that need to visualize large data-sets – 3D applications

4. ICWall: an "off-the-shelf" video wall High-end graphics is very expensive Use tiled display with many projectors Use standard (inexpensive) components – 9 PCs, graphic and network cards, 16 projectors Similar idea as cluster computing, but applied to graphics Current ICWall is strongly simplified version –1 PC with 2 projectors

6. Parallel Programming Sequential programming Single thread of control Parallel programming Multiple threads of control Why parallel programming? Eases programming? Not really. Performance? Yes!

7. Famous quote “Parallel programming may do something to revive the pioneering spirit in programming, which seems to be degenerating into a rather dull and routine occupation’’ S. Gill, Computer Journal, 1958

8. Why do we need parallel processing? Many applications need much faster machines Sequential machines are reaching their speed limits Use multiple processors to solve large problems fast Microprocessors are getting cheaper and cheaper Cheap multiprocessors and multicore CPUs bring parallel processing to the desktop!

9. History 1950s: first ideas (see Gill’s quote) 1967 first parallel computer (ILLIAC IV) 1970s programming methods, experimental machines 1980s: parallel languages (SR, Linda, Orca), commercial supercomputers 1990s: software standardization (MPI), clusters, large-scale machines (Blue Gene) 2000s: grid computing: combining resources world-wide (Globus)

10. Large-scale parallel machines Many parallel machines exist See http://www.top500.orghttp://www.top500.org Current #1 is IBM BlueGene/L with 131072 CPUs 131072

11. Challenging Applications Modeling ozone layer, climate, ocean Quantum chemistry Protein folding General: computational science Aircraft modeling Handling use volumes of data from scientific instruments –Lofar (astronomy) –LHC (CERN, high-energy physics) Computer chess Analyzing multimedia content Generating movies

12. About this Course Goal: Study how to write programs that run in parallel on a large number of machines. Focus on programming methods, languages, applications Prerequisites: Some knowledge about sequential languages Little knowledge about networking and operating systems

13. Aspects of Parallel Computing Algorithms and applications Programming methods, languages, and environments Parallel machines and architectures

14. Course Outline Introduction in algorithms and applications Parallel machines and architectures Overview of parallel machines, trends in top-500 Cluster computers, BlueGene Programming methods, languages, and environments Message passing (SR, MPI, Java) Higher-level language: HPF Applications N-body problems, search algorithms, bioinformatics Grid computing Multimedia content analysis on Grids (guest lecture Frank Seinstra)

15. Course Information Examination Written exam based on: - Reader: available electronically from Blackboard - Lectures More information (and slides): http://www.cs.vu.nl/~bal/college07.html

16. Practicum Parallel Programming Separate practicum (6 ECTS) Implement ASP + SOR algorithms in C/MPI Implement IDA* search algorithm in Java/RMI Test and measure the programs on our DAS cluster

17. More information Register by email to ndrost@cs.vu.nl (Niels Drost) now Starts after MPI lecture (mid October) See http://www.cs.vu.nl/pp-cursus/ for a complete description