1. komponenta

Lecture type	Total
Lectures	30
Exercises	15

COURSE AIMS AND OBJECTIVES:
The goal of the course is to introduce the basic techniques for developing efficient parallel algorithms to the students. Students should learn to develop parallel versions of the typical algorithms applied to data arrays, trees, graphs, and matrices, as well as to the study examples from applications. In this process, they should master the basic techniques of data and algorithm operations reorganization, in order to speed up parallel implementation. This speed-up is achieved by efficient distribution of work among processors, detection of dependencies or independences between data and operations, minimization of communication between processors as well as between various levels of hierarchical memory, and optimal synchronization of processor work. At the end, students will be able to apply these techniques to a simple software tool or library.

COURSE DESCRIPTION AND SYLLABUS:
1. Introduction: development and classification of parallel computers
2. Parallel architectures and programming models
3. Performance measures of parallel algorithms (efficiency)
4. Basic techniques for designing parallel algorithms
5. Fast algorithms on trees
6. Fast algorithms for merging sorted arrays, for searching and sorting arrays
7. Matrix multiplication on hierarchical memory
8. Parallel algorithms for solving linear systems: iterative methods, with application to Poisson's equation
9. Solving the project assignment

1. Algorithms and Parallel Computing, F. Gebali, John Wiley & Sons, Inc., New Jersey, 2011.
2. Parallel Programming; For Multicore and Cluster Systems, T. Rauber, G. Rünger, Springer-Verlag Berlin Heidelberg, 2010.
3. An Introduction to Parallel Algorithms, J. Jájá, Addison-Wesley Publishing Company, Reading, Massachusetts, 1992.
4. Introduction to Parallel Computing, W. P. Petrsen, P. Arbenz, Oxford Univerity Press., Oxford, 2004.

Ostali izborni predmeti - Regular study - Computer Science and Mathematics
Vezani kolegiji D - Regular study - Computer Science and Mathematics

Ostali izborni predmeti - Regular study - Computer Science and Mathematics
Vezani kolegiji D - Regular study - Computer Science and Mathematics

Ostali izborni predmeti - Regular study - Computer Science and Mathematics
Vezani kolegiji D - Regular study - Computer Science and Mathematics

Ostali izborni predmeti - Regular study - Computer Science and Mathematics
Vezani kolegiji D - Regular study - Computer Science and Mathematics