Fundamental Algorithms - Winter 14: Difference between revisions
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| term = Winter 14 | | term = Winter 14 | ||
| lecturer = [[Michael Bader|Prof. Dr. Michael Bader]] | | lecturer = [[Michael Bader|Prof. Dr. Michael Bader]] | ||
| timeplace = | | timeplace = Mon 8.30-10.00, lecture hall MI HS 3 (first lecture on Oct 13, 8.30) | ||
| credits = 2 SWS (2V) / 3 ECTS | | credits = 2 SWS (2V) / 3 ECTS | ||
| audience = Computational Science and Engineering; Biomedical Computing (elective) | | audience = Computational Science and Engineering; Biomedical Computing (elective) |
Revision as of 11:59, 4 August 2014
- Term
- Winter 14
- Lecturer
- Prof. Dr. Michael Bader
- Time and Place
- Mon 8.30-10.00, lecture hall MI HS 3 (first lecture on Oct 13, 8.30)
- Audience
- Computational Science and Engineering; Biomedical Computing (elective)
- Tutorials
- ---
- Exam
- written exam at end of semester
- Semesterwochenstunden / ECTS Credits
- 2 SWS (2V) / 3 ECTS
- TUMonline
- https://campus.tum.de/tumonline/wbStpModHB.detailPage?&pKnotenNr=458187 (module description)
Contents
The course will provide an overview on the analysis of fundamental algorithms. Topics will be:
- Fundamentals: Models of Computation, Complexity Measures
- Sorting: Bubble-Sort, Merge-Sort, Quick-Sort, Median-Algorithms, Lower Bounds, etc.: sorting in parallel
- Searching: Hashing, Search Tress, etc.
- Arithmetic Problems: parallel prefix computation, parallel matrix and vector operations
- Foundations of parallel algorithms and simple models of parallel computation
- Algorithms on (weighted) graphs: traversals, shortest paths, etc.
Lecture Notes and Material
will be made available during the course.
Literature
- Cormen, Leiserson, Rivest, Stein: Introduction to Algorithms; MIT Press
- Berman, Paul: Algorithms: Sequential, Parallel, and Distributed; Cengage Learning Emea 2004
- Heun: Grundlegende Algorithmen; Vieweg 2000
- Sedgewick: Algorithms; Pearson Education
- Shackleford, Computing and Algorithms; Addison Wesley Longman
- Kleinberg, Tardos: Algorithm Design; Pearson Education