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Multi-core processors yield the possibility making parallel computations on standard computers. Implementing an application
using parallelisms is a nontrivial matter. The goals of the course are an theoretical and practical introduction to contemporary
software technologies used for parallel programming, practically debugging parallel programs, and practically tuning parallel
program performance.
Last update: T_KSI (19.04.2007)
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Students will solve 5 homework assignments from selected technologies for parallel and distributed computing. At the end, the students must pass a final test, which may be accompanied by an oral exam (where a student explains the solution).
The characteristics of the credit requirements do not allow multiple attempts to fulfill them, except for the final coding test. More details are on the course web page. Last update: Kruliš Martin, doc. RNDr., Ph.D. (22.01.2026)
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A. Grama, A. Gupta, G. Karypis, V. Kumar: Introduction to Parallel Computing, Second Edition, Addison Wesley, 2003 C. Hughes, T. Hughes: Parallel and Distributed Programming Using C++, Addison Wesley, 2003 B. Lewis, D.J. Berg: PThreads Primer: A Guide to Multithreaded Programming, Sun Soft Press, 1996 G.E. Karniadakis, R.M. Kirby II: Parallel Scientific Computing in C++ and MPI: A Seamless Approach to Parallel Algorithms and their Implementation, Cambridge University Press, 2003 M. McCool, A.D. Robison, J. Reinders: Structured Parallel Programming, Morgan Kaufmann Publishers, 2012 Intel Threading Analysis Tools, www.intel.com Intel Cluster Tools, www.intel.com OpenMP, www.openmp.org Last update: Yaghob Jakub, RNDr., Ph.D. (18.09.2013)
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The content of the course is continuously updated to cover selected modern technologies related to parallel programming for shared-memory systems. Details are available on the web page of the course. Last update: Kruliš Martin, doc. RNDr., Ph.D. (22.01.2026)
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