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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 elaborate 5 homeworks from selected technologies for parallel and distributed computing. Each task will be scored 0-4 points depending on the speedup achieved against the reference serial version of the solution. The final grade from the exam corresponds to the sum of points obtained: 12 and over - excellent 9-11 - very well 6-8 - well less than 6 - failed
Credit is obtained for at least 5 points, where it is necessary to have at least one point from each homework.
More details on the course page. Last update: Yaghob Jakub, RNDr., Ph.D. (25.02.2020)
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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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Last update: Yaghob Jakub, RNDr., Ph.D. (22.04.2016)
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