1. |
Course title |
Parallel computing and algorithms |

2. |
Year of study, study programme |
3, 1-31 03 09 Computer Mathematics and Systems Analysis |

3. |
Semester of study |
5 |

4. |
Number of credits |
3 |

5. |
Lecturer |
Lavrova Olga Anatolievna |

6. |
Course Objective |
Formation of theoretical knowledge and practical skills for solving optimization problems and constructing parallel algorithms for these problems. As a result of studying the student should be able to – construct extremal problems on sets of finite-dimensional spaces; – analyze convex sets, convex functions, problems of convex and linear programming; – solve optimization problems by means of parallel computing and algorithms. |

7. |
Prerequisites |
Computer Mathematics. Calculus. Programming Methods and Informatics. Optimization Methods. Numerical Methods |

8. |
Course content |
1. 2. 3. 4. |

9. |
Recommended Literature |
1. Materials to the course «Einfürung in die Mathematische Optimierung», Prof. Kaibel, Otto-von-Guericke University, Magdeburg, Germany 2013/14: video-lectures in German, slides for lectures, homework tasks. 2. R. T. Rockafellar, Convex Analysis. Princeton University Press, 1970. 3. A. Ruszcynski, Nonlinear Optimization. Princeton University Press, 2006. 4. A. Gramma, A. Gupta, G. Karypis, V. Kumar Introduction to Parallel Computing, Addison Wesley, 2003. 5. Дорошенко А.Е Математические модели и методы организаций высокопроизводительных вычислений Киев: Наукова думка, 2000. |

10. |
Teaching Methods |
Lectures, laboratory classes |

11. |
Teaching language |
Russian, German |

12. |
Requirements, current control |
Control of the student’s work takes place in the form of interviews, tests and reports on laboratory works with their oral defense. Credits are held either orally or in writing. |

13. |
Method of certification |
Credit |