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19E074PMPI - Programming multiprocessor platforms for engineering applications

Course specification
Course title Programming multiprocessor platforms for engineering applications
Acronym 19E074PMPI
Study programme Electrical Engineering and Computing
Module
Type of study bachelor academic studies
Lecturer (for classes)
Lecturer/Associate (for practice)
Lecturer/Associate (for OTC)
ESPB 6.0 Status elective
Condition none
The goal Acquaintance with complex engineering problems and algorithms in information-communication systems. Understanding of parallelization concept in solution of complex problems. Presenting the most commonly used approaches to multiprocessor platform programming.
The outcome Identification of engineering problems that are effectively solved by parallelization using multiprocessor platforms. Training for programming multiprocessor platforms in order to solve complex problems in information-communication systems.
Contents
Contents of lectures Importance of multi-processor platforms in IC systems. Acquaintance with programming and architecture of basic platforms (OpenMP,GPGPU,MPI). Classification of engineering applications related to required computer resources and parallelizability. Computing demanding algorithms in telecommunication networks, radio communication, theory of information, microwave technique and multimedia technologies
Contents of exercises Training for practical use of programs for calculating demanding budgets on different platforms. Writing programs running on multi-processor platforms. Solving a specific problem of choice from one of the areas (TM, RK, TI, MTT, MMT) on one of the multiple-processor platforms.
Literature
  1. B. Kolundzija, A. Djordjevic, Electromagnetic Modeling of Composite Metallic and Dielectric Structures, Artech House, 2002.
  2. Y. Zhang, T. Sarkar, Parallel Solution of Integral Equation-Based EM Problems in the Frequency Domain, 2009.
  3. B. Chapman, G. Jost, R. Pas Using OpenMP Portable Shared Memory Parallel Programming, 2007
  4. D. Storti, M. Yurtoglu CUDA for Engineers: An Introduction to High-Performance Parallel Computing, 1st Edition, 2015
  5. G. Karniadakis, R. Kirby Parallel Scientific Computing in C++ and MPI: A Seamless Approach to Parallel Algorithms and their Implementation, 2003
Number of hours per week during the semester/trimester/year
Lectures Exercises OTC Study and Research Other classes
2 2 1
Methods of teaching Lectures, problem solving classes, computer lab classes, and project.
Knowledge score (maximum points 100)
Pre obligations Points Final exam Points
Activites during lectures 70 Test paper 30
Practical lessons Oral examination
Projects
Colloquia
Seminars