| 1. | Course Title | High Performance Computing | |||||||||||
| 2. | Code | 4ФЕИТ07013 | |||||||||||
| 3. | Study program | 7-NKS, 8-KM-INN | |||||||||||
| 4. | Organizer of the study program (unit, institute, department) | Faculty of Electrical Engineering and Information Technologies | |||||||||||
| 5. | Degree (first, second, third cycle) | Second cycle | |||||||||||
| 6. | Academic year/semester | I/1 | 7. | Number of ECTS credits | 6.00 | ||||||||
| 8. | Lecturer | Dr Goran Jakimovski | |||||||||||
| 9. | Course Prerequisites | ||||||||||||
| 10. | Course Goals (acquired competencies):
Architectures, techniques and technologies for high performance calculations. Acquired knowledge for all possible aspects and applicability to high performance calculations. |
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| 11. | Course Syllabus:
Architectures for high-performance computing. Compilers for High Performance Systems. Removal of program loops. Parallelization. High performance systems. Mass memories. Coupling networks and clusters. Switching networks and clusters. Grid structures. Grid computing. Pipelining. Performance estimation and optimization. Applications for grid environment. High-performance microprocessors. Design and evaluation of modern parallel processors. Principles of parallelism. Instruction level parallelism. Multiprocessor systems. Multicore processors. Memory hierarchy design. Scalable parallel computing. Highly parallel systems. Parallel programming models. Communication primitives, techniques for programming and compiling. Fundamental concepts of parallel algorithms. 2D algorithms. Hypercube algorithms. Hypercube architectures. Мessage passing еnvironment (Message Passing Interface-MPI), parallel virtual machine (Parallel Virtual Machine-PVM). Managing the space for data storage. Deadlock. Techniques for synchronization and load balancing. |
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| 12. | Learning methods:
lectures with presentations, homework and project assignment |
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| 13. | Total number of course hours | 180 | |||||||||||
| 14. | Distribution of course hours | 3 + 3 | |||||||||||
| 15. | Forms of teaching | 15.1 | Lectures-theoretical teaching | 45 hours | |||||||||
| 15.2 | Exercises (laboratory, practice classes), seminars, teamwork | 45 hours | |||||||||||
| 16. | Other course activities | 16.1 | Projects, seminar papers | 30 hours | |||||||||
| 16.2 | Individual tasks | 30 hours | |||||||||||
| 16.3 | Homework and self-learning | 30 hours | |||||||||||
| 17. | Grading | ||||||||||||
| 17.1 | Exams | 0 points | |||||||||||
| 17.2 | Seminar work/project (presentation: written and oral) | 50 points | |||||||||||
| 17.3. | Activity and participation | 0 points | |||||||||||
| 17.4. | Final exam | 50 points | |||||||||||
| 18. | Grading criteria (points) | up to 50 points | 5 (five) (F) | ||||||||||
| from 51 to 60 points | 6 (six) (E) | ||||||||||||
| from 61 to 70 points | 7 (seven) (D) | ||||||||||||
| from 71 to 80 points | 8 (eight) (C) | ||||||||||||
| from 81 to 90 points | 9 (nine) (B) | ||||||||||||
| from 91 to 100 points | 10 (ten) (A) | ||||||||||||
| 19. | Conditions for acquiring teacher’s signature and for taking final exam | 60% success in all pre-exam activities | |||||||||||
| 20. | Forms of assessment | Project assignment and final exam. | |||||||||||
| 21. | Language | Macedonian and English | |||||||||||
| 22. | Method of monitoring of teaching quality | Self-evaluation | |||||||||||
| 23. | Literature | ||||||||||||
| 23.1. | Required Literature | ||||||||||||
| No. | Author | Title | Publisher | Year | |||||||||
| 1. | Fran Berman, Geoffrey Fox, Anthony J. G. Hey | Grid Computing; Making the Global Infrastructure a Reality | John Wiley | 2003 | |||||||||
| 2. | K. Dowd, C. R. Severance, M. Loukides | High Performance Computing (Risc Architectures, Optimization & Benchmarks) | O’Reilly | 1998 | |||||||||
| 3. | R. Buyya | High Performance Cluster Computing: Architectures and Systems, Vol. 1 | Prentice Hall | 1999 | |||||||||
