FI:PA039 Supercomputer Architecture - Course Information
PA039 Supercomputer Architecture and Intensive ComputationsFaculty of Informatics
- Extent and Intensity
- 2/0. 2 credit(s) (plus extra credits for completion). Type of Completion: zk (examination).
Taught in person.
- prof. RNDr. Luděk Matyska, CSc. (lecturer)
RNDr. Jiří Filipovič, Ph.D. (assistant)
- Guaranteed by
- prof. RNDr. Luděk Matyska, CSc.
Department of Computer Systems and Communications - Faculty of Informatics
Contact Person: prof. RNDr. Luděk Matyska, CSc.
Supplier department: Department of Computer Systems and Communications - Faculty of Informatics
- Tue 15. 2. to Tue 17. 5. Tue 14:00–15:50 A217
- ! IA039 Supercomputer Architecture
At least elementary knowledge of programming languages FORTRAN, C and eventually C++ is expected.
- Course Enrolment Limitations
- The course is also offered to the students of the fields other than those the course is directly associated with.
- fields of study / plans the course is directly associated with
- there are 48 fields of study the course is directly associated with, display
- Course objectives
- The main goal of this lecture is to provide information about architectures of high-performance computing systems and basic programming methods for vector and parallel computers. The first part focuses on the hardware, during the second part general optimization methods and programming methodology for parallel computers is discussed. The last part of the lecture is aimed at the programming of distributed systems.
- Learning outcomes
- The graduate will be able to understand and explain properties of modern processors.
The graduate will be also able to analyze the program code and propose optimizations for a particular processor.
The graduate will be able to design and implement a simple parallel program to solve a particular problem.
The graduate will be able to design and realize benchmarks of computer systems or applications.
- High-performance vector and superscalar processors.
- Uniprocessor computers, computers with a small number of processors, massively parallel computers; distributed systems.
- Performance measurements, LINPACK test, TOP 500 list.
- High-performance uniprocessor systems, programming languages, the methodology of efficient program writing, basis optimization methods for vector and superscalar computers.
- Distributed systems, data and task decomposition, coarse grain parallelism, programming systems (PVM, LINDA, ...). Multiprocessor systems with shared memory, programming languages, decomposition of algorithms, basic optimization methods for a small number of processors.
- Massively parallel systems, parallel algorithms, fine grain parallelism.
- Shared, distributed, and distributed shared memory; other alternatives. Sdílená, distribuovaná a distribuovaná sdílená paměť.
- Scalability of computers and tasks.
- PROTIC, Jelica, Milo TOMASEVIC and Veljko MILUTINOVIC. Distributed shared memory. Los Alamitos: IEEE Computer Society, 1998. x, 365 s. ISBN 0-8186-7737-6. info
- FOSDICK, Lloyd D. An introduction to high-performance scientific computing. Cambridge: MIT Press, 1996. ix, 760. ISBN 0262061813. info
- WOLFE, Michael Joseph. High performance compilers for parallel computing. Redwood City: Addison-Wesley Publishing Company, 1996. xiii, 570. ISBN 0-8053-2730-4. info
- WILSON, Greg. Practical parallel programming. Cambridge: MIT Press, 1995. viii, 564. ISBN 0262231867. info
- DOWD, Kevin. High performance computing. Sebastopol: O'Reilly & Associates, 1993. xxv, 371 s. ISBN 1-56592-032-5. info
- Teaching methods
- Standard lecture, no drills nor homework
- Assessment methods
- No continuous evaluation during the semester, Only final exam in a written form (9 questions/subjects explicitly answered or discussed, total 100 points).
- Language of instruction
- Further comments (probably available only in Czech)
- Study Materials
The course is taught annually.
General note: Předmět byl dříve vypisován pod kódem IA039.