IA039 Supercomputer Architecture and Intensive Computations

Faculty of Informatics
Spring 2011
Extent and Intensity
2/0. 2 credit(s) (plus extra credits for completion). Type of Completion: zk (examination).
Teacher(s)
prof. RNDr. Luděk Matyska, CSc. (lecturer)
doc. RNDr. Jiří Filipovič, Ph.D. (lecturer)
Guaranteed by
prof. RNDr. Václav Matyáš, M.Sc., Ph.D.
Department of Computer Systems and Communications – Faculty of Informatics
Contact Person: prof. RNDr. Luděk Matyska, CSc.
Timetable
Fri 10:00–11:50 D3
Prerequisites
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
Course objectives
Main goal of this lecture is to provide information about supercomputing architectures and basic programming methods for vector and parallel computers. First part focuses to the hardware, during the second part general optimization methods and programming methodology for parallel computer is discussed. The last part of the lecture is aimed to distributed systems.
Graduate will be able to understand and explain properties of modern processors.
Graduate will be also able to analyze the program code and propose optimizations for a particular processor.
Graduate will be able to design and implement a simple parallel program to solve a particular problem.
Graduate will be able to design and realize benchmarks of computer systems or applications.
Graduate will be able to design a specially optimized system fo a concrete application.
Syllabus
  • High performance vector and superscalar processors.
  • Uniprocesor computers, computers with small number of processors, massively parallel computers; distributed systems.
  • Performance measurements, LINPACK test, TOP 500 list.
  • High performance uniprocessor systems, programming languages, methodology of efficient program writting, 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, decompozition of algorithms, basis optimization methods for 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.
Literature
  • 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 home work
Assessment methods
No continuous evaluation during the semester, Only final exam in a written form (11 questions/subjects explicitly answered or discussed, total 110 points).
Language of instruction
Czech
Further Comments
Study Materials
The course is taught annually.
Teacher's information
http://www.ics.muni.cz/people/matyska/vyuka/hpc/hpc.html
The course is also listed under the following terms Spring 2004, Spring 2006, Spring 2007, Spring 2008, Spring 2009, Spring 2010, Spring 2012, Spring 2013.
  • Enrolment Statistics (Spring 2011, recent)
  • Permalink: https://is.muni.cz/course/fi/spring2011/IA039