Course detail

Practical Parallel Programming

FIT-PPPAcad. year: 2019/2020

The course covers architecture and programming of parallel systems with functional and data parallelism. First, the parallel system theory and program parallelization are discussed. The detailed description of most proliferated supercomputing systems, interconnection network typologies and routing algorithms is followed by the architecture of parallel and distributed storage systems. The course goes on in message passing programming in standardized interface MPI. Consequently, techniques for parallel debugging and profiling are discussed. Last part of the course is devoted to the description of parallel programming patterns and case studies from the are of linear algebra, physical systems described by partial differential equations, N-Body systems and Monte-Carlo methods. 

Language of instruction

Czech

Number of ECTS credits

5

Mode of study

Not applicable.

Guarantor

doc. Ing. Jiří Jaroš, Ph.D.

Department

Department of Computer Systems (UPSY)

Learning outcomes of the course unit

Overview of principles of current parallel system design and of interconnection networks, communication techniques and algorithms. Survey of parallelization techniques of fundamental scientific problems, knowledge of parallel programming in MPI. Knowledge of basic parallel programming patterns. Practical experience with the work on supercomputers, ability to identify performance issues and propose their solution.
Knowledge of capabilities and limitations of parallel processing, ability to estimate performance of parallel applications. Language means for process/thread communication and synchronization. Competence in hardware-software platforms for high-performance computing and simulations.

Prerequisites

Von-Neumann computer architecture, computer memory hierarchy, cache memories and their organization, programming in assembly and in C/C++. Knowledge gained in courses PRL and AVS.

Co-requisites

Not applicable.

Planned learning activities and teaching methods

Not applicable.

Assesment methods and criteria linked to learning outcomes

Assessment of a project, 10 hours in total and a midterm examination.
Exam prerequisites:
To get 20 out of 40 points for projects and midterm examination.

Course curriculum

Not applicable.

Work placements

Not applicable.

Aims

To get familiar with the architecture of distributed supercomputing systems, their interconnection networks and storage. To orientate oneself in parallel systems on the market, be able to assess communication and computing possibilities of a particular architecture and to predict the performance of parallel applications. Learn how to write portable programs using standardized interfaces and languages, specify parallelism and process communication. To learn how to practically use supercoputer for solving complex engineering problems.

Specification of controlled education, way of implementation and compensation for absences

  • Missed labs can be substituted in alternative dates (monday or friday)
  • There will be a place for missed labs in the last week of the semester.

Recommended optional programme components

Not applicable.

Prerequisites and corequisites

Not applicable.

Basic literature

Not applicable.

Recommended reading

Alternativní kurz o paralelním programování http://www.cs.kent.edu/~jbaker/ParallelProg-Sp11/
MPI Tutoriál: http://mpitutorial.com/

Classification of course in study plans

  • Programme IT-MSC-2 Master's

    branch MBI , 0 year of study, summer semester, compulsory-optional
    branch MSK , 1 year of study, summer semester, compulsory
    branch MMM , 0 year of study, summer semester, elective
    branch MBS , 0 year of study, summer semester, elective
    branch MPV , 1 year of study, summer semester, compulsory
    branch MIS , 0 year of study, summer semester, elective
    branch MIN , 0 year of study, summer semester, elective
    branch MGM , 0 year of study, summer semester, compulsory-optional

  • Programme MITAI Master's

    specialization NBIO , 0 year of study, summer semester, compulsory
    specialization NHPC , 1 year of study, summer semester, compulsory
    specialization NEMB , 2 year of study, summer semester, compulsory
    specialization NSEN , 0 year of study, summer semester, elective
    specialization NVIZ , 0 year of study, summer semester, elective
    specialization NGRI , 0 year of study, summer semester, elective
    specialization NISD , 0 year of study, summer semester, elective
    specialization NSEC , 0 year of study, summer semester, elective
    specialization NCPS , 0 year of study, summer semester, elective
    specialization NNET , 0 year of study, summer semester, elective
    specialization NMAL , 0 year of study, summer semester, elective
    specialization NVER , 0 year of study, summer semester, elective
    specialization NIDE , 0 year of study, summer semester, elective
    specialization NSPE , 0 year of study, summer semester, elective
    specialization NADE , 0 year of study, summer semester, elective
    specialization NMAT , 0 year of study, summer semester, elective
    specialization NISY , 0 year of study, summer semester, elective

Type of course unit

 

Lecture

26 hod., optionally

Teacher / Lecturer

doc. Ing. Jiří Jaroš, Ph.D.

Syllabus

  1. Introduction to parallel processing.
  2. Architectures with distributed memory,
  3. Interconnection networks: topology and routing algorithms, switching, flow control.
  4. Technologies of interconnection networks (Infiniband).
  5. Distributed file systems (Lustre, HPFS).
  6. Message passing interface, pair-wise communications, data types
  7. Collective communications and communicators,
  8. Hybrid programming OpenMP/MPI and one-sided communications.
  9. Parallel code debugging, profiling and tracing. 
  10. Programming patterns for parallel programming.
  11. Case studies: matrix calculations, linear equation systems 
  12. Case studies: solution of PDE systems, finite difference, spectral methods
  13. Case studies: Fluid dynamics, N-Body systems, Monte-Carlo.

Exercise in computer lab

16 hod., compulsory

Teacher / Lecturer

Ing. Filip Vaverka, Ph.D.

Syllabus

  1. MPI: Point-to-point communications
  2. MPI: Collective communications
  3. MPI: Communicators
  4. MPI: Data types, reduction
  5. MPI: Parallel input and output
  6. Profiling and tracing of parallel applications
  7. Matrix calculations.
  8. Finite difference methods.

Project

10 hod., compulsory

Teacher / Lecturer

Ing. Filip Vaverka, Ph.D.

Syllabus

  • A parallel program in MPI on the supercomputer.