191.114 Basics of Parallel Computing
This course is in all assigned curricula part of the STEOP.
This course is in at least 1 assigned curriculum part of the STEOP.

2023S, VU, 2.0h, 3.0EC
TUWEL

Properties

  • Semester hours: 2.0
  • Credits: 3.0
  • Type: VU Lecture and Exercise
  • Format: Presence

Learning outcomes

After successful completion of the course, students are able to

  • Understand and express asymptotic running time and work of parallel algorithms
  • Understand and appreciate characteristics of thread models for parallel computing
  • Read and write programs in OpenMP
  • Read and write programs in MPI
  • Understand and appreciate task parallel models for parallel computing

Subject of course

Motivation and goals of parallel computing, parallel computer architectures, programming models, performance measurement and analysis, introduction to programming paradigms such as MPI (Message Passing Interface), Pthreads, and OpenMP. Other aspects and languages for programming multi-core processors.

Teaching methods

Lectures, assignments

Mode of examination

Immanent

Additional information

ECTS Breakdown:

  • Lectures: 1,5 ECTS
  • Assignments: 1,5 ECTS
  • Lectures 8x2h = 16h
  • Self-study  37h
  • Assignments 2x10h = 20h
  • Written exam 2h = 2h

 Total: 75h = 3 ECTS

 

Lecturers

Institute

Course dates

DayTimeDateLocationDescription
Thu10:00 - 12:0002.03.2023 - 22.06.2023EI 4 Reithoffer HS Lecture
Basics of Parallel Computing - Single appointments
DayDateTimeLocationDescription
Thu02.03.202310:00 - 12:00EI 4 Reithoffer HS Lecture
Thu20.04.202310:00 - 12:00EI 4 Reithoffer HS Lecture
Thu25.05.202310:00 - 12:00EI 4 Reithoffer HS Lecture
Thu22.06.202310:00 - 12:00EI 4 Reithoffer HS Lecture

Examination modalities

Part 1: Completing assignments
Part 2: Exam

Case 1:  in-classroom exams possible
- mode: written exam, closed book

Case 2:  in-classroom exam impossible
- mode: written / open book
- type: TUWEL quiz
- infrastructure required: Computer with Internet connection, webcam

 

Exams

DayTimeDateRoomMode of examinationApplication timeApplication modeExam
Thu10:00 - 12:0027.06.2024FH Hörsaal 3 - MATH assessed01.06.2024 00:00 - 26.06.2024 23:59TISSExam 1

Course registration

Begin End Deregistration end
17.02.2023 08:00 15.03.2023 23:59 20.04.2023 23:59

Curricula

Study CodeObligationSemesterPrecon.Info
066 645 Data Science Not specified

Literature

No lecture notes are available.

Previous knowledge

Knowledge of programming languages, computer architectures, operating systems. Basic Algorithms and Datastructures (asymptotic worst-case analysis).

Programming skills, e.g., in C/C++, Java, or Python.

Continuative courses

Language

English