TDDE65 · 6 credits · Advanced level (A1N) · Datateknik, Datavetenskap
Programming of Parallel Computers - Methods and Tools
Active · next start VT 2027
71%
passed the latest ordinary exam
TEN1 · 3 Jun 2026 · 21 students
79%
passed the ordinary exams, all sittings over the last 5 years
TEN1 · 81 students
83%
Harder than 83% of courses at advanced level
Compared with 285 courses at the same level, ordinary exams over the last three academic years. 52 students.
Part of 9 programmes
- Master of Science in Computer Science and Engineering
- Master of Science in Industrial Engineering and Management - International
- Master of Science in Industrial Engineering and Management
- Master of Science in Information Technology
- Master of Science in Computer Science and Software Engineering
- Master of Science in Applied Physics and Electrical Engineering - International
- Master of Science in Applied Physics and Electrical Engineering
- Master's Programme in Computer Science
- Master's Programme in Mathematics
Exam
TEN1 Written examination
- 5
- 4
- 3
- U
Ordinary exams
79% passed · 81 students
- 71%21
- 71%31
- 93%29
Re-exams
70% passed · 10 students
- 80%5
- 60%5
- Pass the re-exam: 70% (10 students), compared with 79% (81 students) on the ordinary exam
- Get 4 or 5: 34% (91 students)
Show small sittings (3)
Sittings with fewer than 5 students, often credit transfers or special sittings. They are not part of any figure on this page.
- 100%3
- 50%2
- 0%1
Other modules
Partial exams, hand-ins and labs. They are not part of the figures at the top.
Hand-in or lab
LAB1 Laboratory work
- G
Main rounds
100% passed · 60 students
- 100%26
- 100%34
Later rounds
100% passed · 20 students
- 100%20
- Pass a later round: 100% (20 students), compared with 100% (60 students) on the ordinary exam
Show small sittings (2)
Sittings with fewer than 5 students, often credit transfers or special sittings. They are not part of any figure on this page.
- 100%2
- 100%1
About the course
Aim
Parallel computers are used for heavy computations. The student should acquire knowledge about the programming of parallel computers and master selected methods and tools. The course shall also give an overview of how parallel computers can be used in some application areas, such as image analysis and scientific computations. After the course the student is expected to be able to 1) use efficient methods and languages for the programming of parallel computers, 2) program parallel computers with distributed memory (MPI) and shared memory (OpenMP).
Content
Parallel computer architecture: memory hierarchies, shared memory and distributed memory architectures. Vector instructions. Parallel execution models and programming languages. Performance measurements and enhancement. Message passing, multithreaded and dataparallel programming. Design and analysis of fundamental parallel algorithms. Time complexity. Scalability. Scheduling of parallel programs. Grid computing. Tools for parallel programming. MPI (Message passing interface) and OpenMP. Basic parallel algorithms and BLAS (Basic Linear Algebra Subprograms). Application areas. Parallel solving of equation systems. The laboratory course gives practical experience in programming parallel systems (different programming paradigms are used).
- Examiner
- Christoph Kessler
- Scheduled hours
- 52 h
- Main field of study
- Datateknik, Datavetenskap