Parallel and Distributed Programming

5 credits

Syllabus, Master's level, 1TD070

A revised version of the syllabus is available.

Code: 1TD070
Education cycle: Second cycle
Main field(s) of study and in-depth level: Computational Science A1F, Computer Science A1F, Technology A1F
Grading system: Fail (U), Pass (3), Pass with credit (4), Pass with distinction (5)
Finalised by: The Faculty Board of Science and Technology, 10 March 2016
Responsible department: Department of Information Technology

Entry requirements

120 credits in science/engineering. High Performance Programming, 10 credits (or Low-level Parallel Programming, 5 credits, and Scientific Computing and Calculus, 10 credits, where the latter may be included in the 120 credits).

Learning outcomes

To pass, the student should be able to

develop programs with distributed parallelism, parallel debugging included;
construct parallel algorithms, i.e. identify parallelism in a given algorithm and implement it;
analyse properties such as efficiency, speedup etc., of parallel algorithms;
analyse performance of parallel algorithms.

Content

Classification of parallel computers: different kinds of memory organisations, processors, networks and program control flow. Different kinds of parallelism. MPI (Message Passing Interface) programming and data partitioning. Parallelisation of fundamental algorithms in numerical linear algebra and scientific computing: matrix-vector multiplication, matrix-matrix multiplication, FFT (Fast Fourier Transform), N-body simulation, graph algorithms.

Instruction

Lectures, computer labs, assignments and project assignments.

Assessment

Assignments and project presented both as written reports and oral presentations.