Scientific Computing

2018/2019

Prerequisite/Recommended prerequisite for participation in the module

The module adds to the knowledge obtained in the 1st Semester.

Content, progress and pedagogy of the module

Learning objectives

Knowledge

  • Must have knowledge of computer architecture classification (Flynn’s taxonomy).
  • Must have knowledge about typical scientific computing problems with non-real-time constraints.
  • Must have knowledge of parallel computing techniques.
  • Must have knowledge of the relation between physical world problems and mathematical models.
  • Must have knowledge of different computational platforms for different types of scientific computing problems.

Skills

  • Must be able to select suitable hardware platforms for different computational problems.
  • Must be able to program solutions for scientific computing problems by use of various computational platforms (single and multi-core processing units, graphics processing units, compute clusters etc.).
  • Must be able to debug and performance optimize (e.g., time and/or memory consumption) the developed software.
  • Must be able to use various computing platforms to solve different scale computational problems.
  • Document the developed software including validation of the desired functionality.

Competences

  • Must be able to to solve problems where scientific computing is applied.
  • Using the above mentioned knowledge and skills, the student must be able to identify, prioritize, and apply in a structured manner the set of tasks needed for solving a scientific computing problem, which in its solution naturally involves or require high-performance simulation capabilities.
  • The student must be able to create and plan the work and development processes as needed for solving systematically such a problem.
  • The student must be able to select the most appropriate project management method(s) and tool(s) for solving the problem.
  • Must be able to initiate the above mentioned task independently, critically, and responsibly.

Type of instruction

As described in the introduction to Chapter 3.

Exam

Exams

Name of examScientific Computing
Type of exam
Oral exam based on a project
ECTS20
Assessment7-point grading scale
Type of gradingExternal examination
Criteria of assessmentAs stated in Joint Programme Regulations
http:/​/​www.en.tech.aau.dk/​education-programmes/​Education+and+Programmes/​

Facts about the module

Danish titleVidenskabelig beregning
Module codeESNSPAK2P1
Module typeProject
Duration1 semester
SemesterSpring
ECTS20
Empty-place SchemeYes
Location of the lectureCampus Aalborg
Responsible for the module

Organisation

Study BoardStudy Board of Electronics and IT
FacultyTechnical Faculty of IT and Design