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Object-oriented programming, basic notions in, and syntax of, C++
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Objects, classes and its definition, constructors and destructors
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Operators, operator overloading, polymorphism
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Basics of abstract classes, inheritance, generic programming
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Selected components of the C++ standard library
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Structured and unstructured grids, data structures for their implementation
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Implementation of numerical methods for partial differential equations
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Efficient implementation of numerical algorithms
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Finite difference methods on structured grids.
FSF3565 Program Construction in C++ for Scientific Computing 7.5 credits
Information per course offering
Information for Autumn 2024 Start 26 Aug 2024 programme students
- Course location
KTH Campus
- Duration
- 26 Aug 2024 - 13 Jan 2025
- Periods
- P1 (3.5 hp), P2 (4.0 hp)
- Pace of study
25%
- Application code
51000
- Form of study
Normal Daytime
- Language of instruction
English
- Course memo
- Course memo is not published
- Number of places
Places are not limited
- Target group
Only PhD
- Planned modular schedule
- [object Object]
- Schedule
- Part of programme
- No information inserted
Contact
Course syllabus as PDF
Please note: all information from the Course syllabus is available on this page in an accessible format.
Course syllabus FSF3565 (Spring 2019–)Content and learning outcomes
Course contents
Intended learning outcomes
The aim of the course consists of providing knowledge how advanced numerical methods and complex algorithms in Scientific Computing can be implemented in C++.
After completion of the course the students can:
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Construct simple classes for often used mathematical objects;
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Create abstract classes and define simple template classes;
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Implement data structures for manipulating realistic geometry and complex grids for numerically solving partial differential equations;
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Optimize data structures and algorithms in C++ with respect to efficient computations for large-scale problems;
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Implement finite difference methods on structured grids.
Literature and preparations
Specific prerequisites
A Master degree including at least 45 university credits (hp) in in Mathematics (including differential equations and numerical analysis) and Computer Science (including programming). Moreover, English B or equivalent is required.
Recommended prerequisites
Advanced course in numerical analysis (SF2520 or equivalent)
Equipment
Literature
To be announced at least 4 weeks before the course starts.
Examination and completion
If the course is discontinued, students may request to be examined during the following two academic years.
Grading scale
Examination
- PRO1 - Project work, 3.5 credits, grading scale: P, F
- TEN1 - Written exam, 4.0 credits, grading scale: P, F
Based on recommendation from KTH’s coordinator for disabilities, the examiner will decide how to adapt an examination for students with documented disability.
The examiner may apply another examination format when re-examining individual students.
Projects reports
Written examination
Other requirements for final grade
Projects reports accepted.
Written examination passed.
Opportunity to complete the requirements via supplementary examination
Opportunity to raise an approved grade via renewed examination
Examiner
Ethical approach
- All members of a group are responsible for the group's work.
- In any assessment, every student shall honestly disclose any help received and sources used.
- In an oral assessment, every student shall be able to present and answer questions about the entire assignment and solution.