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Before choosing courseDN2230 Fast Numerical Algorithms for Large-Scale Problems 7.5 creditsAdministrate About course

The solution of realistic problems in science, engineering, and society requires computational methods which are well-adapted to the complexity of the computational tasks, despite the rapidly growing power of computer resources. The present course focuses on efficient numerical algorithms for large-scale problems.

Course offering missing for current semester as well as for previous and coming semesters
* Retrieved from Course syllabus DN2230 (Autumn 2009–)

Content and learning outcomes

Course contents

Fast multipole methods (FMM)

Krylov-type iteration methods for unsymmetric and nonlinear problems

Advanced topics in multigrid methods, hierarchical matrices

Wavelet methods

Intended learning outcomes

After having completed the course the student will understand general construction principles of fast numerical algorithms for large-scale problems, their properties and areas of applications. The student should be able to select, develop, and apply such methods in practical problems.

After the course you will be able to

  • analyze the specific properties relevant to the numerical solution of large-scale problems such that you can select and modify appropriately corresponding numerical methods;
  • analyze and follow the relevant research literature;
  • perform such computations, estimate the necesary computer resources, and judge the quality of the results; and
  • develop and implement algorithms adapted to a given problem starting from general construction principles.

Course Disposition

No information inserted

Literature and preparations

Specific prerequisites

Single course students: 90 university credits including 45 university credits in Mathematics or Information Technology. English B, or equivalent.

Recommended prerequisites

DN2221 (Applied Numerical Methods, part 1), and DN2222 (Applied numerical methods, part 2) or equivalent.


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Course literature will be announced at least 4 weeks before course start at course web page.

Examination and completion

If the course is discontinued, students may request to be examined during the following two academic years.

Grading scale

A, B, C, D, E, FX, F


  • HEM1 - Exercises, 4,0 hp, betygsskala: P, F
  • TEN1 - Examination, 3,5 hp, betygsskala: A, B, C, D, E, FX, 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.

In this course all the regulations of the code of honor at the School of Computer science and Communication apply, see:

Other requirements for final grade

Homework (LAB1; 3,75 cr)
Written examination (TEN1; 3,75 cr)

Opportunity to complete the requirements via supplementary examination

No information inserted

Opportunity to raise an approved grade via renewed examination

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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.

Further information

Course web

Further information about the course can be found on the Course web at the link below. Information on the Course web will later be moved to this site.

Course web DN2230

Offered by


Main field of study

No information inserted

Education cycle

Second cycle

Add-on studies

Please discuss with the instructor.


Elias Jarlebring, e-post: