Numerical Methods For Solution of Differential Equations  Tobias Ritschel
 Abstract  RungeKutta methods are used to numerically approximate solutions to initial value problems, which may be used to simulate, for instance, a biological system described by ordinary differential equations. Simulations of such system may be used to test different control strategies and serve as an inexpensive alternative to reallife testing.
In this thesis a toolbox is developed in C and Matlab containing effective numerical RungeKutta methods. Testing thse methods on the time it takes to
simulate a system for a large set of parameters showed that some methods performed well in some cases whereas others were faster in others such that not one method outbested the others. Carrying out the same tests using parallel simulations showed that a speedup of between 11 and 12 is possible in Matlab and in C when using 12 processes, and that different implementations of parallel simulations in C, are suitable for different number of processes.
In all aspects, simulations were obtained much faster in C compared to Matlab.  Type  Bachelor thesis [Academic thesis]  Year  2013  Publisher  Technical University of Denmark, DTU Compute, Email: compute@compute.dtu.dk  Address  Matematiktorvet, Building 303B, DK2800 Kgs. Lyngby, Denmark  Series  B.Sc.201316  Note   Electronic version(s)  [pdf]  Publication link  http://www.compute.dtu.dk/English.aspx  BibTeX data  [bibtex]  IMM Group(s)  Scientific Computing 
