[R-sig-dyn-mod] R vs. fortran for simulation

[Thomas Petzoldt]

Dear Miachael,

first of all: I agree completely with Stephen Ellner and had exactly the 
same experience with both ODE/PDEs and ABMs:

1) Models in R run slower than C/C++ or Fortran, butprogramming in R is 
much faster than in C.

2) You can always implement time-critical parts (and only these!) in C 
or Fortran and then link this to R for data management and visualization 
-- and you do nothing wrong if you implement your first prototypes in 
pure R.

For ABMs, I use data frames for the individuals, so can use R's 
vectorized facilities in a very natural and seemingly quasi-parallel 
way. Just do computations on the whole data frame or use subset, see
http://www.jstatsoft.org/v22/i09


Examples of dynamic models implemented in R vs. C/Fortran and can be 
found in several conference talks and papers, including an extensive 
discussion of performance issues:


Soetaert, K. Petzoldt, T. & Setzer, R. W. (2010): Solving differential 
equations in R: package deSolve. Journal of Statistical Software 33(9), 
1-25. http://www.jstatsoft.org/v33/i09

Petzoldt T. (2009): Dynamic simulation models - is R powerful enough? 
UseR!2009, July 8-10, Rennes, France
http://www.agrocampus-ouest.fr/math/useR-2009/slides/Petzoldt.pdf

Petzoldt, T. and Soetaert, K. (2011): Using R for Systems Understanding 
- A Dynamic Approach. UseR!2011, August 16-18, University of Warwick, 
Coventry, UK,
http://desolve.r-forge.r-project.org/slides/petz_soet2011.pdf


... and even more about this can be found on:
http://desolve.r-forge.r-project.org/



Thank you for asking this question

Thomas P.