Dear boost community, I would like to propose a project for the GSoC 2011, namely to improve the odeint library currently living in the boost sandbox [1] with the (optimistic) goal to put it on a level suitable for a boost review process. I have been working on this library for about one year now, although I couldn't spent much time on it during the last months. The other author of odeint is my colleague Karsten. We have had contact to this mailing list before [2], getting few, but rather positive feedback. The odeint library is a modern, template based, generic, C++ library for integrating (solving) initial value problems of ordinary differential equations. Such an ode is usually given as dx/dt = f(x,t) with x(t=0) = x0. x here is generally vector valued, possibly high dimensional. The easiest method to solve this problem is the Euler-method, where you introduce a small value Dt and then iterate x(t+Dt) = f(x,t)*Dt. Obviously, in real applications one uses more sophisticated methods, a well known class are the Runge-Kutta methods [3], suitable for many cases. Additionally, there exist special methods for system where the time evolution has conserved quantities, called symplectic methods. Furthermore there are methods for stiff systems and many others. For odeint, our first focus lies on Runge-Kutta methods. We have implemented several such methods together with error control routines and lately added dense output functionality. Our very recent code is a generic Runge-Kutta stepper that allows the user to build any Runge-Kutta method at compile time by providing the appropriate constants and is based on fusion::vectors. Karsten wrote a good article on that [4], unfortunately in German. There are also symplectic routines for Hamiltonian systems and we started to add implicit methods as well. We also have unit tests based on the boost test framework and some basic documentation. The library is currently at a level where it can be used in scientific applications and it is indeed in use by us and several other people in an academic environment. The major enhancement of our library over existing ones like gsl or methods from the numerical recipes is that our routines do not depend on the container type used to represent the vector x. So our library works with the usual std::vector<double> and array<double,N> but also with vector< complex<double> > (already a major improvement over gsl and nr, which we get for free, basically) and blitz++ arrays. The major strength of this approach, however, is seen when you want to solve odes on complex networks where you have to implement your own, non-trivial container type representing some kind of network. With odeint you can fully separate the network-implementation from the ode-solving algorithm. Furthermore, we are able to easily employ the power of CUDA devices to solve odes by the help of the thrust library and using thrust::device_vector as our container type. It is also possible to use odeint with arbitrary precision types like the gmp library. Some more, unfortunately slightly out-dated, information about odeint can be found in [5]. What are my plans for a GSoC? 1. There are still some parts of the library which are not satisfactorily designed and need to be rethought. This is where we could really need the help of an experienced mentor to create a clean, well structured library. 2. Add methods with varying order (burlisch stoer). 3. Add dense output and error control to the generic runge-kutta implementation. 4. Add convenience function that allow users an easier access to the libraries capabilities. 5. Create an observer interface that allows the user to analyze properties of the system while integrating the equations. 6. Make everything ready for a boos review. Points 1-5 can surely be realized during the GSoC period, I believe. And whatever time is left I will spend on documentation and review preparation. A few words to myself: I'm currently a PhD student in physics at the University of Potsdam working on problems in the field of nonlinear dynamics. Solving odes is basically every-day-work for me and I have a used many of the routines in odeint for my scientific research. Thanks for reading. I greatly appreciate any feedback! Regards, Mario Mulansky [1] https://svn.boost.org/svn/boost/sandbox/odeint/ [2] http://boost.2283326.n4.nabble.com/library-proposal-odeint-td2670019.html [3] http://en.wikipedia.org/wiki/Runge–Kutta_methods [4] http://www.c-plusplus.de/forum/282091 [5] http://www.codeproject.com/KB/recipes/odeint.aspx