AMDG The review of Karsten Ahnert and Mario Mulansky's ODEInt library will end tomorrow. Only a few reviews have been submitted so far. If you plan to submit a review, please let me know. If anyone needs more time, we can see about extending the review period. -------------------------------------- About the library: odeint provides routines for numerically solving Ordinary Differential Equations, a task heavily required when approaching scientific problems numerically. In odeint we have implemented the most common algorithms in a modern, generic way which provides several advantages over existing implementations. The main focus of odeint is to separate algorithms from the underlying basic computation unit. This allows for example to easily use the power of modern GPUs via CUDA or OpenCL to speed up computational heavy simulations. Features: - provides most of the standard algorithms, including step size control, dense ouput and extrapolation routines - symplectic routines for Hamiltonian systems - implicit routines based on boost::ublas (MTL4 in progress) - high level integrate functions - interchangeable computation backend with existing bindings to CUDA and OpenCL - native support of ODEs defined for complex values - support of Boost.Units in most of the algorithms - support of arbitrary precision types You can download the library and view the documentation here: zip: http://github.com/headmyshoulder/odeint-v2/zipball/master github: http://headmyshoulder.github.com/odeint-v2/ docs: http://headmyshoulder.github.com/odeint-v2/doc/index.html -------------------------------------- Please always state in your review, whether you think the library should be accepted as a Boost library! Additionally please consider giving feedback on the following general topics: - What is your evaluation of the design? - What is your evaluation of the implementation? - What is your evaluation of the documentation? - What is your evaluation of the potential usefulness of the library? - Did you try to use the library? With what compiler? Did you have any problems? - How much effort did you put into your evaluation? A glance? A quick reading? In-depth study? - Are you knowledgeable about the problem domain? In Christ, Steven Watanabe