The Brian simulator is designed to be a simulator written entirely in python. To cope with the speed of C/C++-based simulators, Brian can generate compiled code from the python network model. This code can also be compiled for graphics processors (GPUs), which promise high speedups for computational problems that can be parallelized efficiently. The Brian developers describe how to do just that in their article on vectorized algorithms for neuronal simulations, which is one of my current favorite papers.

Today, and that was the initial motivation for this post, I came across the announcement for the new version of Theano, a compiler for evaluation mathematical expressions on CPUs and GPUs. I haven't tried it out yet, but it looks definitely promising. But the really interesting fact is that there is vivid development toward making Python not only an ubiquitous language for scientific computing (a goal which has largely been achieved already), but also an alternative in terms of performance to established software packages.

Without licence fees, and fully open source.