[wladimir]

Have you looked at Theano ( http://deeplearning.net/software/theano/ ) ? It is a Python-based JIT for GPUs. Using Python you can build the computation pipeline symbolically, and the formulas are automatically converted to GPU code and scheduled as deemed fit (this can be extended to multiple GPUs, and could theoretically scale to an even higher level).

I think this is a promising idea for the future of array-oriented computing, as it can make use of one more level of parallelism / scaling than the current Numpy paradigm, which is limited to one operation at a time and the user providing the ordering of operations.