CPU is supported through OpenCL by these libraries. Remember, OpenCL code can run on CPUs. As for Aura, it is pre-alpha, not a lot of functionality there yet, I'm still figuring out the interface. So not usable yet, but keep an eye on it, it will be.
For me, the most important thing in both CUDA and OpenCL is the programming model. It allows us to describe data parallel problems and related data (in)dependence explicitly. Compilers should be (and already are) able to generate efficient code from this. It is not as nice as it could be, we have to write kernels by hand etc. But there are libraries that make our lives easier (we discussed them earlier). And there is also C++ AMP which tries to integrate better. Yet still, while we have all these options and we can solve most of our problems with more or less effort and elegance, I believe there must be something better out there: the right way to describe data parallel and task parallel problems as well as concurrency etc. Maybe the FP guys are on to something, I don't know. I'll be on the lookout.
[0] http://www.pds.ewi.tudelft.nl/fileadmin/pds/homepages/shenji... [1] http://comparch.gatech.edu/hparch/papers/lee_plc2013.pdf