Not only are there few, their numbers are growing much more slowly than traditional C/Fortan/MPI environments. The "massive" in massively parallel is getting more and more massive every year. Running computations at full speed at these scales, 100K+ cores in multiple levels of hierarchy (same die, same board, same blade, same switch, etc) is a hugely mundane architectural problem. Not only is there no architecture besides MPI which has nearly as much effort invested in this problem, none are currently making the investment, so none have a chance to catch up within the next decade. The only way you will see FP doing massive parallelism at speeds even close to current best is if they wrap the C MPI interface, and I have yet to see any functional message-passing APIs which aren't tarted-up imperative environments. (If anyone knows any please share.) At it's core, message passing programming involves managing data, deciding where it resides and where it needs to go, which is kind of antithetical to FP.
You mention MapReduce, which I think is more of a data-center thing subtly but fundamentally different from HPC, involving less computation and more I/O. FP has a good shot there (cf. Erlang) but not much chance at cracking the HPC market.