  We discuss an implementation of adaptive fast multipole methods targeting
hybrid multicore CPU- and GPU-systems. From previous experiences with the
computational profile of our version of the fast multipole algorithm, suitable
parts are off-loaded to the GPU, while the remaining parts are threaded and
executed concurrently by the CPU. The parameters defining the algorithm affects
the performance and by measuring this effect we are able to dynamically balance
the algorithm towards optimal performance. Our setup uses the dynamic nature of
the computations and is therefore of general character.
