  ChaNGa is an N-body cosmology simulation application implemented using
Charm++. In this paper, we present the parallel design of ChaNGa and address
many challenges arising due to the high dynamic ranges of clustered datasets.
We focus on optimizations based on adaptive techniques for scaling to more than
128K cores. We demonstrate strong scaling on up to 512K cores of Blue Waters
evolving 12 and 24 billion particles. We also show strong scaling of highly
clustered datasets on up to 128K cores.
