Existing high-level, source-to-source compilers can accept input programs in a high-level language (e.g., C) and perform complex automatic parallelization and other mappings using various optimizations. These optimizations often require trade-offs and can benefit from the user's involvement in the process. However, because of the inherent complexity, the barrier to entry for new users of these high-level optimizing compilers can often be high. We propose visualization as an effective gateway for non-expert users to gain insight into the effects of parameter choices and so aid them in the selection of levels best suited to their specific optimization goals.

The origin of mass is one of the deepest mysteries in science. Neutrons and protons, which account for almost all visible mass in the Universe, emerged from a primordial plasma through a cataclysmic phase transition microseconds after the Big Bang. However, most mass in the Universe is invisible. The existence of dark matter, which interacts with our world so weakly that it is essentially undetectable, has been established from its galactic-scale gravitational effects. Here we describe results from the first truly physical calculations of the cosmic phase transition and a groundbreaking first-principles investigation into composite dark matter, studies impossible with previous state-of-the-art methods and resources. By inventing a powerful new algorithm, "DSDR," and implementing it effectively for contemporary supercomputers, we attain excellent strong scaling, perfect weak scaling to the LLNL BlueGene/Q two million cores, sustained speed of 7.2 petaflops, and time-to-solution speedup of more than 200 over the previous state-of-the-art.