  Designing efficient cooling systems for integrated circuits (ICs) relies on a
deep understanding of the electro-thermal properties of transistors. To shed
light on this issue in currently fabricated FinFETs, a quantum mechanical
solver capable of revealing atomically-resolved electron and phonon transport
phenomena from first-principles is required. In this paper, we consider a
global, data-centric view of a state-of-the-art quantum transport simulator to
optimize its execution on supercomputers. The approach yields coarse- and
fine-grained data-movement characteristics, which are used for performance and
communication modeling, communication-avoidance, and data-layout
transformations. The transformations are tuned for the Piz Daint and Summit
supercomputers, where each platform requires different caching and fusion
strategies to perform optimally. The presented results make ab initio device
simulation enter a new era, where nanostructures composed of over 10,000 atoms
can be investigated at an unprecedented level of accuracy, paving the way for
better heat management in next-generation ICs.
