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A Data-Centric Approach to Extreme-Scale Ab initio Dissipative Quantum Transport Simulations

Alexandros Ziogas from ETH Zurich gave this talk at Supercomputing Frontiers Europe. “The computational efficiency of a state of the art ab initio #quantum transport (QT) solver, capable of revealing the coupled electro-thermal properties of atomically-resolved nano-transistors, has been improved by up to two orders of magnitude through a data centric reorganization of the application. The approach yields coarse-and fine-grained data-movement characteristics that can be used for performance and communication modeling, communication-avoidance, and dataflow transformations.”