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Publications of SPCL
|A. Nikolaos Ziogas, T. Ben-Nun, G. Indalecio Fernández, T. Schneider, M. Luisier, T. Hoefler:|
|A Data-Centric Approach to Extreme-Scale Ab initio Dissipative Quantum Transport Simulations|
(In Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis (SC19), Nov. 2019)
Won ACM Gordon Bell Prize
AbstractThe 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 cen- tric 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. The resulting code has been tuned for two top-6 hybrid supercomputers, reaching a sus- tained performance of 85.45 Pflop/s on 4,560 nodes of Summit (42.55% of the peak) in double precision, and 90.89 Pflop/s in mixed precision. These computational achievements enable the restruc- tured QT simulator to treat realistic nanoelectronic devices made of more than 10,000 atoms within a 14× shorter duration than the original code needs to handle a system with 1,000 atoms, on the same number of CPUs/GPUs and with the same physical accuracy.
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