LAPACK Users' guide (third ed.)
LAPACK Users' guide (third ed.)
SuperLU_DIST: A scalable distributed-memory sparse direct solver for unsymmetric linear systems
ACM Transactions on Mathematical Software (TOMS)
A column pre-ordering strategy for the unsymmetric-pattern multifrontal method
ACM Transactions on Mathematical Software (TOMS)
Silicon CMOS devices beyond scaling
IBM Journal of Research and Development - Advanced silicon technology
A multi-level parallel simulation approach to electron transport in nano-scale transistors
Proceedings of the 2008 ACM/IEEE conference on Supercomputing
A Parallel Sparse Linear Solver for Nearest-Neighbor Tight-Binding Problems
Euro-Par '08 Proceedings of the 14th international Euro-Par conference on Parallel Processing
A hybrid method for the parallel computation of Green's functions
Journal of Computational Physics
A Parallel Implementation of Electron-Phonon Scattering in Nanoelectronic Devices up to 95k Cores
Proceedings of the 2010 ACM/IEEE International Conference for High Performance Computing, Networking, Storage and Analysis
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We present a multi-dimensional, atomistic, quantum transport simulation approach to investigate the performances of realistic nanoscale transistors for various geometries and material systems. The central computation consists in solving the Schrödinger equation with open boundary conditions several thousand times. To do that, a Wave Function approach is used since it can be relatively easily parallelized. To further improve the computational efficiency, three additional levels of parallelization are identified, the work load is optimally balanced between the CPUs, computational interleaving is applied where possible, and a mixed precision scheme is introduced. Using two different device types, a high electron mobility and a band-to-band tunneling transistor, sustained performances up to 1.28 PFlop/s in double precision (55% of the peak performance) and 1.44 PFlop/s in mixed precision are reached on 221,400 cores on the CRAY-XT5 Jaguar at Oak Ridge National Lab.