ANSWERS - Accelerating nano-device simulations with extreme-scale algorithms and software co-integration
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Abstract
Nanosizing has revolutionized the design of electronic components to the point where their material properties and atomic configuration almost entirely determine their functionality. To accelerate the emergence of novel device concepts, advanced simulation tools relying on quantum mechanics and treating the different material regions at the atomic scale are needed. Electronic structure calculators and quantum transport simulators have established themselves as powerful engines to study the equilibrium and out-of-equilibrium properties of nanostructures. However, both approaches suffers from the same deficiencies: they are usually limited to small atomic systems and they are subject to lame compromises between short simulation times (empirical models) and accurate results (ab-initio approaches). These restrictions are mainly due to the underlying numerical algorithms, matrix diagonalizations for electronic structure calculations and sparse linear systems of equations for quantum transport problems, that do not scale well on large core numbers and poorly exploit the available computational resources.
This project is supported by the Swiss Platform for Advanced Scientific Computing (PASC).
Additional information
Publications
- Luisier M., Ducry . F., Hossein . M. ., Hashemia B., Brück S. ., Calderara M., Schenk O. (2018) Advanced Algorithms for Ab-initio Device Simulations. IEEE Xplore:. IEEE Xplore. 2018 International Conference on Simulation of Semiconductor Processes and Devices (SISPAD). Austin, TX, USA, USA. 24-26 Sept. 2018
- Simpson T., Pasadakis D., Kourounis D., Fujita K., Yamaguchi T. ., Ichimura T. ., Schenk O. (2018) Balanced Graph Partition Refinement using the Graph p-Laplacian. Proceedings of the ACM Platform for Advanced Scientific Computing Conference. ACM. PASC’18. Platform for Advanced Scientific Computing Conference (PASC). Basel. July 02 - 04, 2018
- Petra C. G., Schenk O., Lubin M., Gaertner K. (2014) An Augmented Incomplete Factorization Approach for Computing the Schur Complement in Stochastic Optimization, SIAM Journal on Scientific Computing:C139-C162
- Petra C. G. ., Schenk O., Anitescu M. (2014) Real-Time Stochastic Optimization of Complex Energy Systems on High-Performance Computers, Computing in Science Engineering:32-42