Monte Carlo Methods for Electron Transport: Scalability Study

The Monte Carlo methods (MCMs) are very convenient for parallel implementation because in many cases they can use powerful High performance computing (HPC) resources for achieving accurate results without losing their parallel efficiency. This advantage of MCMs is used by the scientists for solving large-scale mathematical problems derived from the life science, finances, computational physics, computational chemistry, and many other fields. In this work we consider a Monte Carlo method for solving quantum-kinetic integral equations describing electron transport in semiconductors. The presented algorithm is a part of set of algorithms involved in SET (Simulation of Electron Transport) application which is developed by our team. The SET application can be successfully used to support simulation of semiconductor devices at the nano-scale as well as other problems in computational electronics. Here we study scalability of the presented a Monte Carlo algorithm using Bulgarian HPC resources. Numerical results for parallel efficiency and computational cost are also presented. In addition we discuss the coordinated use of heterogeneous HPC resources from one and the same application in order to achieve a good performance.