Ultra-fast Carrier Transport Simulation on the Grid. Quasi-Random Approach

Abstract

The problem for simulation ultra-fast carrier transport in nano-electronics devices is a large scale computational problem and requires HPC and/or Grid computing resources. The most widely used techniques for modeling this carrier transport are Monte Carlo methods. In this work we consider a set of stochastic algorithms for solving quantum kinetic equations describing quantum effects during the femtosecond relaxation process due to electron-phonon interaction in one-band semiconductors or quantum wires. The algorithms are integrated in a Grid-enabled package named S tochas-tic A Lgorithms for U ltra-fast T ransport in s E miconductors (SALUTE). There are two main reasons for running this package on the computational Grid: (i) quantum problems are very computationally intensive; (ii) the inherently parallel nature of Monte Carlo applications makes efficient use of Grid resources. Grid (distributed) Monte Carlo applications require that the underlying random number streams in each subtask are independent in a statistical sense. The efficient application of quasi-Monte Carlo algorithms entails additional difficulties due to the possibility of job failures and the inhomogeneous nature of the Grid resource. In this paper we study the quasi-random approach in SALUTE and the performance of the corresponding algorithms on the grid, using the scrambled Halton, Sobol and Niederreiter sequences. A large number of tests have been performed on the EGEE and SEEGRID grid infrastructures using specially developed grid implementation scheme. Novel results for energy and density distribution, obtained in the inhomogeneous case with applied electric field are presented.