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 Stochas-tic ALgorithms for
Ultra-fast Transport in sEmiconductors (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.