Numerical Semiconductor Device and Process Simulation on Shared Memory Multiprocessors: Algorithms, Architectures, Results

Abstract

We present PARDISO, a new parallel sparse direct linear solver for large-scale parallel semiconductor device and process simulations on shared memory multiprocessors. Since robust transient 2-D and 3-D simulations necessitate large computing resources, the choice of architectures, algorithms and their implementations becomes of utmost importance. Sparse direct methods are the most robust methods over a wide range of numerical properties and therefore PARDISO has been integrated into complex semiconductor device and process simulation packages. We have investigated popular shared memory multiprocessors and the most popular numerical algorithms commonly used for the solution of the classical drift-diffusion and the diffusion-reaction equations in process simulation. The study includes a preconditioned iterative linear solver package and our parallel direct linear solver. Moreover, we have investigated the efficiency and the limits of our parallel approach. Results of several simulations of up to 100’000 vertices for three-dimensional device simulations are presented to illustrate our approach towards robust, parallel semiconductor device and process simulation.