Presents the use of parallel processors for the solution of drift-diffusion semiconductor device equations using an irregular grid discretization. Preconditioning, partitioning and communication scheduling algorithms are developed to implement an efficient and robust iterative linear solver with preconditioning. The parallel program is executed on a 64-node CM-5 and is compared with PILS (a solver for ill-conditioned systems) running on a single processor. We observe an efficiency increase in obtaining parallel speed-ups as the problem size increases. We obtain 60% efficiency for CGS (a fast Lanczos-type solver for nonsymmetric linear systems) with no preconditioning for large problems. Using CGS with processor ILU preconditioning and magnitude threshold-fill-in preconditioning for the CM-5, and CGS with ILU for PILS, we attain 50% efficiency for the solution of large matrices.>

Based on a CGS (conjugate gradient squared) iteration with a partitioned natural ordering, a novel massively parallel algorithm for three-dimensional device simulation is presented. This algorithm requires constant time per matrix iteration independent of the number of grid nodes, and has convergence properties comparable to those of good algorithms currently used on sequential computers. This algorithm has been implemented on the Connection Machine and achieves supercomputer performance for large numbers of grid nodes. Results are presented for a wide variety of devices and mesh sizes.>