Application of parallel sparse direct methods in semiconductor device and process simulation

  • Olaf Schenk
  • Klaus Gärtner
  • Wolfgang Fichtner
IV Applications
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1615)


We present PARDISO, a new scalable parallel sparse direct linear solver on shared memory multiprocessors. In this paper, we describe the parallel factorization algorithm which utilizes the supernode structure of the matrix to reduce the number of memory references with Level 3 BLAS. We also propose enhancements that significantly reduce the communication rate for pipelining parallelism. The result, is a greatly increased factorization performance. Furthermore, 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 semiconductor device and 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 300'000 unknowns for three-dimensional simulations are presented to illustrate our approach towards robust, parallel semiconductor device and process simulation.


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Copyright information

© Springer-Verlag 1999

Authors and Affiliations

  • Olaf Schenk
    • 1
  • Klaus Gärtner
    • 2
  • Wolfgang Fichtner
    • 1
  1. 1.Integrated Systems Laboratory, Swiss Federal Institute of Technology ZurichETH ZurichZurichSwitzerland
  2. 2.Weierstrass Institute for Applied Analysis and StochasticsBerlinGermany

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