University of Illinois Urbana-Champaign

PARASPICE: A parallel direct circuit simulator for shared-memory multiprocessors

Yang, Gung-Chung

This item is only available for download by members of the University of Illinois community. Students, faculty, and staff at the U of I may log in with your NetID and password to view the item. If you are trying to access an Illinois-restricted dissertation or thesis, you can request a copy through your library's Inter-Library Loan office or purchase a copy directly from ProQuest.

Permalink

https://hdl.handle.net/2142/18971

Description

Title
PARASPICE: A parallel direct circuit simulator for shared-memory multiprocessors
Author(s)
Yang, Gung-Chung
Issue Date
1990
Doctoral Committee Chair(s)
Sameh, Ahmed H.
Department of Study
Computer Science
Discipline
Computer Science
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
Ph.D.
Degree Level
Dissertation
Keyword(s)
  • Engineering, Electronics and Electrical
  • Computer Science
Language
eng
Abstract
  • A general approach to parallelizing direct method circuit simulation has been developed via novel algorithms. The approach extracts parallel tasks at the algorithmic level for the three most compute-intensive modules: device model evaluation (LOAD), direct solution of sparse linear systems (SOLVE), and local truncation error estimation (TRUNC), which account for at least 95 percent of the total job time. Therefore, it is suitable for a wide range of shared-memory multiprocessors. The implementation of the approach in SPICE2 resulted in a portable parallel direct circuit simulator, PARASPICE. The superior performance of PARASPICE is demonstrated on an eight-CE Alliant FX/80 using a number of benchmark circuits.
  • The success of PARASPICE lies particularly in the SOLVE module, where the solution of a sequence of structurally identical sparse matrices are required. In this dissertation, a class of new algorithms has been systematically developed via a unified model for parallel sparse matrix computation. This model, which explores the parallelism issue in the pivoting schemes, extracts parallel tasks from the solution procedure by exploiting the sparse structure of the matrix. These algorithms have been implemented in DSPACK, a software package for the direct solution of general sparse matrices. Experiments with DSPACK on the Boeing-Harwell collection of benchmark matrices have shown high overall speedup. DSPACK has been successfully used as a workbench to design parallel sparse solvers for circuit simulation.
Type of Resource
text
Permalink
http://hdl.handle.net/2142/18971
Copyright and License Information
Copyright 1990 Yang, Gung-Chung

Owning Collections

Graduate Dissertations and Theses at Illinois PRIMARY
Graduate Theses and Dissertations at Illinois
Dissertations and Theses - Computer Science
Dissertations and Theses from the Dept. of Computer Science