A VLSI array for stable matrix inversion using gauss-jordan diagonalization

  • A. El-Amawy
  • K. R. Dharmarajan
Conference paper
Part of the Lecture Notes in Control and Information Sciences book series (LNCIS, volume 130)


A purely systolic architecture for computing the inverse of a matrix has been presented. The architecture implements an inversion algorithm based on the Gauss-Jordan diagonalization method with partial pivoting. The architecture employs 4n+1 PEs and has a time complexity of O(n2). Thus the area-time complexity is O(n3), which matches the performance of the fastest systolic implementation of matrix inversion (numerically unstable in most cases), reported to date.

A regular and continuous data flow is maintained within the array. The bilinear array has been supplemented with a buffer array to eliminate the need for costly inter-iteration I/O. Thus, the total number of I/O operations has been minimized and I/O operations are needed only to input the matrix to be inverted and to retrieve its inverse.


Matrix Inversion Systolic Array Input Element VLSI Architecture Pivot Element 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag 1989

Authors and Affiliations

  • A. El-Amawy
    • 1
  • K. R. Dharmarajan
    • 1
  1. 1.Louisiana State UniversityUSA

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