Regular Talks

Solving Irregularly Structured Problems in Parallel

Volume 1457 of the series Lecture Notes in Computer Science pp 68-79


Partitioning sparse rectangular matrices for parallel processing

  • Tamara G. KoldaAffiliated withComputer Science and Mathematics Division, Oak Ridge National Laboratory

* Final gross prices may vary according to local VAT.

Get Access


We are interested in partitioning sparse rectangular matrices for parallel processing. The partitioning problem has been well-studied in the square symmetric case, but the rectangular problem has received very little attention. We will formalize the rectangular matrix partitioning problem and discuss several methods for solving it. We will extend the spectral partitioning method for symmetric matrices to the rectangular case and compare this method to three new methods — the alternating partitioning method and two hybrid methods. The hybrid methods will be shown to be best.