BIB-VERSION:: CS-TR-v2.0
          ID:: STAN//CS-TR-89-1286
       ENTRY:: January 05, 1995
ORGANIZATION:: Stanford University, Department of Computer Science
       TITLE:: Fast sparse matrix factorization on modern workstations
        TYPE:: Technical Report
      AUTHOR:: Rothberg, Edward
      AUTHOR:: Gupta, Anoop
        DATE:: October 1989
       PAGES:: 17
    ABSTRACT:: The performance of workstation-class machines has experienced
               a dramatic increase in the recent past. Relatively
               inexpensive machines which offer 14 MIPS and 2 MFLOPS
               performance are now available, and machines with even higher
               performance are not far off. One important characteristic of
               these machines is that they rely on a small amount of
               high-speed cache memory for their high performance. In this
               paper, we consider the problem of Cholesky factorization of a
               large sparse positive definite system of equations on a high
               performance workstation. We find that the major factor
               limiting performance is the cost of moving data between
               memory and the processor. We use two techniques to address
               this limitation; we decrease the number of memory references
               and we improve cache behavior to decrease the cost of each
               reference. When run on benchmarks from the Harwell-Boeing
               Sparse Matrix Collection, the resulting factorization code is
               almost three times as fast as SPARSPAK on a DECStation 3100.
               We believe that the issues brought up in this paper will play
               an important role in the effective use of high performance
               workstations on large numerical problems.
       NOTES:: [Adminitrivia V1/RAM/19950105]
         END:: STAN//CS-TR-89-1286