Sampling and analytical techniques for data distribution of parallel sparse computation
Tyng–Ruey Chuang, Rong‐Guey Chang, Jenq Kuen Lee · 1997
We present a compile--time method to select compression and distribution schemes for sparse matrices which are computed using Fortran 90 array intrinsic operations. The selection process samples input sparse matrices to determine their sparsity structures. It is also guided by cost functions of various sparse routines as measured from the target machine. The Fortran 90 array expression is then transformed into a sparse array expression that calls the selected compression and distribution routines. 1 Introduction It has long been a challenging research topic to devise general guidelines for selecting efficient compression and distribution schemes for parallel executions of sparse matrix computations. We feel that this problem is difficult at least for the following three reasons. First, the cost of a sparse matrix computation depends greatly on the structures (i.e., the distributions of non--zero elements) of its input matrices [2]. Such information, however, may not be available at c...