Abstract
We present efficient vector and parallel methods for manipulating tensor products of matrices. We consider both computing the matrix-vector product (A 1 ļÄA K )x and solving the system of linear equations (A 1 ļÄA K )x=b. The methods described are independent of K . We accompany this article with a companion algorithm which describes an implementation of a complete set of tensor product routines based on LAPACK and the Level 2 and 3 Basic Linear Algebra Subprograms (BLAS) which provide vectorization and parallelization.
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