Sparse matrix-vector (SpMV) multiplication is a widely used kernel in scientific applications.
In these applications, the SpMV multiplication is usually deeply nested within multiple loops …

Array operations are used in a large number of important scientific codes. To implement
these array operations efficiently, many methods have been proposed in the literature, most …

We have proposed the extended Karnaugh map representation (EKMH) scheme for
multidimensional array representation. We propose two data compression schemes, EKMR …

The sparse matrix‐vector multiplication (SpMV) is of great importance in scientific
computations. Graphics processing unit (GPU)‐accelerated SpMVs for large‐sized problems …

An optimizing compiler includes a vector optimization mechanism that optimizes vector
instructions by eliminating one or more vector element reverse operations. The compiler can …

An application that includes intrinsics defined in one architecture is to execute without
change on a different architecture. Program code that depends on vector element ordering is …

An optimizing compiler includes a vector optimization mechanism that optimizes vector
instructions by eliminating one or more vector element reverse operations. The compiler can …

Array operations are useful in a large number of important scientific codes, such as
molecular dynamics, finite element methods, climate modeling, atmosphere and ocean …

Sparse matrix operations involve a large number of zero operands which makes most of the
operations redundant. The amount of redundancy magnifies when a matrix operation …

An optimizing compiler includes a vector optimization mechanism that optimizes vector
operations that are reformatting-resistant, such as source instructions that do not have a …