Following the initial release of LAPACK and the emerging importance of distributed memory
computing, work began on adapting LAPACK to distributed-memory architectures. Since …

A vast body of theoretical research has focused either on overly simplistic models of parallel
computation, notably the PRAM, or overly specific models that have few representatives in …

Cotton, popularly known as White Gold has been an important commercial crop of National
significance due to the immense influence of its rural economy. Transfer of technology to …

Parallelizing dense matrix computations to distributed memory architectures is a well-
studied subject and generally considered to be among the best understood domains of …

This paper outlines the content and performance of ScaLAPACK, a collection of
mathematical software for linear algebra computations on distributed memory computers …

Abstract The paper describes Parallel Universal Matrix Multiplication Algorithms (PUMMA)
on distributed memory concurrent computers. The PUMMA package includes not only the …

Computing the eigenvalues and orthogonal eigenvectors of an $ n\times n $ symmetric
tridiagonal matrix is an important task that arises while solving any symmetric eigenproblem …

This paper presents a dynamic task scheduling approach to executing dense linear algebra
algorithms on multicore systems (either shared-memory or distributed-memory). We use a …

This paper discusses the design of linear algebra libraries for high performance computers.
Particular emphasis is placed on the development of scalable algorithms for multiple …

FORTRAN M is a small set of extensions to FORTRAN 77 that supports a modular approach
to the design of message-passing programs. It has the following features.(1) Modularity …