We consider the problem of massive matrix multiplication, which underlies many data
analytic applications, in a large-scale distributed system comprising a group of worker …

The current milieu, encourages rapid growth of wireless communication, multimedia
applications, robotics and graphics to have efficient utilization of resources with high …

This paper describes the LINPACK Benchmark and some of its variations commonly used to
assess the performance of computer systems. Aside from the LINPACK Benchmark suite, the …

In the paper we give a straightforward, highly efficient, scalable implementation of common
matrix multiplication operations. The algorithms are much simpler than previously published …

Motivation: Statistical phylogenetics is computationally intensive, resulting in considerable
attention meted on techniques for parallelization. Codon-based models allow for …

We propose COSMA: a parallel matrix-matrix multiplication algorithm that is near
communication-optimal for all combinations of matrix dimensions, processor counts, and …

Feature selection has become a mandatory task in data mining, due to the overwhelming
amount of features in Big Data problems. To handle this high-dimensional data and avoid …

The approximate 'resolution of the identity'second-order many-body perturbation theory
method (RI-MP2) recently introduced by Feyereisen, Fitzgerald and Komornicki utilizes a …

A three-dimensional (3D) matrix multiplication algorithm for massively parallel processing
systems is presented. The P processors are configured as a “virtual” processing cube with …

This article discusses the core factorization routines included in the ScaLAPACK library.
These routines allow the factorization and solution of a dense system of linear equations via …