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Search Publications by: Roldan Pozo (Fed)

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Displaying 1 - 12 of 12

Fast Methods for Finding Multiple Effective Influencers in Real Networks

December 31, 2020
Fern Y. Hunt, Roldan Pozo
We present scalable first hitting time methods for finding a collection of nodes that enables the fastest time for the spread of consensus in a network. That is, given a graph G = (V,E) and a natural number k, these methods find k vertices in G that


July 1, 2005
Ronald F. Boisvert, Roldan Pozo
Our goal here is to provide to non-Java programmers some guidance as to whether Java might be appropriate for scientific applications. We will discuss some of Java's features which promote the safety, reliability, and portability, and then briefly address

An Updated Set of Basic Linear Algebra Subprograms (BLAS)

June 1, 2002
L S. Blackford, Roldan Pozo, Et al
This paper updates the ongoing BLAS effort, and summarizes what types of operations are now available. We now have flavors of BLAS for dense, banded, and sparse vector and matrix operations. Some BLAS are also supported in extended and mixed precision

NIST Sparse BLAS User's Guide

May 1, 2001
K Remington, Roldan Pozo
This document provides a guide and reference manual for a portable numerical library for sparse matrix computations. These Basic Linear Algebra Subprograms (BLAS) provide kernelsfor forming sparse matrix products (of the form C = aAB + bC. where a and b

Java and Numerical Computing

April 1, 2001
Ronald F. Boisvert, J Moreira, M Philippsen, Roldan Pozo
We discuss the advantages and disadvantages of using Java for numerical computing. We provide examples of current performance levels and propose several additional language features that would make Java more easily applied in scientific applications.

Measurement and Standards for Computational Science and Engineering

March 1, 1999
Ronald F. Boisvert, J L. Blue, Daniel W. Lozier, William F. Mitchell, Roldan Pozo, Michael J. Donahue, Donald G. Porter
This report describes current work within ITL on the development of measurement and standards technology to improve the practice of computational science and engineering.