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Physical Sciences and Mathematics Commons™

Open Access. Powered by Scholars. Published by Universities.®

Computer Sciences

Syracuse University

2000

Articles 1 - 5 of 5

Full-Text Articles in Physical Sciences and Mathematics

Mpj: Mpi-Like Message Passing For Java, Bryan Carpenter, Vladimir Getov, Glenn Judd, Anthony Skjellum, Geoffrey C. Fox Jan 2000

Mpj: Mpi-Like Message Passing For Java, Bryan Carpenter, Vladimir Getov, Glenn Judd, Anthony Skjellum, Geoffrey C. Fox

Northeast Parallel Architecture Center

Recently, there has been a lot of interest in using Java for parallel programming. Efforts have been hindered by lack of standard Java parallel programming APIs. To alleviate this problem, various groups started projects to develop Java message passing systems modeled on the successful Message Passing Interface (MPI). Official MPI bindings are currently defined only for C, Fortran, and C++, so early MPI-like environments for Java have been divergent. This paper related an effort undertaken by a working group of the Java Grande Forum, seeking a consensus on an MPI-like API, to enhance the viability of parallel programming using Java.

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Parallel Computers And Complex Systems, Geoffrey C. Fox, Paul D. Coddington Jan 2000

Parallel Computers And Complex Systems, Geoffrey C. Fox, Paul D. Coddington

Northeast Parallel Architecture Center

We present an overview of the state of the art and future trends in high performance parallel and distributed computing, and discuss techniques for using such computers in the simulation of complex problems in computational science. The use of high performance parallel computers can help improve our understanding of complex systems, and the converse is also true — we can apply techniques used for the study of complex systems to improve our understanding of parallel computing. We consider parallel computing as the mapping of one complex system — typically a model of the world — into another complex system — …

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An Hpspmd Programming Model, Bryan Carpenter, Geoffrey C. Fox, Guansong Zhang Jan 2000

An Hpspmd Programming Model, Bryan Carpenter, Geoffrey C. Fox, Guansong Zhang

Northeast Parallel Architecture Center

Building on research carried out in the Parallel Compiler Runtime Consortium (PCRC) project, this article discusses a language model that combines characteristic data-parallel features from the HPF standard with an explicitly SPMD programming style. This model, which we call the HPspmd model, is designed to facilitate direct calls to established libraries for parallel programming with distributed data. We describe a Java-based HPspmd language called HPJava.

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A Pairwise Key Pre-Distribution Scheme For Wireless Sensor Networks, Wenliang Kevin Du, Jing Deng, Yunghsiang S. Han, Pramod K. Varshney Jan 2000

A Pairwise Key Pre-Distribution Scheme For Wireless Sensor Networks, Wenliang Kevin Du, Jing Deng, Yunghsiang S. Han, Pramod K. Varshney

Electrical Engineering and Computer Science - All Scholarship

This paper, we provide a framework in which to study the security of key pre-distribution schemes, propose a new key pre-distribution scheme which substantially improves the resilience of the network compared to previous schemes, and give an in-depth analysis of our scheme in terms of network resilience and associated overhead. Our scheme exhibits a nice threshold property: when the number of compromised nodes is less than the threshold, the probability that communications between any additional nodes are compromised is close to zero. This desirable property lowers the initial payoff of smaller-scale network breaches to an adversary, and makes it necessary …

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Multi-Phase Discrete Particle Swarm Optimization, Buthainah Sabeeh No'man Al-Kazemi, Chilukuri K. Mohan Jan 2000

Multi-Phase Discrete Particle Swarm Optimization, Buthainah Sabeeh No'man Al-Kazemi, Chilukuri K. Mohan

Electrical Engineering and Computer Science - All Scholarship

This paper describes a successful adaptation of the Particle Swarm Optimization algorithm to discrete optimization problems. In the proposed algorithm, particles cycle through multiple phases with differing goals. We also exploit hill climbing. On benchmark problems, this algorithm outperforms a genetic algorithm and a previous discrete PSO formulation.

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