EEG analysis has played a key role in the modeling of the brain's cortical dynamics, but relatively little effort has been devoted to developing EEG as a limited means of communication. If several mental states can be reliably distinguished by recognizing patterns in EEG, then a paralyzed person could communicate to a device such as a wheelchair by composing sequences of these mental states. EEG pattern recognition is a difficult problem and hinges on the success of finding representations of the EEG signals in which the patterns can be distinguished. In this article, we report on a study comparing three EEG representations, the unprocessed signals, a reduced-dimensional representation using the Karhunen &#x2013; Lo&#xe8;ve transform, and a frequency-based representation. Classification is performed with a two-layer neural network implemented on a CNAPS server (128 processor, SIMD architecture) by Adaptive Solutions, Inc. Execution time comparisons show over a hundred-fold speed up over a Sun Sparc 10. The best classification accuracy on untrained samples is 73&#x25; using the frequency-based representation.

Charles W. Anderson

Saikumar V. Devulapalli

Erik A. Stolz

Determining Mental State from EEG Signals Using Parallel Implementations of Neural Networks

In this article we describe the implementation of a numerical weather forecast model on a massively parallel computer system. This model is a production code used for routine weather forecasting at the meteorological institutes of several European countries. The modifications needed to achieve a data-parallel version of this model without explicit message passing are outlined. The achieved performance of different numerical solution methods within this model is presented and compared.

Lex Wolters

Gerard Cats

Nils Gustafsson

Data-Parallel Numerical Weather Forecasting

Flows in estuarial and coastal regions may be described by the shallow-water equations. The processes of pollution transport, sediment transport, and plume dispersion are driven by the underlying hydrodynamics. Accurate resolution of these processes requires a three-dimensional formulation with turbulence modeling, which is very demanding computationally. A numerical scheme has been developed which is both stable and accurate &#x2013; we show that this scheme is also well suited to parallel processing, making the solution of massive complex problems a practical computing possibility. We describe the implementation of the numerical scheme on a Kendall Square Research KSR-1 multiprocessor, and present experimental results which demonstrate that a problem requiring 600,000 mesh points and 6,000 time steps can be solved in under 8 hours using 32 processors.

C. Falc&#xd3; Korn

J. M. Bull

G. D. Riley

P. K. Stansby

Parallelization of a Three-Dimensional Shallow-Water Estuary Model on the KSR-1

We present new parallel algorithms for solving the problem of many body interactions in molecular dynamics (MD). Such algorithms are essential in the simulation of irradiation effects in crystals, where the high energy of the impinging particles dictates computing with large numbers of atoms and for many time cycles. We realized the algorithms using two parallelization methods and compared their performance. Experimental results obtained on a Meiko machine demonstrate that the new algorithms exploit parallelism effectively and can be used to simulate large crystals.

Eli Glikman

Ludmila Ioffe

Itzhak Kelson

Shlomit S. Pinter

Parallel Algorithms for Molecular Dynamics Simulation of Irradiation Effects in Crystals

This article describes the porting and optimization of an explicit, time-dependent, computational fluid dynamics code on an 8,192-node MasPar MP-1. The MasPar is a very fine-grained, single instruction, multiple data parallel computer. The code uses the flux-corrected transport algorithm. We describe the techniques used to port and optimize the code, and the behavior of a test problem. The test problem used to benchmark the flux-corrected transport code on the MasPar was a two-dimensional exploding shock with periodic boundary conditions. We discuss the performance that our code achieved on the MasPar, and compare its performance on the MasPar with its performance on other architectures. The comparisons show that the performance of the code on the MasPar is slightly better than on a CRAY Y-MP for a functionally equivalent, optimized two-dimensional code.

Dan Williams

Luc Bauwens

Simulation of Compressible Flow on a Massively Parallel Architecture

We used a description of a combustion simulation's mathematical and computational methods to develop a version for parallel execution. The result was a reasonable performance improvement on small numbers of processors. We applied several important programming techniques, which we describe, in optimizing the application. This work has implications for programming languages, compiler design, and software engineering.

Gregg Skinner

Rudolf Eigenmann

Parallel Performance of a Combustion Chemistry Simulation

David F. Snelling

Applications Analysis: Guest Editor's Introduction

The performance of transport aircraft can be considerably improved if the process by which the wing boundary layer becomes turbulent can be controlled and extensive areas of laminar flow maintained. In order to design laminar flow control systems, it is necessary to be able to predict the movement of the transition location in response to changes in control variables, e.g., surface suction. At present, the technique which is available to industry requires excessively long computational time &#x2013; so long that it is not suitable for use in the &#x22;design process.&#x22; Therefore, there is a clear need to produce a system which delivers results in near realtime, i.e., in seconds rather than hours. This article details how parallel computing techniques on a KSR-1 produce these performance improvements.

R. W. Ford

D. I. A. Poll

A Parallel Processing Approach to Transition Prediction for Laminar Flow Control System Design

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Scientific Programming provides a forum for research results in, and practical experience with, software engineering environments, tools, languages, and models of computation aimed specifically at supporting scientific and engineering computing.

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