Asynchronous cellular logic network as a co-processor for a general-purpose massively parallel array

The simulation of fire is a challenging task due to its occurrence on multiple space-time scales and the non-linear interaction of multiple physical processes. Current state-of-the-art software such as the Fire Dynamics Simulator (FDS) implements most of the required physics, yet a significant drawback of this implementation is its limited scalability on modern massively parallel hardware. The current paper presents a massively parallel implementation of a Gas Kinetic Scheme (GKS) on General Purpose Graphics Processing Units (GPGPUs) as a potential alternative modeling and simulation approach. The implementation is validated for turbulent natural convection against experimental data. Subsequently, it is validated for two simulations of fire plumes, including a small-scale table top setup and a fire on the scale of a few meters. We show that the present GKS achieves comparable accuracy to the results obtained by FDS. Yet, due to the parallel efficiency on dedicated hardware, our GKS implementation delivers a reduction of wall-clock times of more than an order of magnitude. This paper demonstrates the potential of explicit local schemes in massively parallel environments for the simulation of fire.

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Massively parallel array processor for logic, fault, and design error simulation

Proceedings of 1995 1st IEEE Symposium on High Performance Computer Architecture ◽

10.1109/hpca.1995.386529 ◽

2002 ◽

Cited By ~ 2

Author(s):

Y. Hur ◽

S.A. Szygenda ◽

E. Scott Fehr ◽

G.E. Ott ◽

Sungho Kang

Keyword(s):

Massively Parallel ◽

Array Processor ◽

Parallel Array ◽

Design Error ◽

Error Simulation

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General purpose massively parallel systems: the role of programming environments

Proceedings of the First International Conference on Massively Parallel Computing Systems (MPCS) The Challenges of General-Purpose and Special-Purpose Computing ◽

10.1109/mpcs.1994.367028 ◽

2002 ◽

Author(s):

F. Baiardi ◽

L. Ricci

Keyword(s):

Parallel Systems ◽

General Purpose ◽

Massively Parallel ◽

Programming Environments ◽

Massively Parallel Systems

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CELLULAR AUTOMATA AS A COMPUTATIONAL MODEL FOR LOW-LEVEL VISION

International Journal of Modern Physics C ◽

10.1142/s0129183193000033 ◽

1993 ◽

Vol 04 (01) ◽

pp. 5-16 ◽

Cited By ~ 6

Author(s):

ALBERTO BROGGI ◽

VINCENZO D'ANDREA ◽

GIULIO DESTRI

Keyword(s):

Cellular Automata ◽

Computational Model ◽

Ad Hoc ◽

Parallel Architecture ◽

General Purpose ◽

Massively Parallel ◽

Low Level ◽

Actual Application ◽

Computer Vision Applications ◽

Hard Real Time

In this paper we discuss the use of the Cellular Automata (CA) computational model in computer vision applications on massively parallel architectures. Motivations and guidelines of this approach to low-level vision in the frame of the PROMETHEUS project are discussed. The hard real-time requirement of actual application can be only satisfied using an ad hoc VLSI massively parallel architecture (PAPRICA). The hardware solutions and the specific algorithms can be efficiently verified and tested only using, as a simulator, a general purpose machine with a parent architecture (CM-2). An example of application related to feature extraction is discussed.

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Applications of remote image sensing with the NASA massively parallel processor

Philosophical Transactions of the Royal Society of London. Series A, Mathematical and Physical Sciences ◽

10.1098/rsta.1988.0025 ◽

1988 ◽

Vol 324 (1579) ◽

pp. 365-372 ◽

Cited By ~ 3

Keyword(s):

Image Processing ◽

Space Station ◽

Image Data ◽

General Purpose ◽

Massively Parallel ◽

Imaging Data ◽

Parallel Processor ◽

Image Sensing ◽

Faint Object ◽

Massively Parallel Processor

Satellite observing systems are producing image observations of the Earth’s surface and atmosphere with spectral and spatial resolutions that result in data rates that current general-purpose computing systems are incapable of processing and analysing. As a result, current processing systems have been able to analyse only limited amounts of image data with less than optimal algorithms for generating high-quality geophysical parameters. A massively parallel processor (mpp) is operationally available at NASA/GSFC for routine image-analysis applications. Research studies with the mpp are being pursued in the area of interactive spatial contextual classifications for the land thematic mapper data, automatic SIR-B stereo terrain mapping, icemotion detection, faint-object image restoration and other general purpose ocean and land image-processing systems. Several applications are presented comparing the mpp products with enhancements of imaging data with standard image-processing methods. Finally, a work-station parallel processor for space station on-board image processing will be described.

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