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» Computing stable models in parallel
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127
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EUROPAR
2010
Springer
15 years 4 months ago
Estimating and Exploiting Potential Parallelism by Source-Level Dependence Profiling
Manual parallelization of programs is known to be difficult and error-prone, and there are currently few ways to measure the amount of potential parallelism in the original sequent...
Jonathan Mak, Karl-Filip Faxén, Sverker Jan...
125
Voted
ICPPW
2003
IEEE
15 years 9 months ago
Parallelization of Cellular Neural Networks for Image Processing on Cluster Architectures
In this paper a simple but effective approach for parallelization of cellular neural networks for image processing is developed. Digital gray-scale images were used to evaluate th...
Thomas Weishäupl, Erich Schikuta
105
Voted
IPPS
2006
IEEE
15 years 9 months ago
Algorithmic models for sensor networks
Developing algorithms for sensor networks—and proving their correctness and performance—, requires simplifying but still realistic models. This paper surveys various models in...
Stefan Schmid, Roger Wattenhofer
81
Voted
IPPS
1997
IEEE
15 years 7 months ago
A BSP Approach to the Scheduling of Tightly-Nested Loops
This paper addresses the scheduling of uniformdependence loop nests within the framework of the bulksynchronous parallel (BSP) model. Two broad classes of tightly-nested loops are...
Radu Calinescu
ICANN
2005
Springer
15 years 9 months ago
Robust Structural Modeling and Outlier Detection with GMDH-Type Polynomial Neural Networks
Abstract. The paper presents a new version of a GMDH type algorithm able to perform an automatic model structure synthesis, robust model parameter estimation and model validation i...
Tatyana I. Aksenova, Vladimir Volkovich, Alessandr...