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» A proposal for parallel self-adjusting computation
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108
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PDCN
2004
15 years 1 months ago
K-Means VQ algorithm using a low-cost parallel cluster computing
It is well-known that the time and memory necessary to create a codebook from large training databases have hindered the vector quantization based systems for real applications. T...
Paulo Sergio Lopes de Souza, Alceu de Souza Britto...
ASPDAC
2006
ACM
119views Hardware» more  ASPDAC 2006»
15 years 6 months ago
Using speculative computation and parallelizing techniques to improve scheduling of control based designs
Recent research results have seen the application of parallelizing techniques to high-level synthesis. In particular, the effect of speculative code transformations on mixed contr...
Roberto Cordone, Fabrizio Ferrandi, Marco D. Santa...
95
Voted
ICDAR
2003
IEEE
15 years 5 months ago
A Low-Cost Parallel K-Means VQ Algorithm Using Cluster Computing
In this paper we propose a parallel approach for the Kmeans Vector Quantization (VQ) algorithm used in a twostage Hidden Markov Model (HMM)-based system for recognizing handwritte...
Alceu de Souza Britto Jr., Paulo Sergio Lopes de S...
JCP
2008
162views more  JCP 2008»
15 years 12 days ago
A Hypercube-based Scalable Interconnection Network for Massively Parallel Computing
An important issues in the design of interconnection networks for massively parallel computers is scalability. A new scalable interconnection network topology, called Double-Loop H...
Youyao Liu, Jungang Han, Huimin Du
101
Voted
CEC
2008
IEEE
15 years 7 months ago
A parallel surrogate-assisted multi-objective evolutionary algorithm for computationally expensive optimization problems
Abstract— This paper presents a new efficient multiobjective evolutionary algorithm for solving computationallyintensive optimization problems. To support a high degree of parall...
Anna Syberfeldt, Henrik Grimm, Amos Ng, Robert Ivo...