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CDES
2006
136views Hardware» more  CDES 2006»
13 years 9 months ago
Using Task Recomputation During Application Mapping in Parallel Embedded Architectures
- Many memory-sensitive embedded applications can tolerate small performance degradations if doing so can reduce the memory space requirements significantly. This paper explores th...
Suleyman Tosun, Mahmut T. Kandemir, Hakduran Koc
ISPASS
2009
IEEE
14 years 2 months ago
Machine learning based online performance prediction for runtime parallelization and task scheduling
—With the emerging many-core paradigm, parallel programming must extend beyond its traditional realm of scientific applications. Converting existing sequential applications as w...
Jiangtian Li, Xiaosong Ma, Karan Singh, Martin Sch...
HCW
2000
IEEE
14 years 5 days ago
A Heuristic Algorithm for Mapping Communicating Tasks on Heterogeneous Resources
A heuristic algorithm that maps data-processing tasks onto heterogeneous resources (i.e., processors and links of various capacities) is presented. The algorithm tries to achieve ...
Kenjiro Taura, Andrew A. Chien
KES
1999
Springer
14 years 20 hour ago
Dynamic Demes parallel genetic algorithm
Abstract—Dynamic Demes is a new method for the parallelisation of evolutionary algorithms. It was derived as a combination of two other parallelisation algorithms: the master-sla...
Mariusz Nowostawski, Riccardo Poli
AUSDM
2006
Springer
177views Data Mining» more  AUSDM 2006»
13 years 11 months ago
On The Optimal Working Set Size in Serial and Parallel Support Vector Machine Learning With The Decomposition Algorithm
The support vector machine (SVM) is a wellestablished and accurate supervised learning method for the classification of data in various application fields. The statistical learnin...
Tatjana Eitrich, Bruno Lang