Matches in SemOpenAlex for { <https://semopenalex.org/work/W3006665629> ?p ?o ?g. }
Showing items 1 to 89 of
89
with 100 items per page.
- W3006665629 endingPage "148" @default.
- W3006665629 startingPage "136" @default.
- W3006665629 abstract "Training of Artificial Neural Networks (ANNs) for large data sets is a time consuming mission. In this paper, accelerating the training of artificial neural networkis achievedby a parallel training using either Multicore Central Processing Unit(CPU) orGeneral Purpose Graphics Processing Unit (GPGPU). The trainingis implemented using five datasets with diverse amounts of patterns and with different neural network parameters in Multilayer Perceptron (MLP). The results show a significant increase in computation speed, which is increasednearly linear with the number of cores in multicore processor for problems with medium and large training datasets.Also, a considerable speed up is achieved when the GPU is used to train the MLP withthe large training datasets. While a single core processor is a better choice when the data set size is small.The optimal number of cores or the type of the parallel platform should be employed according to the load of computation." @default.
- W3006665629 created "2020-02-24" @default.
- W3006665629 creator A5043883552 @default.
- W3006665629 creator A5085747255 @default.
- W3006665629 date "2015-07-28" @default.
- W3006665629 modified "2023-09-28" @default.
- W3006665629 title "Training Acceleration of Multi-Layer Perceptron using Multicore CPU and GPU under MATLAB Environment" @default.
- W3006665629 doi "https://doi.org/10.33899/rengj.2015.101566" @default.
- W3006665629 hasPublicationYear "2015" @default.
- W3006665629 type Work @default.
- W3006665629 sameAs 3006665629 @default.
- W3006665629 citedByCount "0" @default.
- W3006665629 crossrefType "journal-article" @default.
- W3006665629 hasAuthorship W3006665629A5043883552 @default.
- W3006665629 hasAuthorship W3006665629A5085747255 @default.
- W3006665629 hasBestOaLocation W30066656291 @default.
- W3006665629 hasConcept C111919701 @default.
- W3006665629 hasConcept C11413529 @default.
- W3006665629 hasConcept C117896860 @default.
- W3006665629 hasConcept C121332964 @default.
- W3006665629 hasConcept C121684516 @default.
- W3006665629 hasConcept C153294291 @default.
- W3006665629 hasConcept C154945302 @default.
- W3006665629 hasConcept C173608175 @default.
- W3006665629 hasConcept C179717631 @default.
- W3006665629 hasConcept C21442007 @default.
- W3006665629 hasConcept C2777211547 @default.
- W3006665629 hasConcept C2778119891 @default.
- W3006665629 hasConcept C2779851693 @default.
- W3006665629 hasConcept C2780365114 @default.
- W3006665629 hasConcept C2780365336 @default.
- W3006665629 hasConcept C41008148 @default.
- W3006665629 hasConcept C45374587 @default.
- W3006665629 hasConcept C459310 @default.
- W3006665629 hasConcept C49154492 @default.
- W3006665629 hasConcept C50630238 @default.
- W3006665629 hasConcept C50644808 @default.
- W3006665629 hasConcept C60908668 @default.
- W3006665629 hasConcept C68339613 @default.
- W3006665629 hasConcept C74650414 @default.
- W3006665629 hasConcept C78766204 @default.
- W3006665629 hasConcept C9390403 @default.
- W3006665629 hasConceptScore W3006665629C111919701 @default.
- W3006665629 hasConceptScore W3006665629C11413529 @default.
- W3006665629 hasConceptScore W3006665629C117896860 @default.
- W3006665629 hasConceptScore W3006665629C121332964 @default.
- W3006665629 hasConceptScore W3006665629C121684516 @default.
- W3006665629 hasConceptScore W3006665629C153294291 @default.
- W3006665629 hasConceptScore W3006665629C154945302 @default.
- W3006665629 hasConceptScore W3006665629C173608175 @default.
- W3006665629 hasConceptScore W3006665629C179717631 @default.
- W3006665629 hasConceptScore W3006665629C21442007 @default.
- W3006665629 hasConceptScore W3006665629C2777211547 @default.
- W3006665629 hasConceptScore W3006665629C2778119891 @default.
- W3006665629 hasConceptScore W3006665629C2779851693 @default.
- W3006665629 hasConceptScore W3006665629C2780365114 @default.
- W3006665629 hasConceptScore W3006665629C2780365336 @default.
- W3006665629 hasConceptScore W3006665629C41008148 @default.
- W3006665629 hasConceptScore W3006665629C45374587 @default.
- W3006665629 hasConceptScore W3006665629C459310 @default.
- W3006665629 hasConceptScore W3006665629C49154492 @default.
- W3006665629 hasConceptScore W3006665629C50630238 @default.
- W3006665629 hasConceptScore W3006665629C50644808 @default.
- W3006665629 hasConceptScore W3006665629C60908668 @default.
- W3006665629 hasConceptScore W3006665629C68339613 @default.
- W3006665629 hasConceptScore W3006665629C74650414 @default.
- W3006665629 hasConceptScore W3006665629C78766204 @default.
- W3006665629 hasConceptScore W3006665629C9390403 @default.
- W3006665629 hasIssue "3" @default.
- W3006665629 hasLocation W30066656291 @default.
- W3006665629 hasOpenAccess W3006665629 @default.
- W3006665629 hasPrimaryLocation W30066656291 @default.
- W3006665629 hasRelatedWork W1531984995 @default.
- W3006665629 hasRelatedWork W1842862600 @default.
- W3006665629 hasRelatedWork W2023954774 @default.
- W3006665629 hasRelatedWork W2755264124 @default.
- W3006665629 hasRelatedWork W2794923745 @default.
- W3006665629 hasRelatedWork W2806898911 @default.
- W3006665629 hasRelatedWork W2952476118 @default.
- W3006665629 hasRelatedWork W2962920366 @default.
- W3006665629 hasRelatedWork W758363276 @default.
- W3006665629 hasRelatedWork W2166635987 @default.
- W3006665629 hasVolume "23" @default.
- W3006665629 isParatext "false" @default.
- W3006665629 isRetracted "false" @default.
- W3006665629 magId "3006665629" @default.
- W3006665629 workType "article" @default.