Web Distributed Computing for Evolutionary Training of Artificial Neural Networks. Balabanov, T.; Keremedchiev, D.; and Goranov, I. In Proceedings of the International Conference on Information Technologies (InfoTech-2016), pages 210–216.
Web Distributed Computing for Evolutionary Training of Artificial Neural Networks [link]Paper  abstract   bibtex   
Evolutionary algorithms (EAs) are widely used in artificial neural networks training. EAs are computationally interesting because it is possible ot separate the problem solving in smaller pieces and to calculate these smaller pieces on different machines (distributed computing). Distributed computing platforms are well established and the most popular is BOINC, created in Berkeley. The problem in distributed computing platforms is the heterogeneity of the computational environment. The best way for solving heterogeneity is by using well established technology such as AJAX. In this study a web based distributed computing platform is presented (JavaScript and AJAX). The platform is used for ANN training with EAs. [Excerpt: Conclusion] The realization of calculations in a distributed environment as AJAX web-based system leads to a very high degree of expandability of the system. Practically, distributed computing can run on any device supporting modern web browser able to run JavaScript and AJAX. The calculation is carried out within the web browser which is a process in an address space of the operating system. The OS in turn is running on physical hardware. Though comparable in performance boost, the calculations are unreliable (presence of interpreter) as opposed to the implementation of languages like C / C ++ or Assembler.
@inproceedings{balabanovWebDistributedComputing2016,
  title = {Web Distributed Computing for Evolutionary Training of Artificial Neural Networks},
  booktitle = {Proceedings of the {{International Conference}} on {{Information Technologies}} ({{InfoTech}}-2016)},
  author = {Balabanov, Todor and Keremedchiev, Delyan and Goranov, Ilia},
  date = {2016-09},
  pages = {210--216},
  url = {https://www.researchgate.net/publication/308400389_Web_Distributed_Computing_for_Evolutionary_Training_of_Artificial_Neural_Networks},
  abstract = {Evolutionary algorithms (EAs) are widely used in artificial neural networks training. EAs are computationally interesting because it is possible ot separate the problem solving in smaller pieces and to calculate these smaller pieces on different machines (distributed computing). Distributed computing platforms are well established and the most popular is BOINC, created in Berkeley. The problem in distributed computing platforms is the heterogeneity of the computational environment. The best way for solving heterogeneity is by using well established technology such as AJAX. In this study a web based distributed computing platform is presented (JavaScript and AJAX). The platform is used for ANN training with EAs.

[Excerpt: Conclusion] The realization of calculations in a distributed environment as AJAX web-based system leads to a very high degree of expandability of the system. Practically, distributed computing can run on any device supporting modern web browser able to run JavaScript and AJAX. The calculation is carried out within the web browser which is a process in an address space of the operating system. The OS in turn is running on physical hardware. Though comparable in performance boost, the calculations are unreliable (presence of interpreter) as opposed to the implementation of languages like C / C ++ or Assembler.},
  keywords = {*imported-from-citeulike-INRMM,~INRMM-MiD:c-14144795,artificial-neural-networks,computer-science,evolutionary-techniques,optimisation,parallelism,web-and-information-technologies},
  venue = {Bulgaria}
}
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