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Framework for Deep Reinforcement Learning with GPU-CPU Multiprocessing

Ivan Sosin; Oleg Svidchenko; Aleksandra Malysheva; Daniel Kudenko; Aleksei Shpilman


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{
  "description": "<p>One of the main challenges faced in Deep Reinforcement Learning is that running simulations may be CPU-heavy, while the optimal computing device for training neural networks is a GPU. One way to overcome this problem is building a custom machine with GPU to CPU proportions that avoid bottlenecking one or the other. Another is to have the GPU machine work together with the CPU machine and/or launching one or both via cloud computing service. We have designed a framework for such a tandem interaction.</p>\n\n<p>Authors: Ivan Sosin, Oleg Svidchenko, Aleksandra Malysheva, Daniel Kudenko, Aleksei Shpilman.</p>", 
  "license": "", 
  "creator": [
    {
      "affiliation": "JetBrains Research", 
      "@type": "Person", 
      "name": "Ivan Sosin"
    }, 
    {
      "affiliation": "JetBrains Research", 
      "@type": "Person", 
      "name": "Oleg Svidchenko"
    }, 
    {
      "affiliation": "JetBrains Research", 
      "@type": "Person", 
      "name": "Aleksandra Malysheva"
    }, 
    {
      "affiliation": "JetBrains Research", 
      "@type": "Person", 
      "name": "Daniel Kudenko"
    }, 
    {
      "affiliation": "JetBrains Research", 
      "@type": "Person", 
      "name": "Aleksei Shpilman"
    }
  ], 
  "url": "https://zenodo.org/record/1938263", 
  "codeRepository": "https://github.com/iasawseen/MultiServerRL/tree/v1.0", 
  "datePublished": "2018-12-04", 
  "version": "v1.0", 
  "@context": "https://schema.org/", 
  "identifier": "https://doi.org/10.5281/zenodo.1938263", 
  "@id": "https://doi.org/10.5281/zenodo.1938263", 
  "@type": "SoftwareSourceCode", 
  "name": "Framework for Deep Reinforcement Learning with GPU-CPU Multiprocessing"
}
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