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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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{
  "publisher": "Zenodo", 
  "DOI": "10.5281/zenodo.1938263", 
  "title": "Framework for Deep Reinforcement Learning with GPU-CPU Multiprocessing", 
  "issued": {
    "date-parts": [
      [
        2018, 
        12, 
        4
      ]
    ]
  }, 
  "abstract": "<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>", 
  "author": [
    {
      "family": "Ivan Sosin"
    }, 
    {
      "family": "Oleg Svidchenko"
    }, 
    {
      "family": "Aleksandra Malysheva"
    }, 
    {
      "family": "Daniel Kudenko"
    }, 
    {
      "family": "Aleksei Shpilman"
    }
  ], 
  "version": "v1.0", 
  "type": "article", 
  "id": "1938263"
}
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