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Benchmarking Machine Learning in HEP

Sabina Manafli


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{
  "description": "<p>The interest on machine learning workloads in the HEP community has increased exponentially in the last years, making more and more important the need of a thorough benchmarking of the most relevant/significant workloads that are going to run on the experiments. The purpose of this project is to build a set of techniques to benchmark deep neural networks on different<br>\nhardware. By using different tools and methodologies we make several important observations and conclusions based on the performance of deep learning application running on GPUs which have different compute capabilities.</p>", 
  "license": "https://creativecommons.org/licenses/by/4.0/legalcode", 
  "creator": [
    {
      "affiliation": "CERN openlab summer student", 
      "@type": "Person", 
      "name": "Sabina Manafli"
    }
  ], 
  "headline": "Benchmarking Machine Learning in HEP", 
  "image": "https://zenodo.org/static/img/logos/zenodo-gradient-round.svg", 
  "datePublished": "2018-12-05", 
  "url": "https://zenodo.org/record/1967555", 
  "keywords": [
    "CERN openlab", 
    "summer student programme"
  ], 
  "@context": "https://schema.org/", 
  "identifier": "https://doi.org/10.5281/zenodo.1967555", 
  "@id": "https://doi.org/10.5281/zenodo.1967555", 
  "@type": "ScholarlyArticle", 
  "name": "Benchmarking Machine Learning in HEP"
}
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