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High-Level and Efficient Stream Parallelism on Multi-core Systems with SPar for Data Compression Applications

Griebler; Hoffmann; Loff; Danelutto; Fernandes


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{
  "description": "<p>The stream processing domain is present in several real-world applications that are running on multi-core systems. In this paper, we focus on data compression applications that are an important sub-set of this domain. Our main goal is to assess the programmability and efficiency of domain-specific language called SPar. It was specially designed for expressing stream parallelism and it promises higher-level parallelism abstractions without significant performance losses. Therefore, we parallelized Lzip and Bzip2 compressors<br>\nwith SPar and compared with state-of-the-art frameworks. The results revealed that SPar is able to efficiently exploit stream parallelism as well as provide suitable abstractions with less code intrusion and code re-factoring.</p>", 
  "license": "http://creativecommons.org/licenses/by/4.0/legalcode", 
  "creator": [
    {
      "affiliation": "Dalvan", 
      "@type": "Person", 
      "name": "Griebler"
    }, 
    {
      "affiliation": "Renato B.", 
      "@type": "Person", 
      "name": "Hoffmann"
    }, 
    {
      "affiliation": "Junior", 
      "@type": "Person", 
      "name": "Loff"
    }, 
    {
      "affiliation": "Marco", 
      "@type": "Person", 
      "name": "Danelutto"
    }, 
    {
      "affiliation": "Luiz Gustavo", 
      "@type": "Person", 
      "name": "Fernandes"
    }
  ], 
  "url": "https://zenodo.org/record/1194606", 
  "datePublished": "2018-03-09", 
  "@context": "https://schema.org/", 
  "distribution": [
    {
      "contentUrl": "https://zenodo.org/api/files/7b306e6f-673c-4dbf-b1ed-596bf048f71d/data.zip", 
      "@type": "DataDownload", 
      "fileFormat": "zip"
    }
  ], 
  "identifier": "https://doi.org/10.5281/zenodo.1194606", 
  "@id": "https://doi.org/10.5281/zenodo.1194606", 
  "@type": "Dataset", 
  "name": "High-Level and Efficient Stream Parallelism on Multi-core Systems with SPar for Data Compression Applications"
}
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