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hipMAGMA v2.0.0

Cade Brown; Ahmad Abdelfattah; Stanimire Tomov; Jack Dongarra


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{
  "inLanguage": {
    "alternateName": "eng", 
    "@type": "Language", 
    "name": "English"
  }, 
  "description": "<p>The goal of the MAGMA project is to create a new generation of linear algebra libraries that achieves the fastest possible time to an accurate solution on heterogeneous architectures, starting with current multicore + multi-GPU systems. To address the complex challenges stemming from these systems&#39; heterogeneity, massive parallelism, and the gap between compute speed and CPU-GPU communication speed, MAGMA&#39;s research is based on the idea that optimal software solutions will themselves have to hybridize, combining the strengths of different algorithms within a single framework. Building on this idea, the goal is to design linear algebra algorithms and frameworks for hybrid multicore and multi-GPU systems that can enable applications to fully exploit the power that each of the hybrid components offers.</p>", 
  "license": "https://creativecommons.org/licenses/by/4.0/legalcode", 
  "creator": [
    {
      "affiliation": "University of Tennessee", 
      "@type": "Person", 
      "name": "Cade Brown"
    }, 
    {
      "affiliation": "University of Tennessee", 
      "@type": "Person", 
      "name": "Ahmad Abdelfattah"
    }, 
    {
      "affiliation": "University of Tennessee", 
      "@type": "Person", 
      "name": "Stanimire Tomov"
    }, 
    {
      "affiliation": "University of Tennessee", 
      "@type": "Person", 
      "name": "Jack Dongarra"
    }
  ], 
  "url": "https://zenodo.org/record/3928667", 
  "datePublished": "2020-07-02", 
  "version": "2.0.0", 
  "keywords": [
    "dense linear algebra", 
    "GPU computing", 
    "linear algebra"
  ], 
  "@context": "https://schema.org/", 
  "identifier": "https://doi.org/10.5281/zenodo.3928667", 
  "@id": "https://doi.org/10.5281/zenodo.3928667", 
  "@type": "SoftwareSourceCode", 
  "name": "hipMAGMA v2.0.0"
}
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