Conference paper Open Access

Compressed sensing recovery using computational memory

Le Gallo, Manuel; Sebastian, Abu; Cherubini, Giovanni; Giefers, Heiner; Eleftheriou, Evangelos


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{
  "description": "<p>Computational memory (CM) is a promising non-von Neumann approach where certain computational tasks are performed within resistive memory units by exploiting their physical attributes. We propose a new method for fast and robust compressed sensing (CS) recovery of sparse signals using CM. For a signal of size N, this method achieves a potential O(N)-fold complexity reduction compared with a standard software approach. Large-scale experimental demonstrations using more than 256k phase-change memory (PCM) devices are presented along with an in-depth device analysis and array-level considerations.</p>", 
  "license": "https://creativecommons.org/licenses/by/4.0/legalcode", 
  "creator": [
    {
      "affiliation": "IBM Research - Zurich", 
      "@type": "Person", 
      "name": "Le Gallo, Manuel"
    }, 
    {
      "affiliation": "IBM Research - Zurich", 
      "@type": "Person", 
      "name": "Sebastian, Abu"
    }, 
    {
      "affiliation": "IBM Research - Zurich", 
      "@type": "Person", 
      "name": "Cherubini, Giovanni"
    }, 
    {
      "affiliation": "IBM Research - Zurich", 
      "@type": "Person", 
      "name": "Giefers, Heiner"
    }, 
    {
      "affiliation": "IBM Research - Zurich", 
      "@type": "Person", 
      "name": "Eleftheriou, Evangelos"
    }
  ], 
  "headline": "Compressed sensing recovery using computational memory", 
  "image": "https://zenodo.org/static/img/logos/zenodo-gradient-round.svg", 
  "datePublished": "2018-01-25", 
  "url": "https://zenodo.org/record/5301633", 
  "keywords": [
    "In-memory computing, phase change memory, compressed sensing"
  ], 
  "@context": "https://schema.org/", 
  "identifier": "https://doi.org/10.1109/IEDM.2017.8268469", 
  "@id": "https://doi.org/10.1109/IEDM.2017.8268469", 
  "@type": "ScholarlyArticle", 
  "name": "Compressed sensing recovery using computational memory"
}
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