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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{
  "DOI": "10.1109/IEDM.2017.8268469", 
  "author": [
    {
      "family": "Le Gallo, Manuel"
    }, 
    {
      "family": "Sebastian, Abu"
    }, 
    {
      "family": "Cherubini, Giovanni"
    }, 
    {
      "family": "Giefers, Heiner"
    }, 
    {
      "family": "Eleftheriou, Evangelos"
    }
  ], 
  "issued": {
    "date-parts": [
      [
        2018, 
        1, 
        25
      ]
    ]
  }, 
  "abstract": "<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>", 
  "title": "Compressed sensing recovery using computational memory", 
  "type": "paper-conference", 
  "id": "5301633"
}
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