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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<oai_dc:dc xmlns:dc="" xmlns:oai_dc="" xmlns:xsi="" xsi:schemaLocation="">
  <dc:creator>Le Gallo, Manuel</dc:creator>
  <dc:creator>Sebastian, Abu</dc:creator>
  <dc:creator>Cherubini, Giovanni</dc:creator>
  <dc:creator>Giefers, Heiner</dc:creator>
  <dc:creator>Eleftheriou, Evangelos</dc:creator>
  <dc:description>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.</dc:description>
  <dc:subject>In-memory computing, phase change memory, compressed sensing</dc:subject>
  <dc:title>Compressed sensing recovery using computational memory</dc:title>
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