Conference paper Open Access

Compressed sensing recovery using computational memory

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


Dublin Core Export

<?xml version='1.0' encoding='utf-8'?>
<oai_dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
  <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:date>2018-01-25</dc:date>
  <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:identifier>https://zenodo.org/record/5301633</dc:identifier>
  <dc:identifier>10.1109/IEDM.2017.8268469</dc:identifier>
  <dc:identifier>oai:zenodo.org:5301633</dc:identifier>
  <dc:relation>info:eu-repo/grantAgreement/EC/H2020/682675/</dc:relation>
  <dc:rights>info:eu-repo/semantics/openAccess</dc:rights>
  <dc:rights>https://creativecommons.org/licenses/by/4.0/legalcode</dc:rights>
  <dc:subject>In-memory computing, phase change memory, compressed sensing</dc:subject>
  <dc:title>Compressed sensing recovery using computational memory</dc:title>
  <dc:type>info:eu-repo/semantics/conferencePaper</dc:type>
  <dc:type>publication-conferencepaper</dc:type>
</oai_dc:dc>
5
9
views
downloads
Views 5
Downloads 9
Data volume 8.2 MB
Unique views 4
Unique downloads 8

Share

Cite as