Large-scale memristive associative memories
| dc.contributor.author | Eero Lehtonen | |
| dc.contributor.author | Jussi Poikonen | |
| dc.contributor.author | Mika Laiho | |
| dc.contributor.author | Pentti Kanerva | |
| dc.contributor.organization | fi=Technology Research Center TRC|en=Technology Research Center TRC| | |
| dc.contributor.organization-code | 1.2.246.10.2458963.20.58905910210 | |
| dc.converis.publication-id | 1615182 | |
| dc.converis.url | https://research.utu.fi/converis/portal/Publication/1615182 | |
| dc.date.accessioned | 2022-10-28T12:31:14Z | |
| dc.date.available | 2022-10-28T12:31:14Z | |
| dc.description.abstract | <div> Associative memories, in contrast to conventional address-based memories, are inherently fault-tolerant and allow retrieval of data based on partial search information. This paper considers the possibility of implementing large-scale associative memories through memristive devices jointly with CMOS circuitry. An advantage of a memristive associative memory is that the memory elements are located physically above the CMOS layer, which yields more die area for the processing elements realized in CMOS. This allows for high-capacity memories even while using an older CMOS technology, as the capacity of the memory depends more on the feature size of the memristive crossbar than on that of the CMOS components. In this paper, we propose the memristive implementations, and present simulations and error analysis of the autoassociative content-addressable memory, the Willshaw memory, and the sparse distributed memory. Furthermore, we present a CMOS cell that can be used to implement the proposed memory architectures.</div> | |
| dc.format.pagerange | 562 | |
| dc.format.pagerange | 574 | |
| dc.identifier.eissn | 1063-8210 | |
| dc.identifier.jour-issn | 1063-8210 | |
| dc.identifier.olddbid | 176997 | |
| dc.identifier.oldhandle | 10024/160091 | |
| dc.identifier.uri | https://www.utupub.fi/handle/11111/32742 | |
| dc.identifier.url | http://ieeexplore.ieee.org | |
| dc.identifier.urn | URN:NBN:fi-fe2021042714207 | |
| dc.okm.affiliatedauthor | Poikonen, Jussi | |
| dc.okm.affiliatedauthor | Laiho, Mika | |
| dc.okm.affiliatedauthor | Lehtonen, Eero | |
| dc.okm.discipline | 113 Computer and information sciences | en_GB |
| dc.okm.discipline | 213 Electronic, automation and communications engineering, electronics | en_GB |
| dc.okm.discipline | 221 Nanotechnology | en_GB |
| dc.okm.discipline | 113 Tietojenkäsittely ja informaatiotieteet | fi_FI |
| dc.okm.discipline | 213 Sähkö-, automaatio- ja tietoliikennetekniikka, elektroniikka | fi_FI |
| dc.okm.discipline | 221 Nanoteknologia | fi_FI |
| dc.okm.internationalcopublication | international co-publication | |
| dc.okm.internationality | International publication | |
| dc.okm.type | A1 ScientificArticle | |
| dc.publisher | IEEE | |
| dc.relation.doi | 10.1109/TVLSI.2013.2250319 | |
| dc.relation.ispartofjournal | IEEE Transactions on Very Large Scale Integration (VLSI) Systems | |
| dc.relation.issue | 3 | |
| dc.relation.volume | 22 | |
| dc.source.identifier | https://www.utupub.fi/handle/10024/160091 | |
| dc.title | Large-scale memristive associative memories | |
| dc.year.issued | 2014 |
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