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Vourkas et al., 2016 - Google Patents

Memristor-based nanoelectronic computing circuits and architectures

Vourkas et al., 2016

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Document ID
14893821587591197623
Author
Vourkas I
Sirakoulis G
Publication year

External Links

Snippet

Continued dimensional and functional scaling of Complementary Metal-Oxide- Semiconductor (CMOS) technology is driving information processing into a broadening spectrum of new applications. Many of these applications are enabled by performance gains …
Continue reading at media.hugendubel.de (PDF) (other versions)

Classifications

    • GPHYSICS
    • G11INFORMATION STORAGE
    • G11CSTATIC STORES
    • G11C13/00Digital stores characterised by the use of storage elements not covered by groups G11C11/00, G11C23/00 - G11C25/00
    • G11C13/0002Digital stores characterised by the use of storage elements not covered by groups G11C11/00, G11C23/00 - G11C25/00 using resistance random access memory [RRAM] elements
    • G11C13/0021Auxiliary circuits
    • GPHYSICS
    • G11INFORMATION STORAGE
    • G11CSTATIC STORES
    • G11C13/00Digital stores characterised by the use of storage elements not covered by groups G11C11/00, G11C23/00 - G11C25/00
    • G11C13/0002Digital stores characterised by the use of storage elements not covered by groups G11C11/00, G11C23/00 - G11C25/00 using resistance random access memory [RRAM] elements
    • G11C13/0007Digital stores characterised by the use of storage elements not covered by groups G11C11/00, G11C23/00 - G11C25/00 using resistance random access memory [RRAM] elements comprising metal oxide memory material, e.g. perovskites
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00Computer systems based on biological models
    • G06N3/02Computer systems based on biological models using neural network models
    • G06N3/06Physical realisation, i.e. hardware implementation of neural networks, neurons or parts of neurons
    • G06N3/063Physical realisation, i.e. hardware implementation of neural networks, neurons or parts of neurons using electronic means
    • G06N3/0635Physical realisation, i.e. hardware implementation of neural networks, neurons or parts of neurons using electronic means using analogue means
    • GPHYSICS
    • G11INFORMATION STORAGE
    • G11CSTATIC STORES
    • G11C13/00Digital stores characterised by the use of storage elements not covered by groups G11C11/00, G11C23/00 - G11C25/00
    • G11C13/0002Digital stores characterised by the use of storage elements not covered by groups G11C11/00, G11C23/00 - G11C25/00 using resistance random access memory [RRAM] elements
    • G11C13/0009RRAM elements whose operation depends upon chemical change
    • GPHYSICS
    • G11INFORMATION STORAGE
    • G11CSTATIC STORES
    • G11C11/00Digital stores characterised by the use of particular electric or magnetic storage elements; Storage elements therefor
    • G11C11/02Digital stores characterised by the use of particular electric or magnetic storage elements; Storage elements therefor using magnetic elements
    • GPHYSICS
    • G11INFORMATION STORAGE
    • G11CSTATIC STORES
    • G11C11/00Digital stores characterised by the use of particular electric or magnetic storage elements; Storage elements therefor
    • G11C11/56Digital stores characterised by the use of particular electric or magnetic storage elements; Storage elements therefor using storage elements with more than two stable states represented by steps, e.g. of voltage, current, phase, frequency
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/50Computer-aided design
    • GPHYSICS
    • G11INFORMATION STORAGE
    • G11CSTATIC STORES
    • G11C2213/00Indexing scheme relating to G11C13/00 for features not covered by this group

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