Reprint

Low Power Memory/Memristor Devices and Systems

Edited by
January 2023
250 pages
  • ISBN978-3-0365-6185-1 (Hardback)
  • ISBN978-3-0365-6186-8 (PDF)

This book is a reprint of the Special Issue Low Power Memory/Memristor Devices and Systems that was published in

Chemistry & Materials Science
Engineering
Physical Sciences
Summary

This reprint focusses on achieving low-power computation using memristive devices. The topic was designed as a convenient reference point: it contains a mix of techniques starting from the fundamental manufacturing of memristive devices all the way to applications such as physically unclonable functions, and also covers perspectives on, e.g., in-memory computing, which is inextricably linked with emerging memory devices such as memristors. Finally, the reprint contains a few articles representing how other communities (from typical CMOS design to photonics) are fighting on their own fronts in the quest towards low-power computation, as a comparison with the memristor literature. We hope that readers will enjoy discovering the articles within.

Format
  • Hardback
License
© 2022 by the authors; CC BY-NC-ND license
Keywords
Logic-in-Memory (LiM); Von Neumann’s bottleneck; memory-wall; memristor; memristive logic; Non-Volatile Memory (NVM); Resistive RAM; in-memory computing; majority logic; adder; Boolean logic; parallel-prefix adder; floating-gate transistor; nonvolatile memory; continuous-time programming; floating-gate memory array; FPAA; reconfigurable; MRAM; TRNG; PUF; morphable security primitive; hardware security primitive; RRAM; resistive-switching; cross-point; memory; memristor; neuromorphic; pattern recognition; multilayer perceptron; BNN; logic-in-memory; RRAM; SIMPLY; physical design; power grid; power-gating; SRPG; selective SRPG; floorplanning; place and route; resistive RAM (ReRAM); non-volatile memory (NVM); majority logic; memristor; 1Transistor-1Resistor (1T–1R); in-memory computing; processing-in-memory; parallel-prefix adder; logic-in-memory; memristive logic; memristor; silicon oxide; silicon nitride; SOI technology; resistive switching; electrical characteristics; laser treatment; thermal treatment; in-memory computing; energy modeling; non-von neumann; instruction set; compilation; stencils; convolutions; sram; energy wall; memory wall; low-bandwidth TIA; equalizer; multi-stage main amplifier; amplitude response; group delay variation; graph coloring; cellular nonlinear networks; memristor oscillatory networks; locally-active memristors; control theory