Emerging Memory and Computing Devices in the Era of Intelligent Machines
Abstract
Computing systems are undergoing a transformation from logic-centric towards memory-centric architectures, where overall performance and energy efficiency at the system level are determined by the density, performance, functionality and efficiency of the memory, rather than the logic sub-system.
Keywords
n/a; image classification; bipolar resistive switching characteristics; bioelectronic devices; self-directed channel (SDC); programmable ramp-down current pulses; nanoparticles; protein; DRAM; convolutional neural networks; silicon oxide-based memristors; electrochemical metallization cell; magnetic tunnel junction; power gating; resistance switching mechanism; BCH; Fast Fourier Transform; nucleic acid; biomemory; conductive filament; resistive random access memory (RRAM); non-von Neumann architecture; emerging technologies; Galois field; variability; logic-in-memory; charge spreading; memristor; Hebbian training; crossbar; quantum point contact; SONOS; bionanohybrid material; ECG; neuromorphic computing; CUDA; low-latency; iBM; Oxygen-related trap; nonvolatile memory; phase change memory; floating gate; non-von neumann architecture; 3D-stacked; STT-MRAM; solution-based dielectric; GPU; Internet of things; configurable logic-in-memory architecture; memory wall; biologic gate; synaptic weight; guide training; ion conduction; perpendicular Nano Magnetic Logic (pNML); Weibull distribution; real-time system; in-DRAM cache; task placement; dynamic voltage scaling; MCU (microprogrammed control unit); wire resistance; multi-level cell; chalcogenide; decoder; character recognition; matrix-vector multiplication; hybrid; magnetoresistive random access memory; blockchain; electrochemical metallization (ECM); RISC-V; U-shape recessed channel; neuromorphic system; in-memory computing; crossbar array; associative processor; low-power; plasma treatment; voltage-controlled magnetic anisotropy; flash memory; resistive memory; analogue computing; bioprocessor; annealing temperatures; data retention; flip-flop; low-power techniqueISBN
9783039285037, 9783039285020Publisher website
www.mdpi.com/booksPublication date and place
2020Classification
History of engineering and technology


