Results 111 to 120 of about 227,405 (293)
Emerging Memory and Device Technologies for Hardware‐Accelerated Model Training and Inference
Advanced Electronic Materials, EarlyView.This review investigates the suitability of various emerging memory technologies as compute‐in‐memory hardware for artificial intelligence (AI) applications. Distinct requirements for training‐ and inference‐centric computing are discussed, spanning device physics, materials, and system integration.
Yoonho Cho +6 more
wiley +1 more source
Gate-sizing-based single Vdd test for bridge defects in multi-voltage designs
, 2010 The use of multiple voltage settings for dynamic power management is an effective design technique. Recent research has shown that testing for resistive bridging faults in such designs requires more than one voltage setting for 100% fault coverage ...
Harrod, Peter +9 more
core +1 more source
Advanced Electronic Materials, EarlyView.Resistive memory devices are explored for operation at extremely low temperatures relevant to quantum computing. The study reveals how transistor behavior strongly influences memory performance under cryogenic conditions and introduces an optimized programming strategy.
Emilio Pérez‐Bosch Quesada +11 more
wiley +1 more source
, 2013 As silicon manufacturing process scales to and beyond the 65-nm node, process variation can no longer be ignored. The impact of process variation on integrated circuit performance and power has received significant research input.
Zhong, Shida
core +1 more source
SPIKA: an energy-efficient time-domain hybrid CMOS-RRAM compute-in-memory macro
Frontiers in ElectronicsThe increasing significance of machine learning (ML) has led to the development of circuit architectures suited to handling its multiply-accumulate-heavy computational load such as Compute-In-Memory (CIM). A big class of such architectures uses resistive
Khaled Humood +6 more
doaj +1 more source
Advanced Electronic Materials, EarlyView.In this work, low‐resolution infrared imaging is combined with a 28 nm FeFET IMC architecture to enable compact, energy‐efficient edge inference. MLC FeFET devices are experimentally characterized, and controlled multi‐level current accumulation is validated at crossbar array level.
Alptekin Vardar +9 more
wiley +1 more source
DenRAM: neuromorphic dendritic architecture with RRAM for efficient temporal processing with delays
Nature CommunicationsNeuroscience findings emphasize the role of dendritic branching in neocortical pyramidal neurons for non-linear computations and signal processing. Dendritic branches facilitate temporal feature detection via synaptic delays that enable coincidence ...
Simone D’Agostino +8 more
doaj +1 more source
Silicon Nitride Resistive Memories
Advanced Electronic Materials, EarlyView.Amorphous SiNx is an attractive resistance switching material for ReRAM applications due to its physicochemical properties, such as humidity resistance, low oxygen diffusivity, and is used as a metal diffusion blocker. By modifying the ratio between N and Si atoms, the microstructure of the SiNx is affected, rendering it possible to change the ...
Alexandros‐Eleftherios Mavropoulis +7 more
wiley +1 more source
In-place Repair for Resistive Memories Utilizing Complementary Resistive Switches
, 2016 Recent advances in resistive memory technologies have demonstrated their potential to serve as next generation random access memories (RAM) which are fast, low-power, ultra-dense, and nonvolatile.
Kwang-Ting Cheng +7 more
core +1 more source
Environmental Effects on RRAM Cells Based on 2D Halide Perovskite Materials
Advanced Electronic Materials, EarlyView.RRAM offers high speed, scalability, and low power, positioning it as a next‐generation non‐volatile memory. Two‐dimensional halide perovskites show promise due to tunable optoelectronic properties and flexible processing but suffer from environmental sensitivity. This review examines degradation from humidity, temperature, light, and strain, discusses
Mojtaba Joodaki +3 more
wiley +1 more source