Jove
Visualize
Contáctanos
JoVE
x logofacebook logolinkedin logoyoutube logo
ACERCA DE JoVE
Visión GeneralLiderazgoBlogCentro de Ayuda JoVE
AUTORES
Proceso de PublicaciónConsejo EditorialAlcance y PolíticasRevisión por ParesPreguntas FrecuentesEnviar
BIBLIOTECARIOS
TestimoniosSuscripcionesAccesoRecursosConsejo Asesor de BibliotecasPreguntas Frecuentes
INVESTIGACIÓN
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchivo
EDUCACIÓN
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualCentro de Recursos para ProfesoresSitio de Profesores
Términos y Condiciones de Uso
Política de Privacidad
Políticas

Videos de Conceptos Relacionados

MOS Capacitor01:25

MOS Capacitor

940
A Metal-Oxide-Semiconductor (MOS) capacitor is a fundamental structure used extensively in semiconductor device technology, particularly in the fabrication of integrated circuits and MOSFETs (metal-oxide-semiconductor field-effect transistors). The MOS capacitor consists of three layers: a metal gate, a dielectric oxide, and a semiconductor substrate.
The metal gate is typically made from highly conductive materials such as aluminum or polysilicon. Beneath the metal gate lies a thin layer of...
940
Understanding Memory01:19

Understanding Memory

603
Memory is the retention of information or experiences over time, facilitated through three main processes: encoding, storage, and retrieval. Encoding is the process of inputting information into the memory system. For instance, when listening to a lecture, watching a play, reading a book, or having a conversation, the brain is actively encoding information. This initial stage involves transforming sensory input into a form that can be processed and stored by the brain. Various factors, such as...
603
Non-ohmic Devices00:51

Non-ohmic Devices

1.2K
In most substances, the current flow is proportional to the voltage applied to it. A simple relationship between the values of current, voltage, and resistance is known as Ohm's law. Nonohmic devices do not exhibit a linear relationship between voltage and current. One such device is the semiconducting circuit element known as a diode. A diode is a circuit device that allows current flow in only one direction.
Consider a simple circuit consisting of a battery, a diode, and a resistor. A...
1.2K
System of Memory01:23

System of Memory

6.4K
Memory is categorized into three major systems: sensory memory, short-term memory (STM), and long-term memory (LTM). These systems differ in their capacity and the duration for which they can hold information. Sensory memory captures raw sensory input from the environment, holding it for just a few seconds or less. For example, on hearing a brief, loud sound, like a car horn honking, the sound seems to linger in the mind for a moment even after it stops. This is an instance of sensory memory...
6.4K
Design Example: Resistive Touchscreen01:14

Design Example: Resistive Touchscreen

415
A device engineer plays a crucial role in designing user interfaces for mobile devices. One such interface is the resistive touchscreen, which fundamentally consists of two metallic layers: a flexible upper layer and a rigid lower layer, separated by a narrow gap. The high resistance between these two layers is a key characteristic of this design.
When a user touches the screen, the two layers make contact at a specific point known as the touchpoint. This contact reduces the resistance between...
415
Semiconductors01:22

Semiconductors

856
There is variation in the electrical conductivity of materials - metals, semiconductors, and insulators that are showcased with the help of the energy band diagrams.
Metals such as copper (Cu), zinc (Zn), or lead (Pb) have low resistivity and feature conduction bands that are either not fully occupied or overlap with the valence band, making a bandgap non-existent. This allows electrons in the highest energy levels of the valence band to easily transition to the conduction band upon gaining...
856

También podría leer

Artículos Relacionados

Artículos vinculados a este trabajo por autores compartidos, revista y gráfico de citas.

Ordenar por
Same author

From uric acid to tophi: multistage molecular and cellular mechanisms of tophi formation.

Frontiers in immunology·2026
Same author

Effects of colloidal delivery systems for curcumin-Brassica rapa L. polysaccharide mixture encapsulation on physicochemical properties, stability, and gut microbiota modulation.

International journal of biological macromolecules·2026
Same author

Programmed cell death in gouty nephropathy: molecular mechanisms and therapeutic implications.

Frontiers in immunology·2026
Same author

The effect of amylose/amylopectin ratio on the stability of starch-O/W emulsion.

Journal of the science of food and agriculture·2026
Same author

Decision-making for indoor residual spraying in the post-elimination phase of visceral leishmaniasis in Nepal.

PLoS neglected tropical diseases·2026
Same author

Challenges and opportunities of the full phase-out of fossil fuels under the 1.5 °C goal.

Nature communications·2026
Same journal

Family of magnetic field-boosted superconductors in rhombohedral graphene.

Nature·2026
Same journal

What's the human cost of US research turmoil? A new film finds out.

Nature·2026
Same journal

Daily briefing: Ovaries start a second job after menopause.

Nature·2026
Same journal

Audio long read: Is the peptide craze backed by science? The promise behind the hype.

Nature·2026
Same journal

Scientists fight back against far-right plans to restrict academic freedom in Germany.

Nature·2026
Same journal

How AI can crack open the 'hidden curriculum' for neurodivergent students.

Nature·2026
Ver todos los artículos relacionados

Video Experimental Relacionado

Updated: Sep 1, 2025

A Method for Growing Bio-memristors from Slime Mold
07:46

A Method for Growing Bio-memristors from Slime Mold

Published on: November 2, 2017

9.0K

Un chip de computación en memoria basado en memoria de acceso aleatorio resistivo

Weier Wan1,2, Rajkumar Kubendran3,4, Clemens Schaefer5

  • 1Stanford University, Stanford, CA, USA. weierwan@stanford.edu.

Nature
|August 17, 2022
PubMed
Resumen
Este resumen es generado por máquina.

Este estudio presenta NeuRRAM, un nuevo chip de cálculo en memoria (CIM) que utiliza memoria de acceso aleatorio resistivo (RRAM). NeuRRAM logra una eficiencia energética y una precisión superiores para las tareas de inteligencia artificial (IA) en dispositivos de borde.

Más Videos Relacionados

Assembly and Characterization of Biomolecular Memristors Consisting of Ion Channel-doped Lipid Membranes
08:07

Assembly and Characterization of Biomolecular Memristors Consisting of Ion Channel-doped Lipid Membranes

Published on: March 9, 2019

7.9K
In Situ Transmission Electron Microscopy with Biasing and Fabrication of Asymmetric Crossbars Based on Mixed-Phased a-VOx
09:49

In Situ Transmission Electron Microscopy with Biasing and Fabrication of Asymmetric Crossbars Based on Mixed-Phased a-VOx

Published on: May 13, 2020

4.1K

Videos de Experimentos Relacionados

Last Updated: Sep 1, 2025

A Method for Growing Bio-memristors from Slime Mold
07:46

A Method for Growing Bio-memristors from Slime Mold

Published on: November 2, 2017

9.0K
Assembly and Characterization of Biomolecular Memristors Consisting of Ion Channel-doped Lipid Membranes
08:07

Assembly and Characterization of Biomolecular Memristors Consisting of Ion Channel-doped Lipid Membranes

Published on: March 9, 2019

7.9K
In Situ Transmission Electron Microscopy with Biasing and Fabrication of Asymmetric Crossbars Based on Mixed-Phased a-VOx
09:49

In Situ Transmission Electron Microscopy with Biasing and Fabrication of Asymmetric Crossbars Based on Mixed-Phased a-VOx

Published on: May 13, 2020

4.1K

Área de la Ciencia:

  • Ciencias de los materiales
  • Ingeniería informática
  • Inteligencia artificial

Sus antecedentes:

  • Los dispositivos de borde requieren hardware eficiente en energía para funcionalidades complejas de IA.
  • La computación en memoria (CIM) utilizando memoria de acceso aleatorio resistivo (RRAM) ofrece una solución mediante la integración de memoria y computación.
  • Los chips RRAM-CIM existentes se enfrentan a desafíos para equilibrar la eficiencia energética, la versatilidad del modelo y la precisión.

Objetivo del estudio:

  • Desarrollar un chip CIM basado en RRAM, NeuRRAM, que supere las compensaciones entre eficiencia, versatilidad y precisión.
  • Para demostrar mejoras simultáneas en múltiples jerarquías de diseño: algoritmos, arquitectura, circuitos y dispositivos.
  • Habilitar funcionalidades avanzadas de IA directamente en dispositivos de borde con una eficiencia energética sin precedentes.

Principales métodos:

  • Co-optimización entre algoritmos, arquitectura, circuitos y dispositivos para el diseño de RRAM-CIM.
  • Desarrollo de un nuevo chip CIM basado en RRAM llamado NeuRRAM.
  • Integración de dispositivos RRAM densos, analógicos y no volátiles para el cálculo en memoria.

Principales resultados:

  • NeuRRAM logra una eficiencia energética dos veces mayor en comparación con los chips RRAM-CIM anteriores.
  • El chip demuestra versatilidad al reconfigurar núcleos CIM para diversas arquitecturas de modelos de IA.
  • La precisión de la inferencia es comparable a los modelos de software con cuantización de peso de cuatro bits en varias tareas de IA, incluida la clasificación de imágenes y el reconocimiento de voz.

Conclusiones:

  • NeuRRAM representa un avance significativo en la tecnología CIM basada en RRAM.
  • El enfoque de co-optimización aborda con éxito las compensaciones de eficiencia, versatilidad y precisión.
  • Esta tecnología allana el camino para un procesamiento de IA altamente eficiente y preciso en dispositivos de borde.