Skip to main content

next-gen semiconductor designs for AI

AI Computational Performance Enhancement through ECRAM Devices

next-gen semiconductor

Introduction

  • A research group has revealed that using ECRAM devices in analog hardware can significantly boost AI computational performance, underscoring its commercialization prospects. The study is published in Science Advances.

AI Technology Development and Hardware Challenges

  • The fast-paced development of AI technology, such as generative AI, has pushed the scalability boundaries of traditional digital hardware (CPUs, GPUs, ASICs, etc.). This challenge has led to active exploration of analog hardware designed specifically for AI computation.
  • Analog hardware modulates semiconductor resistance through external voltage or current and employs a cross-point array structure with intersecting memory devices to execute parallel AI computations. Despite its advantages over digital hardware for certain computational tasks and continuous data processing, fulfilling the varied demands for computational learning and inference poses significant challenges.

Addressing Analog Hardware Shortcomings

  • Addressing the shortcomings of analog hardware memeory devices, a research team led by Professor Seyoung Kim from the Department of Materials Science and Engineering and Semiconductor Engineering investigated Electrochemical Random Access Memory (ECRAM), which controls electrical conductivity via ion movement and concentraion.

ECRAM Device Structure and Performance

  • Unlike standard semiconductor memory, these devices employ a three-terminal structure with separate data read and write channels, facilitating low-power operation.
  • The team's study involved fabricating ECRAM devices based on three-terminal semiconductors within a 64x64 array. Experimental results showed the hardware displayed superior electrical and switching characterstics, combined with yield and consistency.

Integration of the Tiki-Taka Algorithm

  • The study further integrated the Tiki-Taka algorithm, a pioneering analog learning algorithm, with the high-yield hardware, which notably improved the accuracy of AI neural network training processes.

Weight Retention Property and Learning Improvement

  • The researchers notably showcased how the 'weight retention' property of hardware training affects learning, proving that their method avoids overloading artificial neural networks and underscoring the technology's commercialization potential.

Advancement in ECRAM Device Arrays

  • This research marks a key advancement from the 10x10 ECRAM device arrays documented in the literature, successfully scaling up to a larger array with diverse device features.

Conclusion

Professor Seyoung Kim from POSTECH remarked, 'Through the advancement of large-scale arrays with innovative memory technologies and the creation of analog-specific AI algorithms, we have uncovered a significant potential for AI computational performance and energy efficiency that exceeds current digital methods.'

Source

Labels:

Comments

Post a Comment

Popular posts from this blog

NASA chile scientists comet 3i atlas nickel mystery

NASA and Chilean Scientists Study 3I/ATLAS, A Comet That Breaks the Rules Interstellar visitors are rare guests in our Solar System , but when they appear they often rewrite the rules of astronomy. Such is the case with 3I/ATLAS , a fast-moving object that has left scientists puzzled with its bizarre behaviour. Recent findings from NASA and Chilean researchers reveal that this comet-like body is expelling an unusual plume of nickel — without the iron that typically accompanies it. The discovery challenges conventional wisdom about how comets form and evolve, sparking both excitement and controversy across the scientific community. A Cosmic Outsider: What Is 3I/ATLAS? The object 3I/ATLAS —the third known interstellar traveler after "Oumuamua (2017) and 2I/Borisov (2019) —was first detected in July 2025 by the ATLAS telescope network , which scans he skies for potentially hazardous objects. Earlier images from Chile's Vera C. Rubin Observatory had unknowingly captured it, but ...
Post a Comment
Read more

bermuda triangle rogue waves mystery solved

Bermuda Triangle Mystery: Scientist Claims Rogue Waves May Explain Vanishing Ships and Aircraft for decades, the Bermuda Triangle has captured the world's imagination, often described as a supernatural hotspot where ships vanish and aircraft disappear without a trace. From ghostly ships adrift to unexplained plane crashes, this stretch of ocean between Bermuda, Puerto Rico and Florida remains one of the most infamous maritime mysteries. But now, Dr. Simon Boxall, an oceanographer at the University of Southampton , suggests the answer may not be extraterrestrial at all. Instead, he argues that the truth lies in rogue waves — giant, unpredictable surges of water capable of swallowing even the largest ships within minutes. The Bermuda Triangle: A Legacy of Fear and Fascination The Bermuda Triangle has inspired decades of speculation , with theories ranging from UFO abductions to interdimensional rifts. Popular culture, documentaries and countless books have kept the legend alive, of...
Post a Comment
Read more

nist breakthrough particle number concentration formula

NIST Researchers Introduce Breakthrough Formula for Particle Number Concentration Understanding the number of particles in a sample is a fundamental task across multiple scientific fields — from nanotechnology to food science. Scientists use a measure called Particle Number Concentration (PNC) to determine how many particles exist in a given volume, much like counting marbles in a jar. Recently, researchers at the National Institute of Standards and Technology (NIST) have developed a novel formula that calculates particle concentrations with unprecedented accuracy. Their work, published in Analytical Chemistry , could significantly improve precision in drug delivery, nanoplastic assessment and monitoring food additives. Related reading on Nanotechnology advancements: AI systems for real-time flood detection . What is Particle Number Concentration (PNC)? Defining PNC Particle Number Concentration indicates the total count of particles within a specific volume of gas or liquid,...
Post a Comment
Read more