Loading...
News Article

Researchers design new analog chip architecture with high precision

News

Design combines the best of digital and analog computing and delivers >10x energy efficiency.

While most of computing in the world is still digital, the data around us is captured in analog via sensors–images through cameras, temperature, and sound, for example and has to be converted in a digital form for precision. But imagine an autonomous vehicle which needs to capture what’s on the road etc. and then make decisions instantaneously, this data needs to be converted—very quickly with low energy and high precision. What if newly designed analog chips could provide the precision of digital computing with the energy-saving and high-speed advantages of analog computing?

If a computer chip is made up of various circuits, a memristor is a relatively small-sized component of a circuit that stores and processes data very efficiently. In a previous paper from the lab of USC Viterbi School of Engineering Electrical and Computer Engineering professor, J. Joshua Yang, researchers were able to tweak a memristor to achieve unprecedented precision. His lab within USC Viterbi and its School of Advanced Computing is focused on developing devices for computing.

The lab has designed a new circuit and architecture to achieve even higher precision with the same memristors, which could greatly extend the applications of such technology beyond the traditional low-precision territory, such as neural networks. Moreover, says Yang, this innovation is applicable to other types of memory technologies as well, including magnetic memories that use the same device as the read-head of the magnetic hard disk drives, and phase change memories that use the same material as the compact discs (CDs).

Normally, says Yang, it is very challenging to quickly program an analog device precisely to a target value. Yang’s lab developed circuit architecture and corresponding algorithm to do exactly that. This innovation makes analog computing using analog devices much more attractive for many applications.

Yang says it has, ‘higher efficiency and higher speed with accuracy of the digital systems.”

This type of improvement is critical, says Yang as such innovations can be applied to train neural networks which are needed to develop artificial intelligence (AI) and machine learning (ML) but thus far can only be done in very expensively with digital systems. The innovation will also enable new applications beyond AI and ML, such as scientific computing for such as weather forecasting.

The paper, “Programming memristor arrays with arbitrarily high precision for analog computing” was featured in Science, was written with Wenhao Song , Ye Zhuo, Peter A. Beerel, Mike Shuo-Wei Chen at USC, along with Qiangfei Xia at University of Massachusetts, Mark Barnell and Qing Wu at Air Force Research Lab, Information Directorate, Rome, NY, USA. The research was conducted with Miao Hu, Gleen Ge, and other engineers of TetraMem Inc., a startup co-founded by Yang.

The previous paper on which this research builds on previous paper in this lab was featured in Nature.

Silicon photonics: accelerating growth in the race for high-speed optical interconnects
CCD-in-CMOS technology enables ultra-fast burst mode imaging
2025 6G A look forward
Critical Manufacturing climbs Deloitte’s Technology Fast 50
Semiconductors: The most important thing you probably know the least about
Imec and partners unveil SWIR sensor with lead-free quantum dot photodiodes
Lattice introduces small and mid-range FPGA offerings
SEMI and SMT inspection solutions at NEPCON Japan 2025
Nordic Semiconductor and Kigen demonstrate Remote SIM Provisioning for Massive IoT
Spirent collaborates with Siemens
Quobly forges strategic collaboration with STMicroelectronics
New standards in pressure measurement systems for the semiconductor industry
IBM delivers optics breakthrough
Semiconductor equipment sales to reach $139 Billion in 2026
Marvell introduces 1.6 Tbps LPO Chipset
ACM research strengthens Atomic Layer Deposition portfolio
CEA-Leti demonstrates embedded FeRAM platform compatible with 22nm FD-SOI node
Lattice introduces small and mid-range FPGA offerings
Solace unlocks full potential of event-driven integration
Advantest to showcase latest test solutions at SEMICON Japan 2024
CEA-Leti device integrates light sensing and modulation
Nordic launches Thingy:91 X prototyping platform for cellular IoT and Wi-Fi locationing
Imec achieves seamless InP Chiplet integration on 300mm RF Silicon Interposer
High-precision SMU
Powering India’s energy future
China’s Nvidia probe puts global investors ‘on notice’
POET Technologies appoints new director
Imec demonstrates core building blocks of a scalable, CMOS-fab compatible superconducting digital technology
Imec proposes double-row CFET for the A7 technology node
ULVAC launches new deposition system
Beebolt and SEMI Announce Strategic Partnership to Drive Supplier Resilience and Agility
esmo group introduces Automated Final Test Manipulator
×
Search the news archive

To close this popup you can press escape or click the close icon.
Logo
x
Logo
×
Register - Step 1

You may choose to subscribe to the Silicon Semiconductor Magazine, the Silicon Semiconductor Newsletter, or both. You may also request additional information if required, before submitting your application.


Please subscribe me to:

 

You chose the industry type of "Other"

Please enter the industry that you work in:
Please enter the industry that you work in: