First Programmable Memristor Computer Aims to Bring AI Processing Down from the Cloud


Reading time ( words)

Building a Programmable Memristor Computer

To build the first programmable memristor computer, Lu’s team worked with associate professor Zhengya Zhang and professor Michael Flynn, both of electrical and computer engineering at U-M, to design a chip that could integrate the memristor array with all the other elements needed to program and run it. Those components included a conventional digital processor and communication channels, as well as digital/analog converters to serve as interpreters between the analog memristor array and the rest of the computer.

Lu’s team then integrated the memristor array directly on the chip at U-M’s Lurie Nanofabrication Facility. They also developed software to map machine learning algorithms onto the matrix-like structure of the memristor array.

The team demonstrated the device with three bread-and-butter machine learning algorithms:

  • Perceptron, which is used to classify information. They were able to identify imperfect Greek letters with 100% accuracy
  • Sparse coding, which compresses and categorizes data, particularly images. The computer was able to find the most efficient way to reconstruct images in a set and identified patterns with 100% accuracy
  • Two-layer neural network, designed to find patterns in complex data. This two-layer network found commonalities and differentiating factors in breast cancer screening data and then classified each case as malignant or benign with 94.6% accuracy.

There are challenges in scaling up for commercial use—memristors can’t yet be made as identical as they need to be and the information stored in the array isn’t entirely reliable because it runs on analog’s continuum rather than the digital either/or. These are future directions of Lu’s group.

Lu plans to commercialize this technology. The study is titled, “A fully integrated reprogrammable memristor–CMOS system for efficient multiply–accumulate operations.” The research is funded by the Defense Advanced Research Projects Agency, the center for Applications Driving Architectures (ADA), and the National Science Foundation.

Share

Print


Suggested Items

CES Press Kickoff Presentation

01/07/2020 | Nolan Johnson, I-Connect007
On January 5, Editor Nolan Johnson attended the CES press kickoff presentation “2020 Trends to Watch,” which was hosted by CES Vice President of Research Steve Koenig and CES Director of Research Lesley Rohrbaugh. Koenig and Rohrbaugh set the stage for the week with their presentation, answering the question, “What’s happening in the industry?”

NASA Sounding Rocket Technology Could Enable Simultaneous, Multi-Point Measurements — First-Ever Capability

10/21/2019 | NASA
NASA engineers plan to test a new avionics technology — distributed payload communications — that would give scientists a never-before-offered capability in sounding rocket-based research.

Worldwide Semiconductor Equipment Billings at $13.3 Billion in 2Q19; Down 20%

09/12/2019 | SEMI
Worldwide semiconductor manufacturing equipment billings reached $13.3 billion in the second quarter of 2019, down 20% from the same quarter of 2018 and 3% from than the previous quarter.



Copyright © 2020 I-Connect007. All rights reserved.