Tag Archives: green computing

Bringing memristors to the masses and cutting down on energy use

One of my earliest posts featuring memristors (May 9, 2008) focused on their potential for energy savings but since then most of my postings feature research into their application in the field of neuromorphic (brainlike) computing. (For a description and abbreviated history of the memristor go to this page on my Nanotech Mysteries Wiki.)

In a sense this July 30, 2018 news item on Nanowerk is a return to the beginning,

A new way of arranging advanced computer components called memristors on a chip could enable them to be used for general computing, which could cut energy consumption by a factor of 100.

This would improve performance in low power environments such as smartphones or make for more efficient supercomputers, says a University of Michigan researcher.

“Historically, the semiconductor industry has improved performance by making devices faster. But although the processors and memories are very fast, they can’t be efficient because they have to wait for data to come in and out,” said Wei Lu, U-M professor of electrical and computer engineering and co-founder of memristor startup Crossbar Inc.

Memristors might be the answer. Named as a portmanteau of memory and resistor, they can be programmed to have different resistance states–meaning they store information as resistance levels. These circuit elements enable memory and processing in the same device, cutting out the data transfer bottleneck experienced by conventional computers in which the memory is separate from the processor.

A July 30, 2018 University of Michigan news release (also on EurekAlert), which originated the news item, expands on the theme,

… unlike ordinary bits, which are 1 or 0, memristors can have resistances that are on a continuum. Some applications, such as computing that mimics the brain (neuromorphic), take advantage of the analog nature of memristors. But for ordinary computing, trying to differentiate among small variations in the current passing through a memristor device is not precise enough for numerical calculations.

Lu and his colleagues got around this problem by digitizing the current outputs—defining current ranges as specific bit values (i.e., 0 or 1). The team was also able to map large mathematical problems into smaller blocks within the array, improving the efficiency and flexibility of the system.

Computers with these new blocks, which the researchers call “memory-processing units,” could be particularly useful for implementing machine learning and artificial intelligence algorithms. They are also well suited to tasks that are based on matrix operations, such as simulations used for weather prediction. The simplest mathematical matrices, akin to tables with rows and columns of numbers, can map directly onto the grid of memristors.

The memristor array situated on a circuit board.

The memristor array situated on a circuit board. Credit: Mohammed Zidan, Nanoelectronics group, University of Michigan.

Once the memristors are set to represent the numbers, operations that multiply and sum the rows and columns can be taken care of simultaneously, with a set of voltage pulses along the rows. The current measured at the end of each column contains the answers. A typical processor, in contrast, would have to read the value from each cell of the matrix, perform multiplication, and then sum up each column in series.

“We get the multiplication and addition in one step. It’s taken care of through physical laws. We don’t need to manually multiply and sum in a processor,” Lu said.

His team chose to solve partial differential equations as a test for a 32×32 memristor array—which Lu imagines as just one block of a future system. These equations, including those behind weather forecasting, underpin many problems science and engineering but are very challenging to solve. The difficulty comes from the complicated forms and multiple variables needed to model physical phenomena.

When solving partial differential equations exactly is impossible, solving them approximately can require supercomputers. These problems often involve very large matrices of data, so the memory-processor communication bottleneck is neatly solved with a memristor array. The equations Lu’s team used in their demonstration simulated a plasma reactor, such as those used for integrated circuit fabrication.

This work is described in a study, “A general memristor-based partial differential equation solver,” published in the journal Nature Electronics.

It was supported by the Defense Advanced Research Projects Agency (DARPA) (grant no. HR0011-17-2-0018) and by the National Science Foundation (NSF) (grant no. CCF-1617315).

Here’s a link and a citation for the paper,

A general memristor-based partial differential equation solver by Mohammed A. Zidan, YeonJoo Jeong, Jihang Lee, Bing Chen, Shuo Huang, Mark J. Kushner & Wei D. Lu. Nature Electronicsvolume 1, pages411–420 (2018) DOI: https://doi.org/10.1038/s41928-018-0100-6 Published: 13 July 2018

This paper is behind a paywall.

For the curious, Dr. Lu’s startup company, Crossbar can be found here.

Cellulose Nanofibrillated Fiber Based Transistors from the University of Wisconsin-Madison

There’s a team of researchers at the University of Wisconsin-Madison working to substitute silicon used in computer chips with cellulose derived from wood (my May 27, 2015 posting). Their latest effort, featuring mobile electronics, is described in a July 1, 2015 news item on Azonano,

A report published by the U.S. Environmental Protection Agency in 2012 showed that about 152 million mobile devices are discarded every year, of which only 10 percent is recycled — a legacy of waste that consumes a tremendous amount of natural resources and produces a lot of trash made from expensive and non-biodegradable materials like highly purified silicon.

Now researchers from the University of Wisconsin-Madison have come up with a new solution to alleviate the environmental burden of discarded electronics. They have demonstrated the feasibility of making microwave biodegradable thin-film transistors from a transparent, flexible biodegradable substrate made from inexpensive wood, called cellulose nanofibrillated fiber (CNF). This work opens the door for green, low-cost, portable electronic devices in future.

A June 30, 2015 American Institute of Physics news release by Zhengzheng Zhang, which originated the news item, describes the research in more detail,

“We found that cellulose nanofibrillated fiber based transistors exhibit superior performance as that of conventional silicon-based transistors,” said Zhenqiang Ma, the team leader and a professor of electrical and computer engineering at the UW-Madison. “And the bio-based transistors are so safe that you can put them in the forest, and fungus will quickly degrade them. They become as safe as fertilizer.”

Nowadays, the majority of portable electronics are built on non-renewable, non-biodegradable materials such as silicon wafers, which are highly purified, expensive and rigid substrates, but cellulose nanofibrillated fiber films have the potential to replace silicon wafers as electronic substrates in environmental friendly, low-cost, portable gadgets or devices of the future.

Cellulose nanofibrillated fiber is a sustainable, strong, transparent nanomaterial made from wood. Compared to other polymers like plastics, the wood nanomaterial is biocompatible and has relatively low thermal expansion coefficient, which means the material won’t change shape as the temperature changes. All these superior properties make cellulose nanofibril an outstanding candidate for making portable green electronics.

To create high-performance devices, Ma’s team employed silicon nanomembranes as the active material in the transistor — pieces of ultra-thin films (thinner than a human hair) peeled from the bulk crystal and then transferred and glued onto the cellulose nanofibrill substrate to create a flexible, biodegradable and transparent silicon transistor.To create high-performance devices, Ma’s team employed silicon nanomembranes as the active material in the transistor — pieces of ultra-thin films (thinner than a human hair) peeled from the bulk crystal and then transferred and glued onto the cellulose nanofibrill substrate to create a flexible, biodegradable and transparent silicon transistor.

But to make portable electronics, the biodegradable transistor needed to be able to operate at microwave frequencies, which is the working range of most wireless devices. The researchers thus conducted a series of experiments such as measuring the current-voltage characteristics to study the device’s functional performance, which finally showed the biodegradable transistor has superior microwave-frequency operation capabilities comparable to existing semiconductor transistors.

“Biodegradable electronics provide a new solution for environmental problems brought by consumers’ pursuit of quickly upgraded portable devices,” said Ma. “It can be anticipated that future electronic chips and portable devices will be much greener and cheaper than that of today.”

Next, Ma and colleagues plan to develop more complicated circuit system based on the biodegradable transistors.

Here’s a link to and a citation for the team’s latest paper,

Microwave flexible transistors on cellulose nanofibrillated fiber substrates by Jung-Hun Seo, Tzu-Hsuan Chang, Jaeseong Lee, Ronald Sabo, Weidong Zhou, Zhiyong Cai, Shaoqin Gong, and Zhenqiang Ma.  Applied Physics Letters, Volume 106, Issue 26 or  Appl. Phys. Lett. 106, 262101 (2015); http://dx.doi.org/10.1063/1.4921077

This is an open access paper.