Memory-hungry, power-sapping big data might finally have met its match.
Electrical engineers at Northwestern Engineering and the University of Messina in Italy have developed a new magnetic memory device that could potentially support the surge of data-centric computing, which requires ever-increasing power, storage, and speed.
Based on antiferromagnetic (AFM) materials, the device is the smallest of its kind ever demonstrated and operates with record-low electrical current to write data.
“The rise of big data has enabled the emergence of artificial intelligence (AI) in the cloud and on edge devices and is fundamentally transforming the computing, networking, and data storage industries,” said Pedram Khalili, associate professor of electrical and computer engineering in the McCormick School of Engineering, who led the research. “However, existing hardware cannot sustain the rapid growth of data-centric computing. Our technology potentially could solve this challenge.”
The research was published February 10 in the journal Nature Electronics.
Khalili co-led the study with Giovanni Finocchio, an associate professor of electrical engineering at the University of Messina. The team also included Matthew Grayson, a professor of electrical and computer engineering at Northwestern Engineering. Jiacheng Shi and Victor Lopez-Dominguez, who are both members of Khalili’s laboratory, served as co-first authors of the paper.
From promise to probable
Although AI offers promise to improve many areas of society, including health care systems, transportation, and security, it can only meet its potential if computing can support it.
Ideally, AI needs all the best parts of today’s memory technologies: Something as fast as static random access memory (SRAM) and with a storage capacity similar to dynamic random access memory (DRAM) or Flash. On top of that, it also needs low power dissipation.
“There is no existing memory technology that meets all of these demands,” Khalili said. “This has resulted in a so-called ‘memory bottleneck’ that severely limits the performance and energy consumption of AI applications today.”
To meet this challenge, Khalili and his collaborators looked to AFM materials. In AFM materials, electrons behave like tiny magnets due to a quantum mechanical property called “spin,” but the material itself does not demonstrate a macroscopic magnetization because the spins are aligned in antiparallel fashion.
Typically, memory devices require an electric current to retain stored data. But in AFM materials, it is the magnetically ordered spins that perform this task, so a continuously applied electric current is not needed. As an added bonus, the data cannot be erased by external magnetic fields. Because densely packed devices will not interact with magnetic fields, AFM-based devices are very secure and easy to scale down to small dimensions.
Easily adoptable technology
Because they are inherently fast and secure and use lower power, AFM materials have been explored in past studies. But previous researchers experienced difficulties controlling the magnetic order within the materials.
Khalili and his team used pillars of antiferromagnetic platinum manganese — a geometry not previously explored. With a diameter of just 800 nanometers, these pillars are 10 times smaller than earlier AFM-based memory devices.
Importantly, the resulting device is compatible with existing semiconductor manufacturing practices, which means that current manufacturing companies could easily adopt the new technology without having to invest in new equipment.
“This brings AFM memory — and thus highly scaled and high-performance magnetic random-access memory (MRAM) — much closer to practical applications,” Khalili said. “This is a big deal for industry as there is a strong demand today for technologies and materials to extend the scaling and performance of MRAM and increase the return on the huge investment that industry has already made in this technology to bring it to manufacturing.”
Khalili’s team is already working on the next steps toward this translation to applications.
“We are working now to further downscale these devices and to improve methods to read out their magnetic state,” Khalili said. “We also are looking at even more energy-efficient ways to write data into AFM materials, such as replacing the electric current with an electric voltage, a challenging task that could further increase the energy efficiency by another order of magnitude or more.”
The Latest Updates from Bing News & Google News
Go deeper with Bing News on:
Magnetic memory device
- Apple Prepares OLED iPad Pro With An M4 Chip
In preparation for its AI reveal at this year’s Worldwide Developers Conference (WWDC), Apple will reportedly launch a new OLED iPad Pro on May 7th. According to Mark Gurman from Bloomberg, there is ...
- Revolutionizing Technology: Spintronics Market Surges, Expected to Reach US$ 1.4 Billion by 2033
Spintronics Market is set to cross worth of US$ 1,394.2 Million at 7.3% CAGR during forecast period 2023 to 2033 | Data analysis by Future Market Insights, Inc.
- The Best iPads, According To An Apple Expert
Whether for work or for play, the best iPads feature powerful processors and long battery life. Here our top picks.
- Enhancing memory technology: Multiferroic nanodots for low-power magnetic storage
Traditional memory devices are volatile and the current non-volatile ones rely on either ferromagnetic or ferroelectric materials for data storage. In ferromagnetic devices, data is written or stored ...
- Revolutionizing memory technology: multiferroic nanodots for low-power magnetic storage
(Nanowerk News) Traditional memory devices are volatile and the current non-volatile ones rely on either ferromagnetic or ferroelectric materials for data storage. In ferromagnetic devices, data is ...
Go deeper with Google Headlines on:
Magnetic memory device
[google_news title=”” keyword=”magnetic memory device” num_posts=”5″ blurb_length=”0″ show_thumb=”left”]
Go deeper with Bing News on:
Magnetic random-access memory
- A Paradigm Shift in RAM Is About to Make Computing Unstoppable
Every computer needs Random Access Memory (or RAM) for an operating system’s temporary storage, and there’s many ways to achieve this need for memory speed. One of the leading methods is ...
- Ultrafast laser-powered 'magnetic RAM' is on the horizon after new discovery
Researchers have found an elemental physical interaction between light and magnetism that might lead to the next generation of computing memory.
- Downscaling storage devices: magnetic memory based on the chirality of spiral magnets
Spintronic devices, represented by magnetic random access memory (MRAM), utilize the magnetization direction of ferromagnetic materials to memorize information. Because of their non-volatility and ...
- Magnetic Tunnel Junctions: Harnessing Quantum Tunneling for Spintronic Devices
MTJs are the core elements of magnetic random access memory (MRAM), a type of non-volatile memory that combines the speed of SRAM, the density of DRAM, and the non-volatility of flash memory. In MRAM, ...
- "Perfect" memory that could one day replace three types of storage gets very early prototype — SOT-MRAM is cache, system memory and storage rolled into one
Industrial Technology Research Institute (ITRI) and Taiwan Semiconductor Manufacturing Company (TSMC) have announced the creation of a SOT-MRAM (spin-orbit torque magnetic random-access memory ...
Go deeper with Google Headlines on:
Magnetic random-access memory
[google_news title=”” keyword=”magnetic random-access memory” num_posts=”5″ blurb_length=”0″ show_thumb=”left”]