Novel ultra-low power memory for neuromorphic computing​ developed

Cut: Illustration of the ultra-low power phase change memory device developed through this study and the comparison of power consumption by the newly developed phase change memory device compared to conventional phase change memory devices. Image: KAIST

A team of Korean researchers has developed a new memory device that can be used to replace existing memory or used in implementing neuromorphic computing for next-generation artificial intelligence hardware for its low processing costs and its ultra-low power consumption.

KAIST announced that Professor Shinhyun Choi’s research team in the School of Electrical Engineering has developed a next-generation phase change memory device featuring ultra-low-power consumption that can replace DRAM and NAND flash memory.

Phase change memory is a memory device that stores and/or processes information by changing the crystalline states of materials to be amorphous or crystalline using heat, thereby changing its resistance state.

Existing phase change memory has problems such as an expensive fabrication process for making highly scaled devices. It also requires a substantial amount of power for operation. To solve these problems, Choi’s research team developed an ultra-low power phase change memory device by electrically forming a very small nanometre (nm) scale phase changeable filament without expensive fabrication processes. This new development has the advantage of not only having a very low processing cost but also of enabling operation with ultra-low power consumption.

DRAM, one of the most popular memory options, is very fast, but has volatile characteristics in which data disappear when the power is turned off. NAND flash memory, a storage device, has relatively slow read/write speeds, but it has non-volatile characteristic that enables it to preserve data even when the power is cut off.

Phase change memory, on the other hand, combines the advantages of DRAM and NAND flash memory, offering high speed and non-volatile characteristics. For this reason, phase change memory is being highlighted as a next-generation memory that can replace existing memory. It is being actively researched as a memory technology or neuromorphic computing technology that mimics the human brain.

Conventional phase change memory devices require a substantial amount of power to operate, making it difficult to make practical large-capacity memory products or realize a neuromorphic computing system. To maximize the thermal efficiency for memory device operation, previous research efforts focused on reducing the power consumption by shrinking the physical size of the device through the use of lithography technologies, but these had limitations in terms of practicality as the degree of improvement in power consumption was minimal whereas the cost and the difficulty of fabrication increased with each improvement.

To solve the power consumption problem of phase change memory, Choi’s research team created a method to electrically form phase change materials in an extremely small area, successfully implementing an ultra-low-power phase change memory device that consumes 15 times less power than a conventional phase change memory device fabricated with the expensive lithography tool.

Choi said: “The phase change memory device we have developed is significant as it offers a novel approach to solve the lingering problems in producing a memory device at a greatly improved manufacturing cost and energy efficiency. We expect the results of our study to become the foundation of future electronic engineering, enabling various applications including high-density three-dimensional vertical memory and neuromorphic computing systems as it opened up the possibilities to choose from a variety of materials.” He went on to add, “I would like to thank the National Research Foundation of Korea and the National NanoFab Center for supporting this research.”

The study, in which See-On Park, a student of MS-PhD Integrated Program, and Seokman Hong, a doctoral student of the School of Electrical Engineering at KAIST, participated as first authors, was published in the April issue of the academic journal Nature.

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