Voltage‐Summation‐Based Compute‐in‐Memory Technology with Capacitive Synaptic Devices

Previous compute‐in‐memory (CIM) technologies use current summation for executing matrix–vector multiplication (MVM) operations and are gaining attention as next‐generation artificial intelligence (AI) computing systems. Despite their advantages, these technologies encounter significant difficulties, such as managing wide current ranges in large arrays, overcoming substantial “IR (current‐resistance)‐drop” issues, and integrating with complementary metal–oxide–semiconductor operating circuits. Herein, an innovative voltage‐summation‐based CIM (V‐CIM) technology is introduced; this technology represents a paradigm shift that employs capacitive coupling at a floating voltage summation node for MVM operations. By using a differential pair of input voltages (|ΔV|) with opposite signs relative to the reference voltage, the accumulated MVM results at the floating summation node cancel out, eliminating IR‐drop. Representing the MVM result as an analog voltage simplifies the neuron circuit design and significantly reduces energy consumption. V‐CIM technology is reported with two types of capacitive synaptic devices: read‐only and programmable. A prototype V‐CIM chip using read‐only capacitors is developed, demonstrating the superiority of V‐CIM in image classification applications. For programmable capacitive synaptic devices, a memcapacitor device based on logic‐compatible embedded flash memory is introduced. The work sheds light on ultralow‐power, highly integrated, and highly reliable AI computing systems based on CIM technology.

Object Details

• Location: Deutsche Nationalbibliothek Frankfurt am Main
• Extent: Online-Ressource
• Language: Englisch

References and Relationships

• Bibliographic citation: Voltage‐Summation‐Based Compute‐in‐Memory Technology with Capacitive Synaptic Devices ; day:17 ; month:02 ; year:2025 ; extent:10 ; Advanced intelligent systems ; (17.02.2025) (gesamt 10)

Contributors, Places and Time

• Creator: Kim, Jung Nam ; Kim, Yong Woo ; Kim, Boram ; Kim, Doo‐Hyun ; Lee, Gil Sung ; Chae, Dong‐Hyuk ; Je, Minkyu ; Koo, Minsuk ; Kim, Yoon

Further information

• DOI: 10.1002/aisy.202500028
• URN: urn:nbn:de:101:1-2502181322108.038295513378
• Rights: Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
• Last update: 15.08.2025, 7:35 AM CEST