-
公开(公告)号:US20230047277A1
公开(公告)日:2023-02-16
申请号:US17871855
申请日:2022-07-22
Inventor: Seyoung KIM , Doyoon KIM , Hyunjeong KWAK , Jeonghoon SON , Chuljun LEE
Abstract: Provided is a three-dimensional vertical memory device including: a semiconductor substrate, a vertical columnar channel region provided on the semiconductor substrate and having a void of a predetermined size therein; a source electrode and a drain electrode spaced apart from each other with the channel region interposed therebetween; and a gate stack formed on the channel region.
-
公开(公告)号:US20250077854A1
公开(公告)日:2025-03-06
申请号:US18652689
申请日:2024-05-01
Inventor: Seyoung KIM , Doyoon KIM
Abstract: A digital-analog memory integrated deep learning accelerator system may include: a main digital device including a first array, the first array having digital circuits and configured to store weights for on-chip learning; an analog device including a second array, the second array having analog circuits and configured to update and store gradient information about the weights during the on-chip learning; and a sub-digital device including a third array, the third array having digital circuits and configured to store values read from the second array and to transfer a value exceeding a threshold to the first array. The digital-analog memory integrated deep learning accelerator system may perform a matrix-level learning process through an array set including the first array, the second array, and the third array. An artificial neural network learning method for a digital-analog memory integrated deep learning accelerator system is also disclosed.
-
公开(公告)号:US20240220784A1
公开(公告)日:2024-07-04
申请号:US18381273
申请日:2023-10-18
Inventor: Seyoung KIM , Doyoon KIM
IPC: G06N3/063
CPC classification number: G06N3/063
Abstract: A synaptic array device according to one embodiment of the present disclosure comprises a first synaptic array representing weight values, a second synaptic array receiving the error gradient of the weights of the first synaptic array and representing gradient values refined in row units, and a third synaptic array receiving the gradient values refined in row units from the second synaptic array and passing the portion of the received gradient values exceeding a threshold to the first synaptic array, wherein the third synaptic array derives a moving average value by averaging accumulated values of the gradient values received from the second synaptic array and passes the derived moving average value to the second synaptic array.
-
-