Stable, Low Power and Bit-Interleaving Aware SRAM Memory for Multi-Core Processing Elements
The machine learning and convolutional neural network (CNN)-based intelligent artificial accelerator needs significant parallel data processing from the cache memory. The separate read port is mostly used to design built-in computational memory (CRAM) to reduce the data processing bottleneck. This m...
Saved in:
Main Authors: | Nandakishor Yadav, Youngbae Kim, Shuai Li, Kyuwon Ken Choi |
---|---|
Format: | article |
Language: | EN |
Published: |
MDPI AG
2021
|
Subjects: | |
Online Access: | https://doaj.org/article/ba7d2eb2ee1949f5af18969e8295843e |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Analysis and Optimization of Defect Generation Due to Mechanical Stress in High-Density SRAM
by: Kazunari Ishimaru, et al.
Published: (2021) -
Computing In-Memory Design Based on Double Word Line and Double Threshold 4T SRAM
by: LIN Zhiting, NIU Jianchao+, WU Xiulong, PENG Chunyu
Published: (2021) -
An SRAM Compiler for Monolithic-3-D Integrated Circuit With Carbon Nanotube Transistors
by: Daehyun Kim, et al.
Published: (2021) -
Development and Validation of a Web-Based Reading Test for Normal and Low Vision Patients
by: Labiris G, et al.
Published: (2021) -
Desobedecer el lenguaje : alteridad, lectura y escritura /
by: Skliar, Carlos
Published: (2015)