A 1-16b Reconfigurable 80Kb 7T SRAM-Based Digital Near-Memory Computing Macro for Processing Neural Networks-Reference-Cited by-同舟云学术

A 1-16b Reconfigurable 80Kb 7T SRAM-Based Digital Near-Memory Computing Macro for Processing Neural Networks

Published:2023-04 Issue:4 Volume:70 Page:1580-1590
ISSN:1549-8328
Container-title:IEEE Transactions on Circuits and Systems I: Regular Papers
language:
Short-container-title:IEEE Trans. Circuits Syst. I

Author:

Kim Hyunjoon¹^ORCID,Mu Junjie¹^ORCID,Yu Chengshuo¹^ORCID,Kim Tony Tae-Hyoung¹^ORCID,Kim Bongjin²^ORCID

Affiliation:

1. School of Electrical and Electronic Engineering, Nanyang Technological University, Nanyang Ave, Singapore

2. Department of Electrical and Computer Engineering, University of California at Santa Barbara, Santa Barbara, CA, USA

Funder

Samsung Fund from Samsung Korea

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Hardware and Architecture

Link

http://xplorestaging.ieee.org/ielx7/8919/10089883/10012044.pdf?arnumber=10012044

Reference40 articles.

1. A 28 nm 384 kb 6T-SRAM computation-in-memory macro with 8b precision for AI edge chips;su;IEEE Int Solid-State Circuits Conf (ISSCC) Dig Tech Papers,2021

2. A 40-nm 118.44-TOPS/W Voltage-Sensing Compute-in-Memory RRAM Macro With Write Verification and Multi-Bit Encoding

3. 15.1 A Programmable Neural-Network Inference Accelerator Based on Scalable In-Memory Computing

4. A Reconfigurable 4T2R ReRAM Computing In-Memory Macro for Efficient Edge Applications

5. A 351 TOPS/W and 372.4 GOPS compute-in-memory SRAM macro in 7 nm FinFET CMOS for machine-learning applications;dong;IEEE Int Solid-State Circuits Conf (ISSCC) Dig Tech Papers,2020

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