Mingu Kang
Mingu Kang
IBM TJ Watson Research Center
Verified email at ibm.com
Cited by
Cited by
A 20nm 1.8 V 8Gb PRAM with 40MB/s program bandwidth
Y Choi, I Song, MH Park, H Chung, S Chang, B Cho, J Kim, Y Oh, D Kwon, ...
Solid-State Circuits Conference Digest of Technical Papers (ISSCC), 2012 …, 2012
An energy-efficient VLSI architecture for pattern recognition via deep embedding of computation in SRAM
M Kang, MS Keel, NR Shanbhag, S Eilert, K Curewitz
2014 IEEE International Conference on Acoustics, Speech and Signal …, 2014
A 42pJ/decision 3.12 TOPS/W robust in-memory machine learning classifier with on-chip training
SK Gonugondla, M Kang, N Shanbhag
2018 IEEE International Solid-State Circuits Conference-(ISSCC), 490-492, 2018
A multi-functional in-memory inference processor using a standard 6T SRAM array
M Kang, SK Gonugondla, A Patil, NR Shanbhag
IEEE Journal of Solid-State Circuits 53 (2), 642-655, 2018
FinFET SRAM optimization with fin thickness and surface orientation
M Kang, SC Song, SH Woo, HK Park, MH Abu-Rahma, L Ge, BM Han, ...
IEEE Transactions on Electron Devices 57 (11), 2785-2793, 2010
An energy-efficient memory-based high-throughput VLSI architecture for convolutional networks
M Kang, SK Gonugondla, MS Keel, NR Shanbhag
2015 IEEE International Conference on Acoustics, Speech and Signal …, 2015
A variation-tolerant in-memory machine learning classifier via on-chip training
SK Gonugondla, M Kang, NR Shanbhag
IEEE Journal of Solid-State Circuits 53 (11), 3163-3173, 2018
PROMISE: An End-to-End Design of a Programmable Mixed-Signal Accelerator for Machine-Learning Algorithms
P Srivastava*, M Kang* (*equal contribution), SK Gonugondla, S Lim, ...
International Symposium on Computer Architecture (ISCA18), 2018
A 481pJ/decision 3.4 M decision/s multifunctional deep in-memory inference processor using standard 6T SRAM array
M Kang, S Gonugondla, A Patil, N Shanbhag
arXiv preprint arXiv:1610.07501, 2016
An in-memory VLSI architecture for convolutional neural networks
M Kang, S Lim, S Gonugondla, NR Shanbhag
IEEE Journal on Emerging and Selected Topics in Circuits and Systems 8 (3 …, 2018
A 19.4 nJ/decision 364K decisions/s in-memory random forest classifier in 6T SRAM array
M Kang, SK Gonugondla, NR Shanbhag
ESSCIRC 2017-43rd IEEE European Solid State Circuits Conference, 263-266, 2017
Energy-efficient and high throughput sparse distributed memory architecture
M Kang, EP Kim, M Keel, NR Shanbhag
2015 IEEE International Symposium on Circuits and Systems (ISCAS), 2505-2508, 2015
In-memory computing architectures for sparse distributed memory
M Kang, NR Shanbhag
IEEE transactions on biomedical circuits and systems 10 (4), 855-863, 2016
A 19.4-nJ/decision, 364-K decisions/s, in-memory random forest multi-class inference accelerator
M Kang, SK Gonugondla, S Lim, NR Shanbhag
IEEE Journal of Solid-State Circuits 53 (7), 2126-2135, 2018
Compute memory
N Shanbhag, MG Kang, MS Keel
US Patent 9,697,877, 2017
Asymmetric independent-gate MOSFET SRAM for high stability
M Kang, HK Park, J Wang, G Yeap, SO Jung
IEEE transactions on Electron Devices 58 (9), 2959-2965, 2011
Generalized water-filling for source-aware energy-efficient SRAMs
Y Kim, M Kang, LR Varshney, NR Shanbhag
IEEE Transactions on Communications 66 (10), 4826-4841, 2018
Stable SRAM bitcell design utilizing independent gate FinFET
M Kang, SO Jung, H Park, SC Song, M Abu-Rahma, BM Han, L Ge, ...
US Patent 9,865,330, 2018
Compute memory
N Shanbhag, M Kang, MS Keel
uS Patent US9697877B2.[Online]. Available: https://patents. google. com …, 2017
Accurate projection of Vccminby modeling “dual slope” in FinFET based SRAM, and impact of long term reliability on end of life Vccmin
H Park, SC Song, SH Woo, MH Abu-Rahma, L Ge, MG Kang, BM Han, ...
2010 IEEE International Reliability Physics Symposium, 1008-1013, 2010
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