E-LIB Suche - Ergebnisse für: Shanbhag, Naresh R.

1

Energy-Accuracy Trade-Offs for Resistive In-Memory Computin..:

Roy, Saion K. ; Shanbhag, Naresh R.
IEEE Journal on Exploratory Solid-State Computational Devices and Circuits. 10 (2024) - p. 22-30 , 2024

Link: https://doi.org/10.1109/..

2

Enhancing the Accuracy of 6T SRAM-Based In-Memory Architect..:

Kim, Hyungyo ; Shanbhag, Naresh R.
IEEE Transactions on Signal Processing. 72 (2024) - p. 2799-2811 , 2024

Link: https://doi.org/10.1109/..

3

Enhancing the Accuracy of Resistive In-Memory Architectures..:

, In: ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP),

Ou, Han-Mo ; Shanbhag, Naresh R. - p. 1-5 , 2023

Link: https://doi.org/10.1109/..

4

PRIVE: Efficient RRAM Programming with Chip Verification fo..:

, In: 2023 Design, Automation & Test in Europe Conference & Exhibition (DATE),

He, Wangxin ; Meng, Jian ; Gonugondla, Sujan Kumar... - p. 1-6 , 2023

Link: https://doi.org/10.23919..

5

Compute SNR-boosted 22 nm MRAM-based In-memory Computing Ma..:

, In: ESSCIRC 2023- IEEE 49th European Solid State Circuits Conference (ESSCIRC),

Roy, Saion K. ; Ou, Han-Mo ; Ahmed, Mostafa G.... - p. 25-28 , 2023

Link: https://doi.org/10.1109/..

6

IMPQ: Reduced Complexity Neural Networks Via Granular Preci..:

, In: ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP),

Gonugondla, Sujan Kumar ; Shanbhag, Naresh R. - p. 66-70 , 2022

Link: https://doi.org/10.1109/..

7

Fundamental Limits on Energy-Delay-Accuracy of In-Memory Ar..:

Gonugondla, Sujan K. ; Sakr, Charbel ; Dbouk, Hassan.
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems. 41 (2022) 10 - p. 3188-3201 , 2022

Link: https://doi.org/10.1109/..

8

Fundamental Limits on the Computational Accuracy of Resisti..:

, In: 2022 IEEE International Symposium on Circuits and Systems (ISCAS),

Roy, Saion K. ; Patil, Ameya ; Shanbhag, Naresh R. - p. 384-388 , 2022

Link: https://doi.org/10.1109/..

9

Benchmarking In-Memory Computing Architectures:

Shanbhag, Naresh R. ; Roy, Saion K.
IEEE Open Journal of the Solid-State Circuits Society. 2 (2022) - p. 288-300 , 2022

Link: https://doi.org/10.1109/..

10

Comprehending In-memory Computing Trends via Proper Benchma..:

, In: 2022 IEEE Custom Integrated Circuits Conference (CICC),

Shanbhag, Naresh R. ; Roy, Saion K. - p. 01-07 , 2022

Link: https://doi.org/10.1109/..

11

Signal Processing Methods to Enhance the Energy Efficiency ..:

Sakr, Charbel ; Shanbhag, Naresh R.
IEEE Transactions on Signal Processing. 69 (2021) - p. 6462-6472 , 2021

Link: https://doi.org/10.1109/..

12

Future Prospects:

, In: Deep In-memory Architectures for Machine Learning,

Kang, Mingu ; Gonugondla, Sujan ; Shanbhag, Naresh R. - p. 161-162 , 2020

Link: https://doi.org/10.1007/..

13

DIMA Prototype Integrated Circuits:

, In: Deep In-memory Architectures for Machine Learning,

Kang, Mingu ; Gonugondla, Sujan ; Shanbhag, Naresh R. - p. 49-79 , 2020

Link: https://doi.org/10.1007/..

14

Deep In-memory Architectures for Machine Learning:

Kang, Mingu ; Gonugondla, Sujan ; Shanbhag, Naresh R - 1st ed. 2020 . , 2020

Link: https://doi.org/10.1007/..

15

Correction to: Deep In-memory Architectures for Machine Lea..:

, In: Deep In-memory Architectures for Machine Learning,

Kang, Mingu ; Gonugondla, Sujan ; Shanbhag, Naresh R. - p. C1-C1 , 2020

Link: https://doi.org/10.1007/..