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2023

Spiking Neural Networks with Dynamic Time Steps for Vision Transformers

Gourav Datta, Zeyu Liu, Anni Li, Peter A Beerel

arXiv preprint arXiv:2311.16456, 2023

RNA-ViT: reduced-dimension approximate normalized attention vision transformers for latency efficient private inference

Dake Chen, Yuke Zhang, Souvik Kundu, Chenghao Li, Peter A Beerel

2023 IEEE/ACM International Conference on Computer Aided Design (ICCAD), 1-9, 2023

Let's Roll: Synthetic Dataset Analysis for Pedestrian Detection Across Different Shutter Types

Yue Hu, Gourav Datta, Kira Beerel, Peter Beerel

arXiv preprint arXiv:2309.08136, 2023

Results from the coldflux superconductor integrated circuit design tool project

Coenrad J Fourie, Kyle Jackman, Johannes Delport, Lieze Schindler, Tessa Hall, Pascal Febvre, Lucas Iwanikow, Olivia Chen, Christopher L Ayala, Nobuyuki Yoshikawa, Mark Law, Thomas A Weingartner, Yanzhi Wang, Peter Beerel, Sandeep Gupta, Haipeng Zha, Sasan Razmkhah, Mustafa Altay Karamuftuoglu, Arash Fayyazi, Mingye Li, Murali Annavaram, Shahin Nazarian, Massoud Pedram

IEEE Transactions on Applied Superconductivity 33 (8), 1-26, 2023

Bridging the Gap Between Spiking Neural Networks & LSTMs for Latency & Energy Efficiency

Gourav Datta, Haoqin Deng, Robert Aviles, Zeyu Liu, Peter A Beerel

2023 IEEE/ACM International Symposium on Low Power Electronics and Design …, 2023

Open Access Edited by

Bert Offrein, Michael Wynn Hopkins, Leslie Samuel Smith, Md Abdullah-Al Kaiser, MAA Kaiser, G Datta, Z Wang, AP Jacob, PA Beerel, AR Jaiswal

Physical neuromorphic computing and its industrial applications, 148, 2023

C2PI: An Efficient Crypto-Clear Two-Party Neural Network Private Inference

Yuke Zhang, Dake Chen, Souvik Kundu, Haomei Liu, Ruiheng Peng, Peter A Beerel

2023 60th ACM/IEEE Design Automation Conference (DAC), 1-6, 2023

Island-based random dynamic voltage scaling vs ML-enhanced power side-channel attacks

Dake Chen, Christine Goins, Maxwell Waugaman, Georgios D Dimou, Peter A Beerel

Proceedings of the Great Lakes Symposium on VLSI 2023, 333-338, 2023

Technology-circuit-algorithm tri-design for processing-in-pixel-in-memory (p2m)

Md Abdullah-Al Kaiser, Gourav Datta, Sreetama Sarkar, Souvik Kundu, Zihan Yin, Manas Garg, Ajey P Jacob, Peter A Beerel, Akhilesh R Jaiswal

Proceedings of the Great Lakes Symposium on VLSI 2023, 613-618, 2023

Sparse mixture once-for-all adversarial training for efficient in-situ trade-off between accuracy and robustness of DNNs

Souvik Kundu, Sairam Sundaresan, Sharath Nittur Sridhar, Shunlin Lu, Han Tang, Peter A Beerel

ICASSP 2023-2023 IEEE International Conference on Acoustics, Speech and …, 2023

In-sensor & neuromorphic computing are all you need for energy efficient computer vision

Gourav Datta, Zeyu Liu, Md Abdullah-Al Kaiser, Souvik Kundu, Joe Mathai, Zihan Yin, Ajey P Jacob, Akhilesh R Jaiswal, Peter A Beerel

ICASSP 2023-2023 IEEE International Conference on Acoustics, Speech and …, 2023

Quantpipe: Applying adaptive post-training quantization for distributed transformer pipelines in dynamic edge environments

Haonan Wang, Connor Imes, Souvik Kundu, Peter A Beerel, Stephen P Crago, John Paul Walters

ICASSP 2023-2023 IEEE International Conference on Acoustics, Speech and …, 2023

Sal-vit: Towards latency efficient private inference on vit using selective attention search with a learnable softmax approximation

Yuke Zhang, Dake Chen, Souvik Kundu, Chenghao Li, Peter A Beerel

Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2023

Information Sciences Institute

Publications

2023

Spiking Neural Networks with Dynamic Time Steps for Vision Transformers

RNA-ViT: reduced-dimension approximate normalized attention vision transformers for latency efficient private inference

Let's Roll: Synthetic Dataset Analysis for Pedestrian Detection Across Different Shutter Types

Results from the coldflux superconductor integrated circuit design tool project

Bridging the Gap Between Spiking Neural Networks & LSTMs for Latency & Energy Efficiency

Open Access Edited by

C2PI: An Efficient Crypto-Clear Two-Party Neural Network Private Inference

Island-based random dynamic voltage scaling vs ML-enhanced power side-channel attacks

Technology-circuit-algorithm tri-design for processing-in-pixel-in-memory (p2m)

Sparse mixture once-for-all adversarial training for efficient in-situ trade-off between accuracy and robustness of DNNs

In-sensor & neuromorphic computing are all you need for energy efficient computer vision

Quantpipe: Applying adaptive post-training quantization for distributed transformer pipelines in dynamic edge environments

ViTA: A vision transformer inference accelerator for edge applications

Neuromorphic-P2M: processing-in-pixel-in-memory paradigm for neuromorphic image sensors

On the security of sequential logic locking against oracle-guided attacks

Learning to linearize deep neural networks for secure and efficient private inference

Sal-vit: Towards latency efficient private inference on vit using selective attention search with a learnable softmax approximation

Firefly: A synthetic dataset for ember detection in wildfire

Making models shallow again: Jointly learning to reduce non-linearity and depth for latency-efficient private inference

Enabling ISPless low-power computer vision