Peter A. Beerel

ORCID

Publication Activity (10 Years)

Years Active: 1991-2024
Publications (10 Years): 139

Top Venues

CoRR

ASYNC

DATE

IEEE Trans. Comput. Aided Des. Integr. Circuits Syst.

Publications

Robert S. Aviles, Xi Li, Lei Lu, Zhaorui Ni, Peter A. Beerel
An Efficient and Scalable Clocking Assignment Algorithm for Multi-Threaded Multi-Phase Single Flux Quantum Circuits. CoRR (2024)
Sreetama Sarkar, Souvik Kundu, Peter A. Beerel
Linearizing Models for Efficient yet Robust Private Inference. CoRR (2024)
Robert S. Aviles, Peter A. Beerel
A Novel Optimization Algorithm for Buffer and Splitter Minimization in Phase-Skipping Adiabatic Quantum-Flux-Parametron Circuits. CoRR (2024)
Dake Chen, Christine Goins, Maxwell Waugaman, Georgios D. Dimou, Peter A. Beerel
Island-based Random Dynamic Voltage Scaling vs ML-Enhanced Power Side-Channel Attacks. CoRR (2023)
Souvik Kundu, Shunlin Lu, Yuke Zhang, Jacqueline Tiffany Liu, Peter A. Beerel
Learning to Linearize Deep Neural Networks for Secure and Efficient Private Inference. ICLR (2023)
Shashank Nag, Gourav Datta, Souvik Kundu, Nitin Chandrachoodan, Peter A. Beerel
ViTA: A Vision Transformer Inference Accelerator for Edge Applications. CoRR (2023)
Shashank Nag, Gourav Datta, Souvik Kundu, Nitin Chandrachoodan, Peter A. Beerel
ViTA: A Vision Transformer Inference Accelerator for Edge Applications. ISCAS (2023)
Dake Chen, Yuke Zhang, Souvik Kundu, Chenghao Li, Peter A. Beerel
RNA-ViT: Reduced-Dimension Approximate Normalized Attention Vision Transformers for Latency Efficient Private Inference. ICCAD (2023)
Souvik Kundu, Yuke Zhang, Dake Chen, Peter A. Beerel
Making Models Shallow Again: Jointly Learning to Reduce Non-Linearity and Depth for Latency-Efficient Private Inference. CoRR (2023)
Gourav Datta, Haoqin Deng, Robert Aviles, Zeyu Liu, Peter A. Beerel
Bridging the Gap Between Spiking Neural Networks & LSTMs for Latency & Energy Efficiency. ISLPED (2023)
Yuke Zhang, Dake Chen, Souvik Kundu, Haomei Liu, Ruiheng Peng, Peter A. Beerel
C2PI: An Efficient Crypto-Clear Two-Party Neural Network Private Inference. CoRR (2023)
Md. Abdullah-Al Kaiser, Gourav Datta, Zixu Wang, Ajey P. Jacob, Peter A. Beerel, Akhilesh R. Jaiswal
Neuromorphic-P2M: processing-in-pixel-in-memory paradigm for neuromorphic image sensors. Frontiers Neuroinformatics 17 (2023)
Zihan Yin, Gourav Datta, Md. Abdullah-Al Kaiser, Peter A. Beerel, Ajey P. Jacob, Akhilesh Jaiswal
Design Considerations for 3D Heterogeneous Integration Driven Analog Processing-in-Pixel for Extreme-Edge Intelligence. ICRC (2023)
Gourav Datta, Zeyu Liu, Md. Abdullah-Al Kaiser, Souvik Kundu, Joe Mathai, Zihan Yin, Ajey P. Jacob, Akhilesh R. Jaiswal, Peter A. Beerel
In-Sensor & Neuromorphic Computing Are all You Need for Energy Efficient Computer Vision. ICASSP (2023)
Yue Hu, Gourav Datta, Kira Beerel, Peter A. Beerel
Let's Roll: Synthetic Dataset Analysis for Pedestrian Detection Across Different Shutter Types. CoRR (2023)
Yue Hu, Xinan Ye, Yifei Liu, Souvik Kundu, Gourav Datta, Srikar Mutnuri, Namo Asavisanu, Nora Ayanian, Konstantinos Psounis, Peter A. Beerel
FireFly A Synthetic Dataset for Ember Detection in Wildfire. CoRR (2023)
Souvik Kundu, Yuke Zhang, Dake Chen, Peter A. Beerel
Making Models Shallow Again: Jointly Learning to Reduce Non-Linearity and Depth for Latency-Efficient Private Inference. CVPR Workshops (2023)
Souvik Kundu, Rui-Jie Zhu, Akhilesh Jaiswal, Peter A. Beerel
Recent Advances in Scalable Energy-Efficient and Trustworthy Spiking Neural networks: from Algorithms to Technology. CoRR (2023)
Md. Abdullah-Al Kaiser, Gourav Datta, Sreetama Sarkar, Souvik Kundu, Zihan Yin, Manas Garg, Ajey P. Jacob, Peter A. Beerel, Akhilesh R. Jaiswal
Technology-Circuit-Algorithm Tri-Design for Processing-in-Pixel-in-Memory (P2M). CoRR (2023)
Souvik Kundu, Sairam Sundaresan, Sharath Nittur Sridhar, Shunlin Lu, Han Tang, Peter A. Beerel
Sparse Mixture Once-for-all Adversarial Training for Efficient In-Situ Trade-Off Between Accuracy and Robustness of DNNs. CoRR (2023)
Gourav Datta, Zeyu Liu, Anni Li, Peter A. Beerel
Spiking Neural Networks with Dynamic Time Steps for Vision Transformers. CoRR (2023)
Dake Chen, Xuan Zhou, Yinghua Hu, Yuke Zhang, Kaixin Yang, Andrew Rittenbach, Pierluigi Nuzzo, Peter A. Beerel
Unraveling Latch Locking Using Machine Learning, Boolean Analysis, and ILP. CoRR (2023)
Yuke Zhang, Dake Chen, Souvik Kundu, Haomei Liu, Ruiheng Peng, Peter A. Beerel
PI: An Efficient Crypto-Clear Two-Party Neural Network Private Inference. DAC (2023)
Chenghao Li, Dake Chen, Yuke Zhang, Peter A. Beerel
Mitigate Replication and Copying in Diffusion Models with Generalized Caption and Dual Fusion Enhancement. CoRR (2023)
Yinghua Hu, Yuke Zhang, Kaixin Yang, Dake Chen, Peter A. Beerel, Pierluigi Nuzzo
On the Security of Sequential Logic Locking Against Oracle-Guided Attacks. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 42 (11) (2023)
Fang Chen, Gourav Datta, Souvik Kundu, Peter A. Beerel
Self-Attentive Pooling for Efficient Deep Learning. WACV (2023)
Dake Chen, Xuan Zhou, Yinghua Hu, Yuke Zhang, Kaixin Yang, Andrew Rittenbach, Pierluigi Nuzzo, Peter A. Beerel
Unraveling Latch Locking Using Machine Learning, Boolean Analysis, and ILP. ISQED (2023)
Yuke Zhang, Dake Chen, Souvik Kundu, Chenghao Li, Peter A. Beerel
SAL-ViT: Towards Latency Efficient Private Inference on ViT using Selective Attention Search with a Learnable Softmax Approximation. ICCV (2023)
Souvik Kundu, Sairam Sundaresan, Massoud Pedram, Peter A. Beerel
FLOAT: Fast Learnable Once-for-All Adversarial Training for Tunable Trade-off between Accuracy and Robustness. WACV (2023)
Souvik Kundu, Sairam Sundaresan, Sharath Nittur Sridhar, Shunlin Lu, Han Tang, Peter A. Beerel
Sparse Mixture Once-for-all Adversarial Training for Efficient in-situ Trade-off between Accuracy and Robustness of DNNs. ICASSP (2023)
Gourav Datta, Zeyu Liu, Zihan Yin, Linyu Sun, Akhilesh R. Jaiswal, Peter A. Beerel
Enabling ISPless Low-Power Computer Vision. WACV (2023)
Dake Chen, Christine Goins, Maxwell Waugaman, Georgios D. Dimou, Peter A. Beerel
Island-based Random Dynamic Voltage Scaling vs ML-Enhanced Power Side-Channel Attacks. ACM Great Lakes Symposium on VLSI (2023)
Yue Hu, Xinan Ye, Yifei Liu, Souvik Kundu, Gourav Datta, Srikar Mutnuri, Namo Asavisanu, Nora Ayanian, Konstantinos Psounis, Peter A. Beerel
FireFly: A Synthetic Dataset for Ember Detection in Wildfire. ICCV (Workshops) (2023)
Haonan Wang, Connor Imes, Souvik Kundu, Peter A. Beerel, Stephen P. Crago, John Paul Walters
Quantpipe: Applying Adaptive Post-Training Quantization For Distributed Transformer Pipelines In Dynamic Edge Environments. ICASSP (2023)
Gourav Datta, Zeyu Liu, James Diffenderfer, Bhavya Kailkhura, Peter A. Beerel
When Bio-Inspired Computing meets Deep Learning: Low-Latency, Accurate, & Energy-Efficient Spiking Neural Networks from Artificial Neural Networks. CoRR (2023)
Souvik Kundu, Shunlin Lu, Yuke Zhang, Jacqueline Liu, Peter A. Beerel
Learning to Linearize Deep Neural Networks for Secure and Efficient Private Inference. CoRR (2023)
Md. Abdullah-Al Kaiser, Gourav Datta, Sreetama Sarkar, Souvik Kundu, Zihan Yin, Manas Garg, Ajey P. Jacob, Peter A. Beerel, Akhilesh R. Jaiswal
Technology-Circuit-Algorithm Tri-Design for Processing-in-Pixel-in-Memory (P2M). ACM Great Lakes Symposium on VLSI (2023)
Souvik Kundu, Yao Fu, Bill Ye, Peter A. Beerel, Massoud Pedram
Toward Adversary-aware Non-iterative Model Pruning through Dynamic Network Rewiring of DNNs. ACM Trans. Embed. Comput. Syst. 21 (5) (2022)
Haonan Wang, Connor Imes, Souvik Kundu, Peter A. Beerel, Stephen P. Crago, John Paul Walters
QuantPipe: Applying Adaptive Post-Training Quantization for Distributed Transformer Pipelines in Dynamic Edge Environments. CoRR (2022)
Souvik Kundu, Shikai Wang, Qirui Sun, Peter A. Beerel, Massoud Pedram
BMPQ: Bit-Gradient Sensitivity-Driven Mixed-Precision Quantization of DNNs from Scratch. DATE (2022)
Gourav Datta, Souvik Kundu, Zihan Yin, Joe Mathai, Zeyu Liu, Zixu Wang, Mulin Tian, Shunlin Lu, Ravi Teja Lakkireddy, Andrew Schmidt, Wael Abd-Almageed, Ajey Jacob, Akhilesh R. Jaiswal, Peter A. Beerel
M-DeTrack: Processing-in-Pixel-in-Memory for Energy-efficient and Real-Time Multi-Object Detection and Tracking. VLSI-SoC (2022)
Gourav Datta, Peter A. Beerel
Can Deep Neural Networks be Converted to Ultra Low-Latency Spiking Neural Networks? DATE (2022)
Yuke Zhang, Yinghua Hu, Pierluigi Nuzzo, Peter A. Beerel
TriLock: IC Protection with Tunable Corruptibility and Resilience to SAT and Removal Attacks. CoRR (2022)
Peter A. Beerel, Marios Georgiou, Ben Hamlin, Alex J. Malozemoff, Pierluigi Nuzzo
Towards a Formal Treatment of Logic Locking. IACR Trans. Cryptogr. Hardw. Embed. Syst. 2022 (2) (2022)
Gourav Datta, Zeyu Liu, Md. Abdullah-Al Kaiser, Souvik Kundu, Joe Mathai, Zihan Yin, Ajey P. Jacob, Akhilesh R. Jaiswal, Peter A. Beerel
In-Sensor & Neuromorphic Computing are all you need for Energy Efficient Computer Vision. CoRR (2022)
Gourav Datta, Zihan Yin, Ajey Jacob, Akhilesh R. Jaiswal, Peter A. Beerel
Toward Efficient Hyperspectral Image Processing inside Camera Pixels. CoRR (2022)
Peter A. Beerel, Marios Georgiou, Ben Hamlin, Alex J. Malozemoff, Pierluigi Nuzzo
Towards a Formal Treatment of Logic Locking. IACR Cryptol. ePrint Arch. 2022 (2022)
Yang Hu, Connor Imes, Xuanang Zhao, Souvik Kundu, Peter A. Beerel, Stephen P. Crago, John Paul Walters
PipeEdge: Pipeline Parallelism for Large-Scale Model Inference on Heterogeneous Edge Devices. DSD (2022)
Fang Chen, Gourav Datta, Souvik Kundu, Peter A. Beerel
Self-Attentive Pooling for Efficient Deep Learning. CoRR (2022)
Gourav Datta, Zeyu Liu, Peter A. Beerel
Hoyer regularizer is all you need for ultra low-latency spiking neural networks. CoRR (2022)
Huimei Cheng, Xi Li, Yichen Gu, Peter A. Beerel
Converting Flip-Flop to Clock-Gated 3-Phase Latch-Based Designs Using Graph-Based Retiming. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 41 (4) (2022)
Moisés Herrera, Peter A. Beerel
Radiation Hardening by Design Techniques for the Mutual Exclusion Element. ACM Great Lakes Symposium on VLSI (2022)
Gourav Datta, Zihan Yin, Ajey P. Jacob, Akhilesh R. Jaiswal, Peter A. Beerel
Towards Energy-Efficient Hyperspectral Image Processing Inside Camera Pixels. ECCV Workshops (6) (2022)
Yuke Zhang, Yinghua Hu, Pierluigi Nuzzo, Peter A. Beerel
TriLock: IC Protection with Tunable Corruptibility and Resilience to SAT and Removal Attacks. DATE (2022)
Gourav Datta, Haoqin Deng, Robert Aviles, Peter A. Beerel
Towards Energy-Efficient, Low-Latency and Accurate Spiking LSTMs. CoRR (2022)
Xi Li, Min Pan, Tong Liu, Peter A. Beerel
Multi-Phase Clocking for Multi-Threaded Gate-Level-Pipelined Superconductive Logic. ISVLSI (2022)
Gourav Datta, Zeyu Liu, Zihan Yin, Linyu Sun, Akhilesh R. Jaiswal, Peter A. Beerel
Enabling ISP-less Low-Power Computer Vision. CoRR (2022)
Gourav Datta, Souvik Kundu, Zihan Yin, Ravi Teja Lakkireddy, Joe Mathai, Ajey Jacob, Peter A. Beerel, Akhilesh R. Jaiswal
P2M: A Processing-in-Pixel-in-Memory Paradigm for Resource-Constrained TinyML Applications. CoRR (2022)
Souvik Kundu, Sairam Sundaresan, Massoud Pedram, Peter A. Beerel
A Fast and Efficient Conditional Learning for Tunable Trade-Off between Accuracy and Robustness. CoRR (2022)
Souvik Kundu, Gourav Datta, Massoud Pedram, Peter A. Beerel
Towards Low-Latency Energy-Efficient Deep SNNs via Attention-Guided Compression. CoRR (2021)
Gourav Datta, Souvik Kundu, Peter A. Beerel
Training Energy-Efficient Deep Spiking Neural Networks with Single-Spike Hybrid Input Encoding. IJCNN (2021)
Yinghua Hu, Yuke Zhang, Kaixin Yang, Dake Chen, Peter A. Beerel, Pierluigi Nuzzo
Fun-SAT: Functional Corruptibility-Guided SAT-Based Attack on Sequential Logic Encryption. CoRR (2021)
Yinghua Hu, Yuke Zhang, Kaixin Yang, Dake Chen, Peter A. Beerel, Pierluigi Nuzzo
Fun-SAT: Functional Corruptibility-Guided SAT-Based Attack on Sequential Logic Encryption. HOST (2021)
Gourav Datta, Peter A. Beerel
Can Deep Neural Networks be Converted to Ultra Low-Latency Spiking Neural Networks? CoRR (2021)
Dake Chen, Chunxiao Lin, Peter A. Beerel
GF-Flush: A GF(2) Algebraic Attack on Secure Scan Chains. CoRR (2021)
Souvik Kundu, Shikai Wang, Qirui Sun, Peter A. Beerel, Massoud Pedram
BMPQ: Bit-Gradient Sensitivity Driven Mixed-Precision Quantization of DNNs from Scratch. CoRR (2021)
Gourav Datta, Yunkun Lin, Bo Zhang, Peter A. Beerel
Metastability in Superconducting Single Flux Quantum (SFQ) Logic. IEEE Trans. Circuits Syst. I Regul. Pap. 68 (5) (2021)
Souvik Kundu, Mahdi Nazemi, Peter A. Beerel, Massoud Pedram
DNR: A Tunable Robust Pruning Framework Through Dynamic Network Rewiring of DNNs. ASP-DAC (2021)
Xi Li, Soheil Nazar Shahsavani, Xuan Zhou, Massoud Pedram, Peter A. Beerel
A Variation-aware Hold Time Fixing Methodology for Single Flux Quantum Logic Circuits. ACM Trans. Design Autom. Electr. Syst. 26 (6) (2021)
Dake Chen, Chunxiao Lin, Peter A. Beerel
GF-Flush: A GF(2) Algebraic Attack on Dynamically Secured Scan Chains. DFT (2021)
Souvik Kundu, Qirui Sun, Yao Fu, Massoud Pedram, Peter A. Beerel
Analyzing the Confidentiality of Undistillable Teachers in Knowledge Distillation. NeurIPS (2021)
Gourav Datta, Souvik Kundu, Akhilesh R. Jaiswal, Peter A. Beerel
HYPER-SNN: Towards Energy-efficient Quantized Deep Spiking Neural Networks for Hyperspectral Image Classification. CoRR (2021)
Yang Hu, Connor Imes, Xuanang Zhao, Souvik Kundu, Peter A. Beerel, Stephen P. Crago, John Paul Walters
Pipeline Parallelism for Inference on Heterogeneous Edge Computing. CoRR (2021)
Gourav Datta, Souvik Kundu, Peter A. Beerel
Training Energy-Efficient Deep Spiking Neural Networks with Single-Spike Hybrid Input Encoding. CoRR (2021)
Sourya Dey, Sara Babakniya, Saikrishna C. Kanala, Marco Paolieri, Leana Golubchik, Peter A. Beerel, Keith M. Chugg
Deep-n-Cheap: An Automated Efficient and Extensible Search Framework for Cost-Effective Deep Learning. SN Comput. Sci. 2 (4) (2021)
Souvik Kundu, Massoud Pedram, Peter A. Beerel
HIRE-SNN: Harnessing the Inherent Robustness of Energy-Efficient Deep Spiking Neural Networks by Training with Crafted Input Noise. ICCV (2021)
Souvik Kundu, Massoud Pedram, Peter A. Beerel
HIRE-SNN: Harnessing the Inherent Robustness of Energy-Efficient Deep Spiking Neural Networks by Training with Crafted Input Noise. CoRR (2021)
Souvik Kundu, Gourav Datta, Massoud Pedram, Peter A. Beerel
Spike-Thrift: Towards Energy-Efficient Deep Spiking Neural Networks by Limiting Spiking Activity via Attention-Guided Compression. WACV (2021)
Sourya Dey, Saikrishna C. Kanala, Keith M. Chugg, Peter A. Beerel
Deep-n-Cheap: An Automated Search Framework for Low Complexity Deep Learning. CoRR (2020)
Jennifer Paykin, Brian Huffman, Daniel M. Zimmerman, Peter A. Beerel
Formal Verification of Flow Equivalence in Desynchronized Designs. ASYNC (2020)
Jennifer Paykin, Brian Huffman, Daniel M. Zimmerman, Peter A. Beerel
Formal Verification of Flow Equivalence in Desynchronized Designs. CoRR (2020)
Huimei Cheng, Xi Li, Yichen Gu, Peter A. Beerel
Saving Power by Converting Flip-Flop to 3-Phase Latch-Based Designs. DATE (2020)
Souvik Kundu, Gourav Datta, Peter A. Beerel, Massoud Pedram
qBSA: Logic Design of a 32-bit Block-Skewed RSFQ Arithmetic Logic Unit. CoRR (2020)
Souvik Kundu, Mahdi Nazemi, Massoud Pedram, Keith M. Chugg, Peter A. Beerel
Pre-Defined Sparsity for Low-Complexity Convolutional Neural Networks. IEEE Trans. Computers 69 (7) (2020)
Souvik Kundu, Mahdi Nazemi, Massoud Pedram, Keith M. Chugg, Peter A. Beerel
Pre-defined Sparsity for Low-Complexity Convolutional Neural Networks. CoRR (2020)
Gourav Datta, Peter A. Beerel
Modeling and Characterization of Metastability in Single Flux Quantum (SFQ) Synchronizers. ISCAS (2020)
Felipe A. Kuentzer, Moisés Herrera, Oliver Schrape, Peter A. Beerel, Milos Krstic
Radiation Hardened Click Controllers for Soft Error Resilient Asynchronous Architectures. ASYNC (2020)
Sai Aparna Aketi, Smriti Gupta, Huimei Cheng, Joycee Mekie, Peter A. Beerel
SERAD: Soft Error Resilient Asynchronous Design Using a Bundled Data Protocol. IEEE Trans. Circuits Syst. I Fundam. Theory Appl. (5) (2020)
Sourya Dey, Saikrishna C. Kanala, Keith M. Chugg, Peter A. Beerel
Deep-n-Cheap: An Automated Search Framework for Low Complexity Deep Learning. ACML (2020)
Arnab Sanyal, Peter A. Beerel, Keith M. Chugg
Neural Network Training with Approximate Logarithmic Computations. ICASSP (2020)
Ramy N. Tadros, Peter A. Beerel
A Theoretical Foundation for Timing Synchronous Systems Using Asynchronous Structures. ACM Trans. Design Autom. Electr. Syst. 25 (2) (2020)
Sai Aparna Aketi, Smriti Gupta, Huimei Cheng, Joycee Mekie, Peter A. Beerel
SERAD: Soft Error Resilient Asynchronous Design using a Bundled Data Protocol. CoRR (2020)
Souvik Kundu, Mahdi Nazemi, Peter A. Beerel, Massoud Pedram
A Tunable Robust Pruning Framework Through Dynamic Network Rewiring of DNNs. CoRR (2020)
Arash Fayyazi, Souvik Kundu, Shahin Nazarian, Peter A. Beerel, Massoud Pedram
CSrram: Area-Efficient Low-Power Ex-Situ Training Framework for Memristive Neuromorphic Circuits Based on Clustered Sparsity. ISVLSI (2019)
Huimei Cheng, Yichen Gu, Peter A. Beerel
Automatic Conversion from Flip-flop to 3-phase Latch-based Designs. CoRR (2019)
Gourav Datta, Haolin Cong, Souvik Kundu, Peter A. Beerel
Metastability-Resilient Synchronization FIFO for SFQ Logic. CoRR (2019)
Huimei Cheng, Hsiao-Lun Wang, Minghe Zhang, Dylan Hand, Peter A. Beerel
Automatic Retiming of Two-Phase Latch-Based Resilient Circuits. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 38 (7) (2019)
Sourya Dey, Kuan-Wen Huang, Peter A. Beerel, Keith M. Chugg
Pre-Defined Sparse Neural Networks With Hardware Acceleration. IEEE J. Emerg. Sel. Topics Circuits Syst. 9 (2) (2019)
Vivek V. Menon, Gaurav Kolhe, Andrew G. Schmidt, Joshua S. Monson, Matthew French, Yinghua Hu, Peter A. Beerel, Pierluigi Nuzzo
System-Level Framework for Logic Obfuscation with Quantified Metrics for Evaluation. SecDev (2019)
Arnab Sanyal, Peter A. Beerel, Keith M. Chugg
Neural Network Training with Approximate Logarithmic Computations. CoRR (2019)

Peter A. Beerel.css-eqlu8i{font-size:small;padding-left:4px;}

Publication Activity (10 Years)

Top Topics

Top Venues

Peter A. Beerel