Abhiroop Bhattacharjee

Ruokai Yin

CoRR, August, 2025

ClipFormer: Key-Value Clipping of Transformers on Memristive Crossbars for Write Noise Mitigation.

[BibT_eX]

[DOI]

IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., February, 2025

Low-power Spike-based Wearable Analytics on RRAM Crossbars.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Symposium on Circuits and Systems, 2025

2024

MCAIMem: A Mixed SRAM and eDRAM Cell for Area and Energy-Efficient On-Chip AI Memory.

[BibT_eX]

[DOI]

Duy-Thanh Nguyen

IEEE Trans. Very Large Scale Integr. Syst., November, 2024

RobustEdge: Low Power Adversarial Detection for Cloud-Edge Systems.

[BibT_eX]

[DOI]

IEEE Trans. Emerg. Top. Comput. Intell., April, 2024

When In-memory Computing Meets Spiking Neural Networks - A Perspective on Device-Circuit-System-and-Algorithm Co-design.

[BibT_eX]

[DOI]

Yuhang Li

CoRR, 2024

TReX- Reusing Vision Transformer's Attention for Efficient Xbar-based Computing.

[BibT_eX]

[DOI]

CoRR, 2024

Are SNNs Truly Energy-efficient? - A Hardware Perspective.

[BibT_eX]

[DOI]

Ruokai Yin

Proceedings of the IEEE International Conference on Acoustics, 2024

HaLo-FL: Hardware-Aware Low-Precision Federated Learning.

[BibT_eX]

[DOI]

Proceedings of the Design, Automation & Test in Europe Conference & Exhibition, 2024

PIVOT- Input-aware Path Selection for Energy-efficient ViT Inference.

[BibT_eX]

[DOI]

Proceedings of the 61st ACM/IEEE Design Automation Conference, 2024

2023

HyDe: A brid PCM/FeFET/SRAM vice-Search for Optimizing Area and Energy-Efficiencies in Analog IMC Platforms.

[BibT_eX]

[DOI]

IEEE J. Emerg. Sel. Topics Circuits Syst., December, 2023

SpikeSim: An End-to-End Compute-in-Memory Hardware Evaluation Tool for Benchmarking Spiking Neural Networks.

[BibT_eX]

[DOI]

IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., November, 2023

<i>SwitchX</i>: Gmin-Gmax Switching for Energy-efficient and Robust Implementation of Binarized Neural Networks on ReRAM Xbars.

[BibT_eX]

[DOI]

ACM Trans. Design Autom. Electr. Syst., July, 2023

<i>XploreNAS</i>: Explore Adversarially Robust and Hardware-efficient Neural Architectures for Non-ideal Xbars.

[BibT_eX]

[DOI]

ACM Trans. Embed. Comput. Syst., July, 2023

SATA: Sparsity-Aware Training Accelerator for Spiking Neural Networks.

[BibT_eX]

[DOI]

Ruokai Yin

IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., June, 2023

HyDe: A Hybrid PCM/FeFET/SRAM Device-search for Optimizing Area and Energy-efficiencies in Analog IMC Platforms.

[BibT_eX]

[DOI]

CoRR, 2023

XploreNAS: Explore Adversarially Robust & Hardware-efficient Neural Architectures for Non-ideal Xbars.

[BibT_eX]

[DOI]

CoRR, 2023

Examining the Role and Limits of Batchnorm Optimization to Mitigate Diverse Hardware-noise in In-memory Computing.

[BibT_eX]

[DOI]

Proceedings of the Great Lakes Symposium on VLSI 2023, 2023

DeepCAM: A Fully CAM-based Inference Accelerator with Variable Hash Lengths for Energy-efficient Deep Neural Networks.

[BibT_eX]

[DOI]

Duy-Thanh Nguyen

Proceedings of the Design, Automation & Test in Europe Conference & Exhibition, 2023

XPert: Peripheral Circuit & Neural Architecture Co-search for Area and Energy-efficient Xbar-based Computing.

[BibT_eX]

[DOI]

Proceedings of the 60th ACM/IEEE Design Automation Conference, 2023

2022

NEAT: Nonlinearity Aware Training for Accurate, Energy-Efficient, and Robust Implementation of Neural Networks on 1T-1R Crossbars.

[BibT_eX]

[DOI]

Lakshya Bhatnagar

IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2022

Examining the Robustness of Spiking Neural Networks on Non-ideal Memristive Crossbars.

[BibT_eX]

[DOI]

Proceedings of the ISLPED '22: ACM/IEEE International Symposium on Low Power Electronics and Design, Boston, MA, USA, August 1, 2022

Rate Coding Or Direct Coding: Which One Is Better For Accurate, Robust, And Energy-Efficient Spiking Neural Networks?

[BibT_eX]

[DOI]

Hyoungseob Park

Proceedings of the IEEE International Conference on Acoustics, 2022

Examining and Mitigating the Impact of Crossbar Non-idealities for Accurate Implementation of Sparse Deep Neural Networks.

[BibT_eX]

[DOI]

Lakshya Bhatnagar

Proceedings of the 2022 Design, Automation & Test in Europe Conference & Exhibition, 2022

MIME: adapting a single neural network for multi-task inference with memory-efficient dynamic pruning.

[BibT_eX]

[DOI]

Proceedings of the DAC '22: 59th ACM/IEEE Design Automation Conference, San Francisco, California, USA, July 10, 2022

2021

END-TRUE: Emerging Nanotechnology-Based Double-Throughput True Random Number Generator.

[BibT_eX]

[DOI]

Shubham Rai

Nishant Gupta

Proceedings of the VLSI-SoC: Technology Advancement on SoC Design, 2021

Metastability with Emerging Reconfigurable Transistors: Exploiting Ambipolarity for Throughput.

[BibT_eX]

[DOI]

Proceedings of the 29th IFIP/IEEE International Conference on Very Large Scale Integration, 2021

Activation Density based Mixed-Precision Quantization for Energy Efficient Neural Networks.

[BibT_eX]

[DOI]

Karina Vasquez

Proceedings of the Design, Automation & Test in Europe Conference & Exhibition, 2021

Efficiency-driven Hardware Optimization for Adversarially Robust Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the Design, Automation & Test in Europe Conference & Exhibition, 2021

2020

NEAT: Non-linearity Aware Training for Accurate and Energy-Efficient Implementation of Neural Networks on 1T-1R Memristive Crossbars.

[BibT_eX]

[DOI]

Lakshya Bhatnagar

CoRR, 2020

SwitchX- Gmin-Gmax Switching for Energy-Efficient and Robust Implementation of Binary Neural Networks on Memristive Xbars.

[BibT_eX]

[DOI]

CoRR, 2020

Rethinking Non-idealities in Memristive Crossbars for Adversarial Robustness in Neural Networks.

[BibT_eX]

[DOI]