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ORCIDAbhiroop Bhattacharjee
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2020 – today
- 2024
[j8]Abhishek Moitra
, Abhiroop Bhattacharjee, Youngeun Kim, Priyadarshini Panda:
RobustEdge: Low Power Adversarial Detection for Cloud-Edge Systems. IEEE Trans. Emerg. Top. Comput. Intell. 8(2): 2101-2111 (2024)- [j7]Duy-Thanh Nguyen, Abhiroop Bhattacharjee, Abhishek Moitra, Priyadarshini Panda:
MCAIMem: A Mixed SRAM and eDRAM Cell for Area and Energy-Efficient On-Chip AI Memory. IEEE Trans. Very Large Scale Integr. Syst. 32(11): 2023-2036 (2024) - [c14]Abhishek Moitra, Abhiroop Bhattacharjee, Priyadarshini Panda:
PIVOT- Input-aware Path Selection for Energy-efficient ViT Inference. DAC 2024: 147:1-147:6 - [c13]Yeshwanth Venkatesha, Abhiroop Bhattacharjee, Abhishek Moitra, Priyadarshini Panda:
HaLo-FL: Hardware-Aware Low-Precision Federated Learning. DATE 2024: 1-6 - [c12]Abhiroop Bhattacharjee, Ruokai Yin, Abhishek Moitra, Priyadarshini Panda:
Are SNNs Truly Energy-efficient? - A Hardware Perspective. ICASSP 2024: 13311-13315 - [i23]Abhiroop Bhattacharjee, Abhishek Moitra, Priyadarshini Panda:
ClipFormer: Key-Value Clipping of Transformers on Memristive Crossbars for Write Noise Mitigation. CoRR abs/2402.02586 (2024) - [i22]Abhishek Moitra, Abhiroop Bhattacharjee, Priyadarshini Panda:
PIVOT- Input-aware Path Selection for Energy-efficient ViT Inference. CoRR abs/2404.15185 (2024) - [i21]Abhishek Moitra, Abhiroop Bhattacharjee, Youngeun Kim, Priyadarshini Panda:
TReX- Reusing Vision Transformer's Attention for Efficient Xbar-based Computing. CoRR abs/2408.12742 (2024) - [i20]Abhishek Moitra, Abhiroop Bhattacharjee, Yuhang Li, Youngeun Kim, Priyadarshini Panda:
When In-memory Computing Meets Spiking Neural Networks - A Perspective on Device-Circuit-System-and-Algorithm Co-design. CoRR abs/2408.12767 (2024) - 2023
- [j6]Abhiroop Bhattacharjee, Abhishek Moitra, Priyadarshini Panda:
HyDe: A brid PCM/FeFET/SRAM vice-Search for Optimizing Area and Energy-Efficiencies in Analog IMC Platforms. IEEE J. Emerg. Sel. Topics Circuits Syst. 13(4): 1073-1082 (2023) - [j5]Ruokai Yin, Abhishek Moitra, Abhiroop Bhattacharjee, Youngeun Kim, Priyadarshini Panda:
SATA: Sparsity-Aware Training Accelerator for Spiking Neural Networks. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 42(6): 1926-1938 (2023) - [j4]Abhishek Moitra, Abhiroop Bhattacharjee, Runcong Kuang, Gokul Krishnan, Yu Cao, Priyadarshini Panda:
SpikeSim: An End-to-End Compute-in-Memory Hardware Evaluation Tool for Benchmarking Spiking Neural Networks. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 42(11): 3815-3828 (2023) - [j3]Abhiroop Bhattacharjee, Abhishek Moitra, Priyadarshini Panda:
XploreNAS: Explore Adversarially Robust and Hardware-efficient Neural Architectures for Non-ideal Xbars. ACM Trans. Embed. Comput. Syst. 22(4): 62:1-62:17 (2023) - [j2]Abhiroop Bhattacharjee, Priyadarshini Panda:
SwitchX: Gmin-Gmax Switching for Energy-efficient and Robust Implementation of Binarized Neural Networks on ReRAM Xbars. ACM Trans. Design Autom. Electr. Syst. 28(4): 60:1-60:21 (2023) - [c11]Abhishek Moitra, Abhiroop Bhattacharjee, Youngeun Kim, Priyadarshini Panda:
XPert: Peripheral Circuit & Neural Architecture Co-search for Area and Energy-efficient Xbar-based Computing. DAC 2023: 1-6 - [c10]Duy-Thanh Nguyen, Abhiroop Bhattacharjee, Abhishek Moitra, Priyadarshini Panda:
DeepCAM: A Fully CAM-based Inference Accelerator with Variable Hash Lengths for Energy-efficient Deep Neural Networks. DATE 2023: 1-6 - [c9]Abhiroop Bhattacharjee, Abhishek Moitra, Youngeun Kim, Yeshwanth Venkatesha, Priyadarshini Panda:
Examining the Role and Limits of Batchnorm Optimization to Mitigate Diverse Hardware-noise in In-memory Computing. ACM Great Lakes Symposium on VLSI 2023: 619-624 - [i19]Duy-Thanh Nguyen, Abhiroop Bhattacharjee, Abhishek Moitra, Priyadarshini Panda:
DeepCAM: A Fully CAM-based Inference Accelerator with Variable Hash Lengths for Energy-efficient Deep Neural Networks. CoRR abs/2302.04712 (2023) - [i18]Abhiroop Bhattacharjee, Abhishek Moitra, Priyadarshini Panda:
XploreNAS: Explore Adversarially Robust & Hardware-efficient Neural Architectures for Non-ideal Xbars. CoRR abs/2302.07769 (2023) - [i17]Abhishek Moitra, Abhiroop Bhattacharjee, Youngeun Kim, Priyadarshini Panda:
XPert: Peripheral Circuit & Neural Architecture Co-search for Area and Energy-efficient Xbar-based Computing. CoRR abs/2303.17646 (2023) - [i16]Abhiroop Bhattacharjee, Abhishek Moitra, Youngeun Kim, Yeshwanth Venkatesha, Priyadarshini Panda:
Examining the Role and Limits of Batchnorm Optimization to Mitigate Diverse Hardware-noise in In-memory Computing. CoRR abs/2305.18416 (2023) - [i15]Abhiroop Bhattacharjee, Abhishek Moitra, Priyadarshini Panda:
HyDe: A Hybrid PCM/FeFET/SRAM Device-search for Optimizing Area and Energy-efficiencies in Analog IMC Platforms. CoRR abs/2308.00664 (2023) - [i14]Abhiroop Bhattacharjee, Ruokai Yin, Abhishek Moitra, Priyadarshini Panda:
Are SNNs Truly Energy-efficient? - A Hardware Perspective. CoRR abs/2309.03388 (2023) - [i13]Abhishek Moitra, Abhiroop Bhattacharjee, Youngeun Kim, Priyadarshini Panda:
RobustEdge: Low Power Adversarial Detection for Cloud-Edge Systems. CoRR abs/2310.06845 (2023) - [i12]Duy-Thanh Nguyen, Abhiroop Bhattacharjee, Abhishek Moitra, Priyadarshini Panda:
MCAIMem: a Mixed SRAM and eDRAM Cell for Area and Energy-efficient on-chip AI Memory. CoRR abs/2312.03559 (2023) - 2022
- [j1]Abhiroop Bhattacharjee, Lakshya Bhatnagar, Youngeun Kim, Priyadarshini Panda:
NEAT: Nonlinearity Aware Training for Accurate, Energy-Efficient, and Robust Implementation of Neural Networks on 1T-1R Crossbars. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 41(8): 2625-2637 (2022) - [c8]Abhiroop Bhattacharjee, Yeshwanth Venkatesha, Abhishek Moitra, Priyadarshini Panda:
MIME: adapting a single neural network for multi-task inference with memory-efficient dynamic pruning. DAC 2022: 499-504 - [c7]Abhiroop Bhattacharjee, Lakshya Bhatnagar, Priyadarshini Panda:
Examining and Mitigating the Impact of Crossbar Non-idealities for Accurate Implementation of Sparse Deep Neural Networks. DATE 2022: 1119-1122 - [c6]Youngeun Kim, Hyoungseob Park, Abhishek Moitra, Abhiroop Bhattacharjee, Yeshwanth Venkatesha, Priyadarshini Panda:
Rate Coding Or Direct Coding: Which One Is Better For Accurate, Robust, And Energy-Efficient Spiking Neural Networks? ICASSP 2022: 71-75 - [c5]Abhiroop Bhattacharjee, Youngeun Kim, Abhishek Moitra, Priyadarshini Panda:
Examining the Robustness of Spiking Neural Networks on Non-ideal Memristive Crossbars. ISLPED 2022: 1:1-1:6 - [i11]Abhiroop Bhattacharjee, Lakshya Bhatnagar, Priyadarshini Panda:
Examining and Mitigating the Impact of Crossbar Non-idealities for Accurate Implementation of Sparse Deep Neural Networks. CoRR abs/2201.05229 (2022) - [i10]Youngeun Kim, Hyoungseob Park, Abhishek Moitra, Abhiroop Bhattacharjee, Yeshwanth Venkatesha, Priyadarshini Panda:
Rate Coding or Direct Coding: Which One is Better for Accurate, Robust, and Energy-efficient Spiking Neural Networks? CoRR abs/2202.03133 (2022) - [i9]Abhiroop Bhattacharjee, Yeshwanth Venkatesha, Abhishek Moitra, Priyadarshini Panda:
MIME: Adapting a Single Neural Network for Multi-task Inference with Memory-efficient Dynamic Pruning. CoRR abs/2204.05274 (2022) - [i8]Ruokai Yin, Abhishek Moitra, Abhiroop Bhattacharjee, Youngeun Kim, Priyadarshini Panda:
SATA: Sparsity-Aware Training Accelerator for Spiking Neural Networks. CoRR abs/2204.05422 (2022) - [i7]Abhiroop Bhattacharjee, Youngeun Kim, Abhishek Moitra, Priyadarshini Panda:
Examining the Robustness of Spiking Neural Networks on Non-ideal Memristive Crossbars. CoRR abs/2206.09599 (2022) - [i6]Abhishek Moitra, Abhiroop Bhattacharjee, Runcong Kuang, Gokul Krishnan, Yu Cao, Priyadarshini Panda:
SpikeSim: An end-to-end Compute-in-Memory Hardware Evaluation Tool for Benchmarking Spiking Neural Networks. CoRR abs/2210.12899 (2022) - 2021
- [c4]Abhiroop Bhattacharjee, Abhishek Moitra, Priyadarshini Panda:
Efficiency-driven Hardware Optimization for Adversarially Robust Neural Networks. DATE 2021: 884-889 - [c3]Karina Vasquez, Yeshwanth Venkatesha, Abhiroop Bhattacharjee, Abhishek Moitra, Priyadarshini Panda:
Activation Density based Mixed-Precision Quantization for Energy Efficient Neural Networks. DATE 2021: 1360-1365 - [c2]Abhiroop Bhattacharjee, Shubham Rai, Ansh Rupani, Michael Raitza, Akash Kumar:
Metastability with Emerging Reconfigurable Transistors: Exploiting Ambipolarity for Throughput. VLSI-SoC 2021: 1-6 - [c1]Shubham Rai, Nishant Gupta, Abhiroop Bhattacharjee, Ansh Rupani, Michael Raitza, Jens Trommer, Thomas Mikolajick, Akash Kumar:
END-TRUE: Emerging Nanotechnology-Based Double-Throughput True Random Number Generator. VLSI-SoC (Selected Papers) 2021: 175-203 - [i5]Karina Vasquez, Yeshwanth Venkatesha, Abhiroop Bhattacharjee, Abhishek Moitra, Priyadarshini Panda:
Activation Density based Mixed-Precision Quantization for Energy Efficient Neural Networks. CoRR abs/2101.04354 (2021) - [i4]Abhiroop Bhattacharjee, Abhishek Moitra, Priyadarshini Panda:
Efficiency-driven Hardware Optimization for Adversarially Robust Neural Networks. CoRR abs/2105.04003 (2021) - 2020
- [i3]Abhiroop Bhattacharjee, Priyadarshini Panda:
Rethinking Non-idealities in Memristive Crossbars for Adversarial Robustness in Neural Networks. CoRR abs/2008.11298 (2020) - [i2]Abhiroop Bhattacharjee, Priyadarshini Panda:
SwitchX- Gmin-Gmax Switching for Energy-Efficient and Robust Implementation of Binary Neural Networks on Memristive Xbars. CoRR abs/2011.14498 (2020) - [i1]Abhiroop Bhattacharjee, Lakshya Bhatnagar, Youngeun Kim, Priyadarshini Panda:
NEAT: Non-linearity Aware Training for Accurate and Energy-Efficient Implementation of Neural Networks on 1T-1R Memristive Crossbars. CoRR abs/2012.00261 (2020)
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last updated on 2024-11-13 23:53 CET by the dblp team
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