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Energy-efficient Hardware Design for Spiking Neural Networks (Extended Abstract).

, , and . ACSSC, page 543-544. IEEE, (2023)

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Workload-Balanced Pruning for Sparse Spiking Neural Networks., , , , , , and . CoRR, (2023)Rate Coding Or Direct Coding: Which One Is Better For Accurate, Robust, And Energy-Efficient Spiking Neural Networks?, , , , , and . ICASSP, page 71-75. IEEE, (2022)Energy-efficient Hardware Design for Spiking Neural Networks (Extended Abstract)., , and . ACSSC, page 543-544. IEEE, (2023)PIVOT- Input-aware Path Selection for Energy-efficient ViT Inference., , and . CoRR, (2024)Noise Sensitivity-Based Energy Efficient and Robust Adversary Detection in Neural Networks., , and . IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 41 (5): 1423-1435 (2022)HyDe: A Hybrid PCM/FeFET/SRAM Device-search for Optimizing Area and Energy-efficiencies in Analog IMC Platforms., , and . CoRR, (2023)ClipFormer: Key-Value Clipping of Transformers on Memristive Crossbars for Write Noise Mitigation., , and . CoRR, (2024)Are SNNs Truly Energy-efficient? - A Hardware Perspective., , , and . CoRR, (2023)DetectX - Adversarial Input Detection using Current Signatures in Memristive XBar Arrays., and . CoRR, (2021)SpikeSim: An end-to-end Compute-in-Memory Hardware Evaluation Tool for Benchmarking Spiking Neural Networks., , , , , and . CoRR, (2022)