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09/06/2023
Are SNNs Truly Energy-efficient? - A Hardware Perspective
Spiking Neural Networks (SNNs) have gained attention for their energy-ef...
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03/30/2023
XPert: Peripheral Circuit Neural Architecture Co-search for Area and Energy-efficient Xbar-based Computing
The hardware-efficiency and accuracy of Deep Neural Networks (DNNs) impl...
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02/15/2023
XploreNAS: Explore Adversarially Robust Hardware-efficient Neural Architectures for Non-ideal Xbars
Compute In-Memory platforms such as memristive crossbars are gaining foc...
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02/09/2023
DeepCAM: A Fully CAM-based Inference Accelerator with Variable Hash Lengths for Energy-efficient Deep Neural Networks
With ever increasing depth and width in deep neural networks to achieve ...
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10/24/2022
SpikeSim: An end-to-end Compute-in-Memory Hardware Evaluation Tool for Benchmarking Spiking Neural Networks
SNNs are an active research domain towards energy efficient machine inte...
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06/20/2022
Examining the Robustness of Spiking Neural Networks on Non-ideal Memristive Crossbars
Spiking Neural Networks (SNNs) have recently emerged as the low-power al...
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04/11/2022
SATA: Sparsity-Aware Training Accelerator for Spiking Neural Networks
Spiking Neural Networks (SNNs) have gained huge attention as a potential...
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04/11/2022
MIME: Adapting a Single Neural Network for Multi-task Inference with Memory-efficient Dynamic Pruning
Recent years have seen a paradigm shift towards multi-task learning. Thi...
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01/31/2022
Rate Coding or Direct Coding: Which One is Better for Accurate, Robust, and Energy-efficient Spiking Neural Networks?
Recent Spiking Neural Networks (SNNs) works focus on an image classifica...
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01/13/2022
Examining and Mitigating the Impact of Crossbar Non-idealities for Accurate Implementation of Sparse Deep Neural Networks
Recently several structured pruning techniques have been introduced for ...
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05/09/2021
Efficiency-driven Hardware Optimization for Adversarially Robust Neural Networks
With a growing need to enable intelligence in embedded devices in the In...
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01/12/2021
Activation Density based Mixed-Precision Quantization for Energy Efficient Neural Networks
As neural networks gain widespread adoption in embedded devices, there i...
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08/25/2020
