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06/28/2023
ReDy: A Novel ReRAM-centric Dynamic Quantization Approach for Energy-efficient CNN Inference
The primary operation in DNNs is the dot product of quantized input acti...
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06/28/2023
DNA-TEQ: An Adaptive Exponential Quantization of Tensors for DNN Inference
Quantization is commonly used in Deep Neural Networks (DNNs) to reduce t...
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12/23/2021
A Survey of Near-Data Processing Architectures for Neural Networks
Data-intensive workloads and applications, such as machine learning (ML)...
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07/20/2021
CREW: Computation Reuse and Efficient Weight Storage for Hardware-accelerated MLPs and RNNs
Deep Neural Networks (DNNs) have achieved tremendous success for cogniti...
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06/06/2019
