2 citations · 4 across the 8 of their papers we have counts for
3 papers · 1 filter
An Energy-Efficient Near-Data Processing Accelerator for DNNs that Optimizes Data Accesses
Bahareh Khabbazan, Marc Riera, Antonio González
The constant growth of DNNs makes them challenging to implement and run efficiently on traditional compute-centric architectures. Some accelerators have attempted to add more compu…
ReDy: A Novel ReRAM-centric Dynamic Quantization Approach for Energy-efficient CNN Inference
Mohammad Sabri, Marc Riera, Antonio González
The primary operation in DNNs is the dot product of quantized input activations and weights. Prior works have proposed the design of memory-centric architectures based on the Proce…
DNA-TEQ: An Adaptive Exponential Quantization of Tensors for DNN Inference
Bahareh Khabbazan, Marc Riera, Antonio González
Quantization is commonly used in Deep Neural Networks (DNNs) to reduce the storage and computational complexity by decreasing the arithmetical precision of activations and weights,…