1 citations · 1 across the 2 of their papers we have counts for
3 papers
Towards Efficient LUT-based PIM: A Scalable and Low-Power Approach for Modern Workloads
Bahareh Khabbazan, Marc Riera, Antonio González
Data movement in memory-intensive workloads, such as deep learning, incurs energy costs that are over three orders of magnitude higher than the cost of computation. Since these wor…
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…
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,…