1 citations · 1 across the 1 of their papers we have counts for
3 papers
Saving RNN Computations with a Neuron-Level Fuzzy Memoization Scheme
Franyell Silfa, Jose-Maria Arnau, Antonio González
Recurrent Neural Networks (RNNs) are a key technology for applications such as automatic speech recognition or machine translation. Unlike conventional feed-forward DNNs, RNNs reme…
E-BATCH: Energy-Efficient and High-Throughput RNN Batching
Franyell Silfa, Jose Maria Arnau, Antonio Gonzalez
Recurrent Neural Network (RNN) inference exhibits low hardware utilization due to the strict data dependencies across time-steps. Batching multiple requests can increase throughput…
Boosting LSTM Performance Through Dynamic Precision Selection
Franyell Silfa, Jose-Maria Arnau, Antonio Gonzàlez
The use of low numerical precision is a fundamental optimization included in modern accelerators for Deep Neural Networks (DNNs). The number of bits of the numerical representation…