no code implementations • 14 Feb 2022 • Franyell Silfa, Jose-Maria Arnau, Antonio González
In this paper, we observe that the output of a neuron exhibits small changes in consecutive invocations.~We exploit this property to build a neuron-level fuzzy memoization scheme, which dynamically caches each neuron's output and reuses it whenever it is predicted that the current output will be similar to a previously computed result, avoiding in this way the output computations.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +2
no code implementations • 20 Jul 2021 • Marc Riera, Jose-Maria Arnau, Antonio Gonzalez
To this end, each weight is replaced offline by an index in the buffer of unique products.
no code implementations • 7 Nov 2019 • Franyell Silfa, Jose-Maria Arnau, Antonio Gonzàlez
Based on this observation, we implement a novel hardware scheme that tracks the evolution of the elements in the LSTM cell state and dynamically selects the appropriate precision in each time step.
no code implementations • 4 Nov 2019 • Reza Yazdani, Olatunji Ruwase, Minjia Zhang, Yuxiong He, Jose-Maria Arnau, Antonio Gonzalez
To solve these issues, we propose an intelligent tiled-based dispatching mechanism for increasing the adaptiveness of RNN computation, in order to efficiently handle the data dependencies.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +2
no code implementations • 6 Jun 2019 • Marc Riera, Jose-Maria Arnau, Antonio Gonzalez
DNN pruning reduces memory footprint and computational work of DNN-based solutions to improve performance and energy-efficiency.
no code implementations • 20 Nov 2017 • Franyell Silfa, Gem Dot, Jose-Maria Arnau, Antonio Gonzalez
The main goal of E-PUR is to support large recurrent neural networks for low-power mobile devices.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +2