Approximate FPGA-based LSTMs under Computation Time Constraints

7 January 2018

Papers citing "Approximate FPGA-based LSTMs under Computation Time Constraints"

5 / 5 papers shown

Title
MOHAQ: Multi-Objective Hardware-Aware Quantization of Recurrent Neural Networks Nesma M. Rezk Tomas Nordstrom D. Stathis Z. Ul-Abdin E. Aksoy A. Hemani MQ 25 1 0 02 Aug 2021
Multi-Precision Policy Enforced Training (MuPPET): A precision-switching strategy for quantised fixed-point training of CNNs A. Rajagopal D. A. Vink Stylianos I. Venieris C. Bouganis MQ 16 14 0 16 Jun 2020
Recurrent Neural Networks: An Embedded Computing Perspective Nesma M. Rezk M. Purnaprajna Tomas Nordstrom Z. Ul-Abdin 43 81 0 23 Jul 2019
Approximate LSTMs for Time-Constrained Inference: Enabling Fast Reaction in Self-Driving Cars Alexandros Kouris Stylianos I. Venieris Michail Rizakis C. Bouganis AI4TS 19 12 0 02 May 2019
Toolflows for Mapping Convolutional Neural Networks on FPGAs: A Survey and Future Directions Stylianos I. Venieris Alexandros Kouris C. Bouganis 19 184 0 15 Mar 2018