FINN-L: Library Extensions and Design Trade-off Analysis for Variable Precision LSTM Networks on FPGAs

11 July 2018

Papers citing "FINN-L: Library Extensions and Design Trade-off Analysis for Variable Precision LSTM Networks on FPGAs"

7 / 7 papers shown

Title
Ultra-low latency recurrent neural network inference on FPGAs for physics applications with hls4ml Elham E Khoda D. Rankin R. Teixeira de Lima Philip C. Harris Scott Hauck ... Chaitanya Paikara R. Rao S. Summers C. Vernieri Aaron Wang AI4CE 20 16 0 01 Jul 2022
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
Accelerating Recurrent Neural Networks for Gravitational Wave Experiments Zhiqiang Que Erwei Wang Umar Marikar Eric A. Moreno J. Ngadiuba ... Vladimir Loncar S. Summers M. Pierini P. Cheung Wayne Luk 11 25 0 26 Jun 2021
Benchmarking Quantized Neural Networks on FPGAs with FINN Quentin Ducasse Pascal Cotret Loïc Lagadec Rob Stewart MQ 21 13 0 02 Feb 2021
ELSA: A Throughput-Optimized Design of an LSTM Accelerator for Energy-Constrained Devices E. Azari S. Vrudhula 12 5 0 19 Oct 2019
Recurrent Neural Networks: An Embedded Computing Perspective Nesma M. Rezk M. Purnaprajna Tomas Nordstrom Z. Ul-Abdin 37 81 0 23 Jul 2019
The implementation of a Deep Recurrent Neural Network Language Model on a Xilinx FPGA Yufeng Hao S. Quigley 35 16 0 26 Oct 2017