An Approach of Feed-Forward Neural Network Throughput-Optimized Implementation in FPGA
Artificial Neural Networks (ANNs) have become an accepted approach for a wide range of challenges. Meanwhile, the advancement of chip manufacturing processes is approaching saturation which calls for new computing solutions. This work presents a novel approach of an FPGA-based accelerator developmen...
Main Authors: | Rihards Novickis, Daniels Jānis Justs, Kaspars Ozols, Modris Greitāns |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2020-12-01
|
Series: | Electronics |
Subjects: | |
Online Access: | https://www.mdpi.com/2079-9292/9/12/2193 |
Similar Items
-
High-Level Synthesis Design for Stencil Computations on FPGA with High Bandwidth Memory
by: Changdao Du, et al.
Published: (2020-08-01) -
Implementing and Comparing Image Convolution Methods on an FPGA at the Register-Transfer Level
by: Hernandez, Anna C
Published: (2019) -
Optimized implementation of an improved KNN classification algorithm using Intel FPGA platform: Covid-19 case study
by: Almomany, A., et al.
Published: (2022) -
FPGA Acceleration of 3D FDTD for Multi- Antennas Microwave Imaging Using HLS
by: Mohammad Amir Mansoori, et al.
Published: (2021-01-01) -
High-Level Annotation of Routing Congestion for Xilinx Vivado HLS Designs
by: Osama Bin Tariq, et al.
Published: (2021-01-01)