Multiplication-Free Lookup-Based CNN Accelerator using Residual Vector Quantization and Its FPGA Implementation

H Fuketa, T Katashita, Y Hori, M Hioki - IEEE Access, 2024 - ieeexplore.ieee.org
In this paper, a table lookup-based computing technique is proposed to perform
convolutional neural network (CNN) inference without multiplication, and its FPGA …

LUT-DLA: Lookup Table as Efficient Extreme Low-Bit Deep Learning Accelerator

G Li, S Ye, C Chen, Y Wang, F Yang, T Cao… - arxiv preprint arxiv …, 2025 - arxiv.org
The emergence of neural network capabilities invariably leads to a significant surge in
computational demands due to expanding model sizes and increased computational …

Fast, Scalable, Energy-Efficient Non-element-wise Matrix Multiplication on FPGA

X Zhu, H Zhang, JK Lee, J Zhu, C Pal, S Saha… - arxiv preprint arxiv …, 2024 - arxiv.org
Modern Neural Network (NN) architectures heavily rely on vast numbers of multiply-
accumulate arithmetic operations, constituting the predominant computational cost …