3 papers
cs.AR2026
MINT: Dynamic-Precision CNN Inference with MSDF Digit-Serial Arithmetic on FPGA
Muhammad Usman, Malik Zohaib Nisar, Florian Aschauer +1
We present MINT, a dynamic-precision CNN inference accelerator based on left-to-right (LR) arithmetic. LR arithmetic computes in most-significant-digit-first manner and exposes use…
cs.LG2025
USEFUSE: Uniform Stride for Enhanced Performance in Fused Layer Architecture of Deep Neural Networks
Muhammad Sohail Ibrahim, Muhammad Usman, Jeong-A Lee
Convolutional Neural Networks (CNNs) are crucial in various applications, but their deployment on resource-constrained edge devices poses challenges. This study presents the Sum-of…
cs.AR2025
DSLR-CNN: Efficient CNN Acceleration using Digit-Serial Left-to-Right Arithmetic
Malik Zohaib Nisar, Muhammad Sohail Ibrahim, Saeid Gorgin +2
Digit-serial arithmetic has emerged as a viable approach for designing hardware accelerators, reducing interconnections, area utilization, and power consumption. However, conventio…