7 citations · 24 across the 16 of their papers we have counts for
17 papers
CHOSEN: Compilation to Hardware Optimization Stack for Efficient Vision Transformer Inference
Mohammad Erfan Sadeghi, Arash Fayyazi, Suhas Somashekar +2
Vision Transformers (ViTs) represent a groundbreaking shift in machine learning approaches to computer vision. Unlike traditional approaches, ViTs employ the self-attention mechani…
PEANO-ViT: Power-Efficient Approximations of Non-Linearities in Vision Transformers
Mohammad Erfan Sadeghi, Arash Fayyazi, Seyedarmin Azizi +1
The deployment of Vision Transformers (ViTs) on hardware platforms, specially Field-Programmable Gate Arrays (FPGAs), presents many challenges, which are mainly due to the substant…
Scalable Superconductor Neuron with Ternary Synaptic Connections for Ultra-Fast SNN Hardware
Mustafa Altay Karamuftuoglu, Beyza Zeynep Ucpinar, Arash Fayyazi +3
A novel high-fan-in differential superconductor neuron structure designed for ultra-high-performance Spiking Neural Network (SNN) accelerators is presented. Utilizing a high-fan-in…
Sensitivity-Aware Mixed-Precision Quantization and Width Optimization of Deep Neural Networks Through Cluster-Based Tree-Structured Parzen Estimation
Seyedarmin Azizi, Mahdi Nazemi, Arash Fayyazi +1
As the complexity and computational demands of deep learning models rise, the need for effective optimization methods for neural network designs becomes paramount. This work introd…
NeuroBlend: Towards Low-Power yet Accurate Neural Network-Based Inference Engine Blending Binary and Fixed-Point Convolutions
Arash Fayyazi, Mahdi Nazemi, Arya Fayyazi +1
This paper introduces NeuroBlend, a novel neural network architecture featuring a unique building block known as the Blend module. This module incorporates binary and fixed-point c…
CrAFT: Compression-Aware Fine-Tuning for Efficient Visual Task Adaptation
Jung Hwan Heo, Seyedarmin Azizi, Arash Fayyazi +1
Transfer learning has become a popular task adaptation method in the era of foundation models. However, many foundation models require large storage and computing resources, which…