1 citations · 1 across the 8 of their papers we have counts for
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Opto-ViT: Architecting a Near-Sensor Region of Interest-Aware Vision Transformer Accelerator with Silicon Photonics
Mehrdad Morsali, Chengwei Zhou, Deniz Najafi +7
Vision Transformers (ViTs) have emerged as a powerful architecture for computer vision tasks due to their ability to model long-range dependencies and global contextual relationshi…
Neuro-Photonix: Enabling Near-Sensor Neuro-Symbolic AI Computing on Silicon Photonics Substrate
Deniz Najafi, Hamza Errahmouni Barkam, Mehrdad Morsali +6
Neuro-symbolic Artificial Intelligence (AI) models, blending neural networks with symbolic AI, have facilitated transparent reasoning and context understanding without the need for…
SA-DS: A Dataset for Large Language Model-Driven AI Accelerator Design Generation
Deepak Vungarala, Mahmoud Nazzal, Mehrdad Morsali +4
In the ever-evolving landscape of Deep Neural Networks (DNN) hardware acceleration, unlocking the true potential of systolic array accelerators has long been hindered by the daunti…
Lightator: An Optical Near-Sensor Accelerator with Compressive Acquisition Enabling Versatile Image Processing
Mehrdad Morsali, Brendan Reidy, Deniz Najafi +6
This paper proposes a high-performance and energy-efficient optical near-sensor accelerator for vision applications, called Lightator. Harnessing the promising efficiency offered b…
Enabling Normally-off In-Situ Computing with a Magneto-Electric FET-based SRAM Design
Deniz Najafi, Mehrdad Morsali, Ranyang Zhou +4
As an emerging post-CMOS Field Effect Transistor, Magneto-Electric FETs (MEFETs) offer compelling design characteristics for logic and memory applications, such as high-speed switc…
OISA: Architecting an Optical In-Sensor Accelerator for Efficient Visual Computing
Mehrdad Morsali, Sepehr Tabrizchi, Deniz Najafi +4
Targeting vision applications at the edge, in this work, we systematically explore and propose a high-performance and energy-efficient Optical In-Sensor Accelerator architecture ca…
IMA-GNN: In-Memory Acceleration of Centralized and Decentralized Graph Neural Networks at the Edge
Mehrdad Morsali, Mahmoud Nazzal, Abdallah Khreishah +1
In this paper, we propose IMA-GNN as an In-Memory Accelerator for centralized and decentralized Graph Neural Network inference, explore its potential in both settings and provide a…
A Near-Sensor Processing Accelerator for Approximate Local Binary Pattern Networks
Shaahin Angizi, Mehrdad Morsali, Sepehr Tabrizchi +1
In this work, a high-speed and energy-efficient comparator-based Near-Sensor Local Binary Pattern accelerator architecture (NS-LBP) is proposed to execute a novel local binary patt…