45 citations · 166 across the 41 of their papers we have counts for
9 papers · 1 filter
XbarSim: A Decomposition-Based Memristive Crossbar Simulator
Anzhelika Kolinko, Md Hasibul Amin, Ramtin Zand +1
Given the growing focus on memristive crossbar-based in-memory computing (IMC) architectures as a potential alternative to current energy-hungry machine learning hardware, the avai…
Matmul or No Matmul in the Era of 1-bit LLMs
Jinendra Malekar, Mohammed E. Elbtity, Ramtin Zand
The advent of 1-bit large language models (LLMs) has attracted considerable attention and opened up new research opportunities. However, 1-bit LLMs only improve a fraction of model…
AssemAI: Interpretable Image-Based Anomaly Detection for Manufacturing Pipelines
Renjith Prasad, Chathurangi Shyalika, Ramtin Zand +4
Anomaly detection in manufacturing pipelines remains a critical challenge, intensified by the complexity and variability of industrial environments. This paper introduces AssemAI,…
HiRISE: High-Resolution Image Scaling for Edge ML via In-Sensor Compression and Selective ROI
Brendan Reidy, Sepehr Tabrizchi, Mohamadreza Mohammadi +3
With the rise of tiny IoT devices powered by machine learning (ML), many researchers have directed their focus toward compressing models to fit on tiny edge devices. Recent works h…
Towards Efficient Deployment of Hybrid SNNs on Neuromorphic and Edge AI Hardware
James Seekings, Peyton Chandarana, Mahsa Ardakani +2
This paper explores the synergistic potential of neuromorphic and edge computing to create a versatile machine learning (ML) system tailored for processing data captured by dynamic…
Flex-TPU: A Flexible TPU with Runtime Reconfigurable Dataflow Architecture
Mohammed Elbtity, Peyton Chandarana, Ramtin Zand
Tensor processing units (TPUs) are one of the most well-known machine learning (ML) accelerators utilized at large scale in data centers as well as in tiny ML applications. TPUs of…
Multi-Objective Neural Architecture Search for In-Memory Computing
Md Hasibul Amin, Mohammadreza Mohammadi, Ramtin Zand
In this work, we employ neural architecture search (NAS) to enhance the efficiency of deploying diverse machine learning (ML) tasks on in-memory computing (IMC) architectures. Init…
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…
Realtime Facial Expression Recognition: Neuromorphic Hardware vs. Edge AI Accelerators
Heath Smith, James Seekings, Mohammadreza Mohammadi +1
The paper focuses on real-time facial expression recognition (FER) systems as an important component in various real-world applications such as social robotics. We investigate two…