59 citations · 90 across the 35 of their papers we have counts for
9 papers · 1 filter
DRAM-Locker: A General-Purpose DRAM Protection Mechanism against Adversarial DNN Weight Attacks
Ranyang Zhou, Sabbir Ahmed, Arman Roohi +2
In this work, we propose DRAM-Locker as a robust general-purpose defense mechanism that can protect DRAM against various adversarial Deep Neural Network (DNN) weight attacks affect…
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…
Threshold Breaker: Can Counter-Based RowHammer Prevention Mechanisms Truly Safeguard DRAM?
Ranyang Zhou, Jacqueline Liu, Sabbir Ahmed +3
This paper challenges the existing victim-focused counter-based RowHammer detection mechanisms by experimentally demonstrating a novel multi-sided fault injection attack technique…
DIAC: Design Exploration of Intermittent-Aware Computing Realizing Batteryless Systems
Sepehr Tabrizchi, Shaahin Angizi, Arman Roohi
Battery-powered IoT devices face challenges like cost, maintenance, and environmental sustainability, prompting the emergence of batteryless energy-harvesting systems that harness…
DNN-Defender: A Victim-Focused In-DRAM Defense Mechanism for Taming Adversarial Weight Attack on DNNs
Ranyang Zhou, Sabbir Ahmed, Adnan Siraj Rakin +1
With deep learning deployed in many security-sensitive areas, machine learning security is becoming progressively important. Recent studies demonstrate attackers can exploit system…
Semi-decentralized Inference in Heterogeneous Graph Neural Networks for Traffic Demand Forecasting: An Edge-Computing Approach
Mahmoud Nazzal, Abdallah Khreishah, Joyoung Lee +3
Prediction of taxi service demand and supply is essential for improving customer's experience and provider's profit. Recently, graph neural networks (GNNs) have been shown promisin…
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…
NeSe: Near-Sensor Event-Driven Scheme for Low Power Energy Harvesting Sensors
Sepehr Tabrizchi, Mehrdad Morsali, Shaahin Angizi +1
Digital technologies have made it possible to deploy visual sensor nodes capable of detecting motion events in the coverage area cost-effectively. However, background subtraction,…