4 citations · 19 across the 17 of their papers we have counts for
17 papers
Single-Cell Universal Logic-in-Memory Using 2T-nC FeRAM: An Area and Energy-Efficient Approach for Bulk Bitwise Computation
Rudra Biswas, Jiahui Duan, Shan Deng +7
This work presents a novel approach to configure 2T-nC ferroelectric RAM (FeRAM) for performing single cell logic-in-memory operations, highlighting its advantages in energy-effici…
Towards High-Resolution Alignment and Super-Resolution of Multi-Sensor Satellite Imagery
Philip Wootaek Shin, Vishal Gaur, Rahul Ramachandran +4
High-resolution satellite imagery is essential for geospatial analysis, yet differences in spatial resolution across satellite sensors present challenges for data fusion and downst…
A Full Spectrum of 3D Ferroelectric Memory Architectures Shaped by Polarization Sensing
Jiahui Duan, Asif Khan, Xiao Gong +2
Ferroelectric memories have attracted significant interest due to their non-volatile storage, energy efficiency, and fast operation, making them prime candidates for future memory…
STAMP-2.5D: Structural and Thermal Aware Methodology for Placement in 2.5D Integration
Varun Darshana Parekh, Zachary Wyatt Hazenstab, Srivatsa Rangachar Srinivasa +3
Chiplet-based architectures and advanced packaging has emerged as transformative approaches in semiconductor design. While conventional physical design for 2.5D heterogeneous syste…
Disharmony: Forensics using Reverse Lighting Harmonization
Philip Wootaek Shin, Jack Sampson, Vijaykrishnan Narayanan +2
Content generation and manipulation approaches based on deep learning methods have seen significant advancements, leading to an increased need for techniques to detect whether an i…
KALAHash: Knowledge-Anchored Low-Resource Adaptation for Deep Hashing
Shu Zhao, Tan Yu, Xiaoshuai Hao +2
Deep hashing has been widely used for large-scale approximate nearest neighbor search due to its storage and search efficiency. However, existing deep hashing methods predominantly…
PIFS-Rec: Process-In-Fabric-Switch for Large-Scale Recommendation System Inferences
Pingyi Huo, Anusha Devulapally, Hasan Al Maruf +6
Deep Learning Recommendation Models (DLRMs) have become increasingly popular and prevalent in today's datacenters, consuming most of the AI inference cycles. The performance of DLR…
Synergistic and Efficient Edge-Host Communication for Energy Harvesting Wireless Sensor Networks
Cyan Subhra Mishra, Jack Sampson, Mahmut Taylan Kandmeir +2
There is an increasing demand for intelligent processing on ultra-low-power internet of things (IoT) device. Recent works have shown substantial efficiency boosts by executing infe…
Reimagining Sense Amplifiers: Harnessing Phase Transition Materials for Current and Voltage Sensing
Md Mazharul Islam, Shamiul Alam, Mohammad Adnan Jahangir +5
Energy-efficient sense amplifier (SA) circuits are essential for reliable detection of stored memory states in emerging memory systems. In this work, we present four novel sense am…
Voltage-controlled Cryogenic Boolean Logic Family Based on Ferroelectric SQUID
Shamiul Alam, Md Shafayat Hossain, Kai Ni +2
The recent progress in quantum computing and space exploration led to a surge in interest in cryogenic electronics. Superconducting devices such as Josephson junction, Josephson fi…
CMOS-Compatible Ising Machines built using Bistable Latches Coupled through Ferroelectric Transistor Arrays
Antik Mallick, Zijian Zhao, Mohammad Khairul Bashar +8
Realizing compact and scalable Ising machines that are compatible with CMOS-process technology is crucial to the effectiveness and practicality of using such hardware platforms for…
Seeker: Synergizing Mobile and Energy Harvesting Wearable Sensors for Human Activity Recognition
Cyan Subhra Mishra, Jack Sampson, Mahmut Taylan Kandemir +1
There is an increasing demand for intelligent processing on emerging ultra-low-power internet of things (IoT) devices, and recent works have shown substantial efficiency boosts by…
An Oscillator-based MaxSAT solver
Mohammad Khairul Bashar, Jaykumar Vaidya, Antik Mallick +8
The quest to solve hard combinatorial optimization problems efficiently -- still a longstanding challenge for traditional digital computers -- has inspired the exploration of many…
Exploiting Activation based Gradient Output Sparsity to Accelerate Backpropagation in CNNs
Anup Sarma, Sonali Singh, Huaipan Jiang +5
Machine/deep-learning (ML/DL) based techniques are emerging as a driving force behind many cutting-edge technologies, achieving high accuracy on computer vision workloads such as i…
Transformer-based Machine Learning for Fast SAT Solvers and Logic Synthesis
Feng Shi, Chonghan Lee, Mohammad Khairul Bashar +3
CNF-based SAT and MaxSAT solvers are central to logic synthesis and verification systems. The increasing popularity of these constraint problems in electronic design automation enc…
Hotspot Prevention Through Runtime Reconfiguration in Network-On-Chip
G. M. Link, N. Vijaykrishnan
Many existing thermal management techniques focus on reducing the overall power consumption of the chip, and do not address location-specific temperature problems referred to as ho…
Thermal-Aware Task Allocation and Scheduling for Embedded Systems
W. -L. Hung, Y. Xie, N. Vijaykrishnan +2
Temperature affects not only the reliability but also the performance, power, and cost of the embedded system. This paper proposes a thermal-aware task allocation and scheduling al…