2 citations · 3 across the 6 of their papers we have counts for
6 papers
Bayesian Optimization of Crossbar-Based Compute-In-Memory System Design for Efficient DNN Inference
Arnob Saha, Bibhas Manna, Nikhil Kotikalapudi +4
Leveraging the high density and energy efficiency of Compute-In-Memory (CIM) crossbar-based Deep Neural Network (DNN) accelerators requires optimal Design Space Exploration (DSE),…
Trilinear Compute-in-Memory Architecture for Energy-Efficient Transformer Acceleration
Md Zesun Ahmed Mia, Jiahui Duan, Kai Ni +1
Self-attention in Transformers generates dynamic operands that force conventional Compute-in-Memory (CIM) accelerators into costly non-volatile memory (NVM) reprogramming cycles, d…
Energy-Aware Spike Budgeting for Continual Learning in Spiking Neural Networks for Neuromorphic Vision
Anika Tabassum Meem, Muntasir Hossain Nadid, Md Zesun Ahmed Mia
Neuromorphic vision systems based on spiking neural networks (SNNs) offer ultra-low-power perception for event-based and frame-based cameras, yet catastrophic forgetting remains a…
RMAAT: Astrocyte-Inspired Memory Compression and Replay for Efficient Long-Context Transformers
Md Zesun Ahmed Mia, Malyaban Bal, Abhronil Sengupta
The quadratic complexity of self-attention mechanism presents a significant impediment to applying Transformer models to long sequences. This work explores computational principles…
Neuromorphic Cybersecurity with Semi-supervised Lifelong Learning
Md Zesun Ahmed Mia, Malyaban Bal, Sen Lu +4
Inspired by the brain's hierarchical processing and energy efficiency, this paper presents a Spiking Neural Network (SNN) architecture for lifelong Network Intrusion Detection Syst…
Delving Deeper Into Astromorphic Transformers
Md Zesun Ahmed Mia, Malyaban Bal, Abhronil Sengupta
Preliminary attempts at incorporating the critical role of astrocytes - cells that constitute more than 50\% of human brain cells - in brain-inspired neuromorphic computing remain…