12 citations · 32 across the 9 of their papers we have counts for
9 papers
PIVOT- Input-aware Path Selection for Energy-efficient ViT Inference
Abhishek Moitra, Abhiroop Bhattacharjee, Priyadarshini Panda
The attention module in vision transformers(ViTs) performs intricate spatial correlations, contributing significantly to accuracy and delay. It is thereby important to modulate the…
Are SNNs Truly Energy-efficient? A Hardware Perspective
Abhiroop Bhattacharjee, Ruokai Yin, Abhishek Moitra +1
Spiking Neural Networks (SNNs) have gained attention for their energy-efficient machine learning capabilities, utilizing bio-inspired activation functions and sparse binary spike-d…
RobustEdge: Low Power Adversarial Detection for Cloud-Edge Systems
Abhishek Moitra, Abhiroop Bhattacharjee, Youngeun Kim +1
In practical cloud-edge scenarios, where a resource constrained edge performs data acquisition and a cloud system (having sufficient resources) performs inference tasks with a deep…
HyDe: A Hybrid PCM/FeFET/SRAM Device-search for Optimizing Area and Energy-efficiencies in Analog IMC Platforms
Abhiroop Bhattacharjee, Abhishek Moitra, Priyadarshini Panda
Today, there are a plethora of In-Memory Computing (IMC) devices- SRAMs, PCMs & FeFETs, that emulate convolutions on crossbar-arrays with high throughput. Each IMC device offers it…
Examining the Role and Limits of Batchnorm Optimization to Mitigate Diverse Hardware-noise in In-memory Computing
Abhiroop Bhattacharjee, Abhishek Moitra, Youngeun Kim +2
In-Memory Computing (IMC) platforms such as analog crossbars are gaining focus as they facilitate the acceleration of low-precision Deep Neural Networks (DNNs) with high area- & co…
Input-Aware Dynamic Timestep Spiking Neural Networks for Efficient In-Memory Computing
Yuhang Li, Abhishek Moitra, Tamar Geller +1
Spiking Neural Networks (SNNs) have recently attracted widespread research interest as an efficient alternative to traditional Artificial Neural Networks (ANNs) because of their ca…