47 citations · 73 across the 8 of their papers we have counts for
14 papers
Large Language Models Inference Engines based on Spiking Neural Networks
Adarsha Balaji, Sandeep Madireddy, Prasanna Balaprakash
Foundational models based on the transformer architecture are currently the state-of-the-art in general language modeling, as well as in scientific areas such as material science a…
Design-Technology Co-Optimization for NVM-based Neuromorphic Processing Elements
Shihao Song, Adarsha Balaji, Anup Das +1
Neuromorphic hardware platforms can significantly lower the energy overhead of a machine learning inference task. We present a design-technology tradeoff analysis to implement such…
Implementing Spiking Neural Networks on Neuromorphic Architectures: A Review
Phu Khanh Huynh, M. Lakshmi Varshika, Ankita Paul +3
Recently, both industry and academia have proposed several different neuromorphic systems to execute machine learning applications that are designed using Spiking Neural Networks (…
DFSynthesizer: Dataflow-based Synthesis of Spiking Neural Networks to Neuromorphic Hardware
Shihao Song, Harry Chong, Adarsha Balaji +3
Spiking Neural Networks (SNN) are an emerging computation model, which uses event-driven activation and bio-inspired learning algorithms. SNN-based machine-learning programs are ty…
Dynamic Reliability Management in Neuromorphic Computing
Shihao Song, Jui Hanamshet, Adarsha Balaji +5
Neuromorphic computing systems uses non-volatile memory (NVM) to implement high-density and low-energy synaptic storage. Elevated voltages and currents needed to operate NVMs cause…
NeuroXplorer 1.0: An Extensible Framework for Architectural Exploration with Spiking Neural Networks
Adarsha Balaji, Shihao Song, Twisha Titirsha +6
Recently, both industry and academia have proposed many different neuromorphic architectures to execute applications that are designed with Spiking Neural Network (SNN). Consequent…