89 citations · 314 across the 33 of their papers we have counts for
10 papers · 1 filter
Design of Many-Core Big Little μBrain for Energy-Efficient Embedded Neuromorphic Computing
M. Lakshmi Varshika, Adarsha Balaji, Federico Corradi +3
As spiking-based deep learning inference applications are increasing in embedded systems, these systems tend to integrate neuromorphic accelerators such as Brain to improve ener…
Design Technology Co-Optimization for Neuromorphic Computing
Ankita Paul, Shihao Song, Anup Das
We present a design-technology tradeoff analysis in implementing machine-learning inference on the processing cores of a Non-Volatile Memory (NVM)-based many-core neuromorphic hard…
A Design Flow for Mapping Spiking Neural Networks to Many-Core Neuromorphic Hardware
Shihao Song, M. Lakshmi Varshika, Anup Das +1
The design of many-core neuromorphic hardware is getting more and more complex as these systems are expected to execute large machine learning models. To deal with the design compl…
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…
Improving Inference Lifetime of Neuromorphic Systems via Intelligent Synapse Mapping
Shihao Song, Twisha Titirsha, Anup Das
Non-Volatile Memories (NVMs) such as Resistive RAM (RRAM) are used in neuromorphic systems to implement high-density and low-power analog synaptic weights. Unfortunately, an RRAM c…
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…
Special Session: Reliability Analysis for ML/AI Hardware
Shamik Kundu, Kanad Basu, Mehdi Sadi +4
Artificial intelligence (AI) and Machine Learning (ML) are becoming pervasive in today's applications, such as autonomous vehicles, healthcare, aerospace, cybersecurity, and many c…
On the Role of System Software in Energy Management of Neuromorphic Computing
Twisha Titirsha, Shihao Song, Adarsha Balaji +1
Neuromorphic computing systems such as DYNAPs and Loihi have recently been introduced to the computing community to improve performance and energy efficiency of machine learning pr…
Endurance-Aware Mapping of Spiking Neural Networks to Neuromorphic Hardware
Twisha Titirsha, Shihao Song, Anup Das +4
Neuromorphic computing systems are embracing memristors to implement high density and low power synaptic storage as crossbar arrays in hardware. These systems are energy efficient…