89 citations · 214 across the 26 of their papers we have counts for
7 papers · 1 filter
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…
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…
Enabling Resource-Aware Mapping of Spiking Neural Networks via Spatial Decomposition
Adarsha Balaji, Shihao Song, Anup Das +5
With growing model complexity, mapping Spiking Neural Network (SNN)-based applications to tile-based neuromorphic hardware is becoming increasingly challenging. This is because the…
PyCARL: A PyNN Interface for Hardware-Software Co-Simulation of Spiking Neural Network
Adarsha Balaji, Prathyusha Adiraju, Hirak J. Kashyap +4
We present PyCARL, a PyNN-based common Python programming interface for hardware-software co-simulation of spiking neural network (SNN). Through PyCARL, we make the following two k…
Neural and Synaptic Array Transceiver: A Brain-Inspired Computing Framework for Embedded Learning
Georgios Detorakis, Sadique Sheik, Charles Augustine +6
Embedded, continual learning for autonomous and adaptive behavior is a key application of neuromorphic hardware. However, neuromorphic implementations of embedded learning at large…