5 citations · 10 across the 7 of their papers we have counts for
7 papers · 1 filter
On the Mitigation of Read Disturbances in Neuromorphic Inference Hardware
Ankita Paul, Shihao Song, Twisha Titirsha +1
Non-Volatile Memory (NVM) cells are used in neuromorphic hardware to store model parameters, which are programmed as resistance states. NVMs suffer from the read disturb issue, whe…
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…
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…
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…
Thermal-Aware Compilation of Spiking Neural Networks to Neuromorphic Hardware
Twisha Titirsha, Anup Das
Hardware implementation of neuromorphic computing can significantly improve performance and energy efficiency of machine learning tasks implemented with spiking neural networks (SN…
Reliability-Performance Trade-offs in Neuromorphic Computing
Twisha Titirsha, Anup Das
Neuromorphic architectures built with Non-Volatile Memory (NVM) can significantly improve the energy efficiency of machine learning tasks designed with Spiking Neural Networks (SNN…