Travis Johnston

Highlights

Coefficient of variation (CoV) and total fuel injected results for the best spiking neural networks for each generation of evolution for all ten runs for the engine simulator.  The best network is defined as the network with the lowest fuel injected that is also below the CoV threshold of 3 percent (averaged over ten test runs).

Neuromorphic computing offers one path forward for AI at the edge.  However, accessing and effectively utilizing a neuromorphic hardware platform is non-trivial.  In this work, researchers…

Visual Analytics System Overview: The system consists of three different views: a lineage view (1), a fitness-parameter view (2), and a network architecture view (3). CDA ORNL

Deep learning is actively used in a wide range of fields for scientific discovery. To effectively apply deep learning to a particular problem, it is important to select an appropriate network…

Resilience and Robustness of Spiking Neural Networks for Neuromorphic Systems - CDA ORNL

Though robustness and resilience are commonly quoted as features of neuromorphic computing systems, the expected performance of neuromorphic systems in the face of hardware failures is not clear.…

Multi-Objective Optimization for Size and Resilience of Spiking Neural Networks

Neuromorphic architectures are designed and developed with the goal of having small, low power chips that can perform control and machine learning tasks. However, the power consumption of the…

Evolving Energy Efficient Convolutional Neural Networks

In this work, we discuss an approach for that utilizes high-performance computing (HPC) to evolve the hyperparameters and topology of convolutional neural networks in order to investigate the ability…