Mark Plagge
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View article: Leveraging dendritic complexity for neuromorphic computing
Leveraging dendritic complexity for neuromorphic computing Open
Beyond-von Neumann computing approaches are necessary to sustain the growth of microelectronics and the increasing appetite for artificial intelligence/machine learning algorithms. Neuromorphic computing is an emerging paradigm that takes …
View article: Performance and Energy Simulation of Spiking Neuromorphic Architectures for Fast Exploration
Performance and Energy Simulation of Spiking Neuromorphic Architectures for Fast Exploration Open
Recent work in neuromorphic computing has proposed a range of new architectures for Spiking Neural Network (SNN)-based systems. However, neuromorphic design lacks a framework to facilitate exploration of different SNN-based architectures a…
View article: SEEK: Scoping neuromorphic architecture impact enabling advanced sensing capabilities
SEEK: Scoping neuromorphic architecture impact enabling advanced sensing capabilities Open
Many sensor modalities used for proliferation detection are expanding hyperspectrally, hyperspatially, and hypertemporally. While these assets are often tasked with high-consequence image processing tasks, the significant computational cos…
View article: ATHENA: Analytical Tool for Heterogeneous Neuromorphic Architectures
ATHENA: Analytical Tool for Heterogeneous Neuromorphic Architectures Open
The ASC program seeks to use machine learning to improve efficiencies in its stockpile stewardship mission. Moreover, there is a growing market for technologies dedicated to accelerating AI workloads. Many of these emerging architectures p…
View article: Modeling Analog Tile-Based Accelerators Using SST
Modeling Analog Tile-Based Accelerators Using SST Open
Analog computing has been widely proposed to improve the energy efficiency of multiple important workloads including neural network operations, and other linear algebra kernels. To properly evaluate analog computing and explore more comple…
View article: Exploring characteristics of neural network architecture computation for enabling SAR ATR
Exploring characteristics of neural network architecture computation for enabling SAR ATR Open
Neural network approaches have periodically been explored in the pursuit of high performing SAR ATR solutions. With deep neural networks (DNNs) now offering many state-of-the-art solutions to computer vision tasks, neural networks are once…
View article: Comparing Neural Accelerators & Neuromorphic Architectures The False Idol of Operations
Comparing Neural Accelerators & Neuromorphic Architectures The False Idol of Operations Open
Accompanying the advanced computing capabilities neural networks are enabling across a suite of application domains, there is a resurgence in interest in understanding what architectures can efficiently enable these advanced computational …
View article: Neural Inspired Computation Remote Sensing Platform.
Neural Inspired Computation Remote Sensing Platform. Open
Remote sensing (RS) data collection capabilities are rapidly evolving hyper-spectrally (sensing more spectral bands), hyper-temporally (faster sampling rates) and hyper-spatially (increasing number of smaller pixels). Accordingly, sensor t…