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A resurgence in neuromorphic architectures enabling remote sensing computation

Proceedings - 2019 IEEE Space Computing Conference, SCC 2019

Vineyard, Craig M.; Severa, William M.; Kagie, Matthew J.; Scholand, Andrew J.; Hays, Park H.

Technological advances have enabled exponential growth in both sensor data collection, as well as computational processing. However, as a limiting factor, the transmission bandwidth in between a space-based sensor and a ground station processing center has not seen the same growth. A resolution to this bandwidth limitation is to move the processing to the sensor, but doing so faces size, weight, and power operational constraints. Different physical constraints on processor manufacturing are spurring a resurgence in neuromorphic approaches amenable to the space-based operational environment. Here we describe historical trends in computer architecture and the implications for neuromorphic computing, as well as give an overview of how remote sensing applications may be impacted by this emerging direction for computing.

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TYPE Conference Poster YEAR 2019
DOIOSTIScopus

A vision for managing extreme-scale data hoards

Proceedings - International Conference on Distributed Computing Systems

Logan, Jeremy; Mehta, Kshitij; Heber, Gerd; Klasky, Scott; Kurc, Tahsin; Podhorszki, Norbert; Widener, Patrick W.; Wolf, Matthew

Scientific data collections grow ever larger, both in terms of the size of individual data items and of the number and complexity of items. To use and manage them, it is important to directly address issues of robust and actionable provenance. We identify three key drivers as our focus: managing the size and complexity of metadata, lack of a priori information to match usage intents between publishers and consumers of data, and support for campaigns over collections of data driven by multi-disciplinary, collaborating teams. We introduce the Hoarde abstraction as an attempt to formalize a way of looking at collections of data to make them more tractable for later use. Hoarde leverages middleware and systems infrastructures for scientific and technical data management. Through the lens of a select group of challenging data usage scenarios, we discuss some of the aspects of implementation, usage, and forward portability of this new view on data management.

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TYPE Conference Poster YEAR 2019
DOIOSTIScopus
Results 2101–2150 of 9,998
Results 2101–2150 of 9,998