Toward exascale computing through neuromorphic approaches.

Thumbnail image of item number 1 in: 'Toward exascale computing through neuromorphic approaches.'.
Thumbnail image of item number 2 in: 'Toward exascale computing through neuromorphic approaches.'.
Thumbnail image of item number 3 in: 'Toward exascale computing through neuromorphic approaches.'.
Thumbnail image of item number 4 in: 'Toward exascale computing through neuromorphic approaches.'.
Showing 1-4 of 18 pages in this report.

PDF Version Also Available for Download.

Description

While individual neurons function at relatively low firing rates, naturally-occurring nervous systems not only surpass manmade systems in computing power, but accomplish this feat using relatively little energy. It is asserted that the next major breakthrough in computing power will be achieved through application of neuromorphic approaches that mimic the mechanisms by which neural systems integrate and store massive quantities of data for real-time decision making. The proposed LDRD provides a conceptual foundation for SNL to make unique advances toward exascale computing. First, a team consisting of experts from the HPC, MESA, cognitive and biological sciences and nanotechnology domains will ... continued below

Physical Description

18 p.

Creation Information

James, Conrad D. September 1, 2010.

Context

This report is part of the collection entitled: Office of Scientific & Technical Information Technical Reports and was provided by UNT Libraries Government Documents Department to Digital Library, a digital repository hosted by the UNT Libraries. More information about this report can be viewed below.

Who

People and organizations associated with either the creation of this report or its content.

Author

Sponsor

Publisher

Provided By

UNT Libraries Government Documents Department

Serving as both a federal and a state depository library, the UNT Libraries Government Documents Department maintains millions of items in a variety of formats. The department is a member of the FDLP Content Partnerships Program and an Affiliated Archive of the National Archives.

About | Browse this Partner

Contact Us

Corrections Questions

What

Descriptive information to help identify this report. Follow the links below to find similar items on the Digital Library.

Description

While individual neurons function at relatively low firing rates, naturally-occurring nervous systems not only surpass manmade systems in computing power, but accomplish this feat using relatively little energy. It is asserted that the next major breakthrough in computing power will be achieved through application of neuromorphic approaches that mimic the mechanisms by which neural systems integrate and store massive quantities of data for real-time decision making. The proposed LDRD provides a conceptual foundation for SNL to make unique advances toward exascale computing. First, a team consisting of experts from the HPC, MESA, cognitive and biological sciences and nanotechnology domains will be coordinated to conduct an exercise with the outcome being a concept for applying neuromorphic computing to achieve exascale computing. It is anticipated that this concept will involve innovative extension and integration of SNL capabilities in MicroFab, material sciences, high-performance computing, and modeling and simulation of neural processes/systems.

Physical Description

18 p.

Language

Item Type

Identifier

Unique identifying numbers for this report in the Digital Library or other systems.

  • Report No.: SAND2010-6312
  • Grant Number: AC04-94AL85000
  • DOI: 10.2172/1007316 | External Link
  • Office of Scientific & Technical Information Report Number: 1007316
  • Archival Resource Key: ark:/67531/metadc831633

Collections

This report is part of the following collection of related materials.

Office of Scientific & Technical Information Technical Reports

Reports, articles and other documents harvested from the Office of Scientific and Technical Information.

Office of Scientific and Technical Information (OSTI) is the Department of Energy (DOE) office that collects, preserves, and disseminates DOE-sponsored research and development (R&D) results that are the outcomes of R&D projects or other funded activities at DOE labs and facilities nationwide and grantees at universities and other institutions.

About | Browse this Collection

What responsibilities do I have when using this report?

Digital Files

When

Dates and time periods associated with this report.

Creation Date

  • September 1, 2010

Added to The UNT Digital Library

  • May 19, 2016, 3:16 p.m.

Description Last Updated

  • Dec. 9, 2016, midnight

Usage Statistics

When was this report last used?

Yesterday: 0
Past 30 days: 1
Total Uses: 6
More Statistics

Interact With This Report

Here are some suggestions for what to do next.

Start Reading

Thumbnail image of item number 1 in: 'Toward exascale computing through neuromorphic approaches.'.
Thumbnail image of item number 2 in: 'Toward exascale computing through neuromorphic approaches.'.
Thumbnail image of item number 3 in: 'Toward exascale computing through neuromorphic approaches.'.
Thumbnail image of item number 4 in: 'Toward exascale computing through neuromorphic approaches.'.

PDF Version Also Available for Download.

Citations, Rights, Re-Use

International Image Interoperability Framework

IIF Logo

We support the IIIF Presentation API

James, Conrad D. Toward exascale computing through neuromorphic approaches., report, September 1, 2010; United States. (digital.library.unt.edu/ark:/67531/metadc831633/: accessed July 18, 2018), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.