Title:	First Considerations in Computing and Using Hypersurface Curvature for Energy Efficiency
Authors:	Hauenstein, Jacob D. Newman, Timothy S.
Advisor:
Citation:	WSCG 2023: full papers proceedings: 1. International Conference in Central Europe on Computer Graphics, Visualization and Computer Vision, p. 186-193.
Issue Date:	2023
Publisher:	Václav Skala - UNION Agency
Document type:	konferenční příspěvek conferenceObject
URI:	http://hdl.handle.net/11025/54424
ISBN:	978-80-86943-32-9
ISSN:	2464–4617 (print) 2464–4625 (CD/DVD)
Keywords:	energetická účinnost;zelená technologie;zakřivení;objemová data;hyperpovrch
Keywords in different language:	power efficiency;green computing;curvature;volumetric data;hypersurface
Abstract in different language:	Energy consumption for computing and using hypersurface curvature in volume dataset analysis and visualization is studied here. Usage in both the base case and when more energy-optimal strategies, particularly computational (especially for linear algebraic steps) strategies, are the primary foci here and are considered for analysis tasks that are precursors to visualization. Compilation-based effects on energy usage are a secondary focus. Efforts here are on Intel x86, which is popular and has power measurement capabilities. Additionally, a first-time visualization of hypersurface curvature distributions in a brain imaging scenario is exhibited. The work aims to advance under standing of computing’s energy footprint and to provide guidance for energy-responsible volume data analysis
Rights:	© Václav Skala - UNION Agency
Appears in Collections:	WSCG 2023: Full Papers Proceedings

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