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Published byDina Peters Modified over 8 years ago
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Operated by Los Alamos National Security, LLC for the U.S. Department of Energy's NNSA UNCLASSIFIED Optimizing the Energy Usage and Cognitive Value of Extreme Scale Data Analysis Approaches 05 January 2015 (LA-UR-15-20105)
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Operated by Los Alamos National Security, LLC for the U.S. Department of Energy's NNSA UNCLASSIFIED Scientific discovery at the exascale is a unique challenge – Extreme data sizes – Constraints: minimizing data movement, energy usage and storage usage Our project unifies researchers in extreme data analysis, supercomputing energy usage, and scalable algorithms with researchers in perception and human cognition Goal: To significantly improve the way analysis algorithms are developed, measured and used at the petascale and in the future at exascale – Perceptual optimization of visualization algorithms and cognitive optimization of interactive methods in visualization tools Project Vision Slide 2
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Operated by Los Alamos National Security, LLC for the U.S. Department of Energy's NNSA UNCLASSIFIED Project Team Slide 3
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Operated by Los Alamos National Security, LLC for the U.S. Department of Energy's NNSA UNCLASSIFIED Power and Energy – Initial measurements of proxy apps Scalable Algorithms – Development of proxy workflows Cognition and Perception – Initial perception experiment – Iterative testing/user studies (Amazon Mech.Turk) Paper accepted to CHI 2015: Samsel, Abrams, Petersen, Wendelberger, Geld, Ahrens. “Colormaps That Improve Perception of High-Resolution Ocean Data.” Initial Work Slide 4
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