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Perspectives on Visualization and Science: Communication and DiscoveryJune 11, 2019

Nicholas F. Polys, Ph.D.

Advanced Research Computing: arc.vt.edu

Topic Overview

• Visualization and Scientific Discovery

• What?

• Why?

• Big Data Paradigms

• Where?

• How?

• Access

• Who?

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Visualization and Scientific Discovery

What?

Why?

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Human Vision

Highest bandwidth sense

• Fast, parallel

• Pattern recognition

• Pre-attentive

• Extends memory and cognitive capacity

• (Multiplication test)

• People think visually

• Brain = 8 lbs, vision = 3 lbs

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Visual Thinking

• Many of the great scientists were good at visual thinking:

– Leonardo da Vinci– James Clerk Maxwell– Michael Faraday– Albert Einstein

• This was often at the expense of verbal skills

• Tom West : “In the Mind’s Eye”– See also

http://www.krasnow.gmu.edu/twest/maxwell_visual.html Maxwell’s clay model now in

New Cavendish Laboratory, Cambridge

(picture by Tom West)

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Visualization: A Definition

Generally:

“The use of computer-supported, interactive, visual representations of data to amplify cognition “

Card, McKinlay and Schneiderman

• Scientific Visualization

• Information Visualization

• Virtual Environments

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Visualization as a Scientific Instrument

• Making the invisible visible:

• Tele-scope

• Micro-scope

• Digi-scope

• …

• Femto-scope

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Which state has highest income?

Relationship between income and education?

Outliers?

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Per Capita Income

Colle

ge D

egre

e %

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Order these Chips

?

?

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?

?

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Features: Color

The rainbow spectrum is not a

perceptually linear sequence

(not pre-attentive)!

(Keller 1993; Ware, )

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Spatial Contrast Sensitivity

3x accuity in grayscale:

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Edward Tufte

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Les Mis characters (Jeff Heer)

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Belle II VR

For desktop and Steam VR: VT ICAT

Duer, Upthergrove, Piilonen, Polys, Glasson, et al

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http://www1.phys.vt.edu/~piilonen/VR/

SteamVR

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Visualization: Big Data Paradigms

Where?

How?

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Approaches to Exa-Scalability

Numerous, highly-dimensional observations require special, pragmatic attention:

• Algorithmic Elegance:

• Sampling & Aggregation Strategies

• Data Compression (including POD)

• Brute Force:

• Remote Rendering

• Domain Relevance:

• In-Situ methods

• Human-in-the-Loop Machine Learning (Semantic Interaction)

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Scaling to Interaction

• Frame-rates are essential for throughput & Usability

• Using HPC clusters for Rendering:

• Parallel IO

• Fast network

• Fast GPUs

• Load balancing software like Paraview, Visit

• Experiment: VT’s Blue Ridge

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Visualization Where?

• Remote Rendering

• In-Situ methods

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HPC cluster rendering for Interactive frame rates on big data

12.8 million cells, total 11 GB

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HPC cluster rendering for Interactive frame rates on big data

9600 files total 28 GB

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Remote Visualization

Faiz Abidi, Nicholas Polys, Srijith Rajamohan, Lance Arsenault, and AyatMohammed. 2018. Remote high performance visualization of big data for immersive science. In Proceedings of the High Performance Computing Symposium (HPC '18). Society for Computer Simulation International, San Diego, CA, USA, Article 5, 12 pages.

Master's Thesis, Spring 2017 Faiz AbidiRemote High Performance Visualization of Big Data for Immersive Science URI : http://hdl.handle.net/10919/78210

●TurboVNC scaling study on 10 GB line (VTRNet) to●HyperCube w/ Head tacking and wand

Advanced Research Computing: arc.vt.edu6/13/2019

Paraview HyperCube remote rendering from BlueRidge (interactive head & wand tracking)

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Remote VisualizationCluster Rendering

5.5 Billion points (w/ intensity) of Goodwin Hall via FARO laser scan

With P. Tarazaga & T. Tucker

Interactively

explored in immersive

HyperCube

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In Situ Methods

… Can be sampling strategies, but essentially

Visualization is done at same time as the computation or data capture.

(-) Must know what features you are looking for

(+) saves disk space

(+) Cinema approach by LANL can be used for analysis of ensembles

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Cinema Databases

Structured collections for image-based rendering

• More efficient for storage and visualization at petaand exa –scales

• New interactions to explore between 2 and 3 D !

• Cinema:

• Sciencehttps://cinemascience.github.io/

• Viewer https://cinemaviewer.org/

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Visualization Access

Who?

… For all

• WWW + ISO-IEC X3D:

• Desktops

• Mobiles

• VR

• AR

• 3D Printing

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The Web Is the Interface

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3D Everywhere

• Workstations

• High-Resolution projection

• WWW

• Web3D

• Mobile

• WebVR (HMDs)

• Device-specific interaction

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Display Bandwidth

Metric for Total Display Bandwidth

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Industry Standards unify communities

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Open Standards make it work

www.web3d.org• Portability

• Durability

• IP independence

• International recognition and support

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3dprint.nih.gov

• Molecules

• Cells & tissues

• Anatomical models

• Prosthetics

• Labware

• …

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Take Aways

1. Visualization is a key component of interdisciplinary science

2. Remote rendering, in situ methods, and semantic interaction are key approaches to scaling discovery to big data

3. For reproducibility, broad access, and interoperability, invest in Standards leadership

Contact : Nicholas Polys npolys@vt.edu

Advanced Research Computing: arc.vt.edu

Contact!

Nicholas Polys

npolys@vt.edu

Advanced Research Computing: arc.vt.edu

Appendix

More info~!

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Virginia Tech (VT): Ut Prosim

• A land-grant University serving the Public Good

• Science and the Reproducibility of Research is a core mission

• Investments in a broad spectrum of digital content and access:

• Simulation

• Analytics

• Capture (i.e. scanning)

• Design

• Archival and sharing

• International Standards provide: interoperability, accessibility, and durability

- the basis for a long-term strategy

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VT Advanced Research Computing

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VT Dept. of Computer Science

• www.cs.vt.edu