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Kelly Gaither, Ph.D.
Director of Visualization
CONFERENCIA
Visualizing Yesterday, Today and
Tomorrow: CyberInfrastructure for
Next Generation Science
Kelly Gaither, Ph.D.
Director of Visualization
Senior Research Scientist
Texas Advanced Computing Center
The University of Texas at Austin
Texas Advanced Computing Center (TACC)
Powering Discoveries that Change the World
• Mission: Enable discoveries that advance
science and society through the application of
advanced computing technologies
• Almost 12 years in the making, TACC has
grown from a handful of employees to over 120
full time staff with ~25 students
TACC Visualization Group
• Train the next generation of
scientists to visually analyze
datasets of all sizes.
• Provide resources/services to
local and national user
community.
• Research and develop
tools/techniques for the next
generation of problems facing
the user community.
TACC Visualization Group
• 11 Full Time Staff,
• 2 Undergraduate Students, 3 Graduate Student
• Areas of Expertise: Scientific and Information
Visualization, Large Scale GPU Clusters, Large
Scale Tiled Displays, User Interface Technologies
TACC Visualization Group
• Scalable Visualization Technologies
– Remote and collaborative visualization
– Scalable architectures
– Large data visualization
• Visualization Interfaces and Applications
– Scalable display architectures
– Interaction mechanisms for large scale tiled displays
– Emerging technologies including wearable
computing
What is Visualization?
• “To Envision information is to work at the
intersection of image, word, number, art.”
Edward R. Tufte, Envisioning Information
• “Visualization is any technique for creating from
data images, diagrams, or animations to
communicate a message.”
(http://en.wikipedia.org/wiki/Visualization_computer_graphics)
Computer Graphics versus Visualization
Computer Graphics versus Visualization
Where Does Technology Fit In?
• We have always used technology to create
pictures or visualizations of what we see in our
minds eye.
• What changes over time is the technology we
use.
Visualization Over the Ages
15000 – 10000 BC
1137 AD
1510
Statistical
Graphics
1750 - 1800
1812
1987
The Birth of
Scientific
Visualization
The Birth of Visualization as a Field of Science
• The emphasis on visualization as a field of
science started in 1987 with a special issue of
Computer Graphics on Visualization in
Scientific Computing.
• “Visualization is a method of computing. It transforms the
symbolic into the geometric, enabling researchers to observe
their simulations and computations. Visualization offers a
method for seeing the unseen. It enriches the process of
scientific discovery and fosters profound and unexpected
insights. In many fields it is revolutionizing the way scientists
do science.” Visualization in Scientific Computing, ACM SIGGRAPH 1987
What Was the Catalyst?
• It’s no coincidence that the first US National
Science Foundation funded supercomputing
centers began in 1985.
• This began the tightly coupled relationship
between high performance computing
(HPC), data and visualization.
What are Today’s Transformational
Science Problems?
• What is Transformational Science?
– In 2007, the US driven Augustine report*
provided the recommendation to sustain and
strengthen the nation’s traditional commitment
to long-term basic research that has the
potential to be transformational to maintain the
flow of ideas that fuel the economy, provide
security, and enhance the quality of life.
* Rising Above the Gathering Storm: Energizing and Employing America for a
Brighter Economic Future, National Academy Press, 2007.
Hurricane Prediction
• Forecasters predict the weather using advanced computing technologies.
Image: Greg P. Johnson, Romy Schneider, TACC
Vehicle Design
• Vehicle design
and subsequent
crash testing are
simulated on a
supercomputer
Image courtesy Mississippi
State University
Simulation and Design
Center
Emergency Planning and Response
• Models generated with advanced computing help plan emergency
response to flooding.
Images Courtesy Greg P. Johnson, TACC and Gordon Wells, Center for Space Research
Nano-particle Drug Delivery Visualization
Ben Urick, Jo Wozniak, Karla Vega, TACC; Erik Zumalt, FIC; Shaolie Hossain, Tom
Hughes, ICES.
What Role is Visualization Playing
in Understanding this Science?
Why Are Pictures So
Powerful?
How Critical is Visualization
to Science?
What Role Does the Human Brain
Play in Successful Visualizations?
• “Visualization is so effective and useful because it utilizes one
of the channels to our brain that have the highest bandwidths:
our eyes. But even this channel can be used more or less
efficiently.” [Kosara, 2002]
What Role Does the Human Brain
Play in Successful Visualizations?
• Our vision encompasses:
– seeing color
– detecting motion
– identifying shapes
– gauging distance, speed and size
– seeing objects in three dimensions
– filling in blind spots
– automatically correcting distorted information
– erasing extraneous information that cloud our view.
• Visual cortex makes up 30% of cerebral cortex (77% by volume
of human brain) Trends in Neurosciences, 18:471-474, 1995
• Touch makes up 8% of cerebral cortex
• Hearing makes up 3% of cerebral cortex
Discover Magazine, June 1993: “The Vision Thing: Mainly in the Brain”
Using Visualizations for Knowledge
Discovery
• As data scales, it becomes increasingly
apparent that visualization or visual analysis
becomes key to knowledge discovery
• Managing this bottleneck requires us to
have an understanding of:
– Remote and collaborative visualization (data
manipulation)
– High resolution displays (data synthesis)
Longhorn (Remote and Collaborative
Visualization)
• 256 Dell Dual Socket, Quad Core Intel Nehalem
Nodes
– 240 with 48 GB shared memory/node (6 GB/core)
– 16 with 144 GB shared memory/node (18 GB/core)
– 73 GB Local Disk
– 2 Nvidia GPUs/Node (FX 5800 – 4GB RAM)
• ~14.5 TB aggregate memory
• QDR InfiniBand Interconnect
• Direct Connection to Ranger’s Lustre Parallel File
System
• 10G Connection to 210 TB Local Lustre Parallel File
System
• Jobs launched through SGE
256 Nodes, 2048 Cores, 512 GPUs, 14.5 TB Memory
Kelly Gaither (PI), Valerio Pascucci, Chuck Hansen, David
Ebert, John Clyne (Co-PI), Hank Childs
Longhorn Usage Modalities:
• Remote/Interactive Visualization
– Highest priority jobs
– Remote/Interactive capabilities facilitated through VNC
– Run on 3 hour queue limit boundary
• GPGPU jobs
– Run on a lower priority than the remote/interactive jobs
– Run on a 12 hour queue limit boundary
• CPU jobs with higher memory requirements
– Run on lowest priority when neither remote/interactive nor GPGPU
jobs are waiting in the queue
– Run on a 12 hour queue limit boundary
Software Available on Longhorn
• Programming APIs: OpenGL, vtk (Not natively parallel)
– OpenGL – low level primitives, useful for programming at a
relatively low level with respect to graphics
– VTK (Visualization Toolkit) – open source software system for 3D
computer graphics, image processing, and visualization
– IDL
• Visualization Turnkey Systems
– VisIt – free open source parallel visualization and graphical
analysis tool
– ParaView – free open source general purpose parallel visualization
system
– VAPOR – free flow visualization package developed out of NCAR
– EnSight – commercial turnkey parallel visualization package
targeted at CFD visualization
– Amira – commercial turnkey visualization package targeted at
visualizing scanned medical data (CAT scan, MRI, etc..)
Longhorn Visualization Portal
portal.longhorn.tacc.utexas.edu
What Was the Enabling Technology?
Commodity Graphics Performance
Image Courtesy
Klaus
Mueller, Stony
Brook University
TACC’s Visualization Laboratory (High
Resolution Display Environments)
• Multi-user space with
reserve-able resources
• Seamless
environments from
laptops to large-scale
displays
• Provides large pixel
count displays and a
collaboration room
• Reconfigurable, flexible
environment that can
be used in a variety of
ways
Stallion
• 16x5(15x5) tiled display of Dell 30-
inch flat panel monitors
• 328M(308M) pixel
resolution, 5.12:1(4.7:1) aspect
ratio
• 320(100) processing cores with
over 80GB(36GB) of graphics
memory and 1.2TB(108GB) of
system memory
• 30 TB shared file system
Bronco
• Sony 4K Projector
• 8M pixel resolution, 16:9 aspect
ratio
Collaboration Room (Saddle)
• Dell Precision 690 workstation
• Dell 5100 DLP projector, 10 ft. x
7.5 ft. display
Lasso
Multi-Touch Tiled Display
• 3x2 tiled display(1920x1600) – 12M
Pixels
• PQ Labs multi-touch overlay, 32 point
5mm touch precision
• 11 mm bezels on the displays
Bringing Discovery to a Lab Environment
• Since November 2008, the Vislab has seen
over 20,000 people come through the door.
• Primary Usage Disciplines –
Physics, Astronomy, Geosciences, Biological
Sciences, Petroleum
Engineering, Computational
Engineering, Digital Arts and
Humanities, Architecture, Building Information
Modeling, Computer Science, Education
TACC Vislab Demographics
Vislab resource allocation per
activity type
Vislab usage per science discipline
What Was the Enabling Technology?
Commodity Projectors and Displays
30” LCD
Vislab Challenges
• Complexity – Software, Transferring Materials
to the Displays
• Interaction – Mouse/Keyboard, Joystick, Game
Controllers, Touch, Gesture
• Usability – Systems, Software
• Environment – Individual Display Architectures
vs Space as a Whole
DisplayCluster
• A cross-platform software environment for interactively
driving tiled displays
• Features:
– Media display (Images (up to gigapixels in size, movies
/ animations
– Pixel streaming (Real-time desktop streaming for
collaboration / remote vis)
– Scriptable via Python interface
– Multi-user interaction (iPhone / iPad / Android
devices, Joysticks, Kinect (in development))
– Implementation
(MPI, OpenGL, Qt, FFMPEG, Boost, TUIO, OpenNI, …
)
• Short demonstration:
http://www.youtube.com/watch?v=JwTwa46BhcU
Most Pixels Ever: Cluster Edition
• Create interactive multimedia and data visualizations that span
multiple displays, at very high resolutions
• Enables extremely high resolution Processing sketches
• Licensed and available for download on GitHub:
• https://github.com/TACC/MassivePixelEnvironment
Multi-touch Display and Skeletal Tracking
• Development of device-
agnostic multi-touch
protocols for interaction from
all devices
(phone, table, touchscreen, ki
nect)
• Evaluation of multi-touch
device technologies: optical
infrared detection, image
processing detection
• Skeletal tracking for full
body gesture control
pVis is a wearable visualization computer featuring a cloud-
based visualization pipeline.
• proof-of-concept for wearable, low-
power, richly interactive visualization interfaces
PICO-VIS
Submitted to
SIGGRAPH
Emerging
Technologies
Dynamic, Immersive Visualization Environment
Through the Integration of Multiple Spatially Aware
Visualization Systems
• Motivation:
– Think about the
space as a
whole, rather than a
collection of
individual displays
– Take inspiration from
the biological
ecosystem
Lessons Learned Over the Past
12 Years
• Close collaborations with the science
partners are key.
• Minimize data transfers if possible.
• Scale resources effectively based on use
cases.
• Easy accessibility to and interaction with
technologies encourages participation from
diverse communities.
Thoughts for the Future
• High performance computing environments
are becoming high performance science
environments that provide computing and
analytics
• We are beginning the work to think about the
space as a whole rather than looking at
visualization laboratories as a collection of
individual displays
• The Vislab of the future will be a space that reacts
to users as they enter and will be dynamically
reconfigurable
Thank You
Questions?
Thoughts for the Future
• High performance computing environments
are becoming high performance science
environments that provide computing and
analytics
• We are beginning the work to think about the
space as a whole rather than looking at
visualization laboratories as a collection of
individual displays
• The Vislab of the future will be a space that reacts
to users as they enter and will be dynamically
reconfigurable
Sample Use Cases – Biological Sciences
• Research Motivation:
understand the structure of the
neuropil in the neocortex to
better understand neural
processes.
• People: Chandra Bajaj et. al. UT
Austin
• Methodology: Use Stallion’s
328 Mpixel surface to view
neuropil structure.
Sample Use Cases - Geosciences
• Motivation: understand glacier
recession and fracturing of polar
ice sheets for planning of future
expeditions in Greenland.
• People: Ginny Catania et. al. UT
Austin
• Methodology: Translate workflow
from ArcGIS/ENVI to high
resolution environments. Use
collaborative real-time exploration
of gigapixel-scale satellite imagery.
Sample Use Cases – Architecture/BIM
• Motivation: developing new tools
for building modeling and
construction using large multi-
touch display surfaces
• People: Fernanda Leite, Li
Wang, UT Austin
• Methodology: develop new CAD
interaction methods using gesture
and collaborative multi-touch to
increase productivity in
construction and engineering
design.
Sample Use Cases - Ecology
• Motivation: visualize and explore the
changing vegetation and climate of
the arctic Tundra
• People: Craig Tweedie, UT El Paso
• Methodology: use advanced tools for
high-resolution displays (TACC’s
Massive Pixel Environment – MPE)
for real-time interactive visualization
of point cloud datasets generated
using plane-based LIDAR.
Sample Use Cases - Humanities
• Motivation: use advanced visualization
resources as a tool for the arts and
humanities
• People: TACC Vislab, UT Austin Digital
Humanities
• Methodology: create software to allow non-
trained users the ability to take advantage of
distributed systems and graphics technology.
Develop Massive Pixel Environment(MPE)
and DisplayCluster.
Faces of Mars
Text Universe
Moving Pixels
Sample Use Cases – Virtual Worlds
• Motivation: digitally reconstructing
the past, and live life through
another’s eyes
• People: Janine Barchas, UT Austin
• Methodology: create an immersive
model of the iconic British art exhibit
(The Reynolds Retrospective), which
was a turning point in the history of
modern exhibit practices.
• Prototype with 4 pico projectors, front-
projected
• Uses the Dell M110 1280x800 pico projector
• low price / pixel for projection ($400 / MP )
• Short throw distance (1-10 ft)
• High pixel density
• Lightweight (4"x4"x1"), half a pound.
• Collaboration with Aditi Majumder at UC
Irvine, combining multi-projector edge
blending with TACC's DisplayCluster
software
• Picos are getting cheaper, brighter and
higher-resolution
PICO Wall Project
Aaron Knoll, Aditi Majumder

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Kelly gaither

  • 1. Kelly Gaither, Ph.D. Director of Visualization CONFERENCIA
  • 2. Visualizing Yesterday, Today and Tomorrow: CyberInfrastructure for Next Generation Science Kelly Gaither, Ph.D. Director of Visualization Senior Research Scientist Texas Advanced Computing Center The University of Texas at Austin
  • 3. Texas Advanced Computing Center (TACC) Powering Discoveries that Change the World • Mission: Enable discoveries that advance science and society through the application of advanced computing technologies • Almost 12 years in the making, TACC has grown from a handful of employees to over 120 full time staff with ~25 students
  • 4. TACC Visualization Group • Train the next generation of scientists to visually analyze datasets of all sizes. • Provide resources/services to local and national user community. • Research and develop tools/techniques for the next generation of problems facing the user community.
  • 5. TACC Visualization Group • 11 Full Time Staff, • 2 Undergraduate Students, 3 Graduate Student • Areas of Expertise: Scientific and Information Visualization, Large Scale GPU Clusters, Large Scale Tiled Displays, User Interface Technologies
  • 6. TACC Visualization Group • Scalable Visualization Technologies – Remote and collaborative visualization – Scalable architectures – Large data visualization • Visualization Interfaces and Applications – Scalable display architectures – Interaction mechanisms for large scale tiled displays – Emerging technologies including wearable computing
  • 7. What is Visualization? • “To Envision information is to work at the intersection of image, word, number, art.” Edward R. Tufte, Envisioning Information • “Visualization is any technique for creating from data images, diagrams, or animations to communicate a message.” (http://en.wikipedia.org/wiki/Visualization_computer_graphics)
  • 8. Computer Graphics versus Visualization
  • 9. Computer Graphics versus Visualization
  • 10. Where Does Technology Fit In? • We have always used technology to create pictures or visualizations of what we see in our minds eye. • What changes over time is the technology we use.
  • 11. Visualization Over the Ages 15000 – 10000 BC 1137 AD 1510 Statistical Graphics 1750 - 1800 1812 1987 The Birth of Scientific Visualization
  • 12. The Birth of Visualization as a Field of Science • The emphasis on visualization as a field of science started in 1987 with a special issue of Computer Graphics on Visualization in Scientific Computing. • “Visualization is a method of computing. It transforms the symbolic into the geometric, enabling researchers to observe their simulations and computations. Visualization offers a method for seeing the unseen. It enriches the process of scientific discovery and fosters profound and unexpected insights. In many fields it is revolutionizing the way scientists do science.” Visualization in Scientific Computing, ACM SIGGRAPH 1987
  • 13. What Was the Catalyst? • It’s no coincidence that the first US National Science Foundation funded supercomputing centers began in 1985. • This began the tightly coupled relationship between high performance computing (HPC), data and visualization.
  • 14. What are Today’s Transformational Science Problems? • What is Transformational Science? – In 2007, the US driven Augustine report* provided the recommendation to sustain and strengthen the nation’s traditional commitment to long-term basic research that has the potential to be transformational to maintain the flow of ideas that fuel the economy, provide security, and enhance the quality of life. * Rising Above the Gathering Storm: Energizing and Employing America for a Brighter Economic Future, National Academy Press, 2007.
  • 15. Hurricane Prediction • Forecasters predict the weather using advanced computing technologies. Image: Greg P. Johnson, Romy Schneider, TACC
  • 16. Vehicle Design • Vehicle design and subsequent crash testing are simulated on a supercomputer Image courtesy Mississippi State University Simulation and Design Center
  • 17. Emergency Planning and Response • Models generated with advanced computing help plan emergency response to flooding. Images Courtesy Greg P. Johnson, TACC and Gordon Wells, Center for Space Research
  • 18. Nano-particle Drug Delivery Visualization Ben Urick, Jo Wozniak, Karla Vega, TACC; Erik Zumalt, FIC; Shaolie Hossain, Tom Hughes, ICES.
  • 19. What Role is Visualization Playing in Understanding this Science? Why Are Pictures So Powerful? How Critical is Visualization to Science?
  • 20. What Role Does the Human Brain Play in Successful Visualizations? • “Visualization is so effective and useful because it utilizes one of the channels to our brain that have the highest bandwidths: our eyes. But even this channel can be used more or less efficiently.” [Kosara, 2002]
  • 21. What Role Does the Human Brain Play in Successful Visualizations? • Our vision encompasses: – seeing color – detecting motion – identifying shapes – gauging distance, speed and size – seeing objects in three dimensions – filling in blind spots – automatically correcting distorted information – erasing extraneous information that cloud our view. • Visual cortex makes up 30% of cerebral cortex (77% by volume of human brain) Trends in Neurosciences, 18:471-474, 1995 • Touch makes up 8% of cerebral cortex • Hearing makes up 3% of cerebral cortex Discover Magazine, June 1993: “The Vision Thing: Mainly in the Brain”
  • 22. Using Visualizations for Knowledge Discovery • As data scales, it becomes increasingly apparent that visualization or visual analysis becomes key to knowledge discovery • Managing this bottleneck requires us to have an understanding of: – Remote and collaborative visualization (data manipulation) – High resolution displays (data synthesis)
  • 23. Longhorn (Remote and Collaborative Visualization) • 256 Dell Dual Socket, Quad Core Intel Nehalem Nodes – 240 with 48 GB shared memory/node (6 GB/core) – 16 with 144 GB shared memory/node (18 GB/core) – 73 GB Local Disk – 2 Nvidia GPUs/Node (FX 5800 – 4GB RAM) • ~14.5 TB aggregate memory • QDR InfiniBand Interconnect • Direct Connection to Ranger’s Lustre Parallel File System • 10G Connection to 210 TB Local Lustre Parallel File System • Jobs launched through SGE 256 Nodes, 2048 Cores, 512 GPUs, 14.5 TB Memory Kelly Gaither (PI), Valerio Pascucci, Chuck Hansen, David Ebert, John Clyne (Co-PI), Hank Childs
  • 24. Longhorn Usage Modalities: • Remote/Interactive Visualization – Highest priority jobs – Remote/Interactive capabilities facilitated through VNC – Run on 3 hour queue limit boundary • GPGPU jobs – Run on a lower priority than the remote/interactive jobs – Run on a 12 hour queue limit boundary • CPU jobs with higher memory requirements – Run on lowest priority when neither remote/interactive nor GPGPU jobs are waiting in the queue – Run on a 12 hour queue limit boundary
  • 25. Software Available on Longhorn • Programming APIs: OpenGL, vtk (Not natively parallel) – OpenGL – low level primitives, useful for programming at a relatively low level with respect to graphics – VTK (Visualization Toolkit) – open source software system for 3D computer graphics, image processing, and visualization – IDL • Visualization Turnkey Systems – VisIt – free open source parallel visualization and graphical analysis tool – ParaView – free open source general purpose parallel visualization system – VAPOR – free flow visualization package developed out of NCAR – EnSight – commercial turnkey parallel visualization package targeted at CFD visualization – Amira – commercial turnkey visualization package targeted at visualizing scanned medical data (CAT scan, MRI, etc..)
  • 27. What Was the Enabling Technology?
  • 28. Commodity Graphics Performance Image Courtesy Klaus Mueller, Stony Brook University
  • 29. TACC’s Visualization Laboratory (High Resolution Display Environments) • Multi-user space with reserve-able resources • Seamless environments from laptops to large-scale displays • Provides large pixel count displays and a collaboration room • Reconfigurable, flexible environment that can be used in a variety of ways
  • 30. Stallion • 16x5(15x5) tiled display of Dell 30- inch flat panel monitors • 328M(308M) pixel resolution, 5.12:1(4.7:1) aspect ratio • 320(100) processing cores with over 80GB(36GB) of graphics memory and 1.2TB(108GB) of system memory • 30 TB shared file system
  • 31. Bronco • Sony 4K Projector • 8M pixel resolution, 16:9 aspect ratio
  • 32. Collaboration Room (Saddle) • Dell Precision 690 workstation • Dell 5100 DLP projector, 10 ft. x 7.5 ft. display
  • 33. Lasso Multi-Touch Tiled Display • 3x2 tiled display(1920x1600) – 12M Pixels • PQ Labs multi-touch overlay, 32 point 5mm touch precision • 11 mm bezels on the displays
  • 34. Bringing Discovery to a Lab Environment • Since November 2008, the Vislab has seen over 20,000 people come through the door. • Primary Usage Disciplines – Physics, Astronomy, Geosciences, Biological Sciences, Petroleum Engineering, Computational Engineering, Digital Arts and Humanities, Architecture, Building Information Modeling, Computer Science, Education
  • 35. TACC Vislab Demographics Vislab resource allocation per activity type Vislab usage per science discipline
  • 36. What Was the Enabling Technology?
  • 37. Commodity Projectors and Displays 30” LCD
  • 38. Vislab Challenges • Complexity – Software, Transferring Materials to the Displays • Interaction – Mouse/Keyboard, Joystick, Game Controllers, Touch, Gesture • Usability – Systems, Software • Environment – Individual Display Architectures vs Space as a Whole
  • 39. DisplayCluster • A cross-platform software environment for interactively driving tiled displays • Features: – Media display (Images (up to gigapixels in size, movies / animations – Pixel streaming (Real-time desktop streaming for collaboration / remote vis) – Scriptable via Python interface – Multi-user interaction (iPhone / iPad / Android devices, Joysticks, Kinect (in development)) – Implementation (MPI, OpenGL, Qt, FFMPEG, Boost, TUIO, OpenNI, … ) • Short demonstration: http://www.youtube.com/watch?v=JwTwa46BhcU
  • 40. Most Pixels Ever: Cluster Edition • Create interactive multimedia and data visualizations that span multiple displays, at very high resolutions • Enables extremely high resolution Processing sketches • Licensed and available for download on GitHub: • https://github.com/TACC/MassivePixelEnvironment
  • 41. Multi-touch Display and Skeletal Tracking • Development of device- agnostic multi-touch protocols for interaction from all devices (phone, table, touchscreen, ki nect) • Evaluation of multi-touch device technologies: optical infrared detection, image processing detection • Skeletal tracking for full body gesture control
  • 42. pVis is a wearable visualization computer featuring a cloud- based visualization pipeline. • proof-of-concept for wearable, low- power, richly interactive visualization interfaces PICO-VIS Submitted to SIGGRAPH Emerging Technologies
  • 43. Dynamic, Immersive Visualization Environment Through the Integration of Multiple Spatially Aware Visualization Systems • Motivation: – Think about the space as a whole, rather than a collection of individual displays – Take inspiration from the biological ecosystem
  • 44. Lessons Learned Over the Past 12 Years • Close collaborations with the science partners are key. • Minimize data transfers if possible. • Scale resources effectively based on use cases. • Easy accessibility to and interaction with technologies encourages participation from diverse communities.
  • 45. Thoughts for the Future • High performance computing environments are becoming high performance science environments that provide computing and analytics • We are beginning the work to think about the space as a whole rather than looking at visualization laboratories as a collection of individual displays • The Vislab of the future will be a space that reacts to users as they enter and will be dynamically reconfigurable
  • 47. Thoughts for the Future • High performance computing environments are becoming high performance science environments that provide computing and analytics • We are beginning the work to think about the space as a whole rather than looking at visualization laboratories as a collection of individual displays • The Vislab of the future will be a space that reacts to users as they enter and will be dynamically reconfigurable
  • 48. Sample Use Cases – Biological Sciences • Research Motivation: understand the structure of the neuropil in the neocortex to better understand neural processes. • People: Chandra Bajaj et. al. UT Austin • Methodology: Use Stallion’s 328 Mpixel surface to view neuropil structure.
  • 49. Sample Use Cases - Geosciences • Motivation: understand glacier recession and fracturing of polar ice sheets for planning of future expeditions in Greenland. • People: Ginny Catania et. al. UT Austin • Methodology: Translate workflow from ArcGIS/ENVI to high resolution environments. Use collaborative real-time exploration of gigapixel-scale satellite imagery.
  • 50. Sample Use Cases – Architecture/BIM • Motivation: developing new tools for building modeling and construction using large multi- touch display surfaces • People: Fernanda Leite, Li Wang, UT Austin • Methodology: develop new CAD interaction methods using gesture and collaborative multi-touch to increase productivity in construction and engineering design.
  • 51. Sample Use Cases - Ecology • Motivation: visualize and explore the changing vegetation and climate of the arctic Tundra • People: Craig Tweedie, UT El Paso • Methodology: use advanced tools for high-resolution displays (TACC’s Massive Pixel Environment – MPE) for real-time interactive visualization of point cloud datasets generated using plane-based LIDAR.
  • 52. Sample Use Cases - Humanities • Motivation: use advanced visualization resources as a tool for the arts and humanities • People: TACC Vislab, UT Austin Digital Humanities • Methodology: create software to allow non- trained users the ability to take advantage of distributed systems and graphics technology. Develop Massive Pixel Environment(MPE) and DisplayCluster. Faces of Mars Text Universe Moving Pixels
  • 53. Sample Use Cases – Virtual Worlds • Motivation: digitally reconstructing the past, and live life through another’s eyes • People: Janine Barchas, UT Austin • Methodology: create an immersive model of the iconic British art exhibit (The Reynolds Retrospective), which was a turning point in the history of modern exhibit practices.
  • 54. • Prototype with 4 pico projectors, front- projected • Uses the Dell M110 1280x800 pico projector • low price / pixel for projection ($400 / MP ) • Short throw distance (1-10 ft) • High pixel density • Lightweight (4"x4"x1"), half a pound. • Collaboration with Aditi Majumder at UC Irvine, combining multi-projector edge blending with TACC's DisplayCluster software • Picos are getting cheaper, brighter and higher-resolution PICO Wall Project Aaron Knoll, Aditi Majumder