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Biomedical Analysis and Simulation Supercomputer

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Red Hat Enterprise Linux 5. Sun Grid Engine. SAN. Slide 3. BASS Needs. Already handled: ... Star Trek: City on the Edge of Forever ... – PowerPoint PPT presentation

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Title: Biomedical Analysis and Simulation Supercomputer


1
Biomedical Analysis and Simulation Supercomputer
  • Systems MS RA work
  • (Graphics and Image folks can nap)
  • (Ph.D. intending folks can nap)

2
Biomedical Analysis and Simulation Supercomputer
(BASS)
  • 12 racks CPUs, GPUs, network, disk, backup
  • 256 16 180 CPU cores
  • 180 NVidia G80 image analysis accelerators
  • 46,080 floating-point cores, 250GB RAM
  • 1 TB RAM (128GB 16x32GB )
  • Infiniband 4X DDR connectivity
  • 6 GigE connections (RENCI, BRIC, CISMM, )
  • Red Hat Enterprise Linux 5
  • Sun Grid Engine
  • SAN

3
BASS Needs
  • Already handled
  • Hardware support
  • OS support
  • Installation and configuration
  • Backups
  • Needed
  • Compile and run high-performance apps, libs
  • Interface with RENCI, UIUC, IAM, BRIC, VL
  • Web-based scientist access to codes
  • Go to Supercomputing, bring back cool stuff

4
BASS Opportunities
  • Experience
  • Learn as much as you want about running a CPU
    CUDA GPU InfiniBand cluster
  • Work with real scientists on real apps trying to
    solve CF, clotting disorders studying molecular
    docking,
  • Networking
  • Meet researchers across campus and around the
    country
  • Participate in advisory board meetings with heads
    of centers and institutes
  • Hobnob at the Supercomputing conference

5
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6
Computer Visualization andTools for Science
  • (Graphics Simulation folks, wake up!)
  • (Non-Ph.D. intending folks can nap)
  • Team Computer Science,
  • Physics Astronomy,
  • Applied Materials Sciences

7
Dragon Tamers Needed
8
NanoManipulator
  • 2 Ph.D.s
  • 39 Co-authored papers
  • 7 trips to Europe and Asia
  • Longest was 4 months
  • Most recent last month
  • 1 Commercial product

9
David Borland
  • Flexible-Occlusion Rendering
  • 1 Ph.D.
  • 3 papers
  • 1 patent application
  • Licensed to Siemens

10
Summary of My Approach
  • Teaching visualization (Comp 715)
  • Multidisciplinary teams make custom tools
  • Develop new techniques as needed
  • Build entire systems as needed

Insights
Papers
Patents
Dissertations
Open Source
Commercial
11
Upcoming Challenges
  • Blood Clots and Cell Cytoskeleton
  • Image analysis Glowing webs ? models
  • Optimization Fiber strain profile ? web shape
  • Physical Simulation Nonlinear quasi-static sim
  • Automated Microscopy
  • Find me the interesting parts
  • 3D image stitching
  • GPU 120 Hz tracking of focus-changing spots

12
Roadmap
  • Plan to hire 1-2 students in spring/summer
  • Want to ensure long-term funding for you
  • NSF proposal awarded in October
  • Fellowship students welcome now
  • 991 projects ready now

13
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14
991 The Netflix Prize
  • Image Analysis? Bioinformatics?
  • Wake up!

15
Netflix Prize
  • Increase by 10 ? 1M
  • My plan ?
  • Team registered
  • Data downloaded
  • Parser written and tested
  • Data structures filled (need more RAM)
  • Split N1 ways (1 share for UNC)
  • Dont do it for the money

16
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17
991 Your Favorite Topic Here
  • Not just me, most professors
  • Ask one, well point you to other likely
    candidates

18
Come See the Research!
  • Graphics lab on 2nd floor, room 264
  • 6-8 P.M.
  • Meet the nanoGrad Students
  • Graphics, Simulation, Image Analysis, Control
    Systems
  • Talk with me about RA, Fellow, 991,

19
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20
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21
Extra slides below here
22
Find Great CollaboratorsSupport their Endeavors
23
Lessons
  • Visualization based on goals, not techniques
  • Avoid perceptual pitfalls
  • Get over the rainbow
  • Design specific tools, then generalize
  • Experiment interface, not instrument interface
  • Most definitely not computer interfaces
  • Add novel devices as needed dont be a WIMP

24
Art vs. Science
  • Science is what we understand well enough to
    explain to a computer.
  • Art is everything else.
  • Don Knuth

25
Tools to help ScientistsBuild Better Models
  • Estimate models from images
  • Adjust the models
  • Estimate images from models
  • Display model and experiment

26
Comparing Experiment and Model
  • Scientist or image analysis estimates model
  • Computer produces detailed simulation what would
    be the image for this model?
  • Compare detailed simulation to experiment
  • does the model predict actual image?
  • Scientist or algorithm adjusts model
  • is this a better fit?

27
The Right Tool for the Job
  • All-in-one, not optimal for any
  • Sears ShopSmith
  • Computer (WIMP) interface
  • Finely-tuned for the task
  • Specific power tools table saw, lathe, router
  • Automobile, airplane cockpit
  • Bill Buxton Bow for violin
  • What computers should be

28
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29
Comparison in Model Space
What the scientist infers
The Data
Computed Centerline
30
Comparison in Experiment Space
  • Simulated AFM scanner
  • Scanned surface vs. model surface
  • What should I be seeing?
  • Ongoing collaboration with chemist Dorothy Erie
    to produce a model of what happens when proteins
    DNA are scanned with an AFM

31
  • I am attempting to construct a mnemonic memory
    circuit using stone knives and bearskins Spock
  • Star Trek City on the Edge of Forever
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