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Dv: A toolkit for buildingremote interactive visualization
services
David O’Hallaron
School of Computer Science
Carnegie Mellon University
Martin Aeschlimann, Peter Dinda, Loukas Kallivokas, Julio Lopez, Bruce Lowekamp
Teora, Italy1980
Jacobo Bielak and Omar Ghattas (CMU CE) Thomas Gross (CMU CS and ETH Zurich)
David O’Hallaron (CMU CS and ECE)
Visualization of 1994 Northridge aftershock
Visualization of 1994 Northridge aftershock
Internet service models
• Traditional lightweight service model– small to moderate amount of computation to satisfy requests
– e.g. serving web pages, stock quotes, online trading, search engines
• Proposed heayweight service model– massive amounts of computations to satisfy requests
– scientific visualization, data mining, medical imaging
clientserver
request
response
Typical Quake visualizationpipeline
remotedatabase interpolationinterpolation isosurface
extraction
isosurfaceextraction
scenesynthesis
scenesynthesis
localdisplay
andinput
renderingrenderingreadingreading
FEM solverengine
materialsdatabase
ROI resolution contours scene
vtk library routines
Heavyweight grid service model
Remote compute hosts(allocated once per service
by the service provider)
Local compute hosts(allocated once per request
by the service user)
WAN
Active frames
Framedata
Activeframe
interpreter
Applicationlibrariese.g, vtk
Framedata
Frameprogram
Active Frame Server
Input Active Frame Output Active Frame
Host
Frameprogram
Overview of a Dv visualization service
DvServer
(requestserver)
Remote DV Active Frame Servers
Remotedataset
LocalDv
client
Local DV Active Frame Servers
Responseframes
DvServer
DvServerResponse
frames
Display
...
Request frame
Responseframes
Userinputs
Responseframes
DvServer
Grid-enabling vtk with Dv
reader
localDv
client
response frames (to other Dv servers)
[native data, schedule, flowgraph,control ]
request frame[request server, scheduler, flowgraph, data reader ]
request server
remote machine(Dv request server)
status
... local Dv
serverscheduler
result
...
local machine(Dv client)
Scheduling Dv programs
• Scheduling at request frame creation time– all response frames use same schedule
– performance portability (i.e. adjusting to heterogeneous resources) is possible.
– no adaptivity (i.e., adjusting to dynamic resources)
• Scheduling at response frame creation time– performance portability and limited adaptivity.
• Scheduling at response frame delivery time– performance portability and greatest degree of adaptivity.
– per-frame scheduling overhead a potential disadvantage.
Scheduling scenarios
Ultrahigh Bandwidth
Link
low-endremoteserver
powerfullocal
server
Scheduling scenarios
High Bandwidth
Link
high-endremoteserver
powerfullocal
workstation
Scheduling scenarios
Low Bandwidth
Link
high-endremoteserver
local PC
Scheduling scenarios
HighBandwidth
Link
high-endremoteserver
low-endlocal
PC or PDA
LowBw
Link
powerfullocalproxyserver
Summary
• Heavyweight grid service model– service providers can constrain resources allocated to a
particular service
– service users can contribute resources to improve response time of throughput
• Active frames– general software framework for providing heavyweight
Internet services
– framework can be specialized for a particular service type
• Dv – specialized version of active frame server for vizualization
– grid-enables existing vtk toolkit
– flexible framework for experimenting with scheduling algs