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