AppLeS, NWS and the IPG

Fran Berman

UCSD and NPACI

Rich Wolski

UCSD, U. Tenn. and NPACI

AppLeS and the IPG

Usability,Integration

development ofbasic IPG infrastructure

Development of persistent IPG testbed

Performance

“IPG - aware”programming

Short-term Medium-term Long-term

Application schedulingResource schedulingThroughput scheduling

Multi-schedulingResource economy

Integration of schedulers and other tools, performanceinterfaces

Experience withPilot IPG

Development of prototype performance-oriented applications

Development of necessary research

A Model for the Future• Adaptation is key to the ultimate IPG program

development and execution environment.

• Exchange of performance information fundamental to the success of IPG applications

PSE

Config.object

program

wholeprogramcompiler

Source appli-cation

libraries

Realtimeperf

monitor

Dynamicoptimizer

Grid runtime system

negotiation

Softwarecomponents

Service negotiator

Scheduler

Performance feedback

Perfproblem

Grid Application Development System (GrADS)

Why Application Schedulers?

• Application performance can conflict with performance goals of other system components

• Goal of application scheduler is to prioritize performance of the application over other system components

Agent-based Application Scheduling

Sensor Interface

Reporting Interface

Forecaster

Model ModelModel

NWSUserPrefs

AppPerf

Model

PlannerResource Selector

Application

Act.

IPG /Globus infrastructure

NWS (Wolski)AppLeS (Berman and Wolski)

Performance Prediction

• Given monitored bandwidth data, what will happen next?

Fast Ethernet Bandwidth at SDSC

0

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Time of Day

Meg

abits

per

Sec

ond

Measurements

Tue Wed Thu Fri Sat Sun Mon Tue

13:30

NWS Predictions• Monitored data provides a snapshot of what has

happened.

• What we really want to know is: What will happen?

Fast Ethernet Bandwidth at SDSC

0

10

20

30

40

50

60

70

Time of Day

Me

ga

bits

pe

r S

eco

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Measurements

Exponential SmoothingPredictions

Tue Wed Thu Fri Sat Sun Mon Tue

Monitoring vs. Prediction

Mean Square Error PerformanceSDSC Ethernet

0

20

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60

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140MSE

• Last value not always the best predictor• Hard to develop accurate forecasting models -- why

not use all feasible models?

Monitored data

Do AppLeS and NWS Improve Application Performance?

• Good results with many applications including

– SARA AppLeS

– CompLib AppLeS

– Jacobi2D AppLeS

• AppLeS/NWS applications demonstrate that

– prediction is possible in high-variance environments

– adaptivity can improve performance

SARA AppLeS

• SARA = Synthetic Apperture Radar Atlas– application developed at

JPL and SDSC

• Goal: Process radar images from distributed database for user’s desired image

• AppLeS focuses on resource selection problem

. . .

ComputeServers

DataServers

Client

SARA Experiments

CompLib AppLeS

• Problem: Find the best matches between two gene sequence libraries

• Apply FASTA algorithm to all sequence pairs to determine similarity

• Developed for DOCT testbed

sequence library

sequ

ence

libr

ary

Execution time

0

50

100

150

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350

Small Medium Large

Problem Size

Tim

e (s

)

SuperAppLeSAppLeSMentat

CompLib Experiments

Jacobi2D AppLeS• Important component of

many scientific applications

• Time-balancing used to achieve minimal execution time

• Scheduler solves time-balancing equations for Area

iii Commpt

OperAreaT

N N Areai

Jacobi2D Experiments• Comparison of AppLeS with and without NWS

info, and load-balancing

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ime

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onds

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Problem Size

Comparison of Execution Times

Compile-time Blocked

Compile-time Irregular Strip

Runtime

Applying AppLeS/NWS Methodology to the IPG

• AppLeS/NWS methodology can be used to develop performance-efficient IPG applications

• IPG FY99 projects leverage FY98 project and previous AppLeS/NWS development and research

IPG FY99 Project: A “Parameter Sweep” Template

• INS2D representative of larger class of critical NASA applications

• AppLeS parameter sweep template will build on INS2D model and experiments to target larger class of applications and platforms

• Template will serve as a prototype IPG PSE workbench tool

AppLe S

AP

I

Resources

App-specific

case

gen.

Exp

Act

ActSched.

Act

Exp Exp

AppLeS Project Plan FY99 (Berman,UCSD)

• Expand INS2D AppLeS– to NASA IPG testbed

– to include batch systems

– to target Globus

• Development of Parameter Sweep AppLeS template• Goal: To provide framework for improving turnaround time of parameter study

component of complex AES applications

• AppLeS scheduling agents prototype autonomous agent technology for IPG

• Requires development of strategy for scheduling in mixed batch and interactive environments

Project Personnel: Berman, Casanova (UCSD)Collaborators: Wolski (U. Tenn.), Kesselman (ISI/USC)

NWS Project Plan FY99 (Wolski, U. Tenn.)

• Enhance the NWS to support AppLeS parameter sweep template in NASA Globus environment

– NWS API for parameter sweep template

– integration with Globus

• Integrate NWS with IPG and Globus application performance monitoring tools

– use NWS performance techniques to predict application performance dynamically

• Investigate strategies for monitoring and forecasting batch system performance

– queue wait times in the presence of user priorities, etc.

Project Personnel: Wolski (U. Tenn)Collaborators: Berman (UCSD), Moore (SDSC), Kesselman (ISI/USC)

Possible Additional IPG Projects

• AppLeS/NWS-enhanced Storage Resource Broker

Project: Enhance SRB performance through agent-based

scheduling

Project Personnel: Berman, Wolski

Collaborator: Moore

• AppLeS/NWS-enhanced NetSolve over Globus

Project: Improve scheduling component of NetSolve using

AppLeS/NWS techniques, deploy on Globus IPG platform

Project Personnel: Berman, Wolski, Casanova, Dongarra

Collaborator: Kesselman

Possible Additional IPG Projects

• AppLeS/NWS Applications on Condor

Project: Develop AppLeS application which can achieve

performance in the Condor environment; integrate

Condor and NWS information; leverage Condor/Globus

integration

Project Personnel: Berman, Wolski

Collaborator: Livny, Kesselman

Project Information• NWS Home Page:

http://nws.npaci.edu

• AppLeS + NWS Project Personnel

– Francine Berman– Rich Wolski– Walfredo Cirne– Marcio Faerman– Jaime Frey– Jim Hayes– Graziano Obertelli

• AppLeS Home Page: http://www-cse.ucsd.edu/groups/hpcl/apples.html

– Jenny Schopf– Gary Shao– Neil Spring – Shava Smallen– Alan Su– Dmitrii Zagorodnov