Publishing applications on the Publishing applications on the web via the Easa Portal and web via the Easa Portal and integrating the Sun integrating the Sun Grid Engine Grid Engine By Michael Griffiths & Deniz Savas CiCS Dept. Sheffield University [email protected] [email protected] http://www.sheffield.ac.uk/wrgrid Sept 2007
Publishing applications on the web via the Easa Portal and integrating the Sun Grid Engine Publishing applications on the web via the Easa Portal and integrating.
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Publishing applications on the web via the Easa Publishing applications on the web via the Easa Portal and integrating the Sun Portal and integrating the Sun
Grid EngineGrid Engine By Michael Griffiths
&Deniz Savas
CiCS Dept.
Sheffield University
[email protected] [email protected]
http://www.sheffield.ac.uk/wrgridSept 2007
Sheffield is in South Yorkshire, England
Sheffield University- Sheffield University- factsfacts
Established in 182870 academic departments in 7 faculties
Number of Undergraduate Students: 25,500Number of Post Graduate/Research Students: 5,600Number of International Students : 3,100
‘‘icebergiceberg’ the HPC Cluster at the Computer ’ the HPC Cluster at the Computer CentreCentre
• AMD Opteron based, supplied by Sun Microsystems.
• Processors: 320 ( 160 of these are designated to the Physics Dept. for the PP project )
• Performance: 300GFLOPs • Main Memory: 800GB • User filestore: 9TB • Temporary disk space: 10TB • Physical size: 8 racks • Power usage: 50KW
‘‘icebergiceberg’ cluster hardware components’ cluster hardware components160 general-purpose-use cpu’s; 80 of these are in dual-core configuration with 2 GBytes of memory each. ( V20 Model ) (i.e 40 boxes with 2 cpus + 4 GBytes )
80 are in quad-core configurations with 4 GBytes memory each. ( V40 Model ) ( i.e 20 boxes with 4 cpus + 16 GBytes ) These are also connected via a Myrinet Switch at 2Gbps connection speed.
IPMI Service Processors : Each box contains a service processor with separate network interface for remote monitoring and control.
Inside a V20
Iceberg Cluster ConfigurationIceberg Cluster ConfigurationH
EA
D N
OD
E
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Eth
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Myranet ConnectedWorkers
White Rose GridWhite Rose Grid
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Service Proc 1
Workernode 9
Service Proc n
Workernode n
Service Proc n
Workernode 59
Service Proc n
Workernode 4
Service Proc 1
Workernode 4
Service Proc 1
Workernode 9
Service Proc n
Workernode 9
Service Proc n
Workernode n
Service Proc n
Workernode n
Service Proc n
Workernode 59
Service Proc n
Workernode 59
Service Proc n
Workernode 3
Service Proc 1
Workernode 8
Service Proc n
Workernode n
Service Proc n
Workernode 58
Service Proc n
Workernode 3
Service Proc 1
Workernode 3
Service Proc 1
Workernode 8
Service Proc n
Workernode 8
Service Proc n
Workernode n
Service Proc n
Workernode n
Service Proc n
Workernode 58
Service Proc n
Workernode 58
Service Proc n
Workernode 5
Service Proc 1
Workernode 10
Service Proc n
Workernode n
Service Proc n
Workernode 60
Service Proc n
Workernode 5
Service Proc 1
Workernode 5
Service Proc 1
Workernode 10
Service Proc n
Workernode 10
Service Proc n
Workernode n
Service Proc n
Workernode n
Service Proc n
Workernode 60
Service Proc n
Workernode 60
Service Proc n
YHMAN Network
Grid & HPC applications development toolsGrid & HPC applications development tools
• Development• Fortran77,90, C, C++, Java compilers
• MPI / MPICH-gm
• OpenMP
• Nag Mk 20, 21
• ACML
• Grid• Sun Grid Engine
• Globus 2.4.3 (via gpt 3.0)
• SRB s-client tools
Using the White Rose Grid Using the White Rose Grid
Application PortalApplication Portal
Features and CapabilitiesFeatures and Capabilities
• Web accessible management and execution of applications
• Provides a service for rapid authoring and publication of custom applications
• Easily integrate multiple heterogeneous resources
Potential benefits of an applications portalPotential benefits of an applications portal
• More efficient use of resources
• Ease of use
• Familiar GUI interface
• Capturing of expert knowledge
• Better presentation of legacy software
Potential DevelopmentPotential Development
• Building Expert Systems
• Allowing novice expert to take advantage of parallel HPC resources
• Providing HPC services over the grid
• HPC centres collaborating with each other without having to provide individual usernames, file-storage etc to remote users.
WRG – Application PortalWRG – Application Portal
• Based on EASA
• Three Usage Modes• Users
Run applications
Have storage space
Review old results
• AuthorsBuild and publish applications
• Administrators
UsingUsing
• Accessing
• Managing
• Applications
• Workspace
• Results
• Help
Using:AccessingUsing:Accessing
• Start up a web browser &
http://www.shef.ac.uk/wrgrid/easa.html
• Login using provided user name and password
Using:HelpUsing:Help
• Select Help and Support tab to register
• Apply to Admin for an account
• Apply to authors to register applications
Using:ManagingUsing:Managing
• Installing a client
• Setting password
• Setting Mode• user/author
Using:ApplicationsUsing:Applications
• View and select available applications
Running An ApplicationRunning An Application
User InterfaceUser Interface
Using:WorkspaceUsing:Workspace
• Storage for uploaded files and old job files
Using:ResultsUsing:Results
• Check results
• View job progress
• Export to spreadsheet
Using: ResultsUsing: Results
• Viewing Results
Using:HelpUsing:Help
• Documentation
• Contacts
ConclusionsConclusions
• Disadvantages• Thick Client, License costs
• Advantages• Rapid publication
• Enable virtualization of HPC resources
• Make applications available to broader community, become application focused
• Effective on a network with low bandwidth
• Make applications available to collaboration partners over the internet and outside own organisation
Demonstration Applications Developed for Demonstration Applications Developed for EASAEASA
• Demonstration of Metascheduling Across White Rose Grid
• Monitoring of usage across White Rose Grid
• Running Applications on the local cluster• Fluent
• Ansys
• Generic Matlab and Scilab applications
Metascheduler Demonstration:BackgroundMetascheduler Demonstration:Background
• Enable utilisation of resources across White Rose Grid
• Exploit use of task arrays
• Job submission is seamless
• Demonstration uses a generic scilab application that runs on any of the White Rose Grid Nodes
• Simplistic, but;• effective, manageable and sustainable
Metascheduler Demonstration: MethodMetascheduler Demonstration: Method
• Query and Compare job queues for WRG nodes• qstat –g c• Use slots available and total number of slots to generate weights for
different queues• Compare weights for all queues on different nodes and use to select
node• Use standard EASA job submission technique to submit job to
selected node• EASA does not know about clusters• Special easaqsub submits job to sge, monitors job status will remove
job if wait time exceeded, easaqsub job monitor has completed EASA knows that EASA compute task has completed
Metascheduler Demonstration: Metascheduler Demonstration: Running ScilabRunning Scilab
• User provides scilab scriptfile• Required resource file e.g.
datafiles or files for scilab library routines• Can provide zipped bundle
of scilab resources• Set job submission
information and then submit job
Metascheduler Demonstration: Job Metascheduler Demonstration: Job SubmissionSubmission
• Provide jobname and job description
• Information used for metascheduling
• Jobtime (hours)• Waittime (hours)• Number of tasks (for job
array)• Submission method
• Use metascheduling• Select a particular node
Metascheduler Demonstration : Metascheduler Demonstration : Further DevelopmentsFurther Developments
• Current method successful!• Correctly selects clusters and improves turnaround for scilab compute
tasks
• Current pattern can be extended to other EASA applications
• Provide distributed storage across White rose Grid
• Develop metascheduling strategy introduce greater dependency on user job requirements for node selection
• Exploit other metascheduling systems e.g. SGE transfer queues, CONDOR-G
THE END
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