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Hungarian ClusterGrid and its
        applications




     Szalai Ferenc, NIIF Institute
            szferi@niif.hu

                               http://www.clustergrid.hu
                               http://gug.grid.niif.hu
History
●
    early 2002: Start, design phase
●
    Jul 2002: Condor based production system
    started
●
    early 2003: Condor changed in the grid level to
    own middleware
●
    Jul 2003: development of new operating system
    level services has been started
●
    Nov 2005: development new generation
    ClusterGrid middleware (Grid Underground)
    has been started
●
    Dec 2005: migration to the new operating
    system level services
●
    Feb 2006: change to the new middleware
ClusterGrid Architecure
●
    ClusterGrid is a collection of individual clusters
    and supercomputers integrating them with grid
    middleware
●
    Network oriented arch
    –   using MPLS VPN and 802.1q techniques for
        separation -> „small private internet”
●
    Virtualized central services using XEN:
    –   root DNS, monitoring (munin, nagios), Debian
        repository mirror, entry points
●
    Distributed storage
●
    Clusters: standard Beowulf diskless arch.
    based on GNU/Debian Linux distro
ClusterGrid Architecture




Numbers:
1000 nodes
32 sites (cluster)
22 TB storage
Storage
●
    Goal
    –   build national distributed storage infrastucture for grid,
        HPC, disastery recover backup
    –   reach at least 100 TB, be clever and cheep :)
●
    Solution:
    –   IP (iSCSI) and/or ethernet (AoE) based storage
        elements
    –   intelligent grid storage management using grid services
●
    Current state: AoE based storage in two sites
    (NIIF, SZTAKI) 22 TB
ClusterGrid applications
●
    hunderd of registred users, dozens of active
●
    over 80% unitilization
●
    mainly parameter scanning from
    –   bioinformatics, statistical physics, information
        science, biochemistry etc.
●
    main problem: users are not familiar with
    managing huge amount of job and data
    processing, and porting application to different
    paltforms (solaris, linux, etc.)
●
    strong user support intergarted with normal
    helpdesk
Usecase: Virtual Screening
●
    Virtual screening: find molecules to be the base
    of medicine with brute force technique
●
    big virtual screening: find molecules for human
    histamin receptor 4 (HHR4)
    –   known since 2001, member of GPCR group
●
    using databases: 8 million molecule
●
    using close source, binary only,
    liscenced application:
    Flexx (Biosolveit.de)
●
    Takes 2 month total calcualtion
Grid UnderGround
●
    new generation ClusterGrid middleware.
●
    Since Feb 2006 using in the production system
●
    Design goals:
    –   pure web service based framework (no WSRF)
    –   using selected GGF, W3C standards
    –   simplify service development
    –   focus on core services (info, storage, job management,
        security, monitoring)
    –   KISS: Keep It Simple, Stupid
    –   destop and HPC ware: low memory and cpu usage
    –   open source development
        (http://www.sourceforge.net/projects/gug)
GUG Architecture
●
    Pure python framework:
    –   framework runs as a single daemon
    –   manage threads
    –   handle network communication over HTTP(S)/SOAP
    –   every service is a dinamicaly loadable plugin of the
        framework, services use backends to separate
        interfaces and functions
●
    Mandatory services:
    –   Manager service: manage simple lifecycle of other
        services. Remote management also possible.
    –   Grid Information System: p2p system to route
        advertisements, service descriptions of services
        (better than UDDI)
Example service
class Test:
 def __init__(self, id, local_gis_url, 
  config):
   pass
 def _get_description(self, site_id):
   return ”””<?xml version='1.0'?>
   <ServiceDescription>
   <Site>%s</Site>
   </ServiceDescription>
   ””” % site_id
 def echo(self, x509, x):
   return x
GUG Core Services
●
    VOService (security)
    –   every entity identified by X509 cert
    –   every VO should set up at least one VO service
    –   manage authorization information, organize them into the
        tree
    –   manage VO membership like a maling list
●
    Job management components
    –   Exec: run and manage job in SMP systems (useful on
        destops)
    –   Job Controller: using GGF BES interface and GGF
        JSDL. Interface with common LRMS (eg: Condor, Exec
        etc), no scheduling
    –   SuperScheduler: use the same interace and data model
        as Job Controller, it's a grid level scheduler
GUG Core Services
●
    Storage management components:
    –   file based arch.
    –   Storage Controller: stores and gives back files
        using transport independent protocol like SRM
    –   ShareDirectory: directory and file sharing (same
        interface as Storage Controller)
    –   File System Service: metadata catalog
    –   Storage Manager: provides POSIX like interface
        (mkdir, ls, mv, cp etc.), create replicas on Storage
        Contollers, manage file system entity types as a
        plugin: file, directory, shared directory etc.
GUG Serives and UI
●
    Additional services:
    –   Compiler service: create binaries from source to all
        avalilable platforms. Use job management componets
    –   SNMP based monitoring comming soon
●
    User Interface:
    –   modular command line interface: 'grid' command:
    $ grid storage ls /grid/tmp ­R
      /grid/tmp:
      d   2006­04­12 14:04 proba

        /grid/tmp/proba:
        ­ 8 2006­04­12 14:05 szoveg
        ­ 8 2006­04­12 14:06 szoveg.1
        ­ 8 2006­04­12 14:06 masnev
    $ grid job submit testjob.jsdl

    –   graphical and web interface comming soon
Future: KnowARC
●
    EU funded FP6 project
●
    Goal: create ligthweight, interoperable,
    standard based best grid middleware ever,
    strong industrial support
●
    Solution: merge best features of Nordugrid
    ARC and GUG
●
    Partners: Oslo Univ. (NO), Lund Univ. (SE),
    Uppsala (SE), Lubeck (DE), NBI (DK), SUN
    (HU), s + c ag (DE), Geneve Hospital (CH),
    Josif Safarik Inst. (SK), NIIF
●
    More information: http://www.knowarc.eu

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Hungarian ClusterGrid and its applications

  • 1. Hungarian ClusterGrid and its applications Szalai Ferenc, NIIF Institute szferi@niif.hu http://www.clustergrid.hu http://gug.grid.niif.hu
  • 2. History ● early 2002: Start, design phase ● Jul 2002: Condor based production system started ● early 2003: Condor changed in the grid level to own middleware ● Jul 2003: development of new operating system level services has been started ● Nov 2005: development new generation ClusterGrid middleware (Grid Underground) has been started ● Dec 2005: migration to the new operating system level services ● Feb 2006: change to the new middleware
  • 3. ClusterGrid Architecure ● ClusterGrid is a collection of individual clusters and supercomputers integrating them with grid middleware ● Network oriented arch – using MPLS VPN and 802.1q techniques for separation -> „small private internet” ● Virtualized central services using XEN: – root DNS, monitoring (munin, nagios), Debian repository mirror, entry points ● Distributed storage ● Clusters: standard Beowulf diskless arch. based on GNU/Debian Linux distro
  • 4. ClusterGrid Architecture Numbers: 1000 nodes 32 sites (cluster) 22 TB storage
  • 5. Storage ● Goal – build national distributed storage infrastucture for grid, HPC, disastery recover backup – reach at least 100 TB, be clever and cheep :) ● Solution: – IP (iSCSI) and/or ethernet (AoE) based storage elements – intelligent grid storage management using grid services ● Current state: AoE based storage in two sites (NIIF, SZTAKI) 22 TB
  • 6. ClusterGrid applications ● hunderd of registred users, dozens of active ● over 80% unitilization ● mainly parameter scanning from – bioinformatics, statistical physics, information science, biochemistry etc. ● main problem: users are not familiar with managing huge amount of job and data processing, and porting application to different paltforms (solaris, linux, etc.) ● strong user support intergarted with normal helpdesk
  • 7. Usecase: Virtual Screening ● Virtual screening: find molecules to be the base of medicine with brute force technique ● big virtual screening: find molecules for human histamin receptor 4 (HHR4) – known since 2001, member of GPCR group ● using databases: 8 million molecule ● using close source, binary only, liscenced application: Flexx (Biosolveit.de) ● Takes 2 month total calcualtion
  • 8. Grid UnderGround ● new generation ClusterGrid middleware. ● Since Feb 2006 using in the production system ● Design goals: – pure web service based framework (no WSRF) – using selected GGF, W3C standards – simplify service development – focus on core services (info, storage, job management, security, monitoring) – KISS: Keep It Simple, Stupid – destop and HPC ware: low memory and cpu usage – open source development (http://www.sourceforge.net/projects/gug)
  • 9. GUG Architecture ● Pure python framework: – framework runs as a single daemon – manage threads – handle network communication over HTTP(S)/SOAP – every service is a dinamicaly loadable plugin of the framework, services use backends to separate interfaces and functions ● Mandatory services: – Manager service: manage simple lifecycle of other services. Remote management also possible. – Grid Information System: p2p system to route advertisements, service descriptions of services (better than UDDI)
  • 10. Example service class Test: def __init__(self, id, local_gis_url,  config): pass def _get_description(self, site_id): return ”””<?xml version='1.0'?> <ServiceDescription> <Site>%s</Site> </ServiceDescription> ””” % site_id def echo(self, x509, x): return x
  • 11. GUG Core Services ● VOService (security) – every entity identified by X509 cert – every VO should set up at least one VO service – manage authorization information, organize them into the tree – manage VO membership like a maling list ● Job management components – Exec: run and manage job in SMP systems (useful on destops) – Job Controller: using GGF BES interface and GGF JSDL. Interface with common LRMS (eg: Condor, Exec etc), no scheduling – SuperScheduler: use the same interace and data model as Job Controller, it's a grid level scheduler
  • 12. GUG Core Services ● Storage management components: – file based arch. – Storage Controller: stores and gives back files using transport independent protocol like SRM – ShareDirectory: directory and file sharing (same interface as Storage Controller) – File System Service: metadata catalog – Storage Manager: provides POSIX like interface (mkdir, ls, mv, cp etc.), create replicas on Storage Contollers, manage file system entity types as a plugin: file, directory, shared directory etc.
  • 13. GUG Serives and UI ● Additional services: – Compiler service: create binaries from source to all avalilable platforms. Use job management componets – SNMP based monitoring comming soon ● User Interface: – modular command line interface: 'grid' command: $ grid storage ls /grid/tmp ­R /grid/tmp: d   2006­04­12 14:04 proba /grid/tmp/proba: ­ 8 2006­04­12 14:05 szoveg ­ 8 2006­04­12 14:06 szoveg.1 ­ 8 2006­04­12 14:06 masnev $ grid job submit testjob.jsdl – graphical and web interface comming soon
  • 14. Future: KnowARC ● EU funded FP6 project ● Goal: create ligthweight, interoperable, standard based best grid middleware ever, strong industrial support ● Solution: merge best features of Nordugrid ARC and GUG ● Partners: Oslo Univ. (NO), Lund Univ. (SE), Uppsala (SE), Lubeck (DE), NBI (DK), SUN (HU), s + c ag (DE), Geneve Hospital (CH), Josif Safarik Inst. (SK), NIIF ● More information: http://www.knowarc.eu