NIIF Grid development portfolio

Szalai Ferenc, NIIF Instituteszferi@niif.hu

http://www.clustergrid.huhttp://gug.grid.niif.hu

Introduction● Main force: ClusterGrid Infrastucture

– about 1000 computational node organized in 32 cluster

● Two main direction:– Infrastructure development: virtualization,

distributed storage infrastructure, manage hugh amount of nodes etc.

– Middleware development: Grid Underground (GUG) Project

ClusterGrid Architecture

Numbers:1000 nodes32 sites (cluster)22 TB storage

Pre-GUG histroy

● ClusterGrid since 2002● First middleware: Condor Flock

– problems: strong centralization, required central auth with LDAP, the io overhead was lot because the shadow processes etc.

● Second middleware: Centralized broker based on Apache/Postgresql/PHP– since then Condor just an LRMS– problems: missing storage, missing interoperability

● Final solution :) GUG

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 serviceclass 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

GIS● separates data and metadata● advertisements: (metadata, data) tuple● data: XML description of anything like service,

resource etc.● metadata: source of data, TTL, etc. ● simple routing algorithm based on static peer list

and TTL (we like news feeds :)● two main source of data:

– services (get_description function), – GIS backends: standalone data provideres

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

● 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

The real life say good

● Seamles transaction to new middleware: UI have 'almost' compatibility interface with old ClusterGrid broker

● GUG already tested with real life applications:– virtual screening (pharmacy)– nonlinear dinamics (physics)– compliler optimalization (IT research)– usual ClusterGrid applications