EGEE-II INFSO-RI-031688EGEE and gLite are registered trademarks The EGEE Production Grid Ian Bird EGEE Operations Manager HEPiX Jefferson Lab, 12 th October.

EGEE-II INFSO-RI-031688 EGEE and gLite are registered trademarks

The EGEE Production Grid

Ian Bird

EGEE Operations Manager

HEPiX

Jefferson Lab, 12th October 2006

Enabling Grids for E-sciencE

[email protected] HEPiX; JLab; 9th-13th October 2006 2


EGEE-II INFSO-RI-031688

Outline

• Some history– What led up to where we

are now?– The EGEE project

• What is the EGEE grid infrastructure today?

– What has been achieved?– How is it used?– How does it compare and

relate to other production grids?

• Outlook




Some history … LHC EGEE Grid

• 1999 – Monarc Project– Early discussions on how to organise distributed computing

for LHC

• 2000 – growing interest in grid technology– HEP community was the driver in launching the DataGrid

project

• 2001-2004 - EU DataGrid project– middleware & testbed for an operational grid

• 2002-2005 – LHC Computing Grid – LCG– deploying the results of DataGrid to provide aproduction facility for LHC experiments

• 2004-2006 – EU EGEE project phase 1– starts from the LCG grid– shared production infrastructure– expanding to other communities and sciences

• 2006-2008 – EU EGEE-II – Building on phase 1– Expanding applications and communities …

• … and in the future – Worldwide grid infrastructure??– Interoperating and co-operating infrastructures?

CERN




The EGEE project• EGEE - €32 M

– 1 April 2004 – 31 March 2006– 71 partners in 27 countries, federated in regional Grids

• EGEE-II - €35 M– 1 April 2006 – 31 March 2008– 91 partners in 32 countries – 13 Federations

• Objectives– Large-scale, production-quality

infrastructure for e-Science – Attracting new resources and

users from industry as well asscience

– Improving and maintaining “gLite” Grid middleware




The EGEE Infrastructure

Certification testbeds (SA3)

Pre-production service

Production service

Test-beds & Services

Operations Coordination Centre

Regional Operations Centres

Global Grid User Support

EGEE Network Operations Centre (SA2)

Operational Security Coordination Team

Support Structures

Operations Advisory Group (+NA4)

Joint Security Policy Group EuGridPMA (& IGTF)

Grid Security Vulnerability Group

Security & Policy Groups

Infrastructure:• Physical test-beds & services• Support organisations & procedures• Policy groups




Certification & release preparation

• The goal is to produce a middleware distribution that can be deployed widely

– Not the same as middleware releases from development projects

– More like a Linux distribution – bringing together many pieces from several sources

• Extensive certification test-bed:– Close to 100 machines involved,

CERN + partners

• Emulate the main deployment environments

• Certification testing:– Installation and configuration– Component (service) functionality– System testing (trying to emulate

real workloads and stress testing)– Beginning to use virtualization to

simplify the testing environment

• Deployment into the pre-production system

– Final step of certification – validation by real sites

– Validation by applications – also allows to prepare apps for new versions




Pre-production service

• Pre-production service is now ~ 20 sites• Provides access to some 500 CPU

– Some sites allow access to their full production batch systems for scale tests

• Sites install and test different configurations and sets of services– Try to get good feeling for the quality of the release or updates before

general release to production

– Feedback to: certification, integration, developers, etc.

• P-PS is now used in the way it was intended– For some time it was acting as a second certification test-bed for the gLite-

1.x branch

– Some services may be demonstrated in this environment before going to production (or they may need more work)




Production service

sites

Size of the infrastructure today:

• 196 sites in 42 countries

• ~32 000 CPU

• ~ 3 PB disk, + tape MSS

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~7000 CPU-months/month




Non-LHC VOs

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Workloads of the “other VOs” start to be significant – approaching 8-10K jobs per day; and 1000 cpu-months/month

• one year ago this was the overall scale of work for all VOs

Workloads of the “other VOs” start to be significant – approaching 8-10K jobs per day; and 1000 cpu-months/month

• one year ago this was the overall scale of work for all VOs




Use of the infrastructure

20k jobs running simultaneously




CPU Usage

Virtual Organizations

Jan. ’06

Sep. ’06




Use for massive data transfer

Large LHC experiments now transferring ~ 1PB/month each




Applications on EGEE

• More than 25 applications from anincreasing number of domains– Astrophysics

– Computational Chemistry

– Earth Sciences

– Financial Simulation

– Fusion

– Geophysics

– High Energy Physics

– Life Sciences

– Multimedia

– Material Sciences

– …..

• Application types:• Simulation• Bulk Processing• Responsive Apps.• Workflow• Parallel Jobs

• Legacy Applications




Simulation

• Examples– LHC Monte Carlo simulation

– Fusion

– WISDOM—malaria/avian flu

• Characteristics– Jobs are CPU-intensive

– Large number of independent jobs

– Run by few (expert) users

– Small input; large output

• Needs– Batch-system services

– Minimal data management for storage of results

ATLAS

ITER




Drug Discovery

• WISDOM focuses on in silico drug discovery for neglected and emerging diseases.

• Malaria — Summer 2005– 46 million ligands docked

– 1 million selected

– 1TB data produced; 80 CPU-years used in 6 weeks

• Avian Flu — Spring 2006– H5N1 neuraminidase

– Impact of selected point mutations on eff. of existing drugs

– Identification of new potential drugs acting on mutated N1

• Fall 2006– Extension to other neglected diseases




Bulk Processing

• Examples– HEP processing of raw data, analysis

– Earth observation data processing

• Characteristics– Widely-distributed input data

– Significant amount of input and output data

• Needs– Job management tools (workload management)

– Meta-data services

– More sophisticated data management




Responsive Apps. (I)

• Examples–Prototyping new applications

–Monitoring grid operations

–Direct interactivity

• Characteristics–Small amounts of input and output data

–Not CPU-intensive

–Short response time (few minutes)

• Needs–Configuration which allows “immediate” execution (QoS)

–Services must treat jobs with minimum latency




Responsive Apps. (II)

• Grid as a backend infrastructure:– gPTM3D: interactive analysis of medical images

– GPS@: bioinformatics via web portal

– GATE: radiotherapy planning

– DILIGENT: digital libraries

– Volcano sonification

• Characteristics– Rapid response: a human waiting for the result!

– Many small but CPU-intensive tasks

– User is not aware of “grid”!

• Needs– Interfacing (data & computing) with non-grid application or portal

– User and rights management between front-end and grid




Workflow

• Examples–“Bronze Standard”: image registration

–Flood prediction

• Characteristics–Use of grid and non-grid services

–Complex set of algorithms for the analysis

–Complex dependencies between individual tasks

• Needs–Tools for managing the workflow itself

–Standard interfaces for services (I.e. web-services)




Parallel Jobs

• Examples– Climate modeling

– Earthquake analysis

– Computational chemistry

• Characteristics– Many interdependent, communicating tasks

– Many CPUs needed simultaneously

– Use of MPI libraries

• Needs– Configuration of resources for flexible use of MPI

– Pre-installation of optimized MPI libraries




Legacy Applications

• Examples–Commercial or closed source binaries

–Geocluster: geophysical analysis software

–FlexX: molecular docking software

–Matlab, Mathematics, …

• Characteristics–Licenses: control access to software on the grid

–No recompilation no direct use of grid APIs!

• Needs–License server and grid deployment model

–Transparent access to data on the grid




Grid management: structure

• Operations Coordination Centre (OCC)

– management, oversight of all operational and support activities

• Regional Operations Centres (ROC)

– providing the core of the support infrastructure, each supporting a number of resource centres within its region

– Grid Operator on Duty

• Resource centres – providing resources

(computing, storage, network, etc.);

• Grid User Support (GGUS)

– At FZK, coordination and management of user support, single point of contact for users




Grid Monitoring

• Goal:– Proactively monitor operational state & performance of the grid

– Trigger corrective actions at sites, ROCs, service managers

• Many tools used:– Distributed responsibility for tools maintenance and operation

– Operator portal, Info sys monitor, SFT/SAM, job monitors, etc.

• Site Functional Tests (SFT) Site Availability Monitor (SAM)– Framework to sample/test services at sites and publish results

– Can include ad-hoc tests (e.g. VO-specific) in the framework or externally

– Allows dynamic look-up by VO of sites that are currently OK for them

– SAM: extends the concept to measure service availability

– Web service access to the data

– Intend to use this to generate trouble tickets and alarms

• Primary tools of the operator on duty are – Information system monitoring and SFT/SAM




Site metrics - availability




Support - GGUS




The EGEE Network Operations Centre

• Creating a “Network Support unit” in the EGEE operational model;

• Tasks:– Receive tickets from NRENs, and

forward to GGUS if impact on grid– Receive tickets from GGUS if a

network issue– Troubleshoot & follow up with sites

or NRENs

GGUS

Users

SupportUnits

ENOC

NRENs

GÉANT2

EGEE Network




Interoperation

• Interoperability and interoperation (or co-operation)

• EGEE has interoperability activities with:(enabling the middlewares to work together)

– Open Science Grid (U.S.) – quite far advanced– Nordugrid (ARC) – task in EGEE-II, 4 workshops and ongoing activity– UNICORE – task in EGEE-II– NAREGI (Japan) – 1 workshop, continued activity– GIN (OGF) – active in several areas

• EGEE has interoperation activities with:(enabling the infrastructures to co-operate)

– Open Science Grid – actually in use– Anticipated with NorduGrid (NDGF) for WLCG




Interoperating information systems

EGEE

OSG

Naregi

Teragrid

Pragma

Nordugrid




Related infrastructure projects

DEISATeraGrid

Coordination in SA1 for:

• EELA, BalticGrid, EUMedGrid, EUChinaGrid, SEE-GRID

Interoperation with

• OSG, NAREGI

SA3: • DEISA, ARC, NAREGI




Sustainability: Beyond EGEE-II

• Need to prepare for permanent Grid infrastructure– Maintain Europe’s leading position in global science Grids

– Ensure a reliable and adaptive support for all sciences

– Independent of short project funding cycles

– Modelled on success of GÉANT Infrastructure managed in collaboration

with national grid initiatives




Summary of status

• Today we have an operating production infrastructure – Probably the largest in the world, supporting many science domains– Relied upon by several as their primary source of computing

• We have a managed operations process addressing most areas– Constantly evolving

• Inter/Co-operation is a fact and is becoming more important very quickly– Several applications need to work across grids – and they need support for

that

• A large fraction of the value of the operations activity is in the intangibles – processes, structures, expertise, etc.

• We recognise that there are many outstanding problems with the current state of things: reliability and robustness are the focus for the next year

EGEE-II INFSO-RI-031688EGEE and gLite are registered trademarks The EGEE Production Grid Ian Bird EGEE Operations Manager HEPiX Jefferson Lab, 12 th October.

Documents

egee project egee

egee grid infrastructure

escience egee

regional grids egee

history lhc egee grid

eu egee project phase

production grids

operational grid