Grid@Large workshopLisboa

29 August 2005

Kors Bos NIKHEF, Amsterdam

LCG

LHC Data and Computing Grid Project LCG

2Hubble Telecope: in the Eagle Nebula 7000 ly from Earth in the Serpense Constellation

Newborn stars emerging from compact pockets of dense stellar gas

Creation of matter ?

3

You need a real problem to be able to build an operational grid

Building a generic grid infrastructure without a killing application for which it is vital to have a working grid is much more difficult

Remark 1

4

The Large Hadron Collider

27 km circumference 1296 superconducting dipoles 2500 other magnets 2 proton beams of 7000 GeV each 4 beam crossing points experiments 2835 proton bunches per beam 1.1 x 1011 protons per bunch

5

Records data at 200 Hz, event size = 1 MB 200 MB/sec1 operational yr = 107 seconds 2 PByte/year raw data

Simulated data + derived data + calibration data 4 PByte/yearThere are 4 experiments 16 PByte/year

For at least 10 years

The Data

6

Challenge I: The Data Volume

Annual data production: 16 PetaBytes/year

Concorde(15 Km)

Balloon(30 Km)

CD stack with1 year LHC data!(~ 20 Km)

Mt. Blanc(4.8 Km)

50 CD-ROM

= 35 GB6

cm

7

Remark 2

In data intensive sciences like particle physics the data management is challenge # 1 much more than the

computing needs

Event reconstruction is an embarrassingly parallel problem. The challenge is to get the data to and from the cpu’s. Keeping track of all versions

of the reconstructed data and their location is another.

8

But … Data Analysis is our Challenge II

One event has many tracksReconstruction takes ~1MSI2k/ev. = 10 minutes on a 3 GHz P4100,000 cpu’s needed to keep up with data rateRe-reconstructed many times10% of all data has to simulated alsoSimulation takes ~100 times longerSubsequent analysis steps over all data

BUT … the problem is embarrassingly parallel !

9

Remark 3

Grids offer a cost effective solution for codes that can run in parallel

For many problems codes have not been written with parallel architectures in mind. Many applications that currently run on supercomputers (because they are there) could be executed in a more cost effective

way on a grid of loosely coupled cpu’s.

10

Challenge III : distributed user community

11

Grids fit almost perfectly large international scientific

collaborations

Inversely, if you don’t already have an international collaboration, it is difficult to get grid resources outside your own country as a

economic model is not in place yet.

Remark 4

12

simulation

reconstruction

analysis

interactivephysicsanalysis

batchphysicsanalysis

detector

event summary data

rawdata

eventreprocessing

eventsimulation

analysis objects(extracted by physics topic)

Data Handling and Computation for

Physics Analysisevent filter(selection &

reconstruction)

processeddata

les.r

ober

tson

@ce

rn.c

h

13

LCG Service Hierarchy

Tier-0 – the accelerator centre Data acquisition & initial processing Long-term data curation Distribution of data Tier-1 centres

Canada – Triumf (Vancouver)France – IN2P3 (Lyon)Germany – Forschunszentrum KarlsruheItaly – CNAF (Bologna)Netherlands – NIKHEF/SARA (Amsterdam)Nordic countries – distributed Tier-1

Spain – PIC (Barcelona)Taiwan – Academia SInica (Taipei)UK – CLRC (Oxford)US – FermiLab (Illinois) – Brookhaven (NY)

Tier-1 – “online” to the data acquisition process high availability

Managed Mass Storage – grid-enabled data service

Data-heavy analysis National, regional support

Tier-2 – ~100 centres in ~40 countries Simulation End-user analysis – batch and interactive

14

regional group

LHC Grid

physicsgroup

les.r

ober

tson

@ce

rn.c

h

Tier2

Lab aUni a

Lab m

Lab b

Uni y

Uni x

Tier3physics

department

Desktop Germany

Taipei UK

FranceItaly

USA(2)

Netherlands

NordicTier-1

CERN Tier 0

Spain

Canada

Uni b

physicsgroup

Lab c

Uni n

15

The OPN Network

Optical Private Network of permanent 10Gbit/sec light paths between the Tier-0 CERN and each of the Tier-1’s

Tier-1 to Tier-1 preferably also dedicated light paths (cross border fibres) but not strictly part of OPN

Additional (separate) fibres for Tier-0 to Tier-1 backup connections Security considerations: ACLs because of limited number of

applications and thus ports. Primarily a site issue. In Europe: GEANT2 will deliver the desired connectivity, in the US:

a combination of LHCNet and ESNet and in Asia: ASNet Proposal to be drafted for a Network Operations Centre

16

T0

IN2P3

GridKaTRIUMF

ASCC

Fermilab

Brookhaven

Nordic

CNAF

SARA

PIC

RAL

T2

T2

T2

T2

T2 T2

T2

T2

T2

T2T2

T2T2

General Purpose IP ResearchNetworks:

NREN’s, GEANT2, LHCNet, EsnetAbilene, Dedicated Links …. Etc.

Special PurposeOptical Private Network:

GEANT2+NREN 10Gbit circuits andLHCNet Dedicated 10Gbit Links to US

CERN

CERNCERN

The Network for the LHC

17

Remark 5

If data flows are known to be frequent (always) between the same end-points it is best to

purchase your own wave lengths between those points

A routed network would be more expensive a much harder to maintain. And why have a router when the start and destination addresses

never change.

18

Integration LCG and EGEE

• Goal Create a European-wide production quality multi-science grid infrastructure on top of national & regional grid programs• Scale 70 partners in 27 countries Initial funding (€32M) for 2 years• Activities Grid operations and support joint LCG/EGEE operations team Middleware re-engineering close attention to LHC data analysis requirements Training, support for applications groups • Builds on LCG grid deployment Experience gained in HEP LHC experiments pilot applications

19

25 Universities4 National Labs2800 CPUs

Grid3

July 2005150 Grid sites34 countries15,000 CPUs8 PetaBytes

30 sites3200 cpus

Inter-operation with the Open Science Grid in the US and with NorduGrid: Very early days for standards – still getting basic experience Focus on baseline services to meet specific experiment requirements

20

There is no one grid and we will have to concentrate on interoperability

and insist on standards

We are still in early days for standards as only now working grids emerge and multiple implementations can be tested to work together

Remark 6

21

Operational InfrastructureA grid of this size (still) needs organisation

For stability, support, information sharing, etcIn Europe we follow the EGEE hierarchy

22

Although in contradiction with the definition of a pure grid, the

infrastructure needs to be well managed and tightly controlled

(at least initially)

Remark 7

23

Site Functional TestsInternal testing of the site

A job with an ensemble of tests is submitted to each site (CE) once a day

This job runs on one CPU for about 10 minutes Data is collected at the Operations Management Centre

(CERN) The data is made available publicly through web pages

and in a database These tests look at the site from the inside to check the

environment a job finds when it arrives there

24

You need a good procedure to exclude malfunctioning sites

from a grid

One malfunctioning site can destroy a whole well functioning grid f.e. through the “black hole effect”

Remark 8

25

Grid Status (GStat) TestsExternal monitoring of the sites

BDII and Site BDII monitoring BDII: # of sites found Site BDII: # of ldap objects Old entries indicate the BDII is not being updated Query response time: indication of network and server loading

GIIS monitoring Collect GlueServiceURI objects from each site bdii:

GlueServiceType: The type of service provided GlueServiceAccessPointURL: How to reach the service GlueServiceAccessControlRule: Who can access this service

Organized Services “ALL” by Service Type “VO_name” by VOs

Certificate Lifetimes for CEs and SEs Job submission monitoring

Click Here

In Table Format with all entries listed

End of that tableSelections:The Northers Region Only

26

You need to monitor how the grid as a whole is functioning

The number of sites, number of cpu’s, number of free cpu’s Is one site never getting any jobs or is one site getting all the jobs

Remark 9

27

Core Infrastructure Centres: CERN, CNAF, IN2P3, RAL, FZK, Univ. Indiana, Taipei

Tools: CoD Dashboard Monitoring tools and in-depth testing Communication tool Problem Tracking Tool

24/7 Rotating Duty

Grid Operations Monitoring: CIC on Duty

CIC

CIC

CIC

CIC

CIC

CIC

RC

RC RC

RC

RC

ROC

RC

RCRC

RC

RCRC

ROC

RC

RC RC

RC

RC

ROC

RC

RC

RC

RC

ROC

RCOMC

28

In spite of all atomization you need a person ‘on duty’ to watch the

operations and react if something needs to be done

System administrators are of the focused on fabric management and have to be alerted when they need to do some grid management

Remark 10

29

CIC-On-Duty (COD) workflow

CIC Portal

GOC DB

GGUS

SFT

Gstat…

Interface Ticketing system

Monitoring toolsStatic data

mails

One week duty rotates among CICsProcedures and ToolsEnsure coordination, availability, reliability CH, UK, France, Germany, Italy, RussiaBut also, Univ. Of Indiana, US, ASCC Taipei

Issues:Needs strong link to security groupsNeeds strong link to user supportMonitoring of site responsiveness to problemsScheduling of tests and upgradesAlarms and follow-upWhen and how to remove a site?When and how to suspend a site?When and how to add sites?

30

Tools – 1: CIC Dashboard

Test summary (SFT,GSTAT)

GGUS Ticket status

• `Problem categories

•`Sites list (reporting new problems)

31

Critique 1

At any time ~40 sites out of 140 have problems CIC-on-duty is sometimes unable to open all new tickets ~80% of resources are concentrated in ~20 biggest sites,

failures at big sites have dramatic impact on the availability of resources

Critique on CoD

Prioritise sites: big sites before small sites Prioritise problems: severe problems before warnings Remove problem sites loss of resources Separate compute problems from storage problems Storage sites can not be removed!

32

Job monitoring is something different from grid monitoring and

equally important

Grid monitoring gives a systems perspective of the grid, job monitoring is what the user wants to see

Remark 11

33

User’s Job Monitoring The tool is R-GMA, data is kept in a database Data can be viewed from anywhere A number of R-GMA tables contain information about: Job Status (JobStatusRaw table)

Information from the logging and bookkeeping service The Status of the job, Queued, Running, Done etc. Job-Id, State, Owner, BKServer, Start time, etc

Job Monitor (JobMonitor table) The Metrics of the running job every 5 minutes A script forked off the worker node by the job wrapper Job-Id, Local-Id, User-dn, Local-user, VO, RB, WCTime, CPUTime, Real Mem, etc.

Grid FTP (GridTFP table) Information about file transfers Host, user-name, src, dest, file_name, throughput, start_time, stop_time, etc

Job Status (User Defined Tables) job-step, event-number, etc.

34

Critique on User’s Job Monitoring

Querying a data base is not particularly user friendly Building and populating user defined tables is not

straight forward We have tried to solve the problem with R-GMA but

there are other solutions

Critique 1

35

User Support

Covers Helpdesk, User Information, Training, Problem Tracking, Problem Documentation, Support Staff Information, Metrics, ..

Tool for problem submission and tracking, Tool to access knowledge base and FAQ’s, Tool to status information and contacts, ..

Websites to documentation, information, howto’s, training, support staff, ..

How do I get started? Where do I go for help? What are procedures for

certificates, CA’s, VO’s? Are there examples, templates? etc

Where is my job? Where is the data? Why did my job fail? I don’t understand the error! It says certificate expired, but I think it

is not? It says I’m not the VO, but I am etc

36

DeploymentSupport (DS)

Middleware Problems

LHCexperiments(Alice Atlas CMS LHCb)

Other Communities

(VOs), e.g. EGEE

non-LHCexperiments

(BaBar, CDF, Compass, D0)

Operations Center(CIC / GOC / ROC)

Operations Problems

ResourceCenters (RC)Hardware Problems

Experiment Specific User Support (ESUS)VO spec. (Software) Problems

Global Grid User Support (GGUS)Single Point of Contact

Coordination of UserSupport

Support Teams in LCG & EGEE

37

User Support Workflow

ESUS

GOC+Resource Center

DS

Applicationproblem

Operationproblem

MiddlewareproblemGGUS

User

38

The User’s View

At present many channels used:EIS contact people: support-eis@cern.chLCG Rollout list: LCG-ROLLOUT@LISTSERV.RL.AC.UKExperiment specific: atlas-lcg@cen.chGGUS: http://www.ggus.org

Not a real agreed procedure. GGUS provides a useful portal and problem tracking tools – however requests are forwarded, information spread, etc.

http://www.grid-support.ac.uk/ Grid.it

39

Critique 3

User’s Support Critique GGUS doesn’t work as we expected, but maybe the scope was too

ambitious: Global Grid User Support The setup was made too much top-down rather than starting from the

user. A user wants to talk to her local support people and we should have started from there. Should a user know about GGUS?

Anything that can be done locally should be done locally and if that cannot be done be taken a level up like to the ROC

GGUS was too formal and set up in too much isolation. (Sysadmins got tickets to resolve without even having heard about GGUS)

The new service takes account of these points and is getting better: more adapted procedures integration of a simpler ticketing system; improved application specific (VO) support better integration with the EGEE hierarchy and the US system

40

Do not organise globally what can be done locally

In the Grid community there is a tendency to do everything globally. However there are things that can better be done locally like user

support, training, installation tools, fabric monitoring, accounting, etc.

Critique 4

41

Software Releases Critique

A heavy process, not well adapted to many bugs found in early stages Becoming more and more depended on other packages Hard to coordinate upgrades with on-going production work Difficult to make >100 sites upgrade all at once: local restrictions Difficult to account for local differences: operations systems, patches,

security Conscious decision to not prescribe an installation tool: default just

rpm’s but also YAIM, others use Quattor and yet other tools

Critique 5

42

Operational security

We now have (written and agreed) procedures for: Installation and Resolution of Certification Authorities Release and withdrawal of certificates Joining and leaving the service Adding and Removing Virtual Organisations Adding and Removing users Acceptable Use Policies: Taipei accord Risk assessment Vulnerability Incident response

Legal Issues need to be more addressed urgently

43

Last Operational Issue: The Challenges

Challenges are needed in all operational areas: Monte Carlo Challenges (massive CPU usage) Data Challenges (distributed data analysis) Data Recording Challenges (writing to tape) Service Challenges (raw and derived data distribution round the clock) Security Challenges (not announced beforehand)

Milestones defined by the applications and agreed with the sites in the Grid Deployment Board GDB

Pre-defined metrics determine the level of success/shortfall Massive amount of work, we can do only a few per year. All above

mentioned components are needed Should gradually evolve to pre-production and production status

44

LCG Data Recording Challenge

Simulated data acquisition system to tape at CERN In collaboration with ALICE – as part of their 450 M B/sec data challenge Target – one week sustained at 450 MB/sec – achieved 8 March Succeeded!

Tape server throughput – 1-8 March 2005

45

Service Challenge 2

Data distribution from CERN to some Tier-1 sites Original target – sustain daily average of 500 MByte/sec from CERN to at

least 5 Tier-1 sites for one week by the end of April Target raised to include 7 sites and run for 10 days

BNL, CCIN2P3, CNAF,FNAL, GridKa, RAL,NIKHEF/SARA

Achieved on 2 April – -- average 600 MB/sec-- peak 820 MB/sec

500 MB/sec is 30%of the data distributionthroughput required for LHC

46

Monte Carlo ChallengesRecent ATLAS work

• ATLAS jobs in EGEE/LCG-2 in 2005•In latest period up to 8K jobs/day

• Several times the current capacity for ATLAS at CERN alone – shows the reality of the grid solution

Number of jobs/day ~10,000 concurrent jobs in the system

47

Service Challenge 3 (ongoing)

Target: > 1 GByte/sec of data out of CERN, disk-to-diskWith ~150 MByte/s to individual sitesAnd ~40 Mbytes/s to tape at some Tier-1 sitesSustained for 2 weeks

48

Challenges are paramount on the way to an operational grid

Grid Service Challenges as well as Application Challenges are needed for testing as well as for planning purposes

Remark 12

49

Ramping up to the LHC Grid Service580 days left before LHC turn-on

The grid services for LHC will be ramped-up through two Service Challenges SC3 this year and SC4 next year

These will include the Tier-0, the Tier-1s and the major Tier-2s Each service Challenge includes –

-- a set-up period check out the infrastructure/service to iron out the problems

before the experiments get fully involved schedule allows time to provide permanent fixes for problems

encountered A throughput test

-- followed by a long stable period for the applications to check out their computing model and software chain

50

Grid Services Achieved

We have an operational grid running at ~10,000 concurrent jobs in the system

We have more sites and processors than we anticipated at this stage: ~140 sites, ~12,000 processors

The # of sites is close to that needed for the full LHC grid but only at a few % of the full capacity

Grid operations shared responsibility between operations centres

We have successfully completed a series of Challenges 34 countries working together in a consensus based

organisation

51

Critique 6

Further Improvements Needed

Reliability is still a major issue - a focus for work this year Not enough experience with data management yet: more

Challenges needed Middleware evolution - aim for a solid basic functionality by

end 2005 Support improvement in all area’s Security procedures not well tested yet Legal issues become pressing No economic model yet, accounting, resource sharing,

budgets, etc.

Kors Bos NIKHEF, Amsterdam

LCG

The End