Nicola De Filippis Workshop sulla fisica di ATLAS e CMS, Bologna, 24-26 Nov. 2006 - p. 1 The CMS Computing Software and Analysis Challenge 2006 Department

Nicola De Filippis Workshop sulla fisica di ATLAS e CMS, Bologna, 24-26 Nov. 2006 - p. 1

The CMS Computing Software and Analysis Challenge 2006

Department of Physics and INFN Bari

N. De Filippis

On behalf of the CMS collaboration


ContributorsTommaso Boccali <[email protected]> Andrea Sciaba' <[email protected]>Luca Lista <[email protected]>Sergio Fantinel <[email protected]>Daniele Bonacorsi <[email protected]>Marco Paganoni <[email protected]>Giacinto Donvito <[email protected]>Alessandra Fanfani <[email protected]>Giorgio Maggi <[email protected]>Stefano Belforte <[email protected]>Giuseppe Bagliesi <[email protected]>Francesco Safai Tehrani <[email protected]>Giuseppe Codispoti <[email protected]>Salvatore My <[email protected]>Marcello Abbrescia <[email protected]>Antonio Pierro <[email protected]>Paolo Capiluppi <[email protected]>William Bacchi <[email protected]>Livio Fanò <[email protected]>Carlos Kavka <[email protected]>Ugo Gasparini <[email protected]>Paolo.Meridiani <[email protected]>Frederic Ronga <[email protected]>

Federico CALZOLARI<[email protected]>Guido Cuscela <[email protected]>Massimo Biasotto <[email protected]>Federica Fanzago <[email protected]>Maria.Damato<[email protected]>Marco Corvo <[email protected]>HAJDU Csaba <[email protected]>Simon Metson <[email protected]>, StuartWakefield<[email protected]>Mona Aggarwal <[email protected]>Olivier van der Aa <[email protected]> Giuseppe Mazza <[email protected]>Alex Martin <[email protected]>Dave Newbold <[email protected]>David Colling <[email protected]>[email protected] <paolo [email protected]>Filippo Ambroglini <[email protected]>Giuseppe.Cerati <[email protected]>Patrizia Azzi <[email protected]>Ezio Torrassa <[email protected]>Martino.Margoni <[email protected]>Laura Edera <Laura [email protected]>


What was CSA06?A 50 million event exercise to test the workflow and dataflow as defined in the CMS computing model

A test at 25% of the capacity needed in 2008

Main components:• Preparation of large MC simulated datasets (some with HLT-tags)• Prompt reconstruction at Tier-0:

– Reconstruction at 40 Hz (over 150 Hz) using CMSSW– Application of calibration constants from offline DB– Generation of Reco, AOD, and AlCaReco datasets– Splitting of an HLT-tagged sample into 10 streams

• Distribution of all AOD & some FEVT to all participating Tier-1s• Calibration jobs on AlCaReco datasets at some Tier-1s and CAF • Re-reconstruction performed at Tier-1s• Skim jobs at some Tier-1s with data propagated to Tier-2s• Physics jobs at Tier-2s and Tier-1s on AOD and Reco

Italian

con

trib

uti

on


– June 1 June 14: First Version of Detector and Physics reconstruction SW for CSA06

– June 1: Computing systems ready for Service Challenge SC4

– June 15: physics simulation validation complete

– July 1: start MC production

– Aug.15: Calibration, alignment, HLT (and first version L1 simulation),

reconstruction, and analysis tools ready

– Aug.30: 50 Mevt produced, 5M with HLT pre-processing

– Sep. 1: Computing systems ready for CSA

– Sep 15: Start CSA06

– Oct 1: Smooth operation for CSA06

– Oct 30: End smooth operation for CSA06

– Nov 15: Finish CSA06

Official Timeline


Success metricsMost of performance metrics of the CSA06 are: Number of participating Tier-1 - Goal: 7 - Threshold: 5;

Number of participating Tier-2 - Goal: 20 - Threshold 15;

Weeks of running at sustained rate - Goal: 4 - Threshold: 2;

Tier-0 Efficiency - Goal: 80 % - Threshold: 30 %, measured as unattended uptime fraction over 2 best weeks of the running period;

Running grid jobs (Tier-1+Tier-2) per day (2h jobs typ.) - Goal: 50K - Threshold: 30K;

Grid job efficiency - Goal: 90 % - Threshold: 70 %;

Data serving capability at each participating site from the disk storage to CPU: Goal 1MB/s/execution slot - Threshold : 400 MB/s (Tier-1) or 100 MB/sec (Tier-2)

Data transfer Tier-0 to Tier-1 to tape - Individual goals (threshold at 50 % of goal); for CNAF it was: 25 MB/s;

Data transfer Tier-1 to Tier-2 - Goal: 20 MB/s into each Tier-2 - Threshold: 5 MB/s;

Overall "success" is to have 50 % of participant at or above goal and 90 % above threshold.


• Tier-0 (CERN):

– 1.4M SI2K (~1400 CPUs at CERN)

– 240 TB

• Tier-1 (7 sites):

– 2500 CPUs in total

– 70 TB disk + tape as minimum to participate

• Tier-2 (25 sites):

– 2400 CPUs in total

– Average 10 TB disk at participating Tier-2

Computing resources


CSA06 MC production


ProdAgent tool used to automatise the production:

consists of many agents running in parallel: JobCreator, JobSubmitter, JobTracking, MergeSensor….

ouput files are registered in Data bookeeping service (DBS); blocks of files are registered in Data Location System (DLS) which takes care of mapping of file blocks and storage elements where they exist

Files are merged for optimum size before transfer to CERN

CMS software (CMSSW) installed via grid tools or directly by site admins in remote sites. A local catalogue used to map LFNs to local PFNs via a set of rules

Storage technologies deployed: CASTOR, dCache, DPM

MC production software and tools


MC pre-production 4 production teams active:

1 for OSG with contact person: -- Ajit Mohapatra – Wisconsin (taking care of 7 OSG CMS Tier2)

3 for LCG:-- LCG(1) with contact person Jose Hernandez – Madrid (Spain, France, Belgium, CERN)

-- LCG(2) with contact personCarsten Hof – Aachen (Germany, Estonia, Taiwan, Russia, Switzerland, FNAL)

-- LCG(3) with contact person Nicola De Filippis – Bari (Italy, UK, Hungary)

Large partecipation of CMS T1s and T2s involved


Monitoring of MinBias (1)

Maximum rate per day: 1.15 M


Monitoring of MinBias (2)

T1 -CNAF

Most of the failures at CNAF were related to stageout and stagein

problems with CASTOR2

BariPisa LNL


Dataset statistics• 1. Minimum bias (40M)• 2. Zµµ (2M)• 3. T-Tbar (6M)

– All decays

• 4. We (4M)– events selected in narrow range to illuminate 2 SMs

• 5. Electroweak soup (5M)– Wl nu + Drell-Yan (m>15 GeV) + WW +HWW

• 6. HLT soup (5M): 10 effective MC HLT triggers (no taus pass)– W (leptons) + Drell-Yan (leptons) + t-tbar (all modes) + dijets

• 7. Jet calibration soup (1M)– dijet + Z+jet, various pt-hat ranges

• 8. Soft Muon Soup (2M)– Inclusive muons in minbias + J/Psi production

• 9. Exotics Soup (1M)– LM1 SUSY, Z’ (700 GeV), and excited quark (2000 GeV) [all decays]

12 M of events produced by the LCG(3) team

Total: ~ 66 M eventsTotal FEVT: O(150) TB


Efficiency and problems

Efficiency:• Overall efficiency: 88%

– Probability for a job to end successfully once it is submitted

• Grid efficiency: 95%

– Aborted jobs: jobs not submitted because requirements not met (merge jobs) or jobs once submitted fail due to Grid infrastructure reason

Problems:• stage out was the main cause of job failures. More robust checking were implemented, more attempts to stage, a fallback strategy etc..• merge jobs caused tipically an overload of the storage system because of the high rate of read access; CASTOR2 at CNAF was tuned to cope with the needs of the production (D. Bonacorsi and CNAF admins)• site validation: storage, software tag, software mount points, matching of CE• consistency between fileblock/files in DBS/DLS and the reality at sites.

Support of Italian Tier-1 and Tier-2 very effective also in August


CSA06 reconstruction, calibration/alignment


• Reconstruction with CMSSW_1_0_x (x6)

– All main reconstruction components included

• Detector-specific local reconstruction and clustering

• Tracking (only 1 algo used), vertexing, standalone , jets

• Global (with tracker), electrons, photons, b&tau tagging

– Reconstruction time small (no p/u!): 4.5s/ev MB, 20s/ev TTbar

• Computing model assumes 25 s/ev

• Calibration/Alignment

– Ability to pull in constants from Offline DB included for ECAL, Tracker,

and Muon reconstruction

– Direct access to Oracle or via Frontier cache

Tier-0 tasks in CSA06


• Processing for CSA officially launched October 2– First week mostly minbias (with some EWK) using CMSSW102 while

bugs fixed to improve robustness on signal samples• Second week processing included signal samples at rates generally matched to

T1 bandwidth metrics and using CMSSW103• After having run for about 23 days, 120M events at 100% uptime, decided to increase

scale for last days• Reprocessed all signal samples in ~5 days using CMSSW106 and maximum CPU

usage– Useful to re-do some samples (FEVT, Reco, AOD, AlCaReco) because of some

problems/mistakes in earlier generation (missing files, missing muon objects)• Performance:

– 160 Hz processing rate, peaking at 300 Hz• signals, minbias, and HLT split samples

– 1250 CPUs for prompt reconstruction– 150 CPUs for AOD and AlCaReco production (separate step)– All constants pulled from Frontier

• i.e. full complexity of CSA exercise

• 4 weeks uptime (goal), 207M events processed

Tier-0 operations


• Calibration/alignment tasks:– Specialized tasks to align/calibrate subsystems using start-up miscalibrated

samples, e.g.

• Align a portion of Tracker with HIP algorithm by using Z →sample on the central analysis facility (CAF) for prompt calibration/alignment

• Intercalibrate ECAL crystals by phi symmetry in minbias events, 0/, or by isolated electrons from W/Z

– Specialized reduced RECO data format (AlCaReco) to be used for calibration/alignment stream from Tier-0

– Mechanism to write constants back into offline DB to be used

– Re-reconstruction at Tier-1 required to test new constants

– Propose that miscalibration is applied at RECO

• Datasets for alignment exercise: Zµµ

Calibration/Alignment exercise at Tier-0 CAF


Tracker Alignment exercise

CSA06 misalignment scenario: TIB dets and TOB rods misaligned by applying:

random shifts, drawing from a flat distribution of witdth +/-100 m in (x,y,z) for the double sided modules and in x (sensitive coordinate) for the single sided ones

random rotations, drawing from a flat distribution of witdth +/-10 mrad, in (alpha,beta,gamma) for all the modules TIB double sided dets positions

Alignment exercise: to read the object in the DB, to apply the initial misalignment; to run the iterative HIP algorithm and to determine alignment constants; 1M events used and 10 iterations. jobs running in parallel on 20 CPUs on a dedicated queue at Tier-0; new costants inserted into the DB


• Tomcat and squids (caching servers) in place and tested before CSA• DB populated with some sets of constants

– No miscalib., start-up miscalib. (4%), etc…• But multiple failures on first tests

– Crashes (needed CORAL patch)– Logging of 28K queries/job kills servers (disabled)

• Successfully in CSA by ~Oct.24

In CSAGood TestsFailed

tests

Access to DB via Frontier


• All 7 Tier-1 centers participated in the challenge performing very well– some storage element software or hardware problems at individual sites

– but all have recovered and rapidly cleared any accumulated backlogs

• The longest down time at any site has been about 18 hours

• Files are injected into the CMS data transfer system PhEDEx and transferred using FTS– One central service failures

• Recovery has been rapid

– Highest rate from CERN was 550MB/s

First 3 Week AverageFirst 3 Week Average

Site Rate

ASGC 14.3MB/s

CNAF 18.0MB/s

FNAL 47.8MB/s

GridKa 21.7MB/s

IN2P3 14.6MB/s

PIC 14.4MB/s

RAL 16.4MB/s

Total 147MB/s

Transfer Tier-0/Tier-1s


Transfer Tier-0/Tier-1s

Transfer to Tier1 CNAF overall successfull

…..after the prompt reconstruction at Tier-0:


• To fit data at T2, and to reduce primary datasets to manageable sizes, it was needed to run skim jobs at T1s to select events according to the analyses

• Skim configuration files prepared according to the RECO and AOD format (also including some “MC truth” information)

• Organized skim jobs ran with ProdAgent

• Different skim procedures prepared by the users for running on the same dataset were unified in a single skim job producing different streams

• 10 filters prepared by the Italian people to cope with the analyses prepared

• 4 teams for running skim jobs at tier-1s– N. De Filippis: Electroweak soup (RAL, CNAF, ASGC, IN2P3)

– D. Mason: Jets (FNAL)

– C. Hof: TTbar ( FZK and FNAL)

– J. Hernandez: Zmumu (PIC and CNAF)

• Skim job output files shipped to Tier-2s for end-user analyses

• 9 Oct. – T1 Skim jobs started

Skimming data at Tier-1s


• First RECO/AOD definition completed for CSA06 production• RECO Content:

– Tracker Clusters • Rec-hits skipped for disk space reasons• Can be recomputed from clusters

– Ecal/HCal/Muon RecHits– Track “core” plus “extra” + attached RecHits

• Refitting is straightforward from “attached” hits– Vertices, Ecal Clusters, Calo Towers– “High Level” Objects

• Photons, Electrons (links with tracks missing…), Muons, Jets, Met (from Calo Towers and Generator)• Tau tagging

– HLT output summary• Trigger bits + links to High Level Objects (as candidates…)

– HepMC Generator– Geant 4 Tracks/Vertices

• AOD Content: a proper subset of RECO– Clusters, Hits are dropped– Track “core” only saved

• Can’t refit a track on AOD• Only muon tracks have RecHits attached in AOD

– Vertices, Ecal Clusters, Calo Towers– “High Level” Objects, HepMC Generator

RECO/AOD data formats


Monitoring of skim jobs at Tier-1s


Transfer of skim outputs from Tier-1s to Tier-2s

Problems related to:

• wrong config. of Tier-2 sites

• wrong setup of download agents with FTS

• CNAF related problems (FTS server, CASTOR)


Exceeded 1PB in 1 month!

Total transfer Tier-0 to Tier-1s and Tier-2s


Analyses at Tier-2s (1)

P. Govoni


Analyses at Tier-2s (2)

All INFN Tier2s took part to the last step of the CSA06: the physics analyses starting from the output of skim procedures

Legnaro/ Padua

(W selection )

Rome

(electron reco)

Pisa

(tau validation)

Bari

(tracker misalignment)

(Study of minimum

bias/underlying event)


1) Electron and Z mass reconstruction using the hybrid supercluster energy (barrel only):

Analysis at RomeThree analyses with goal: 1. to study of the electron reconstruction in Z ee events (Meridiani)

2. to measure the W mass in W e events (Tabarelli De Fatis, Malberti, CMS

NOTE 2006-061)

3. to run a simple calibration with W e events (Govoni)

Eff vs pT Eff vs mZ


Analysis at Pisa (1)The general idea is to simulate a "early data taking" activity of the group:

1. the goal is to study the tau tag efficiency from the Z events (like

described in CMS/AN 2006/074)

2. the goal is to study the misidentification with the recoiling jet with Z+jet, Z

events

3. In addition: runvalidation package on skimmed events 3) Thevalidation package has been run on pure di-tau sample and on skimmed ttbar sample (S. Gennai, G. Bagliesi).

Isolation efficiency vs Isolation Cone :

pT of the jet


Monte Carlo tuning for LHC

Pileup undestanding

UE contribution measurements in MB events

Analysis at Pisa (2)Study of minimum bias/underlying event (Fanò, Ambroglini, Bartalini):

MinBiasUE


Analysis at LegnaroGoal: to study the W preselection with different Monte Carlo data samples

Two data samples were considered (Torassa, Margoni, Gasparini): (1) the electroweak soup (3.4 M evts, 50% W and 50% DY) (2) the soft muons (1.8 M evts, 50% minimum bias and 50% J/, pT > 4 GeV)

The transverse momentum, the efficiency vs and vs pT as obtained with the GlobalMuon reconstructor (to be compared with standalone…)

EWK soup


Analysis at BariGoals: to study the effect of tracker misalignment on track reconstruction

performances (De Filippis):a) with the perfect tracker geometry;

b) in the short term and in the long term misalignment scenario by reading misalignment position and errors via frontier/squid from the offline database ORCAOFF.

c) by using the tracker module position and errors as obtained by the output of the alignment process that will be run at CERN T0.

Data samples used: Z→ and TTbar (the second for computing the fake rate)


Analysis jobs at Bari• CRAB_1_4_0 used to submit 1.8 k jobs • grid efficiency = 99 %, appl. eff = 94 % • Bunch of 150 jobs run in different time slots• max 45 jobs run in parallel• the configuration of squid tuned to ensure that the alignment data were read by

the local cache of squid via the frontier client rather than from CERN (blue

histo).

frontier/squid works as expected at tier-2 Bari when

accessing alignment data


The last step of CSA06:Re-reconstruction at Tier-1s

Goals: to demonstrate re-reconstruction from some RAW data at Tier-1s as part of the calibration exercise

Status: access of Offline database via frontier working re-reconstruction demonstrated at ASGC, FNAL, IN2P3, PIC and CNAF Running at RAL and further tests at CNAF

PIC


Problems with CMSSW:

- the "reasonability" of the code was not too much taken into account. Operations were driven by computing, and the feeing was: "whatever you run we do not care. It is enough it is not crashing".

-as it often happens in this case, the release schedule was crazy. Also the initial milestones were somehow crazy, and it meant a really hard work to cope with them.

-CSA06 meant blocking developments for some time, to make sure we were maintaining the backward-compatibility. But it also meant a lot of code had to live either in the head, or in pre releases for some time. It would be better to have specifically two releases ongoing at a time: a production one, and a development one.

- Framework proved to be usable for T0 reconstruction. HLT was not attempted at CSA06 and so no conclusions on that.

What should have to work better (1)


What should have to work better (2)

Storage system: CASTOR and DPM support (in general rfio access ) for CMS application had a lot of problems ( libdpm patched, > 2 GB files required a patch)

CASTOR updates too much critical for the operation during the CSA06 operations: that caused a lot of problems and an emergency status for CNAF

Integration issues:

all the pieces of the CSA06 worked (example: CMSSW releases, PA, skim jobs, DBS/DLS interactions) but

a lot of effort of operation teams to make them integrated each other;

PA: tool that required a lot of “distributed” expertise, dedicated hw/sw setup (at least three machines), real–time monitoring

the CMS SW installation in remote sites was problematic

LCG/OSG performances very good


Conclusions/suggestions

CSA06 was successful at INFN (all the steps were executed) but thanks to the 100 % work of few experts and to the coordinated effort of many people at Tier-1 and Tier-2 sites.

CSA06 was supposed to be a challenge to commission the computing/software/analysis system but in some cases it required also development/deployment of the tools

CSA06 analysis exercises could be as the ramp-up for the physics program/organization in Italy

A new CSA would be the best for 2007 with simulated and real data; focus on start-up operations (calibration and alignment) and analysis preparation


Backup slides


pccms30

ProdAgent UI

Test and backup setup + PhEDEx injection

ProdAgent UI I

pccms6DB mirror

pccms28

Apache 2.0php 4.3.2MySQL 5.0.22

ProdAgent UI II

pccms27

Apache 2.0php 4.3.2MySQL 5.0.22

pccms29

PhEDEx server

PA_035, PA_041PA_045, PA_047

various productions monitored

Managed By different PA versions

Production setup at Bari


Monitoring of production via web interface

First prototype of monitoring was developed by Bari team:


CTF tracksCTF tracks

pixel clus.pixel clus.

island basic custersisland basic custers

ecal hitsecal hits

island super clustersisland super clusters

It. cone, 5It. cone, 5

calo-towerscalo-towers

HB/HE hitsHB/HE hits

Tracker/Vertices E/Gamma HCal/Jets/Met

AOD

RECO

Muons

strip clus.strip clus.preshower hitspreshower hits

HF hitsHF hits

HO hitsHO hitsDT 1D hitsDT 1D hits DT 2D segm.DT 2D segm.

DT 4D segm.DT 4D segm.

CSC 2D hits.CSC 2D hits. CSC segm..CSC segm..

RPC hitsRPC hits

RS tracksRS tracks

RS extraRS extra RS tr. hitsRS tr. hits

GSF tracksGSF tracks

GSF extraGSF extra GSF tr. hitsGSF tr. hits

pixel trackspixel tracks

pixel extrapixel extra pixel tr. hitspixel tr. hits

Stand-Alone muonsStand-Alone muons

Global muonsGlobal muons

METMET

m.p. cone, 7m.p. cone, 7m.p. cone, 5m.p. cone, 5

hybrid super clustershybrid super clusters

calo-tower cand’scalo-tower cand’s

strip.electronsstrip.electrons

b/tau tags

cone-isocone-iso

trk count.trk count.

HLT

trigger res.trigger res.

pix.electronspix.electrons

photonsphotons

Kt jetsKt jets

Particle Candidates

Track extensionsCTF tr. hitsCTF tr. hitsCTF extraCTF extra

corr. hybrid s.c.corr. hybrid s.c.

corr. island s.c.corr. island s.c. S-Alone extraS-Alone extra S-Alone tr. hitsS-Alone tr. hits

Global extraGlobal extra Global tr. hitsGlobal tr. hits

muonsmuons

primary verticesprimary vertices

e/gamma trackse/gamma tracks

Event content: RECO/AOD


Overwhelming response from CSA analysis demonstrationsAbout 25 filters producing ~37 (and 21 jet) datasets !Variety of outputs and sizes: FEVT, RECOSim, AlCaReco

Skimming filters


Analysis at BariGoals: to study the effect of tracker misalignment on track reconstruction performances.

a) with the perfect tracker geometry;b) in the short term and in the long term misalignment scenario by reading misalignment

position and errors via frontier/squid from the offline database ORCAOFF. This step requires to refit tracks with misaligned geometry but it can be done at the T2. The effect of alignment position error APE to be checked.

c) by using the tracker module position and errors as obtained by the output of the alignment process that will be run at CERN T0 to verify the efficiency of the alignment procedure on the track reconstruction. Refit of tracks to be done in the T2.

Global efficiency of track recostruction, track parameter resolution and fake rate are compared in the a), b) and c) cases.

The same analysis was performed in ORCA. Plots and documents at link:http://webcms.ba.infn.it/cms-software/cms-grid/index.php/Main/StudiesOfCMSTrackerMisalignment

Data samples needed: Z→ and TTbar (the second for computing the fake rate)


The CSA06 chain of the needed data samples

a) Z→ and TTbar samples produced during CSA06 pre-production with CMSSW_0_8_2.

b) CSA06 events reconstructed at T0 with CMSW_1_0_3 (and Z with CMSSW_1_0_5 in transfer)

c) 2 skim cfg files used for skimming Z→ and TTbar sample . Skim jobs just run at T1 with CMSW_1_0_4 and CMSSW_1_0_5 and output data in reduced format RECOSIM are produced. RECOSIM includes enough information for misalignment analysis.

Z→ filter: to select HepMC muons from Z decay with |with pT> 5 GeV/c2 and50 < m (Z→Filterefficiency between 50 and 60 %.

bar filter: to select events with two muons with || < 2.5 and pT> 15 GeV/c2

d) RECOSIM produced with CMSSW_1_0_4 transferred at T2-Bari and misalignment analysis run over RECOSIM with CMSSW_1_0_6.

e) ¼ of the full statistics already analyzed at T2-Bari ….waiting for all the statistics of the samples.


Track selectionSelection:

track seeding, building, ambiguity resolution, smoothing with KF. ctfWithMaterialTracks refit after applying alignment uncertainties track associator by to match simtracks with rectracks

Efficiency: number of reco tracks matching simul. tracks / number of simul tracks- Simul. track: pT ≥ 0.9 GeV/c, 0<<2.5 , d0 ≤3 cm, z0 ≤30 cm, nhit>0

- Reco. track: pT ≥ 0.7 GeV/c, 0<<2.6 , d0 ≤120 cm, z0 ≤170 cm, nhit≥8

Fake Rate: number of reco tracks not associated to simul tracks / number of

reco tracks

- Simul. track: pT ≥0.7 GeV/c, 0<<2.6 , d0≤ 300 cm, z0 ≤ 300 cm, nhit>8 not

used because Simtrack does not have the number of simihit method → Tracking

Particle will have but TP is not compatible with CSA data samples

- Reco. track: pT ≥ 0.9 GeV/c 0<<2.5 , d0≤ 3 cm, z0 ≤ 30 cm, nhit≥8

Track parameters resolution: sigma of Gauss fit to distribution of

residuals


Analysis jobs at Bari• CRAB_1_4_0 used to submit 1.8 k jobs • grid efficiency = 99 %, appl. eff = 94 % • Bunch of 150 jobs run in different time slots• max 45 jobs run in parallel• the configuration of squid tuned to ensure that the alignment data were read by

the local cache of squid via the frontier client rather than from CERN (blue

histo).

frontier/squid works as expected at tier-2 Bari when

accessing alignment data


Eff. / PT resolution with muons from Z

The effect of misalignment affects the global track reconstruction efficiency in the first data taking scenario.

The effect of tracker misalignment is enough relevant in track parameters resolution (factor 2-3 of degradation)


Track param. Resol.: d0 and z0

A factor between 2 and 3 in impact parameters resolution due to misalignment


Z mass from di-muonsUsing CSA06 Z→ sample

The Z mass resolution is increased by a factor larger than 2 in the first data taking scenario (RMS from 1.3 to 2.8)

Documents

Nicola De Filippis Workshop sulla fisica di ATLAS e CMS, Bologna, 24-26 Nov. 2006 - p. 1 The CMS Computing Software and Analysis Challenge 2006 Department