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This presentation contains an overview of my work at Nikhef, the Dutch national institute for subatomic physics, in the last few years.
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Physics Data Processing -The online connection
Nikhef colloquium9/2/2009
Sander Klous
Physics Data Processing - Sander Klous 2
Bob Hertzberger
The steamboat view
PDP Activities9/2/2009
My focus
Remote O
nline Farms
Use
Cas
es (i
.e. t
rigge
r per
form
ance
)
Physics Data Processing - Sander Klous 3
Remote Online Farms
• What is a remote online farm?• The connection to the online system• Event routing and streaming• Remote online farms in ATLAS (Hegoi Garitaonandia)
– Debug stream reprocessing– Trigger menu validation– Muon calibration stream
• Do we really need remote online farms?9/2/2009
Physics Data Processing - Sander Klous 4
Concept
9/2/2009
Amsterdam
NIKHEF/SARA
Data Acquisition40 MHz
Level 1
Level 2
Accept 1 in 500
Accept 1 in 50
Accept 1 in 10
Level 3
Computing grid
Networkswitch
Physics Data Processing - Sander Klous 5
Why is this interesting?
9/2/2009
Gary Stix, editor of Scientific American
Janu
ary
2001
Physics Data Processing - Sander Klous 6
Connection to the online system
9/2/2009
ROB
Data Collection Network
L2PU
EFEvent Filter
Back End Network
SFOMassstorage Building 513
ROF
Remote Event Processing Farms
ROF
ROFROF
Packet
Switched
(GEANT)
Ligh
t pat
hLocal Farm
ROBROBROB
SFISFISFILevel 2 Trigger
DDM
Routing and Streaming
Catalin Meirosu
Physics Data Processing - Sander Klous 7
Routing and Streaming introduction
9/2/2009
• Optimizing resources– Online, different routes– Offline, different streams
• Classification of events– Physics– Calibration– Debug– Express– Remote
Hans von der Schmitt
Physics Data Processing - Sander Klous 8
Regions of Interest andPartial Event Building
9/2/2009
Ignacio Aracena
Virtual Point 1
Physics Data Processing - Sander Klous 9
Inclusive or Exclusive streaming
9/2/2009
Hans von der Schmitt
Physics Data Processing - Sander Klous 10
Online monitoring of overlaps
9/2/2009
Brian Petersen
Physics Data Processing - Sander Klous 11
Luminosity blocks
9/2/2009 Hans von der Schmitt
Physics Data Processing - Sander Klous 12
raid25TB
TAGDB
load TAG
recon EXPR
recon PHYS
calib/align
disk150TB
CondDB
Dataacquisition
TIER-0
CASTOR
CPU farm
DDM/DQ2
TIER-1s
3201060
130
440
720
340
720
320
200
200
320
200
200
online
c1
c1
RAW
ESD
AOD
TAG
Express stream handling
9/2/2009
T0MDB
SFO
Rates in MB/s
Final Dress RehearsalData Quality Monitoring
Luc Goossens
Physics Data Processing - Sander Klous 13
Debug stream reprocessing
9/2/2009
Physics Data Processing - Sander Klous 14
Trigger menu validation
9/2/2009
Physics Data Processing - Sander Klous 15
Muon calibration
9/2/2009
Virtual Point 1
MuonCalibration
Group
Physics Data Processing - Sander Klous 16
Do we really need ROFs?
• At the moment: No, not really…– Not for physics at least
• Transition will be gradual– Example: debug stream reprocessing– Limited resources in the CERN Analysis Facility
• Funding will play an important role– Easier to fund online resources in home country– Other factors: energy consumption, human resources
• What will be the first physics use case?9/2/2009
Physics Data Processing - Sander Klous 17
Trigger performance
• Fully Hadronic decays of top pairs• The jet trigger challenge
– Determining trigger efficiencies from data– Tag and probe with leptons– T&P with semi-leptonic decays of top pairs
(Menelaos Tsiakiris)
– Turning the probe around, T&P with jets– Jet trigger efficiencies and rates
• Beyond multi-jet triggers– Topology triggers and remote online farms
9/2/2009
Physics Data Processing - Sander Klous 18
Fully Hadronic decaysof top-antitop pairs
9/2/2009
Physics Data Processing - Sander Klous 19
The jet trigger challenge
• QCD 6 jet background– 1000 to 10000 x Signal
• Is this possible at all?– Long term study
• First look at semi-leptonic decays– Study the possibility to trigger on jets– Extract jet trigger efficiency from data– Cross correlate with muon triggers9/2/2009
Turn on kicks in.Trigger problem
LambacherMunichO(1 fb-1)
Physics Data Processing - Sander Klous 20
Tagged Tagged and Probed
Trigger efficiency from data
Tag and probe• A first example:
di-muon decays of Z bosons
9/2/2009
20 GeV muon turn on curve (CSC note)
Physics Data Processing - Sander Klous 21
Semi leptonic decays of top pairs
• Tag on the jet side and probe on the muon side• Extract number of signal events (1 fb-1)
– Invariant mass reconstruction on hadronic side
9/2/2009
Possible problem: contamination with tau to muon decays
Physics Data Processing - Sander Klous 22
Event by event trigger efficiency
• Determine individual object efficiencies– Extrapolate T&P from di-muon decays of Z-bosons
• Combine objects into an event efficiency• Weigh the event appropriately
9/2/2009
Correct isolation withrespect to closest jet
Correct foreta dependencyWithout corrections
Tamsett – Royal Holloway
Physics Data Processing - Sander Klous 23
Turning the probe around
• More complicated– The jets are multi-object triggers,
e.g. 4J_95: 4 jets above 95 GeV– Thresholds are likely to change
• The missing link:– Trigger efficiency of Semi Leptonic decays– Fully Hadronic decays of top quark pairs
• Is it possible?– If not, can we do better?
9/2/2009
Physics Data Processing - Sander Klous 24
Topology triggers and remote online farms
Topology triggers• Time consuming
– Invariant masses– Likelihood fits
• Budget in point 1– 1500 machines x 8 cores per machine = 12000 cores– 3 kHz EF input rate from LVL2– 12000 / 3000 = 4 seconds per event (all triggers)9/2/2009
Xin Wu
Event FilterMean: 1.57 seconds
2
2
2
2
2
2
2
2
244
12
22
2.3
)175(
2.4
)(
2.4
)4.80(
3.9
)4.80(
01.0
1)(
hadTop
hadTop
lepTop
hadW
lepW
i i
i i
pcorT
pcorTi
MMMMM
EE
(Erik van der Kraaij)
Physics Data Processing - Sander Klous 25
Conclusion
• Remote Online Farms– An interesting research topic– Several farms already in production– Still far from enabling grid for online processing
• Physics Use Cases– Most likely complicated topologies– Fully hadronic decays of top quark pairs– Studies ongoing to understand trigger efficiencies
• The future of grid is in the online connection9/2/2009