WHAT IS A T1? Federico Carminati The Grid of the Americas February 8-11, 2011
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1 WHAT IS A T1? Federico Carminati The Grid of the Americas February 8-11, 2011
2 THE CERN LARGE HADRON COLLIDER LHC LHC is a proton-proton and heavy ion collider Proton-proton center-of-mass energy s pp = 14 TeV Started Sept 2009
3 THE CERN LARGE HADRON COLLIDER LHC LHC is a proton-proton and heavy ion collider Proton-proton center-of-mass energy s pp = 14 TeV Started Sept km around
4 THE CERN LARGE HADRON COLLIDER LHC LHC is a proton-proton and heavy ion collider Proton-proton center-of-mass energy s pp = 14 TeV Started Sept km around
5 THE CERN LARGE HADRON COLLIDER LHC ATLAS LHC is a proton-proton and heavy ion collider Proton-proton center-of-mass energy s pp = 14 TeV Started Sept 2009 CMS Alice ~8-10 PetaBytes/ year ~10 10 events/year ~10 3 batch and interactive users 27 km around LHCb
6 THE CERN LARGE HADRON COLLIDER LHC ATLAS LHC is a proton-proton and heavy ion collider Proton-proton center-of-mass energy s pp = 14 TeV Started Sept 2009 CMS Balloon (30 Km) CD stack with one year of LHC data! (~ 20 Km) Alice ~8-10 PetaBytes/ year ~10 10 events/year ~10 3 batch and interactive users 27 km around LHCb Airplane (10 Km) Mt. Blanc (4.8 Km)
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8 THE GRID IT ALL STARTED WITH MONARC The computing models are remarkably similar T0: First reco, data storage T1: Subsequent recos, MC reco, ordered analysis T2: MC, Chaotic analysis T3: End user analysis ALICE does not have (or admit having ) T3s
9 Today >140 sites ~150k CPU cores >50 PB disk The idea of using the Grid for HEP was launched at CHEP2001 at Padova The Grid has been one of the greatest successes of LHC At the first MONARCH meetings we had no idea of how we could bring different sites to work together Now it is an everyday reality, and it is quickly becoming simply a physicist s working tool
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11 LHCb: CPU at Tier 1s 60% user and 40% reconstruc;on; Ø 200 users Ø 30k jobs/day ALICE: >250 users ~1300 jobs on average over 4 months ATLAS CMS 9
12 THE MONARC MODEL The Monarc model was designed at the end of the last century based on a rigid distribution of tasks between centres of different size and role
13 THE ROLE OF THE T1 IN MONARC The T1 has an important role as Data custody Data serving to a number of dependent T2-3 centres Support and consultancy for dependent T2-3 centres Most of the LHC Grid has been build this way
14 The ALICE Grid
15 T1 The ALICE Grid
16 T1 NorduGrid The ALICE Grid
17 T1 NorduGrid NIKHEF/SARA The ALICE Grid
18 T1 NorduGrid NIKHEF/SARA RAL The ALICE Grid
19 T1 NorduGrid NIKHEF/SARA RAL FZK The ALICE Grid
20 T1 NorduGrid NIKHEF/SARA RAL FZK CERN The ALICE Grid
21 T1 NorduGrid NIKHEF/SARA RAL FZK CERN CCIN2P3 The ALICE Grid
22 T1 NorduGrid NIKHEF/SARA RAL FZK CERN CCIN2P3 CNAF The ALICE Grid
23 T1 NorduGrid NIKHEF/SARA RAL FZK CERN CCIN2P3 CNAF UNAM The ALICE Grid
24 T1 NorduGrid NIKHEF/SARA RAL FZK CERN CCIN2P3 CNAF UNAM KISTI The ALICE Grid
25 THE ALICE ANALYSIS FACILITIES Proof-enabled, Gridaware parallel computing platform Used for early discovery physics, calibration Victim of its own success has doubled twice in the last year at CERN, 480 cores in few days
26 T1 OBLIGATIONS (WLCG MOU)
27 THE GRID DATA TRANSFER Data transfer has been especially successful Out of CERN has peaked above 1GB Transfer between centres also very good Out of CERN Tier 0 traffic: > 4 GB/s input > 13 GB/s served The network is probably the best surprise here Still the least oversubscribed resource we have + the academic/research networks for Tier1/2!
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29 DATA IS STILL THE PROBLEM Data placement is the main problem, particularly for analysis predictive data placement (ATLAS & CMS) or opportunistic (ALICE need single catalogue) Data distribution per se works very well With infinite disk space the two are equivalent If we distributed data generously, deleting them is a real trouble Increasing the disk more difficult than increasing CPU Quotas & monitoring more difficult for data than CPU
30 DESTITUTION OF THE MONARC Given the good performance of the network and the issues with data placement, the Monarc model is evolving from Grid to Cloud
31 DESTITUTION OF THE MONARC Given the good performance of the network and the issues with data placement, the Monarc model is evolving from Grid to Cloud T0 T1 T1 T1 T1 T2 T2 T2 T2 T2 T2 T2 T2 T2 T2 T2 T2
32 DESTITUTION OF THE MONARC Given the good performance of the network and the issues with data placement, the Monarc model is evolving from Grid to Cloud T0 T1 T1 T1 T1 T2 T2 T2 T2 T2 T2 T2 T2 T2 T2 T2 T2
33 A CLOUD OVER THE GRID T hierarchy tends to be softened by userdriven data placement and transfer T1 and T2 are becoming equivalent in the network (OPNng) No longer disk space but network bandwidth will scale with #users and #data
34 SO WHY A T1? Running a T1 means tackle important challenges of providing reliable and continual service to the worldwide community Being well maintained and highly available centres, the T1s are at the forefront of the current evolution of the Grid toward the Cloud and beyond Running at T1 is being at the edge of this evolution, in an ideal position to observe and influence it
35 WHAT ABOUT THE LOCAL COMMUNITY In the ALICE model resources are not dedicated All jobs run in all the centre In this sense a T1 is a contribution to the whole community However the proximity of highly experienced and skilled professionals is an important advantage for the local community The establishment of an AAF system supported by a T1 infrastructure will be a big advantage for the local community
36 WHAT ABOUT RESOURCES A T1 is not about resources, it is about competence and service It is more about people than machines However a T1 service makes sense only beyond a certain level We expect a T1 to have few thousands cores And our experience is that 4 FTE/1000 cores is a reasonable order of magnitude Network provisioning will be of course of paramount importance
37 CONCLUSIONS We are at the beginning of a nice adventure, and I ALICE is looking forward to work with you Commitment and development of human potential are key to the success So good luck and let s go!
38 22
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