1. ATLAS, U.S. ATLAS, and Databases David Malon Argonne National Laboratory DOE/NSF Review of U.S. ATLAS and CMS Computing Projects Brookhaven National Laboratory NOVEMBER 14-17, 2000

2. Outline  Requirements  Technical Choices  Approach  Organization (U.S. and International ATLAS)  Resource Requirements  Schedule  Fallback Issues

3. Requirements  Efficient storage and retrieval of several petabytes of data annually  Global access to data; data replication and distribution to ATLAS institutions worldwide  Event databases (raw, simulation, reconstruction)  Geometry databases  Conditions databases (calibrations, alignment, run conditions)  Statistics and analysis stores

4. Requirements  Access to and storage of physics data through the ATLAS control framework  Metadata databases, and query mechanisms for event and data selection  Schema evolution  Database support for testbeams  Support for physical data clustering and storage optimization  Tertiary storage access and management  Interfaces to fabrication databases, to online data sources, …

5. Technical Choices  Objectivity/DB is the ATLAS baseline datastore technology  Enforce transient/persistent separation to keep physics codes “independent of database supplier”  Use LHC-wide and/or IT-provided technologies wherever possible

6. Approach  Build a nontrivial Objectivity-based event store based on TDR data  Provide a rudimentary generic Objectivity persistency service for storage and access of user-defined data through the control framework; evolve this as ATLAS event model evolves  Use testbeams as testbeds  For IT-supported calibration databases  For evaluating HepODBMS and approaches to naming and user areas  For evaluating alternative transient/persistent separation models  Rely on subsystems for subsystem-specific database content

7. Approach  Build data distribution infrastructure to be grid-aware from the outset; use common grid tools (initially GDMP from CMS)  Participate in the definition of LHC-wide solutions for data and storage management infrastructure  Evaluate and compare technologies, and gain widespread user exposure to baseline technology, prior to first mock data challenge  Understand and address scalability issues in a series of mock data challenges

8. Organization  Shared database coordination responsibility: David Malon (Argonne) and RD Schaffer (Orsay)  Database task leaders from each subsystem  Inner Detector: Stan Bentvelsen  Liquid Argon: Stefan Simion (Nevis), Randy Sobie  Muon Spectrometer: Steve Goldfarb (Michigan)  Tile Calorimeter: Tom LeCompte (Argonne)  Trigger/DAQ: Hans Peter Beck  U.S. Organization: David Malon is Level 3 Manager for databases

9. Resource Requirements  WBS estimates (see document from Torre Wenaus) show 14.6 FTEs in 2001, 15.8 in 2002, with a maximum of 18.5 in 2005  Proposed U.S. share is 3.5 FTE in 2001 (database coordinator and 2.5 developers), 4.5 in 2002, ramping up to a maximum of 6.5

10. Schedule  Framework milestones determine database content support milestones; see David Quarrie’s talk for details  Database content support for simulation and reconstruction needed, e.g., by end of 2001 for Mock Data Challenge 0  December 2000 release:  Access to Objectivity-based event store (TDR data) through the control framework  Rudimentary generic Objectivity persistency service

11. Domain-Specific Schedule  LHC-wide requirements reassessment and a common project for data and storage management will almost certainly commence in 2001  Database evaluation, scalability assessment, and technology comparisions to support a 2001 datastore technology decision  Series production detectors enter testbeam in May 2001

12. Fallback Issues  Expect a shortfall of core database effort in the near term:  3.0 Argonne  0.5 Chicago  3.0 Orsay  1.0-2.0 CERN  0.5-1.0 Milan  0.5-1.0 Lisbon  2.0 U.S. at CERN (pending NSF request)  If all of these materialize, shortfall in rate would not be so large, but the count in October 00 is only 3.0  Currently addressing this by blurring lines between core and subsystem work

13. Fallback Issues  Cannot compromise milestones related to integration into control framework, or support for storage and retrieval of simulation and reconstruction data in the timeframe of the mock data challenges  Have functional flexibility in certain areas (e.g., WBS items relating to security, administration tools); could also delay support for analysis beyond generic services

14. Fallback Issues  Database technology decision is a “floating” milestone— independence of database supplier gives us some temporal flexibility  Could reduce scope, if absolutely necessary, by limiting support for testbeam to a consulting role