Nuclear Physics Data Management Needs Bruce G. Gibbard SLAC DMW2004 Workshop 16-18 March 2004

Overview Addressing a class of Nuclear Physics (NP) experiments utilizing large particle detector systems to study accelerator produced reactions Examples at: BNL (RHIC), JLab, CERN (LHC) Technologies & data management needs of this branch of NP are quite similar to HEP Integrating across its four experiments, the Relativistic Heavy Ion Collider (RHIC) at BNL is currently the most prolific producer of data Study of very high energy collisions of heavy ions (up to Au on Au) High nucleon count, high energy => high multiplicity High multiplicity, high luminosity and fine detector granularity => very high data rates Raw data recording at up to ~250 MBytes/sec A Toroidal Lhc ApparatuS (ATLAS) 17 March 2004 B. Gibbard

Digitized Event In STAR at RHIC 17 March 2004 B. Gibbard

IT Activities of Such NP Experiments Support the basic computing infrastructure for experimental collaboration Typically large, 100’s of physicist, and internationally distributed Manage & distribute code, design, cost, & schedule databases Facilitate communication, documentation and decision making Store, process, support analysis of, and serve data Online recording of Raw data Generation and recording of Simulated data Construction of Summary data from Raw and Simulated data Iterative generation of Distilled Data Subsets from Summary data Serve Distilled Data Subsets and analysis capability to widely distributed individual physicists    Data Intensive Activities 17 March 2004 B. Gibbard

Data Handling Limited 17 March 2004 B. Gibbard

Data Volumes in Current RHIC Run Raw Data (PHENIX) Peak rates to 120 MBytes/sec First 2 months of ’04, Jan & Feb 109 Events 160 TBytes Project ~ 225 TBytes of Raw data for Current Run Derived Data (PHENIX) Construction of Summary Data from Raw Data then production of distilled subsets from that Summary Data Project ~270 TBytes of Derived data Total (all of RHIC) = 1.2 PBytes for Current Run STAR = PHENIX BRAHMS + PHOBOS = ~ 40% of PHENIX 17 March 2004 B. Gibbard

RHIC Raw Data Recording Rate 120MBytes/sec PHENIX 120MBytes/sec STAR 17 March 2004 B. Gibbard

Current RHIC Technology Tertiary Storage StorageTek / HPSS 4 Silos – 4.5 PBytes (1.5 PBytes currently filled) 1000 MB/sec theoretical native I/O bandwidth Online Storage Central NFS served disk ~170 TBytes of FibreChannel Connected RAID 5 ~1200 MBytes/sec served by 32 SUN SMP’s Distributed disk ~300 TBytes of SCSI/IDE Locally mounted on Intel/Linux farm nodes Compute ~1300 Dual Processor Red Hat Linux / Intel Nodes ~2600 CPU’s => ~1,400 kSPECint2K (3-4 TFLOPS) 17 March 2004 B. Gibbard

Projected Growth in Capacity Scale Moore’s Law effect of component replacement in experiment DAQ’s & in computing facilities => ~X6 increase in 5 years Not yet fully specified requirements of RHIC II and eRHIC upgrades are likely to accelerate growth Disk Volume at RHIC  17 March 2004 B. Gibbard

NP Analysis Limitations (1) Underlying the Data Management issue Events (interactions) of interest are rare relative to minimum bias events Threshold / phase space effect for each new energy domain Combinatorics of large multiplicity events of all kinds confound selection of interesting events Combinatorics also create backgrounds to signals of interest Two analysis approaches Topological: typically with Many qualitative &/or quantitative constraints on data sample Relatively low background to signal Modest number of events in final analysis data sample Statistical: frequently with More poorly constrained sample Large background (signal is small difference between large numbers) Large number of events in final analysis data sample 17 March 2004 B. Gibbard

NP Analysis Limitations (2) It seems that it is less frequently possible to do Topological Analyses in NP than in HEP so Statistical Analyses are more often required Evidence for this is rather anecdotal – not all would agree To the extent that it is true, final analysis data sets tend to be large These are the data sets accessed very frequently by large numbers of users … thus exacerbating the data management problem In any case the extraction and the delivery of distilled data subsets to physicists for analysis currently most limits NP analyses 17 March 2004 B. Gibbard

Grid / Data Management Issues Major RHIC experiments are moving (have moved) complete copies of Summary Date to regional analysis centers STAR: to LBNL via Grid Tools PHENIX: to Riken via Tape/Airfreight Evolution toward more sites and full dependence on Grid RHIC, JLab, and NP at the LHC are all very interested and active in Grid development Including high performance reliable Wide Area data movement / replication / access services 17 March 2004 B. Gibbard

Conclusions NP and HEP accelerator/detector experiments have very similar Data Management requirements NP analyses of this type currently tend to be more Data than CPU limited “Mining” of Summary Data and affording end users adequate access (both Local and Wide Area) to the resulting distillate currently most limits NP analysis It is expected that this will remain the case for the next 4-6 years through Upgrades of RHIC and Jlab Start-up of LHC with Wide Area access growing in importance relative to Local access 17 March 2004 B. Gibbard