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Grid Components in STAR: Experience, Needs and Plans

Grid Components in STAR: Experience, Needs and Plans. A. Vaniachine Lawrence Berkeley National Laboratory July 14, 2000 PPDG Workshop, Argonne. Outline. STAR is taking data:. Grid in analysis Grid for production? Plans. Decisions Taken. Event split into components:

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Grid Components in STAR: Experience, Needs and Plans

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  1. Grid Components in STAR: Experience, Needs and Plans A. Vaniachine Lawrence Berkeley National Laboratory July 14, 2000 PPDG Workshop, Argonne

  2. Outline • STAR is taking data: • Grid in analysis • Grid for production? • Plans

  3. Decisions Taken • Event split into components: • daq (raw data) or fzd (Geant3) • dst: legacy C-structures • event: same info in OO • tags: like an n-tuple • hist: for QA • ... • ROOT-based Architecture • Persistency: • STL containers - structural and reference • schema evolution • Analysis: “good-bye” PAW

  4. Grid Components Deployed for Analysis • tag database: to speed up user response • data in ROOT TTree files (n-tuple): • data description stored together with the data (solves the schema evolution problem) • comments preserved • 2-level hierarchy: 500 tags are in seven groups • split mode for structures (not objects: no need to load classes to analyze tags) • indexed tags (Grand Challenge deployed) • efficient cache management • transparent user access to HPSS in principle, to the raw data as well: “the Dream” is coming true

  5. Component-based Architectures • Grand Challenge: • large size components one component per developer • NOVA: • smaller-size components one components per task Needed: small components, easily adaptable to experiments e.g., “ls” for the HPSS

  6. Grid Components for Production? have to use HPPS data storage: • efficient cache management • transparent user access have to load all distributed nodes: • sustained data transfer methods have to use low-cost commodity components: • latency tolerant algorithms $$$ constraints

  7. Plans for PPDG • Deploy file transfer methods for the BNL-LBNL link current rate: rcf  pdsf = 100 GB/day • Managed file caching for high-throughput computing • pdsf as a development test-bed • rcf as a target for deployment

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