wesley-doyle
Uploaded by
22 SLIDES
348 VUES
220LIKES

D Ø MC and Data Processing on the Grid

DESCRIPTION

This report discusses the computational challenges and advancements in data processing for the DØ experiment at the University of Oklahoma. It highlights the efficient management of data at 50 events/sec, with extensive use of a 900 CPU farm and storage solutions like SAM. The paper details the successful integration of remote data processing via SAMGrid, including the reprocessing of over 1 billion events. With future demands for larger datasets and tighter budgets, strategies for shared resources and automation in grid computing are crucial for ongoing success in high-energy physics.

1 / 22

Télécharger la présentation

D Ø MC and Data Processing on the Grid

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. DØ MC and Data Processing on the Grid Brad Abbott University of Oklahoma D0SAR Sept 21, 2006

  2. Computing at DØ • Provide the necessary resources for primary processing of data, reprocessing, fixing, skimming, data analysis, MC production, data handling, data verification… • Provide this in a timely manner to allow researchers to analyze data in efficient manner.

  3. Challenges • Collecting data at ~ 50 events/sec. • Processing time is ~ 70 GHz-sec event • ~ 900 CPU’s on DØ farm running 24/7 to keep up with data • Need Millions of Monte Carlo events • Store data to tape and allow easy access (SAM) • Have ability to reprocess, fix, data in timely manner. • Provide computing resources to analyzers

  4. Local Facilities • 70 TB of project disk CluedØ/CAB • CAB • 2.2 THz of CPU (comparable to the FNAL production farm) • 235TB of SAM Cache • More CPU/Disk on order • CluedØ • An incredible resource by the people for the people! • 1+ THz • SAM Cache • 70 TB (nodes) + 160 TB (servers)

  5. Monday Report August 14, 2006, Typical week Usage What does a typical week look like? ANALYSIS STATIONS data analyzed events projects clued0 15.09T 402M 646 fnal-cabsrv2 115.51T 2685M 1611 fnal-cabsrv1 85.56T 2358M 985 D0 TOTAL 216.16T 5446M 3242

  6. Analysis over time • Events consumed by station since “the beginning of SAM time” • Integrates to 300B events consumed Cabsrv-Blue, red Clued0-grey

  7. Statistics

  8. Current Computing Status • Overall very good. • Reconstruction keeping up with data taking. • Data handling working well • Remote sites for MC, reprocessing, processing, fixing • Significant analysis CPU

  9. Future challenges • Larger data sets • Luminosities > 200 E 30 • Increased sharing of manpower with LHC • Reduced manpower for DØ • Tight budgets • Need to use shared resources

  10. Significantly longer to process Computing resources need to Deal with this Previously Need to plan on luminosities of 400 E 30

  11. DØ computing model • Distributed computing, moving toward automated use of common tools on grid • Scalable • Work with LHC, not against, increased resources • Need to conform to standards • DØ running experiment and is taking data. Need to take prudent approach to computing • SAMgrid

  12. SamGrid • SAM: Data Handling • Over 7PB consumed last year • Up to 1 PB/month • SAMGrid: • JIM: Job submission and monitoring • SAM+JIM: SAMGrid • 20 native execution sites • Automated submission to other grids

  13. Progression on Remote Farms • MC  data reprocessing  processing  skimming* analysis* • Facilities: Dedicated farms  shared farm OSG/LCG • Automation: Expert  regional farmer  any user* *Not yet implemented

  14. Data Reprocessing on Grid • Reprocessing of data: 1 Billion events (250 TB from raw) • SAMGrid as default, using shared resources • 3.5 THz for 6 months – Largest such effort in HEP • Refixing: 1.4 B events in 6 weeks • Used SAMGrid, automated use of LCG,OSG • Finished on time. Very successful

  15. Processing on Grid • Prefer not to do primary processing on Grid. • Can do processing on a few select sites that have been well certified (Has been shown, Cable swap data processed at OU) • Certification of Grid is problematic • Do not need to worry about fair-share, availability of nodes etc.

  16. Cable swap data at OU • First time that primary processing performed at a remote site for DØ • Processed 9463 files • Total of 3421.6 GB • Events: 18391876 • Took ~ 3 months. Partly since we only had ~70 of the available 270 CPU’s

  17. MC Production resources • All produced offsite • MC less stringent, i.e. can always make more • Native SAMGrid Producers: CMS-FNAL. Gridka, LTU, LU, MSU, OU(2), SPRACE, TATA, Westgrid, Wuppertal, FZU • Non-SAMGrid: Lyon and Nikhef • LCG -21 CE’s (10 UK, 6 FR, 3NL, 1 CZ, 1 DE) • OSG 8 CE’s ( UNL, IU, Purdue, SPGRID, OCHEP, TOPDAWG, UWM, CMS-FNAL

  18. Monte Carlo • More than 250 Million events produced • Up to 10 million events/week • LCG and OSG • 59% SAMGrid • 80.4%Europe • 15.7% N. America • 3.5% S. America • 0.3% Asia

  19. Current plans • Reprocessing of Run IIB data needed • 300 million events • Takes ~ 80 GHZ-sec/event to process • Expect to need ~ 2000 CPUs for 4 months to reprocess data • Utilize OSG sites much more extensively • SAM v7 (One version of SAM) • Plan on beginning in November

  20. Current plans (cont) • Overall priority is to reduce manpower needs for midterm and long term by assuring additional functionality is quickly developed. First in SAMGrid mode with rapid transfer to automated forwarding nodes. • CAB running as part of Fermigrid • Moving full functionality to the forwarding mechanisms • Automated production of MC with OSG • Sam shifters take over responsibility of submitting jobs • Automated submission to use full power of interoperability/grid resources

  21. OSG/LCG

  22. Conclusions • DØ computing model very successful • MC and data are continuing to move more toward using Grid resources • LCG has been used more heavily in past but soon OSG will be more heavily utilized • Remote computing critical for continued success of DØ

More Related