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Running LIGO workflows on the OSG

Running LIGO workflows on the OSG. L aser I nterferometer G ravitational Wave O bservatory. Britta Daudert OSG-Users meeting Fermilab July 26/27 207. G070489-00-R. What are Gravitational Waves?. Gravitational waves are ripples in the fabric of space and time.

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Running LIGO workflows on the OSG

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  1. Running LIGO workflows on the OSG Laser Interferometer Gravitational Wave Observatory Britta Daudert OSG-Users meeting Fermilab July 26/27 207 G070489-00-R

  2. What are Gravitational Waves? Gravitational waves are ripples in the fabric of space and time • Emitted by accelerating masses • Sources: Compact Binaries, Bursts, Continuous Wave Source, Stochastic Background G070489-00-R

  3. The Interferometer • GW decreases distance between test masses in one arm of the L, increasing it in the other • Distance is measured by bouncing high-power laser light beams between test masses • L1, H1, H2 detectors G070489-00-R

  4. Workflow Generation Analysis Parameters Metadata Describing Raw Data PIPELINE Glue Pipeline Modules LALApps LAL LDR Data Location Service DAG DAGMan DAX Pegasus DAG G070489-00-R ldas-grid OSG

  5. Inside The Pipeline L1 Data H1Data H2 Data Each chunk Of data is analyzed against Each template Tmpltbank Generates bank of waveform parameters Inspiral Signal to noise ratio test Veto testing H1Trigger L1 Trigger H2 Trigger Trigbank Converts triggers into template bank Inca Consistency tests G070489-00-R Event Candidates

  6. Workflow Size Each observatory produces data Each chunk of data is analyzed with each of the templates A chunk of data takes about 5 minutes to be analyzed Each template bank job takes about 5 minutes Work Templates + Segments G070489-00-R

  7. Running Workflows on the OSG Dax DX x Dag G070489-00-R

  8. The Inspiral Pipeline On UWMilwaukee G070489-00-R

  9. Monitoring with monALISA G070489-00-R

  10. Challenges and Solutions Large Data Sets Long Data Transfer Times Disk Space Problems G070489-00-R

  11. Challenges and Solutions Compressing data (LIGO) Large Data Sets SRM G070489-00-R

  12. Challenges and Solutions Work Flow Design Cleanup issues Disk space problems G070489-00-R

  13. Challenges and Solutions Dynamic Cleanup (Pegasus 2.0) Work Flow Design Depth First (Condor_G) G070489-00-R

  14. G070489-00-R

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