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HEP@Home

This overview provides an introduction to HEP@Home, a distributed computing system based on BOINC. It discusses the project goals, features, behavior, and related work, as well as the use case of ATLAS. It also includes tests and results, and concludes with the benefits and potential of HEP@Home for physicists.

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HEP@Home

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  1. HEP@Home A Distributed Computing System Based on BOINC September - CHEP 2004

  2. Overview • Introduction • BOINC • HEP@Home • ATLAS Use Case • Tests and Results • Conclusions HEP@Home

  3. Introduction • Project participants: • Faculdade de Ciências da Universidade de Lisboa • Faculdade de Engenharia da Universidade do Porto • From Grid-Brick system presented at CHEP2003 • Goals: • Create a distributed computing system • Explore commodity CPU’s and disks and keep them together • Use public computing • Evaluate its use for dedicated HEP clusters. HEP@Home

  4. Overview • Introduction • BOINC • Description • Features • Behavior • Related Work • HEP@Home • ATLAS Use Case • Tests and Results • Conclusions HEP@Home

  5. Description • Stands for Berkeley Open Infrastructure for Network Computing • Generic software platform for distributed computing • Developed by the SETI@Home team • Based on public computing • Key concepts • Project • Application • Workunit (Job) • Result HEP@Home

  6. Features • Generic platform: supports many applications / projects • Projects can be run simultaneously • Common language applications can run as BOINC applications • Fault-tolerance • Monitored through a Web interface • Implements security mechanisms HEP@Home

  7. Behavior Client makes requests, Server is passive • Initial communication • Work request • Hardware characteristics • Server decides • Workunit download • Application • Input files • Results Upload HEP@Home

  8. Related Work • Project-specific solutions: • SETI@Home • Distributed.net • Folding@Home • Commercial solutions • XtremWeb • JXGrid HEP@Home

  9. Overview • Introduction • BOINC • HEP@Home • Background • Additional Features • Behavior • ATLAS Use Case • Tests and Results • Conclusions HEP@Home

  10. Background Grid-Brick project: • Presented at CHEP2003 • Goal was merge storage units with computing farms. • Conclusions: • No central resource manager • Plug and play clients • Increase robustness • Fault-tolerant system HEP@Home

  11. Additional Features • Avoid data movement • User specific applications • Environments • Scripts • Libraries • Environments patches • “get input” apps • Job dependencies HEP@Home

  12. Behavior • Initial communication • Work request • Hardware characteristics • Available input files • Server decides: • Input file exists: ok • No input file: wait, run "get input" app • Workunit download: • Application • Environment / Patches • Results Upload HEP@Home

  13. Overview • Introduction • BOINC • HEP@Home • ATLAS Use Case • Tests and Results • Conclusions HEP@Home

  14. ATLAS Use Case • How can physicists use HEP@Home to run ATLAS jobs. • The actors of this use case can be: • Physicist doing personal job submission • Real production • Let us suppose we have: • Several ATLAS jobs to run • We know what files each job will produce and consume and how to generate or get these files. • We have computers connected to the Internet HEP@Home

  15. ATLAS Use Case • Execution Steps: • Select or submit ATLAS application • Work submission: • environment files (job options files, scripts, etc) • environment patch • input file template • "get input" application • result (output file) template • As a result the user gets the aggregation of the produced output files as a unique output file. HEP@Home

  16. Overview • Introduction • BOINC • HEP@Home • ATLAS Use Case • Tests and Results • Conclusions HEP@Home

  17. Tests • Based on the defined ATLAS Use Case • Typical ATLAS jobs sequence using Muon events: • Generation: e events (1x) • Simulation: e/10 events (10x) • Digitization: e/10 events (10x) • Reconstruction: e/10 events (10x) • Two groups of tests were defined: e = 100, e = 1000. • For each group, 4 tests were made: • One simple client • Two BOINC client • Four BOINC client • Eight BOINC client HEP@Home

  18. Results - Execution Times • Group A: 100 events • Group B: 1000 events HEP@Home

  19. Results - Data Movement • 1000 events in 8 machines: • Seqx: events x00-x99 HEP@Home

  20. Overview • Introduction • BOINC • HEP@Home • ATLAS Use Case • Tests and Results • Conclusions HEP@Home

  21. Conclusions • Several BOINC projects are currently running successfully worldwide • From HEP@Home tests: • Execution of user applications => more flexibility • Environments and patches => easier work submission • Heavier computation => better results • Low data movement => better results • HEP@Home can be brought to physicists daily tasks with not much effort HEP@Home

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