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Monte Carlo Instrument Simulation Activity at ISIS

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Monte Carlo Instrument Simulation Activity at ISIS. Dickon Champion, ISIS Facility. HET Fermi Chopper Simulation. OSIRIS Back Scattering Instrument. m=2 (10cmx10cm). m=3.0 (2cmx4cm). L1. L2. Wish Diffractometer Guide. Polarizing Mirror Component. Single bounce. 0.4°. 1.2°.

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slide4
OSIRIS Back Scattering Instrument

m=2 (10cmx10cm)

m=3.0 (2cmx4cm)

L1

L2

slide7
Polarizing Mirror Component

Single bounce

0.4°

1.2°

slide8
Double bounce

0.4°

1.2°

slide11
Introduction
  • What is Distributed Computing
  • The software we use
  • VITESS Specifics
  • McStas Specifics
  • Conclusions
slide12
What do I mean by ‘Distributed Grid’?
  • A way of speeding up large, compute intensive tasks
  • Break large jobs into smaller chunks
  • Send these chunks out to (distributed) machines
  • Distributed machines do the work
  • Collate and merge the results
slide13
Spare Cycles Concept
  • Typical PC usage is about 10%
  • Most PCs not used at all after 5pm
  • Even with ‘heavily used’ (Outlook, Word, IE) PCs, the CPU is still grossly underutilised
  • Everyone wants a fast PC!
  • Can we use (“steal?”) their unused CPU cycles?
  • [email protected], World Community Grid (www.worldcommunitygrid.org)
slide15
Suitable / Unsuitable Applications
  • CPU Intensive
  • Low to moderate memory use
  • Not too much file output
  • Coarse grained
  • Command line / batch driven
  • Licensing issues?
slide16
Monte Carlo Speed-up Ideas
  • Two scenarios:
  • Single large simulation run
    • Split the neutrons into smaller numbers and execute separately
    • Merge results in some way
  • Many smaller runs
    • Parameter scan
slide17
VITESS – Splitting It
  • Easy mode of operation: fixed executables + data files
  • Executables held on server
  • Split command line into bits – divide Ncount
  • Vary the random seed
  • Create data packages
  • Upload data packages
slide18
VITESS – Running It
  • Use GUI to create instrument – Save As Command
    • “Parameter directory” set to “.”
  • Submit program parses bat file
  • Substitutes ‘V’ and ‘P’
  • Removes ‘header’ and ‘footer’
  • Creates many new bat files with different ‘--Z’s and
slide19
C:\My_GRID\VITESSE\VITESSE\build>Vitess-Submit.exe example_job example.bat req_files 20

logging in to https://bruce.nd.rl.ac.uk:18443/mgsi/rpc_soap.fcgi as tom....

Adding Vitesse dataset....

Adding Vitesse datas....

3e+007 neutrons split into 20 chunks, of -n1500000 neutrons

Total number of Vitesse 'runs' = 20

Uploading data for run #1...

Uploading data for run #2...

.

.

Uploading data for run #19...

Uploading data for run #20...

Adding Vitesse datas to system....

Adding job....

Adding jobstep....

Turning on automatic workunit generation....

Closing jobstep....

All done

Your job_id is 4878

VITESS – Running It

  • Submit program creates many bat files
slide21
VITESS – Merging It
  • Download the ‘chunks’
  • Merge Data files
    • DetectedNeutrons.dat : concatenate
    • vpipes : trajectories & count rate
  • Two classes of files
    • 1D - Values: sum & divide by num chunks-
    • - Errors: square, sum and divide
    • 2D –Sum / num of chunks
slide22
VITESS – Advantages and Problems
  • Many times faster: linear increase
  • Needs verification runs (x3)
  • Typically 11 (potentially) 30+ times faster
    • 12 hours runs in 1 hour!
  • Very large simulations reach random limits
slide23
VITESS – Some Results

176 hours

59 hours

6hrs 20mins

slide24
McStas – Splitting It
  • Different executable for every run
  • Executable must be uploaded at run time
  • Split –n into chunks
  • or run many instances (parameter scan)
  • Create data (+ executable) packages
  • Upload packages
slide25
McStas – Running It
  • Use McGui to create and compile executable
  • Create input file for Submit program
slide26
McStas – Running It
  • Large run
    • Submit program breaks up –n#####
    • Uploads new command line + data + executable
  • Parameter Scan
    • Send each run to a separate machine
slide27
McStas – Merging It
  • Many output files  Separate merge program
  • PGPLOT and Matlab implemented
  • Very similar
  • PGPLOT
    • 1D – intensities: sum and divide. Errors: square, sum and divide. Events: Sum
    • 2D – intensities: sum and divide. Errors: square, sum and divide. Events: Sum
  • Matlab
    • 1D – Same maths, different format
    • 2D – Virtually the same
    • ‘Metadata’ leave untouched
slide28
McStas – Advantages and Problems
  • Security: Do we trust users?
  • 100 times faster[?]
  • Linux version much faster than Windows [?]
  • How do we merge certain fields?
    • values = '1.44156e+006 10459.9 30748';
    • statistics = 'X0=3.5418; dX=1.52975; Y0=0.000822474; dY=1.0288;';
  • Some issue related to randomness of moderator file
slide29
Conclusions
  • Both run well under Grid MP
  • Submit & Retrieve a few hours work
  • Merge a bit more
  • Needs to merge more output formats [?]
  • Issues with very large simulations
  • More info on Grid MP at www.ud.com
slide30
Acknowledgements
  • Tom Griffin - GRID
  • Ed Abel -GRID
  • Stuart Ansell - MCNPX
  • Mark Telling - OSIRIS
  • Robert Dalgliesh - Polarization
  • Laurent Chapon - WISH
  • Judith Peters - HET
  • Heloisa Bordallo - HET
  • Geza Zsigmond -HET
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