ah experiences

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Information about ah experiences

Published on January 22, 2008

Author: Bernardo

Source: authorstream.com

Experiences of Submitting UKDMC and LISA GEANT4 Jobs:  Experiences of Submitting UKDMC and LISA GEANT4 Jobs FIRST I should say thanks for the opportunity of using the growing resource of the GRID particularly for Particle Astrophysics (LISA and UKDMC) which has no direct funding to (or from) the GRIDPP It is increasingly clear we NEED use of the GRID in order to carry out accurate simulations for both LISA and Dark Matter – either to investigate signals or possible backgrounds on micro and macroscopic levels. Specifically this is processor intensive work I am a novice – only 5 weeks usage of the GRID Experiences of Submitting UKDMC and LISA GEANT4 Jobs:  Experiences of Submitting UKDMC and LISA GEANT4 Jobs Experimental configuration Dark Matter LISA Output of >100 Jobs Benefits Comments on Functionality and UI Slide3:  UKDMC Experiment Two-Phase Liquid Xenon, ZEPLIN III:  Two-Phase Liquid Xenon, ZEPLIN III ZEPLIN III, our near future detector will offer extreme levels of signal-to-background discrimination. Interpretation will only be possible with full Monte Carlo studies (a novelty for DM) Prototype Simulation: Full Lab Geometry:  Prototype Simulation: Full Lab Geometry GEANT 4:  GEANT 4 Due to the need to develop Monte Carlo simulations for Dark Matter experiments, I have become involved in the development of Geant4 – particularly exploiting the low energy, radioactivity decay and neutron extensions of the toolkit (see advanced example DMX within the release package) From basic simulations of our prototype system it is clear that greater computing power is required in order to produce high statistics and accurately model our detectors. In addition it is envisaged to develop a simulation of the underground environment, UNEX, to give accurate spectra and particle types within the experimental area. Furthermore, Imperial is also involved in LISA a gravitational wave experiment, where charging of proof masses becomes critical. To simulate the charging rate requires large number of cosmic events with rare hadronic showers resulting in residual charge One High Energy event::  One High Energy event: LXe GXe PMT mirror source Neutrons:  room elastic inelastic outside Neutrons LISA/STEP:  LISA/STEP Gravitational wave experiment STEP = test of the equivalence principle Both rely on floating proof masses with no electrical connections  prone to charging effects from cosmic rays However, charging rate is relatively low (~1 in 5000 particles) LISA Geometry and Geant4 Images:  LISA Geometry and Geant4 Images LISA Geometry and Geant4 Images:  LISA Geometry and Geant4 Images OUTPUT from Grid Running:  OUTPUT from Grid Running Over 100 jobs have been run on the grid to try and estimate the charging rate in the proof mass and test different cuts and processes within Geant4. 1.9 million events have been run in ~300 hours of CPU time The preliminary outcome is as follows: 6secs and Convergence of Charging Rate:  6secs and Convergence of Charging Rate 6secs and Convergence of Charging Rate:  6secs and Convergence of Charging Rate Initial indications of charging rate GRID JOB SUBMISSION – My Experience:  GRID JOB SUBMISSION – My Experience With the auspicious title of DataGrid User….. After running >100 jobs I have had some experience of running of jobs on the DataGrid – mostly good  However, there are a few things that if implemented would be useful, although their unavailability may just be the youthful nature of the GRID and therefore already present, at least in the design… (some of which are due to my ignorance) Things Missing, apparently (1):  Things Missing, apparently (1) Status of job  events run, near completion? Run-time Partial grab of output files  check on job: RB release 1.4 (Dave’s talk) Length of identifier – cumbersome Saving identifiers to file  ease of management of many jobs Request output to be saved to file  automatically when job completed Proxy expiration and file loss – can protect against it, but can occur File back up – prevent losses when things crash, and therefore reduce number of repeat jobs Job clearing and file clearing – particularly if job crashes/disappears Things Missing, apparently (2):  Things Missing, apparently (2) Diagnostics  memory usage (single event leaks) – max/average  CPU Time – can access at runtime with Globus  Disc access = efficiency of local staging, etc… Forced killing of jobs? Clearing of files or keeping of partial files – cancelling jobs loses everything Run time limit/Disk Usage/Memory Usage  in case of problems/diagnostic? Node limit  Batch script to run jobs sequentially without clogging up the farm – from proxy-request? Shared Disc for data? – Input files are ~500 Mbytes and copied 32 times… Things Missing, apparently (3):  Things Missing, apparently (3) What decides resource management? Queued at IC or at RAL – speed of processor? Disc transfer time? Jobs cleared before get output (RB dies) Housekeeping/cleaning of tmp files Script to save output to your account without 3rd party access? Prone to abuse? Tidy up – clear up dangling jobs and tmp files for a given user Things Missing, apparently (4):  Things Missing, apparently (4) Reliability? Compilers and inter-site homogeneity  IC = egcs 1.1.2 whereas RAL = gcc 2.95.2 Level of resource available and average usage/users/CPU power – stage requests, think about optimising problem, look elsewhere More nodes with my VO would naturally be helpful IC = 16 nodes (user limit 14) RAL = 8 nodes elsewhere? Apologies if some of these comments are due to me… Conclusions:  Conclusions The GRID is clearly a very powerful resource that has enabled me to run a lot of jobs in a very short space of time It is clear that Dark Matter and Spacecraft charging studies at this time NEED the GRID - particularly for accurate Monte Carlo simulations of future detectors (ZEPLIN III) and Spacecraft charging rates (LISA/STEP) In running jobs some things could perhaps be more elegant/convenient to use, but on the whole it is not too difficult

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