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Advanced Grid Computing with BatchMake: Efficient Data Processing and Algorithm Design

Explore the power of BatchMake for grid computing, data processing, and algorithm implementation. Learn about BatchMake origins, workflow, Condor usage, and reporting capabilities. Enhance your skills in using BatchMake efficiently for various applications.

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Advanced Grid Computing with BatchMake: Efficient Data Processing and Algorithm Design

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  1. Grid Computing with BatchMake Julien JomierKitware Inc.

  2. Motivation Data Processing Reports & Analysis Algorithm Design & Implementation

  3. Outline • Introduction to BatchMake • Grid Computing with BatchMake • Reporting with the BatchBoards • BatchMake with Slicer • Future plans

  4. BatchMake Origins • Started in 2004 at UNC (CADDLab) • A2D2 from NLM • Kitware funds: KWGrid • BW-NAC: Batchboards • Na-Mic • STTR Kitware-UNC (Styner)

  5. Introduction to BatchMake • Batch script generator • Process of large number of datasets • Common Language (CMake-like) • Generation for: - Shell script - Condor - KWGrid • Run locally or on grid • Cross platform command line and GUI tool • C++ with ITK and FTLK

  6. BatchMake Workflow CommandLine Executable Local Execution ApplicationWrapper Shell Script BatchMake KWGrid Script Script Condor Script

  7. Application Wrapper • Describe command line arguments- Manually (GUI)- Automatically using itkMetaCommand • Currently using internal XML format • .bmm files (BatchMake Modules) • Switching to Slicer’s ModuleDescriptionParser- importing Slicer Module automatically

  8. MetaCommand • C++ class for command line parsing • Output recognized by - BatchMake (-vxml) - Slicer (--xml) • command.SetOption("compileScript","c",false,"Compile a script"); command.AddOptionField("compileScript","filename",MetaCommand::STRING,true); • http://www.itk.org/Wiki/MetaIO • Insight/Utilities/MetaIO

  9. Example Script 1 -SetApp(imSeg @ImageSegmentation) 2 -SetAppOption(imSeg.threshold 10) 3 - 4 -Set(workdir '/BatchMake/Demo/Ellipse_Images') 5 -ListFileInDir(files ${workdir} '*.mha') 6 - 7 -Foreach(file ${files}) • - Set(filename '${workdir}/${file}') • - Set(outfile '${workdir}/out_${file}') 10-SetAppOption(imSeg.inputFilename ${filename}) 11-SetAppOption(imSeg.outputFilename ${outfile}) 12- Run(output ${imSeg}) 13-EndForeach(file)

  10. Condor • Specialized workload management system for compute-intensive jobs • Created by UW-Madison • 15 Years of development • Provides job queueing mechanism, scheduling policy, priority scheme, resource monitoring, and resource management. • Unix and Windows

  11. Condor Universes • Standard Universe (checkpoint) • Vanilla • Parallel Virtual Machine • MPI • Globus • Java (JVM) • Scheduler (no matching)

  12. Condor Example Script Universe = vanilla Executable = EMSegmenter Arguments = ‘brain.mha segmentation.mha --brain’ Output = emsegmentation.out Error = emsegmentation.error Log = emsegmentation.log Requirements = (OpSys =="LINUX" && Arch=="INTEL") Should_transfer_files = YES When_to_transfer_output = ON_EXIT_OR_EVICT Transfer_input_files = brain.mha Queue

  13. Condor Pool Condor Workflow (Vanilla) Central Manager Central Manager Unavailable Execute Machine Dispatch to Central manager = Unavailable Submit job Submit Machine Issue job Busy Workstation Available Execute Machine Central Manager Dispatch to Central manager = Available Execute Machines Idle Workstation Push out job to machine

  14. ClassAd Job ClassAd Match Condor Job Submission Workflow Submit Machine Central Manager Execute Machine 1 Collector Master 3 Master 2 4 Scheduler Negociator 5 Starter

  15. BatchMake Condor Generation

  16. BatchMake Condor Generation • Application/Module description - Inputs/Outputs - Data to transfer to nodes • Loop unrolling • Scope definition • Directed Acyclic Graph (DAG) • Ensure order of execution of jobs

  17. Monitoring Condor Jobs • Flock Monitor (Condor) • Condor Watcher (FLTK) • Condor Web Watcher (Ajax/PHP)

  18. Condor Summary • Pros:- Well supported- (Fairly) easy installation- Complete resources management • Cons:- Script can be complicated- Jobs don’t start right away- Hard to debug

  19. Reporting with BatchMake Developers check-in code CVS/SVN CTest/DART compilessource code Developers review results + MIDASXNat BatchMake validateson datasets Results posted on web(i.e., the batchboard)

  20. Reporting with BatchMake

  21. BatchMake Server • PHP Scripts with MySQL database • Simple C++ HTTP post • Statistical Analysis (Factor analysis: Taguchi). • Dashboard creation capability • User management

  22. BatchBoard Script DashboardHost(http://www.insight-journal.org/batchmake) DashboardUser(‘Julien Jomier') DashboardKey('FKH3BPM1y11VXsMf') CreateExperiment(exp ‘Liver Project‘ ‘Segmentation Experiment' '') CreateMethod(Meth exp 'Registration' 'Register a T1 with noise to a translated T1') AddMethodInput(noiseImageName Meth 'Fixed Image') Set(fixedSlice '${fixedImage}Slice.png') ExtractSlice('${fixedImage}' '${fixedSlice}' 2 1) AddMethodInput(fixedSlice Meth 'Fixed Slice with noise' png) DashboardSend(Meth)

  23. BatchMake and Slicer • BatchMake now distributed with Slicer • Some modules can be run on a collection of data- EMSegment- GaussianBlur • Generic way to run moduleson a collection

  24. BatchMake and MIDAS • STTR Kitware/UNC Martin Styner

  25. Future • Improve packaging • Improve documentation • Improve integration with Slicer • BatchMake and Xnat (discussion)

  26. References • www.batchmake.org • www.insight-journal.org/batchmake

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