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UTAM Reproducible Research Package and C++ Seismic Library

UTAM Reproducible Research Package and C++ Seismic Library. Samuel Brown November 5, 2008. Outline . URRP: UTAM Reproducible Research Package UCSL: UTAM C++ Seismic Library. URRP Motivation.

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UTAM Reproducible Research Package and C++ Seismic Library

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  1. UTAM Reproducible Research Package and C++ Seismic Library Samuel Brown November 5, 2008

  2. Outline • URRP: UTAM Reproducible Research Package • UCSL: UTAM C++ Seismic Library

  3. URRP Motivation • Create a centralized, version-controlled, software release with regression tests, promoting code reuse by students and sponsors. • Provide the ability to reproduce results from all UTAM reports in a uniform and comprehensible manner.

  4. URRP Distribution • URRP is available through a secure subversion repository. • Reproducible scripts have an interface for downloading images and intermediate results through sftp.

  5. Firewall? No svn, no sftp? • Compressed repository snapshots for annual and midyear releases will be available on the UTAM website. • Compressed images and intermediate results reside in a directory tree on the UTAM website, which mirrors the URRP reports directory.

  6. Source Code/Compilation • bash and csh scripts for environment setup. • Top-level SConstruct file with autoconf functionality for C/C++/F90 programs. • Matlab library.

  7. Reproducibility • Report directories contain: • paper.tex – latex report • run.py - python script • other scripts, directories, etc.

  8. run.py • run.py: uniform interface for reproducing results • python only, does not use scons • imperative, not declarative • generates and runs shell scripts interactively • simple mechanisms for downloading data and controlling computation with sources and targets • can interface with PBS

  9. run.py • run.py consists of a number of individual processes • A ‘process’ is a call to the URRP python function process( ) • 1 process for downloading images • 1 process for compiling latex paper • 1 or more processed for reproducing results or downloading intermediate results

  10. A Simple Process Process( cmds=[’matlab –nosplash –nodisplay < xcorr.m’] )

  11. A More Involved Process Process( cmds=[‘ ucsl_fdac par=mod1.par’], sources=[ ‘vp.rsf’, ‘recv_coord.txt’], targets=[ ‘csg1.su’], docmds=1, wdir=‘./csgs’, bdir=‘./batch’, sdir=‘./mod’, pbs=1, nodes=4, ppn=2, walltime=0:30:00 ) )

  12. Outline • URRP: UTAM Reproducible Research Package • UCSL: UTAM C++ Seismic Library

  13. UCSL Motivation • Provide library for rapid development of flexible, robust, high-performance research codes. • Find an appropriate balance between imperative and object-oriented programming. • Provide a high level of abstraction to enable performance and flexibility, ie task-specific file objects with optional MPI I/O.

  14. Applications • Development initially driven by: • Flexible 2D/3D modeling/RTM. • Ray tracing and interferometric imaging of earthquake data.

  15. Forward Modeling – PML • Problem: • When implementing PMLs, there are up to 26 regions requiring a different combination of fields/damping. • To get the best result, all valid regions should be implemented, with full ghost region communication. • For simplicity and performance in the FD kernel, PML regions should reside in separate volumes. • This greatly complicates domain decomposition and communications.

  16. cart_decomp • C++ domain decomposition object. • Computes balanced domain decomposition distributed along any combination of axes using a boundary condition cost function. • Uses MPI topologies. • Builds arrays of subdomain volumes for each PE. • FD application only has to ask for as many volume arrays as are necessary for a given implementation.

  17. cart_halo • C++ ghost region communication object. • Each subdomain group requiring ghost region communication creates a halo object. For 2nd order time acoustic modeling, the subdomain group would be a 2 x nsubdomain volume array. • cart_halo handles all communication between local and remote subdomains with two functions: • start_update(int tslice, int half) • finish_update() • Ability to overlap communication and computation with option to split subdomains along the z axis.

  18. Flexible Implementations • Source and receiver groups are also abstracted as objects. • Implementing a new parallel modeling code is simply a matter of: • Providing kernels for interior and boundary regions. • Providing a time-stepping loop. • Writing a small amount of initialization code.

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