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Scalable Parallel Feature Extraction and Tracking for Large Time-varying 3D Volume Data

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PFET -- Parallel Feature Extraction and Tracking

====

Dependency

  1. open-mpi 1.7.x or above
  2. a modern compiler with C++11 support

Installation

PFET uses cmake to build the base system. After downloading the source code, create a new build directory inside the source directory and run:

cmake ../CMakeFiles.txt

or

ccmake ..

if you prefer to use the GUI.

After configuration, simply run

make

to generate the executable file.

Basic Usage

Assume the MPI libraries are properly installed, use the following script in to run the program in parallel.

mpirun -np X ./<program> <gridDim.x> <gridDim.y> <gridDim.z> ../<config_file_name>

For example:

mpirun -np 8 ./pfet 2 2 2 ../ball.config

will divide the domain into 8 (2 x 2 x 2) subdomains and handle them in parallel.

Configuration File

The last argument of the above script point to a text based configuration file, in which detailed information about the data can be configured.

Parameter Type Description Example
start int Starting index of the file sequence 0
end int Ending index of a file sequence 4
prefix string Prefix of the file name "ball_"
suffix string Suffix of the file name "raw"
path string Path to the data files directory "path/to/dir"
tfPath string Path to transfer function setting "path/to/file"
timeFormat string String formatting for int->string "%3d"
volumeDim list(int) Volume dimension (128, 128, 128)

For example, the following data files will be read in with the above settings:

path/to/file/ball_000.raw
path/to/file/ball_001.raw
path/to/file/ball_002.raw
path/to/file/ball_003.raw
path/to/file/ball_004.raw

Related Publication

Please consider citing the following reference if you find the code helpful.

Yang Wang, Hongfeng Yu, Kwan-Liu Ma. Scalable Parallel Feature Extraction and Tracking for Large Time-varying 3D Volume Data. In Proceedings of EGPGV 2013, pages 17-24.

BibTex
@article{wang2013scalable,
  title={Scalable Parallel Feature Extraction and Tracking for Large Time-varying 3D Volume Data},
  author={Wang, Yang and Yu, Hongfeng and Ma, Kwan-Liu},
  booktitle={Eurographics Symposium on Parallel Graphics and Visualization},
  pages={17--24},
  year={2013},
  organization={The Eurographics Association}
}

Acknowledgments

This software is made available by the VIDI research group at the University of California at Davis through a project sponsored by the U.S. Department of Energy with grants DE-FC02-06ER25777, DE-CS0005334, and DE-FC02-2ER26072.

License

MIT

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Scalable Parallel Feature Extraction and Tracking for Large Time-varying 3D Volume Data

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