Members: Shaowen Wang, Ransom Briggs, Eric Shook
This spatial interpolation application is developed by Shaowen Wang and Ransom Briggs to solve a k-nearest neighbor search problem for inverse distance weighted spatial interpolation. Wikipedia has more information about different types of interpolation and their possible uses.

• No network requirements are made on the Worker Node, the application runs without contacting any other machine

• x86 compatible CPU
• 60 MB disk per job
• 512 MB memory

• Almost any Linux distribution

• Either support the GROW VOMS server or support individual distinguished names

• Meant for reusable application files
• Mounted read-write on the Compute Element
• Mounted at the same path on Worker Nodes

• Meant for temporary data storage until staged out
• Mounted read-write on the Compute Element and Worker Nodes
• Mounted at the same path on Worker Nodes

• Run fork job to create directories in $DATA for staging in and out
• Stage application tarballs into $DATA
• Run fork job to install application from tarball
• Now the site is ready to run jobs

• Stage data into $DATA
• Run batch job with executable name and arguments
• Stage data out of $DATA
• Clean up $DATA

• Change directory to temporary dir ($WNTMP)
• Copy files out of $DATA to $WNTMP
  • Done to ease the load on the NFS server
• Run application executable
• Tar up output files and copy to $DATA
• Clean up working directory

• See OSG Best Practices for more information and other use scenarios

• Does there exist something like $APP, $DATA, and $WNTMP for PRAGMA?