At least on the experimental LHC side, we process/analyse each event independently from every other event, so it's an embarrassingly parallel workload. All we do is split our input dataset up into N files, run N jobs, combine the N outputs.

Because we have so much data (of the order of 25+ PB of raw data per year; it actually balloons to much more than this due to copies in many slightly different formats) and so many users (several thousand physicists on LHC experiments) that's why we have hundreds of GRID sites across the world. The scheduler sends your jobs to sites where the data is located. The output can then be transferred back via various academic/research internet networks.

HEP also tends to invent many of its own 'large-scale computing' solutions. For example most sites tend to use Condor[1] as the batch system, dcache[2] as the distributed storage system, XRootD[3] as the file access protocol, GridFTP[4] as the file transfer protocol. I know there are some sites that use Lustre but it's pretty uncommon.

[1] http://research.cs.wisc.edu/htcondor/ [2] http://www.dcache.org/ [3] http://xrootd.slac.stanford.edu/ [4] http://www.globus.org/toolkit/docs/latest-stable/gridftp/