  We present the implementation of a batch job scheduler designed for
single-point management of distributed tasks on a multi-node compute farm. The
scheduler uses the notion of a meta-job to launch large computing tasks
simultaneously on many nodes from a single user command. Job scheduling on
specific computing nodes is predicated on the availability of user specified
data files co-located with the CPUs where the analysis is meant to take place.
Large I/O intensive data analyses may thus be efficiently conducted on multiple
CPUs without the limitations implied by finite LAN or WAN bandwidths. Although
this Scheduler was developed specifically for the STAR Collaboration at
Brookhaven National Laboratory, its design is sufficiently general, it can be
adapted to virtually any other data analysis tasks carried out by large
scientific collaborations.
