In this thesis, we consider solving job scheduling problems on the CREW PRAM model. We show how to adapt Cole's pipeline merge technique to yield several efficient parallel algorithms for a number of job scheduling problems and one optimal parallel algorithm for the following job scheduling problem: Given a set of n jobs defined by release times, deadlines and processing times, find a schedule that minimizes the maximum lateness of the jobs and allows preemption when the jobs are scheduled to run on one machine. In addition, we present the first NC algorithm for the following job scheduling problem: Given a set of n jobs defined by release times, deadlines and unit processing times, determine if there is a schedule of jobs on one machine, and calculate the schedule if it exists. We identify the notion of a canonical schedule, which is the type of schedule our algorithm computes if there is a schedule. Our algorithm runs in O((log $n)\sp{2}$) time and uses O($n\sp{2}k\sp{2}$) processors, where k is the minimum number of distinct offsets of release times or deadlines.
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