  We consider the problem of scheduling multiprocessor jobs to minimize the
total completion time under the given energy budget. Each multiprocessor job
requires more than one processor at the same moment of time. Processors may
operate at variable speeds. Running a job at a slower speed is more energy
efficient, however it takes longer time and affects the performance. The
complexity of both parallel and dedicated versions of the problem is
investigated. We propose approximation algorithms for various particular cases.
In our algorithms, initially a sequence of jobs and their processing times are
calculated and then a feasible solution is constructed using list-type
scheduling rule.
