  The aggregate power use of computing hardware is an important cost factor in
scientific cluster and distributed computing systems. The Worldwide LHC
Computing Grid (WLCG) is a major example of such a distributed computing
system, used primarily for high throughput computing (HTC) applications. It has
a computing capacity and power consumption rivaling that of the largest
supercomputers. The computing capacity required from this system is also
expected to grow over the next decade. Optimizing the power utilization and
cost of such systems is thus of great interest.
  A number of trends currently underway will provide new opportunities for
power-aware optimizations. We discuss how power-aware software applications and
scheduling might be used to reduce power consumption, both as autonomous
entities and as part of a (globally) distributed system. As concrete examples
of computing centers we provide information on the large HEP-focused Tier-1 at
FNAL, and the Tigress High Performance Computing Center at Princeton
University, which provides HPC resources in a university context.
