Performance and power are two primary design constraints in today's
high-end computing systems. Because of the inherent dependency
between performance and power, reducing power consumption without
impacting system performance is a challenge for the HPC community.
In this paper, we present a run-time system as well as its
underlying performance model for performance-directed, power-aware
cluster computing. Experimental results based on physical
measurements show that NPB benchmarks benefit up to 36% energy
saving and 21% performance gain. On average, our run-time system
leads to 10.7% energy saving with 1.2% performance loss over 9 NPB
benchmarks, and is 1.59X
 improvement in ED2P than CPUSPEED. We also show that our system is
performance directed in the sense that the performance loss for most
application is within the user specified limit. We attribute the
promising results to the accurate performance modeling and
prediction, and effective performance control techniques.