Jobs on high-performance computing systems are deployed mostly with the sole goal of minimizing completion times. This performance demand has been satisfied without paying much attention to power/energy consumption. Consequently, that has become a major concern in high-performance computing systems. In this paper, we address the problem of scheduling precedence-constrained parallel applications on such systems—specifically with heterogeneous resources—accounting for both application completion time and energy consumption. Our scheduling algorithm adopts dynamic voltage scaling (DVS) to minimize energy consumption. DVS can be used with a number of recent commodity processors that are enabled to operate in different voltage supply levels at the expense of sacrificing clock frequencies. In the context of scheduling, this multiple voltage facility implies that there is a trade-off between the quality of schedules and energy consumption. Our algorithm effectively balances these two performance goals using a novel objective function, which takes into account both goals; this claim is verified by the results obtained from our extensive comparative evaluation study.