Shared-memory multiprocessors have dominated all platforms from high-end to desktop computers. On such platforms, it is well known that the interconnect between the processors and the main memory has become a major bottleneck. The bandwidth-aware job scheduling is an effective and relatively easy-to-implement way to relieve the bandwidth contention. Previous policies understood that bandwidth saturation hurt the throughput of parallel jobs so they scheduled the jobs to let the total bandwidth requirement equal to the system peak bandwidth. However, we found that intra-quantum fine-grained bandwidth contention still happened due to a program's irregular fluctuation in memory access intensity, which is mostly ignored in previous policies. In this paper, we quantify the impact of bandwidth contention on overall performance. We found that concurrent jobs could achieve a higher memory bandwidth utilization at the expense of super-linear performance degradation. Based on such an observation, we proposed a new workload scheduling policy. Its basic idea is that interference due to bandwidth contention could be minimized when bandwidth utilization is maintained at the level of average bandwidth requirement of the workload. Our evaluation is based on both SPEC 2006 and NPB workloads. The evaluation results on randomly generated workloads show that our policy could improve the system throughput by 4.1% on average over the native OS scheduler, and up to 11.7% improvement has been observed.