Grid is a non-dedicated and dynamic computing environment. Consequently, different programs have to compete with each other for the same resources, and resource availability varies over time. That causes the performance of user programs to degrade and to become unpredictable. For resolving this problem, we propose a multi-layer resource reconfiguration framework for grid computing. As named, this framework adopts different resource reconfiguration mechanisms for different workloads of resources. We have implemented this framework on a grid-enabled DSM system called Teamster-G. Our experimental result shows that our proposed framework allows Teamster-G not only to fully utilize abundant CPU cycles but also to minimize resource contention between the jobs of resource consumers and those of resource providers. As a result, the job throughput of Teamster-G is effectively increased.