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A transparent distributed shared memory (DSM) system must achieve complete transparency in data distribution, workload distribution, and reconfiguration respectively. The transparency of data distribution allows programmers to be able to access and allocate shared data using the same user interface as is used in shared-memory systems. The transparency of workload distribution and reconfiguration can optimize the parallelism at both the user-level and the kernel-level, and also improve the efficiency of run-time reconfiguration. In this paper, a transparent DSM system referred to as Teamster is proposed and is implemented for clustered symmetric multiprocessors. With the transparency provided by Teamster, programmers can exploit all the computing power of the clustered SMP nodes in a transparent way as they do in single SMP computer. Compared with the results of previous researches, Teamster can realize the transparency of cluster computing and obtain satisfactory system performance.

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.

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