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Dynamic load-balancing of StreamIt cluster computations

This thesis discusses the design and implementation of a dynamic load-balancing mechanism for computationally distributed programs running on a cluster written in the StreamIt programming language. StreamIt is useful for streaming data applications such as MPEG codecs. The structure of the language carries a lot of static information, such as data rates and computational hierarchy, and therefore lends itself well to parallelization. This work details a simulator for StreamIt cluster computations used to measure metrics such as throughput. Built on top of this simulation is an agent-based market used for load balancing the computation at StreamIt checkpoints to adapt to exogenously changing loads on the nodes of the cluster. Thesis Supervisor: Una-May O’Reilly Title: Principal Research Scientist