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As the number of multimedia services grows, so does the computational demands on multimedia data processing. New multi-core hardware architectures provide the required re-sources, however, parallel, distributed applications are much harder to write than sequential programs. Large processing frameworks like Google's MapReduce and Microsoft's Dryad are steps in the right direction, but they are targeted towards batch processing. As such, the authors present P2G, which is a framework, designed to integrate concepts from modern batch processing frameworks into the world of real-time multimedia processing. With P2G they seek to scale transparently with the available resources (following the cloud computing paradigm) and to support heterogeneous computing resources, such as GPU processing cores.
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