Mapping and Synchronizing Streaming Applications on Cell Processors

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Abstract

Developing streaming applications on heterogenous multi-processor architectures like the Cell is difficult. Currently, application developers need to know about hardware details to deal with issues like scheduling, memory management and communication/synchronization. Worse, with multiple alternatives for communication available, developers spend significant time picking the most appropriate one. A poor choice often results in bad performance. With Cell-Space, we shield users from hardware details without compromising performance. Its runtime is based on an evaluation of the different communication primitives. In Cell-Space, developers specify a streaming application as a data flow graph of interacting components. Both task- and data-parallelism are easily expressed and advanced features such as dynamic reconfiguration are fully supported. Beneath a simple interface we include a slew of optimizations not present in other Cell run time environments. We demonstrate the impact of these optimizations and show that Cell-Space applications can efficiently exploit the resources offered by the Cell.