Integrated task and data parallel support for dynamic applications

摘要

There is an emerging class of real-time interactive applica- tions that require the dynamic integration of task and data parallelism. An example is the Smart Kiosk, a free-standing computer device that provides information and entertainment to people in public spaces. The kiosk interface is computa- tionally demanding. It employs vision and speech sensing and an animated graphical talking face for output. The com- putational demands of an interactive kiosk can vary widely with the mimber of customers and the state of the interaction. Unfortunately this makes it difficult to apply current tech- niques for integrated task and data parallel computing, which can produce optimal decompositions for static problems. Using experimental results from a color-based people tracking module, we demonstrate the existence of a small number of distinct operating regimes in the kiosk applica- tion. We refer to this type of program behavior as constrained dynamism. An application exhibiting constrained dynamism can execute efficiently by dynamically switching among a small number of statically determined fixed data parallel strategies. We present a novel framework for integrating task and data parallelism for applications that exhibit constrained dynamism. Our solution has been implemented using Stam- pede, a cluster programming system developed at the Cam- bridge Research Laboratory.