ACM Transactions on Programming Languages and Systems (TOPLAS)
International Journal of Computer Vision
UC: a set-based language for data-parallel programming
Journal of Parallel and Distributed Computing
Optimal latency-throughput tradeoffs for data parallel pipelines
Proceedings of the eighth annual ACM symposium on Parallel algorithms and architectures
A library-based approach to task parallelism in a data-parallel language
Journal of Parallel and Distributed Computing
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Models and scheduling algorithms for mixed data and task parallel programs
Journal of Parallel and Distributed Computing - Special issue on dynamic load balancing
Space-time memory: a parallel programming abstraction for interactive multimedia applications
Proceedings of the seventh ACM SIGPLAN symposium on Principles and practice of parallel programming
Computer Vision and Human-Computer Interaction
Computer Vision and Human-Computer Interaction
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
A Virtual Mirror Interface Using Real-Time Robust Face Tracking
FG '98 Proceedings of the 3rd. International Conference on Face & Gesture Recognition
Scheduling constrained dynamic applications on clusters
SC '99 Proceedings of the 1999 ACM/IEEE conference on Supercomputing
Capsules: Expressing Composable Computations in a Parallel Programming Model
Languages and Compilers for Parallel Computing
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There is an emerging class of real-time interactive applications 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 computationally demanding: It employs vision and speech sensing and an animated graphical talking face for output. The computational demands of an interactive kiosk can vary widely with the number of customers and the state of the interaction. Unfortunately this makes it difficult to apply current techniques 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 application. 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 Stampede, a cluster programming system developed at the Cambridge Research Laboratory.