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IPDPS '05 Proceedings of the 19th IEEE International Parallel and Distributed Processing Symposium (IPDPS'05) - Papers - Volume 01
Distributed Garbage Collection Algorithms for Timestamped Data
IEEE Transactions on Parallel and Distributed Systems
Supporting dynamic migration in tightly coupled grid applications
Proceedings of the 2006 ACM/IEEE conference on Supercomputing
Capsules: Expressing Composable Computations in a Parallel Programming Model
Languages and Compilers for Parallel Computing
SLIPstream: scalable low-latency interactive perception on streaming data
Proceedings of the 18th international workshop on Network and operating systems support for digital audio and video
Exploiting multi-level parallelism for low-latency activity recognition in streaming video
MMSys '10 Proceedings of the first annual ACM SIGMM conference on Multimedia systems
Supporting self-adaptation in streaming data mining applications
IPDPS'06 Proceedings of the 20th international conference on Parallel and distributed processing
A platform for monitoring aspects of human presence in real-time
ISVC'10 Proceedings of the 6th international conference on Advances in visual computing - Volume Part II
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Emerging application domains such as interactive vision, animation, and multimedia collaboration display dynamic scalable parallelism and high-computational requirements, making them good candidates for executing on parallel architectures such as SMPs and clusters of SMPs. Stampede is a programming system that has many of the needed functionalities such as high-level data sharing, dynamic cluster-wide threads and their synchronization, support for task and data parallelism, handling of time-sequenced data items, and automatic buffer management. We present an overview of Stampede, the primary data abstractions, the algorithmic basis of garbage collection, and the issues in implementing these abstractions on a cluster of SMPs. We also present a set of micromeasurements along with two multimedia applications implemented on top of Stampede, through which we demonstrate the low overhead of this runtime and that it is suitable for the streaming multimedia applications.