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PPOPP '95 Proceedings of the fifth ACM SIGPLAN symposium on Principles and practice of parallel programming
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The performance of work stealing in multiprogrammed environments (extended abstract)
SIGMETRICS '98/PERFORMANCE '98 Proceedings of the 1998 ACM SIGMETRICS joint international conference on Measurement and modeling of computer systems
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ACM Computing Surveys (CSUR)
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IEEE Transactions on Parallel and Distributed Systems
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ICPP '02 Proceedings of the 2001 International Conference on Parallel Processing
StreamIt: A Language for Streaming Applications
CC '02 Proceedings of the 11th International Conference on Compiler Construction
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Journal of Parallel and Distributed Computing
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SFCS '94 Proceedings of the 35th Annual Symposium on Foundations of Computer Science
Patterns for parallel programming
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Introduction to Algorithms, Third Edition
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XJava: Exploiting Parallelism with Object-Oriented Stream Programming
Euro-Par '09 Proceedings of the 15th International Euro-Par Conference on Parallel Processing
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PACT '09 Proceedings of the 2009 18th International Conference on Parallel Architectures and Compilation Techniques
Proceedings of the Conference on High Performance Computing Networking, Storage and Analysis
Performance Evaluation of Work Stealing for Streaming Applications
OPODIS '09 Proceedings of the 13th International Conference on Principles of Distributed Systems
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PDCAT '09 Proceedings of the 2009 International Conference on Parallel and Distributed Computing, Applications and Technologies
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ACM Transactions on Architecture and Code Optimization (TACO)
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Work stealing has proven to be an efficient technique for scheduling parallel computations. In its basic form, however, work stealing is not suitable for real-time applications, since the latency of a task is hardly predictable. In this paper, we propose a number of variants and extensions of work stealing suitable for stream processing applications. Such applications are frequently encountered in embedded systems, which often have to obey real-time constraints. Moreover, we give bounds on the maximum latency for certain stealing strategies. Our experimental results show a significant reduction of the latency using these strategies.