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2013 IEEE 19th International Conference on Embedded and Real-Time Computing Systems and Applications (2005)
Hong Kong, China
Aug. 17, 2005 to Aug. 19, 2005
ISSN: 1533-2306
ISBN: 0-7695-2346-3
pp: 416-421
James H. Anderson , University of North Carolina at Chapel Hill
Nathan Fisher , University of North Carolina at Chapel Hill
Sanjoy Baruah , University of North Carolina at Chapel Hill
ABSTRACT
Most prior theoretical research on partitioning algorithms for real-time multiprocessor platforms has focused on ensuring that the cumulative computing requirements of the tasks assigned to each processor does not exceed the processor?s processing power. However, many multiprocessor platforms have only limited amounts of local per-processor memory; if the memory limitation of a processor is not respected, thrashing between "main" memory and the processor?s local memory may occur during run-time and may result in performance degradation. We formalize the problem of task partitioning in a manner that is cognizant of both memory and processing capacity constraints as the memory constrained multiprocessor partitioning problem, prove that this problem is intractable, and present efficient algorithms for solving it under certain — well-defined — conditions.
INDEX TERMS
Multiprocessor systems; Partitioned scheduling; Memory-constrained systems; Utilization-based schedulability tests
CITATION
James H. Anderson, Nathan Fisher, Sanjoy Baruah, "Task Partitioning upon Memory-Constrained Multiprocessors", 2013 IEEE 19th International Conference on Embedded and Real-Time Computing Systems and Applications, vol. 00, no. , pp. 416-421, 2005, doi:10.1109/RTCSA.2005.97
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