Mittermayr, R., & Blieberger, J. (2012). Timing Analysis of Concurrent Programs. In T. Vardanega (Ed.), Proc. 12th International Workshop on Worst-Case Execution Time Analysis (pp. 59–68). Schloss Dagstuhl - Leibniz-Zentrum für Informatik GmbH, Dagstuhl Publishing. https://doi.org/10.4230/OASIcs.WCET.2012.59
Proc. 12th International Workshop on Worst-Case Execution Time Analysis
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ISBN:
978-3-939897-41-5
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Date (published):
2012
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Event name:
12th International Workshop on Worst-Case Execution Time Analysis
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Event date:
10-Jul-2012
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Event place:
Pisa, Italy, EU
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Number of Pages:
10
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Publisher:
Schloss Dagstuhl - Leibniz-Zentrum für Informatik GmbH, Dagstuhl Publishing, Vol. 23, Saarbrücken/Wadern
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Publisher:
Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik, Dagstuhl
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Peer reviewed:
Yes
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Keywords:
Worst-case execution time analysis (WCET); Concurrency; Thread Syn- chronization; Kronecker Algebra; Program Analysis
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Abstract:
Worst-case execution time analysis of multi-threaded software is still a challenge. This comes mainly from the fact that the number of thread interleavings grows exponentially in the number of threads and that synchronization has to be taken into account. In particular, a suitable graph based model has been missing. The idea that thread interleavings can be studied with a matrix calculus is a novel approach in this research area. Our sparse matrix representations of the program are manipulated using Kronecker algebra. The resulting graph represents the multi-threaded program and plays a similar role for concurrent systems as control flow graphs do for sequential programs. Thus a suitable graph model for timing analysis of multi-threaded software has been set up. Due to synchronization it turns out that often only very small parts of the resulting graph are actually needed, whereas the rest is unreachable. A lazy implementation of the matrix operations ensures that the unreachable parts are never calculated. This speeds up processing significantly and shows that our approach is very promising.
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Research Areas:
Computer Engineering and Software-Intensive Systems: 100%