RTDT: A static QoS manager, RT scheduling, HW/SW partitioning CAD tool
Microelectronics Journal
Stochastic robustness metric and its use for static resource allocations
Journal of Parallel and Distributed Computing
Cache modeling in probabilistic execution time analysis
Proceedings of the 45th annual Design Automation Conference
Probabilistic modeling of data cache behavior
EMSOFT '09 Proceedings of the seventh ACM international conference on Embedded software
Failure-dependent execution time analysis
Proceedings of the joint ACM SIGSOFT conference -- QoSA and ACM SIGSOFT symposium -- ISARCS on Quality of software architectures -- QoSA and architecting critical systems -- ISARCS
Resource allocation robustness in multi-core embedded systems with inaccurate information
Journal of Systems Architecture: the EUROMICRO Journal
MMB'12/DFT'12 Proceedings of the 16th international GI/ITG conference on Measurement, Modelling, and Evaluation of Computing Systems and Dependability and Fault Tolerance
Static analysis of the worst-case memory performance for irregular codes with indirections
ACM Transactions on Architecture and Code Optimization (TACO)
A cache design for probabilistically analysable real-time systems
Proceedings of the Conference on Design, Automation and Test in Europe
Challenges and new trends in probabilistic timing analysis
DATE '12 Proceedings of the Conference on Design, Automation and Test in Europe
Maximizing stochastic robustness of static resource allocations in a periodic sensor driven cluster
Future Generation Computer Systems
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Most previous research done in probabilistic schedulabilityanalysis assumes a known distribution of executiontimes for each task of a real-time application. This is howevernot trivial to determine it with a high level of confidence. Methods based on measurements are often biased since not in general exhaustive on all the possible executionpaths, whereas methods based on static analysis aremostly Worst-Case Execution Time 驴 WCET 驴 oriented. Usingstatic analysis, this work proposes a method to obtainprobabilistic distributions of execution times. It assumesthat the given real time application is divided into multipletasks, whose source code is known. Ignoring in this paperhardware considerations and based only on the sourcecode of the tasks, the proposed technique allows designersto associate to any execution path an execution time and aprobability to go through this path. A source code exampleis presented to illustrate the method.