Caches in Embedded Systems improve average case performance, but they are a source of unpredictability, especially in the worst case software timing analysis with the consideration of data caches. This is a critical problem in real-time systems, where tight Worst Case Execution Time (WCET) is required for their schedulability analysis. Few works have studied data cache impacts on the WCET of programs, but only for programs with no input-dependent data accesses. To provide an efficient and accurate analysis for input-dependent data accesses, we develop classified cache architecture and a WCET framework for the architecture. Our work classifies predictable and unpredictable accesses, then allocates them into predictable caches and unpredictable caches accordingly, and uses CME (Cache Miss Equations) and our reuse-distance-based algorithm for their timing analysis respectively. Compared with simulation, our analysis framework produces a very good WCET tightness, and our architecture creates almost no hardware overhead or performance degradation. In addition, we examine NP-completeness of WCET analysis. We also explore data allocation techniques to improve system performance.
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After Bachelor in Computer Science from NEU, I did my Master in Computer Engineering from National University of Singapore. During which,I went to ETH Zurich to conduct research in distributed computing. After my Master, I worked at Motorola and then Gemalto as Software Engineer in Singapore.Now I work at Motorola Mobility in Chicago.
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Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Caches in Embedded Systems improve average case performance, but they are a source of unpredictability, especially in the worst case software timing analysis with the consideration of data caches. This is a critical problem in real-time systems, where tight Worst Case Execution Time (WCET) is required for their schedulability analysis. Few works have studied data cache impacts on the WCET of programs, but only for programs with no input-dependent data accesses. To provide an efficient and accurate analysis for input-dependent data accesses, we develop classified cache architecture and a WCET framework for the architecture. Our work classifies predictable and unpredictable accesses, then allocates them into predictable caches and unpredictable caches accordingly, and uses CME (Cache Miss Equations) and our reuse-distance-based algorithm for their timing analysis respectively. Compared with simulation, our analysis framework produces a very good WCET tightness, and our architecture creates almost no hardware overhead or performance degradation. In addition, we examine NP-completeness of WCET analysis. We also explore data allocation techniques to improve system performance. 116 pp. Englisch. Bestandsnummer des Verkäufers 9783844384703
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Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Li YanhuiAfter Bachelor in Computer Science from NEU, I did my Master in Computer Engineering from National University of Singapore. During which,I went to ETH Zurich to conduct research in distributed computing. After my Master, I w. Bestandsnummer des Verkäufers 5475991
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Taschenbuch. Zustand: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Caches in Embedded Systems improve average case performance, but they are a source of unpredictability, especially in the worst case software timing analysis with the consideration of data caches. This is a critical problem in real-time systems, where tight Worst Case Execution Time (WCET) is required for their schedulability analysis. Few works have studied data cache impacts on the WCET of programs, but only for programs with no input-dependent data accesses. To provide an efficient and accurate analysis for input-dependent data accesses, we develop classified cache architecture and a WCET framework for the architecture. Our work classifies predictable and unpredictable accesses, then allocates them into predictable caches and unpredictable caches accordingly, and uses CME (Cache Miss Equations) and our reuse-distance-based algorithm for their timing analysis respectively. Compared with simulation, our analysis framework produces a very good WCET tightness, and our architecture creates almost no hardware overhead or performance degradation. In addition, we examine NP-completeness of WCET analysis. We also explore data allocation techniques to improve system performance.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 116 pp. Englisch. Bestandsnummer des Verkäufers 9783844384703
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Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Caches in Embedded Systems improve average case performance, but they are a source of unpredictability, especially in the worst case software timing analysis with the consideration of data caches. This is a critical problem in real-time systems, where tight Worst Case Execution Time (WCET) is required for their schedulability analysis. Few works have studied data cache impacts on the WCET of programs, but only for programs with no input-dependent data accesses. To provide an efficient and accurate analysis for input-dependent data accesses, we develop classified cache architecture and a WCET framework for the architecture. Our work classifies predictable and unpredictable accesses, then allocates them into predictable caches and unpredictable caches accordingly, and uses CME (Cache Miss Equations) and our reuse-distance-based algorithm for their timing analysis respectively. Compared with simulation, our analysis framework produces a very good WCET tightness, and our architecture creates almost no hardware overhead or performance degradation. In addition, we examine NP-completeness of WCET analysis. We also explore data allocation techniques to improve system performance. Bestandsnummer des Verkäufers 9783844384703
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Taschenbuch. Zustand: Neu. Cache Modeling for Timing Analysis in Real-Time Systems | Yanhui Li | Taschenbuch | 116 S. | Englisch | 2011 | LAP LAMBERT Academic Publishing | EAN 9783844384703 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu. Bestandsnummer des Verkäufers 106830807
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