Clustered calculation of worst-case execution times
Andreas Ermedahl, Friedhelm Stappert, Jakob Engblom
Abstract
Andreas Ermedahl, Friedhelm Stappert, Jakob Engblom
Abstract
Knowing the Worst-Case Execution Time (WCET) of a program is necessary when designing and verifying real-time systems. A correct WCET analysis method must take into account the possible program flow, such as loop iterations and function calls, as well as the timing effects of different hardware features, such as caches and pipelines.A critical part of WCET analysis is the calculation, which combines flow information and hardware timing information in order to calculate a program WCET estimate. The type of flow information which a calculation method can take into account highly determines the WCET estimate precision obtainable. Traditionally, we have had a choice between precise methods that perform global calculations with a risk of high computational complexity, and local methods that are fast but cannot take into account all types of flow information.This paper presents an innovative hybrid method to handle complex flows with low computational complexity, but still generate safe and tight WCET estimates. The method uses flow information to find the smallest parts of a program that have to be handled as a unit to ensure precision. These units are used to calculate a program WCET estimate in a demand-driven bottom-up manner. The calculation method to use for a unit is not fixed, but could depend on the included flow information and program characteristics.
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Knowing the Worst-Case Execution Time (WCET) of a program is necessary when designing and verifying real-time systems. A correct WCET analysis method must take into account the possible program flow, such as loop iterations and function calls, as well as the timing effects of different hardware features, such as caches and pipelines.A critical part of WCET analysis is the calculation, which combines flow information and hardware timing information in order to calculate a program WCET estimate. The type of flow information which a calculation method can take into account highly determines the WCET estimate precision obtainable. Traditionally, we have had a choice between precise methods that perform global calculations with a risk of high computational complexity, and local methods that are fast but cannot take into account all types of flow information.This paper presents an innovative hybrid method to handle complex flows with low computational complexity, but still generate safe and tight WCET estimates. The method uses flow information to find the smallest parts of a program that have to be handled as a unit to ensure precision. These units are used to calculate a program WCET estimate in a demand-driven bottom-up manner. The calculation method to use for a unit is not fixed, but could depend on the included flow information and program characteristics.
Key concepts: Computer science, Worst-case execution time, Information flow, Execution time, Flow (mathematics), Program analysis, Function (biology), Computational complexity theory