Worst case timing analysis of input dependent data cache behavior

Staschulat, Jan; Ernst, Rolf

doi:10.1109/ecrts.2006.33

Cited by 29 publications

(16 citation statements)

References 15 publications

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“…SymTA/P uses a static analysis approach for data cache behavior, which combines symbolic execution to identify input dependent memory accesses and uses integer linear programming to bound the worst case data cache behavior for input dependent memory accesses [SE06].…”

Section: Employed Methodsmentioning

confidence: 99%

The worst-case execution-time problem—overview of methods and survey of tools

Wilhelm

Engblom²,

Ermedahl

et al. 2008

ACM Trans. Embed. Comput. Syst.

1,458

1,029

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Abstract. The determination of upper bounds on execution times, commonly called WorstCase Execution Times (WCETs), is a necessary step in the development and validation process for hard real-time systems. This problem is hard if the underlying processor architecture has components such as caches, pipelines, branch prediction, and other speculative components. This article describes different approaches to this problem and surveys several commercially available tools and research prototypes.

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Section: Employed Methodsmentioning

confidence: 99%

The worst-case execution-time problem—overview of methods and survey of tools

Wilhelm

Engblom²,

Ermedahl

et al. 2008

ACM Trans. Embed. Comput. Syst.

1,458

1,029

View full text Add to dashboard Cite

show abstract

“…They note; however, that the handling of associativity is incomplete and does not scale. Staschulat and Ernst (2006) investigated the problem of data cache analysis where there are dependencies on inputs. They identify Single Data Sequences (SDS) where the memory blocks accessed and the control flow are both independent of inputs.…”

Section: Discussionmentioning

confidence: 99%

Response-time analysis for fixed-priority systems with a write-back cache

2018

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This paper introduces analyses of write-back caches integrated into response-time analysis for fixed-priority preemptive and non-preemptive scheduling. For each scheduling paradigm, we derive four different approaches to computing the additional costs incurred due to write backs. We show the dominance relationships between these different approaches and note how they can be combined to form a single state-of-the-art approach in each case. The evaluation explores the relative performance of the different methods using a set of benchmarks, as well as making comparisons with no cache and a write-through cache. We also explore the effect of write buffers used to hide the latency of write-through caches. We show that depending upon the depth of the buffer used and the policies employed, such buffers can result in domino effects. Our evaluation shows that even ignoring domino effects, a substantial write buffer is needed to match the guaranteed performance of write-back caches.

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“…More recently, Staschulat et al proposed a framework to calculate WCET of tasks [17]. This framework considers both input-independent and input-dependent accesses and calculates a tight bound of the effect of input-dependent accesses on input-independent ones.…”

Section: Related Workmentioning

confidence: 99%