An End-to-End Toolchain: From Automated Cost Modeling to Static WCET and WCEC Analysis
An End-to-End Toolchain: From Automated Cost Modeling to Static WCET and WCEC Analysis
复制标题
端到端工具链：从自动成本建模到静态 WCET 和 WCEC 分析
DOI：
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发表时间：
2017
期刊：
影响因子：
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通讯作者：
Wolfgang Schröder
中科院分区：
文献类型：
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作者：
V. Sieh;Robert Burlacu;Timo Hönig;Heiko Janker;Phillip Raffeck;Peter Wägemann;Wolfgang Schröder
可靠的细粒度代价模型是实时系统静态预测程序代码最坏情况执行时间（WCET）以保证实时性的基础。类似的考虑适用于能量受限系统，其中最坏情况能耗（WCEC）值是强制性的，以确保满足预定义的能量预算。这些成本模型通常不适用于商用现货（COTS）硬件平台，尽管静态最坏情况分析工具需要这些模型来预测程序代码的WCET和WCEC。为了解决这个问题，我们提出了NEO，这是一个端到端的工具链，可以自动生成WCET和WCEC分析的成本模型。NEO利用自动生成的基准，这些基准是1）一个测试级仿真和2）在目标平台上自动进行的执行时间和能耗测量的输入。收集的值（即，每个指令的出现次数、每个基准的执行时间和能耗）被组合为数学优化问题。制定的问题，这是为了揭示最坏情况下的行为，产生相应的成本模型的解决方案。为了静态地确定基准的上限，我们将成本模型集成到最先进的WCET分析仪PLATIN中。我们对COTS硬件的评估表明，我们的开源端到端工具链NEO可以产生准确的最坏情况边界。
Reliable and fine-grained cost-models are fundamental for real-time systems to statically predict worst-case execution time (WCET) estimates of program code in order to guarantee timeliness. Analogous considerations hold for energy-constrained systems where worst-case energy consumption (WCEC) values are mandatory to ensure meeting predefined energy budgets. These cost models are generally unavailable for commercial off-the-shelf (COTS) hardware platforms, although static worst-case analysis tools require those models in order to predict the WCET as well as the WCEC of program code. To solve this problem, we present NEO, an end-to-end toolchain to automate cost-model generation for both WCET and WCEC analyses. NEO exploits automatically generated benchmarks, which are input for 1) an instruction-level emulation and 2) automatically conducted execution-time and energy-consumption measurements on the target platform. The gathered values (i.e., occurrences per instruction, execution-time and energy-consumption per benchmark) are combined as mathematical optimization problems. The solutions to the formulated problems, which are designed to reveal the worst-case behavior, yield the respective cost models. To statically determine upper bounds of benchmarks, we integrated the cost models into the state-of-the-art WCET analyzer PLATIN. Our evaluations on COTS hardware reveal that our open-source, end-to-end toolchain NEO yields accurate worst-case bounds.
DOI：
10.1109/rtas.2017.37
发表时间：
2017-04
期刊：
2017 IEEE Real-Time and Embedded Technology and Applications Symposium (RTAS)
影响因子：
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作者：
Christian J. Dietrich;Peter Wägemann;Peter Ulbrich;Daniel Lohmann
通讯作者：
Christian J. Dietrich;Peter Wägemann;Peter Ulbrich;Daniel Lohmann
用于时序分析的基准生成
DOI：
10.1109/rtas.2017.6
发表时间：
2017
期刊：
2017 IEEE Real-Time and Embedded Technology and Applications Symposium (RTAS)
影响因子：
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作者：
P. Wägemann;T. Distler;C. Eichler;W. Schröder-Preikschat
通讯作者：
W. Schröder-Preikschat