多路径程序中基于测量的缓存代表性

Suzana Milutinovic, J. Abella, E. Mezzetti, F. Cazorla
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引用次数: 0

摘要

嵌入式实时系统中的自动驾驶汽车增加了关键软件的大小和复杂性,其性能需求由高性能硬件功能(如缓存)覆盖,然而,这阻碍了获得对所有程序执行路径有效的WCET估计。这需要在WCET过程中评估所有缓存布局是否被正确地考虑在内。对于基于度量的计时分析(最常见的分析方法),我们提供了一个解决方案来实现缓存代表性和全路径覆盖:我们创建了一个用于分析目的的修改程序,其中缓存影响在任何路径上都是上界的,并推导出在测试活动缓存布局中捕获所需的最小运行次数,从而导致高执行时间。
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Measurement-Based Cache Representativeness on Multipath Programs
Autonomous vehicles in embedded real-time systems increase critical-software size and complexity whose performance needs are covered with high-performance hardware features like caches, which however hampers obtaining WCET estimates that hold valid for all program execution paths. This requires assessing that all cache layouts have been properly factored in the WCET process. For measurement-based timing analysis, the most common analysis method, we provide a solution to achieve cache representativeness and full path coverage: we create a modified program for analysis purposes where cache impact is upper-bounded across any path, and derive the minimum number of runs required to capture in the test campaign cache layouts resulting in high execution times.
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