Publication | Open Access
Fast and exact analysis for LRU caches
26
Citations
32
References
2019
Year
EngineeringVerificationComputer ArchitectureComputational ComplexityMemory Model (Programming)Software AnalysisFormal VerificationHardware SecurityHigh-performance ArchitectureStatic CheckingParallel ComputingMemory AccessesLru CachesRuntime VerificationAbstract InterpretationComputer EngineeringCachingComputer ScienceStatic Program AnalysisExternal-memory AlgorithmProgram AnalysisFormal MethodsParallel ProgrammingSystem Software
For applications in worst-case execution time analysis and in security, it is desirable to statically classify memory accesses into those that result in cache hits, and those that result in cache misses. Among cache replacement policies, the least recently used (LRU) policy has been studied the most and is considered to be the most predictable. The state-of-the-art in LRU cache analysis presents a tradeoff between precision and analysis efficiency: The classical approach to analyzing programs running on LRU caches, an abstract interpretation based on a range abstraction, is very fast but can be imprecise. An exact analysis was recently presented, but, as a last resort, it calls a model checker, which is expensive. In this paper, we develop an analysis based on abstract interpretation that comes close to the efficiency of the classical approach, while achieving exact classification of all memory accesses as the model-checking approach. Compared with the model-checking approach we observe speedups of several orders of magnitude. As a secondary contribution we show that LRU cache analysis problems are in general NP-complete.
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