contrasting characteristics and cache performance of technical and multi-user commercial workloads
Experience has shown that many widely used benchmarks are poor predictors of the performance of systems running commercial applications. Research into this anomaly has long been hampered by a lack of address traces from representative multi-user commercial workloads. This paper presents research, using traces of industry-standard commercial benchmarks, which examines the characteristic differences between technical and commercial workloads and illustrates how those differences affect cache performance. Commercial and technical environments differ in their respective branch behavior, operating system activity, I/O, and dispatching characteristics. A wide range of uniprocessor instruction and data cache geometries were studied. The instruction cache results for commercial workloads demonstrate that instruction cache performance can no longer be neglected because these workloads have much larger code working sets than technical applications. For database workloads, a breakdown of kernel and user behavior reveals that the application component can exhibit behavior similar to the operating system and therefore, can experience miss rates equally high. This paper also indicates that dispatching or process switching characteristics must be considered when designing level-two caches. The data presented shows that increasing the associativity of second-level caches can reduce miss rates significantly. Overall, the results of this research should help system designers choose a cache configuration that will perform well in commercial markets.
cache performance cache cache performance commercial workloads experience benchmark systems applications research addressing traces paper affect environments behavior operating system activity operating system activation process instruction data cache data instruction caches demonstrate code technical applications database user behavior component switch association help configurability market memory subsystems standardization multi user industrial caches