2013 · 347 citations · 41 references
ComputingComputer EngineeringComputer SystemsCloud Performance OptimizationOperating SystemsQueuing TheoryBottleneck IdentificationCpu SchedulingLatency OptimizationPerformance Bottleneck AnalysisPerformance ModelingPerformance OptimizationApplication ProfilingInterferencePerformance InterferencePerformance ProfilingProfilingServer UtilizationSystem ProfilingWorkload Characterization
Ensuring the quality of service (QoS) for latency-sensitive applications while allowing co-locations of multiple applications on servers is critical for improving server utilization and reducing cost in modern warehouse-scale computers (WSCs). Recent work relies on static profiling to precisely predict the QoS degradation that results from performance interference among co-running applications to increase the number of "safe" co-locations. However, these static profiling techniques have several critical limitations: 1) a priori knowledge of all workloads is required for profiling, 2) it is difficult for the prediction to capture or adapt to phase or load changes of applications, and 3) the prediction technique is limited to only two co-running applications.
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