Publication | Closed Access
Bubble-flux
345
Citations
39
References
2013
Year
Unknown Venue
Cluster ComputingEngineeringComputer ArchitectureSoftware AnalysisQos DegradationSystems EngineeringStatic Profiling TechniquesParallel ComputingPerformance PredictionProfiling ToolComputer EngineeringComputer SciencePerformance Analysis ToolProgram AnalysisSoftware TestingCloud ComputingStatic ProfilingSystem Performance AnalysisPerformance PortabilitySystem Software
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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