Automatic Bottleneck Detection
نویسندگان
چکیده
We describe the diagnosis and treatment of bottlenecks in computer systems using decison theoretic techniques. The techniques rely on a high-level functional model of the interaction between application workloads, the operating system (Windows NT), and system hardware. Given a workload description, the model predicts the values of system counters observable with the Windows NT performance monitoring tool. Uncertainty in workloads, predictions, and counter values are characterized with Gaussian distributions. During diagnostic inference, observed performance monitor values are used to nd the most probable assignment to the workload parameters. In this paper we provide some background on performance modeling and automated bottleneck detection, describe the structure of the system model, and discuss empirical procedures for model veri cation. Our method for inferring the cause of the bottleneck is discussed. Initial results in diagnosing bottlenecks are presented. Based on the diagnosis of the bottleneck we can make both a recommendation of the most coste ective hardware upgrade, and a prediction of the performance counter values and throughput once the upgrade is installed.
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