Abstract:
Techniques for managing energy use of a computing deployment are provided. In one embodiment, a computer system can establish a performance model for one or more components of the computing deployment, where the performance model models a relationship between one or more tunable parameters of the one or more components and an end-to-end performance metric, and where the end-to-end performance metric reflects user-observable performance of a service provided by the computing deployment. The computer system can further execute an algorithm to determine values for the one or more tunable parameters that minimize power consumption of the one or more components, where the algorithm guarantees that the determined values will not cause the end-to-end performance metric, as calculated by the performance model, to cross a predefined threshold. The computer system can then enforce the determined values by applying changes to the one or more components.
Abstract:
Exemplary methods, apparatuses, and systems receive a first input/output (I/O) trace from a first workload and run the first I/O trace through a cache simulation to determine a first miss ratio curve (MRC) for the first workload. A second I/O trace from the first workload is received and run through the cache simulation to determine a second MRC for the first workload. First and second cache sizes corresponding to a target miss rate for the first workload are determined using the first and second MRCs. A fingerprint of each of the first and I/O traces is generated. The first cache size, the second cache size, or a combination of the first and second cache sizes is selected as a cache size for the first workload based upon a comparison of the first and second fingerprints. A recommended cache size is generated based upon the selected cache size.
Abstract:
Exemplary methods, apparatuses, and systems receive a first input/output (I/O) trace including storage addresses that were subject to a plurality of I/O requests from a first workload during a first period of time. The first I/O trace is run through a cache simulation using a plurality of simulated cache sizes. A first state of the cache simulation is stored upon completing the first I/O trace simulation. The first I/O trace is deleted in response to storing the first state. A second I/O trace including storage addresses that were subject to a plurality of I/O requests from the first workload during a second period of time is received. A cumulative miss ratio curve for the first workload is generated by loading the stored first state as a starting point for simulating the second I/O trace and running the second I/O trace through the cache simulation.
Abstract:
Methods, systems, and computer programs are provided for measuring the performance of display images received on a remote computer display. One method includes an operation for detecting calls from an application to an application programming interface (API), which is provided for rendering images on a display image, each call causing an update of the display image. Further, the method includes an operation for embedding data for measuring performance in display frames of the display image based on the detecting. The embedding results in modified displayed frames with respective data for measuring performance. The modified displayed frames are transmitted to a remote client, which results in received modified display frames having respective received data for measuring the performance. In addition, the method includes an operation for calculating the remote display quality for the given application based on the received modified display frames and the respective received data for measuring performance.