Microsoft
Copilot PC Power Insights
In the first part of the capstone project the student team will work to characterize power consumption across a variety of test cases in Surface Computers. Students will utilize both hardware and software to collect statistical data that is analyzed across system settings, app workloads, and app settings. Because acquiring such data manually would be tedious at best, all aspects that can be automated shall be: data acquisition, test case setup, and data analysis. Machine learning on the output data set will highlight the sources of variability and the effect sizes across conditions. In the second part of the project the student team will build on the first part, leveraging the automation work product to develop a Test App that characterizes the power performance of relevant Apps as determined by the telemetry analytics leadership. Based on previous data, a rating system would be established, and the App under Test (AUT) would receive an energy rating. Requirements: - Detailed planning will be co-developed between Microsoft and the student capstone team. - Computing hardware and any instrumentation will be provided by Microsoft and shall be returned at the end of the project. - All monitoring and development tools shall leverage retail software The student team will work to deliver statistical characterization of Power Consumption of Surface Computers on a variety of scenarios determined by the team. Emphasis will be put in Design of Experiments to help understand power consumption behaviors representing real use cases.
Faculty Adviser
Jose Gutierrez,
Affiliate Adjunct Professor,
Electrical & Computer Engineering
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