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GPU Scheduler Modeling for Early Power-Performance Estimation of Mobile Applications
User experience and battery life are key concerns for smartphone makers. Given the growing trend of graphic-rich applications on mobile devices, embedded Graphics Processing Units (GPUs) are increasingly being incorporated in smartphone hardware platforms. In this project the intern will develop fast, early and accurate models of embedded GPUs, before the GPU hardware is available. These models will be useful for early optimization of smartphone applications by determining the appropriate application code to execute on the GPU and by using the appropriate policy to schedule jobs on the GPU across multiple applications, while minimizing energy consumption.
Faculty Supervisor:
Samar Abdi
Student:
Partner:
BlackBerry (Waterloo, ON)
Discipline:
Computer science
Sector:
Information and cultural industries; Manufacturing
University:
Concordia University
Program:
Accelerate
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Mitacs is funded by the Government of Canada, the Government of Alberta, the Government of British Columbia, Research Manitoba, the Government of New Brunswick, the Government of Newfoundland and Labrador, the Government of Nova Scotia, the Government of Ontario, Innovation PEI, the Government of Quebec, the Government of Saskatchewan, and the Government of Yukon.