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Details of Grant 

EPSRC Reference: EP/P003915/1
Title: SchedUling on heterogeneous Mobile Multicores based on quality of ExpeRience
Principal Investigator: Leather, Dr H
Other Investigators:
Researcher Co-Investigators:
Project Partners:
Advanced Risc Machines (Arm) AMD (Advanced Micro Devices) (Global) Bell Labs Ireland
Codeplay Software Ltd Critical Blue Ltd Microsoft
Department: Sch of Informatics
Organisation: University of Edinburgh
Scheme: First Grant - Revised 2009
Starts: 31 December 2016 Ends: 30 December 2018 Value (£): 101,027
EPSRC Research Topic Classifications:
Computer Sys. & Architecture Fundamentals of Computing
Mobile Computing
EPSRC Industrial Sector Classifications:
Information Technologies Communications
Related Grants:
Panel History:
Panel DatePanel NameOutcome
10 Jun 2016 EPSRC ICT Prioritisation Panel - Jun 2016 Announced
Summary on Grant Application Form
Users want mobile devices that appear fast and responsive, but at the same time have long lasting batteries and do not overheat. Achieving both of these at once is difficult. The workloads employed to evaluate mobile optimisations are rarely representative of real mobile applications and are oblivious to user perception, focussing only on performance. As a result hardware and software designers' decisions do not respect the user's Quality of Experience (QoE). The device either runs faster than necessary for optimal QoE, wasting energy, or the device runs too slowly, spoiling QoE. SUMMER will develop the first framework to record, replay, and analyse mobile workloads that represent and measure real user experience. Our work will expose for the first time the real Pareto trade-off between the user's QoE and energy consumption. The results of this project will permit others, from computer architects up to library developers, to make their design decisions with QoE as their optimisation target. To show the power of this new approach, we will design the first energy efficient operating system scheduler for heterogeneous mobile processors which takes QoE into account. With heterogeneous mobile processors just now entering the market, a scheduler able to use them optimally is urgently needed. We expect our scheduler to be at least 50% more energy efficient on average than the standard Linux scheduler on an ARM BIG.LITTLE system.
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