SchedUling on heterogeneous Mobile Multicores based on quality of ExpeRience

Completed

Energy Efficiency(Residential and commercial)
Not Energy Related

Basic and strategic applied research

PHYSICAL SCIENCES AND MATHEMATICS (Computer Science and Informatics)

Not Cross-cutting
Sociological economical and environmental impact of energy (Consumer attitudes and behaviour)

Dr H Leather
Sch of Informatics
University of Edinburgh

Standard

EPSRC

31 December 2016

30 December 2018

24 months

£101,027

Info. & commun. Technol.

Scotland

NC : ICT

Dr H Leather, Sch of Informatics, University of Edinburgh

Project Contact, Microsoft Corporation (USA)
Project Contact, Advanced Micro Devices, Inc. (AMD), USA
Project Contact, Critical Blue Ltd
Project Contact, Bell Labs Ireland
Project Contact, Arm Holdings
Project Contact, Codeplay Software Ltd

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

12/02/19