Energy-efficient Computing Through Fine-grained Energy Accounting
Lead Research Organisation:
University of Leeds
Department Name: Sch of Computing
Abstract
Energy efficiency is becoming increasingly important in today's world of battery-powered mobile devices and power-limited servers. While performance optimisation is a familiar topic for developers, few are even aware of the effects that source code changes will have on the energy profiles of their programs. Without knowledge of these effects, compiler and operating system writers cannot create automatic energy optimisers. To realise the needed energy savings, we require the capability to track energy consumption and associate it with code and data at a fine granularity. Furthermore, compilers and operating systems must exploit this capability to optimise applications automatically.
This project will investigate novel techniques for software-centric modelling, measurement, accounting and optimisation of energy efficiency in computing systems. Energy consumption will be matched against programming language abstractions, providing developers with the information that they need. The project will use this fine-grained accounting to build novel compiler optimisations that target energy consumption. It will create low-energy runtime systems that adapt to environmental changes.
This project will investigate novel techniques for software-centric modelling, measurement, accounting and optimisation of energy efficiency in computing systems. Energy consumption will be matched against programming language abstractions, providing developers with the information that they need. The project will use this fine-grained accounting to build novel compiler optimisations that target energy consumption. It will create low-energy runtime systems that adapt to environmental changes.
Organisations
Studentship Projects
Project Reference | Relationship | Related To | Start | End | Student Name |
---|---|---|---|---|---|
EP/W524372/1 | 30/09/2022 | 29/09/2028 | |||
2883684 | Studentship | EP/W524372/1 | 30/09/2023 | 30/03/2027 | Huawei Zhang |