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Keynote 2: Geoff Merrett

Geoff V. Merrett is an Associate Professor in the School of Electronics and Computer Science, University of Southampton, UK, where he is head of the Centre for Internet of Things and Pervasive Systems. He received the BEng and PhD degrees in Electronic Engineering from Southampton in 2004 and 2009 respectively. He is internationally known for his research into the system-level energy management of mobile and self-powered embedded systems, and he has published over 175 journal and conference papers in these areas. He has given invited talks on his research (e.g. DAC, DATE), and had a number of best paper nominations and awards (e.g. DATE, CODES-ISSS, IJCAI). He has been an Investigator on over £20M of UK-government-funded projects; for example ‘PRiME’ on energy-efficient many-core computing systems, where he leads the applications and demonstrators theme. He is technical director of the Arm-ECS Research Centre, an award winning industry-academia collaboration between the University of Southampton and Arm. He has edited a number of research books, including the recently published IET Press book titled "Multi- and Many-Core Computing: Software and Hardware". He is a member of the IEEE, IET and Fellow of the HEA.

keynote speaker

Managing Power in Heterogeneous Multicore Systems

Power- and energy-efficiency continues to be a primary concern in the design and management of computing systems, through from mobile devices (battery life and temperature) to HPC (electricity bills and temperature). Managing this is an increasingly complex task, as systems shift from having a single processing element to multi- and many-core computing platforms with numerous cores of differing types. In this talk I will present our research into the runtime management (RTM) of such systems that have come out of the PRiME ( research project. I will present a range of different approaches that we have developed and experimentally validated, and the key findings that we have made along the way. These encompass 1) exploring RTM on both novel and heterogeneous/homogeneous COTS multi-core platforms, 2) the impact of core scaling on RTMs, 3) issues and approaches for managing concurrently executing workloads on shared resource, and 4) comparing the impact of offline vs online characterisation approaches. I will also present a range of open-source tools that we have developed and released through these projects, spanning simulation and runtime power models for multi-core CPUs, to a framework for researchers to incorporate multi-core runtime management into their system and enable level comparison with the SoA.