ESWeek Tutorial - Spectrum of Run-time Management for Modern and Next Generation Multi/Many-core Systems
CALL FOR PARTICIPATION
Tutorial: Spectrum of Run-time Management for Modern and Next Generation Multi/Many-core Systems
ESWEEK satellite event
Sunday, September 30, 2018 9:00 a.m. - 1:00 p.m. | Torino, Italy | https://www.imitator.fr/tutorials/ESWEEK18/
Note - that tutorial registration can still be added, including to an existing conference registration, now or later at any time, and there is no difference between early or late or on-site registration fees.
SUNDAY September 30, 9:00am - 1:00pm | Einaudi
EVENT TYPE: TUTORIAL
SESSION 2T
Spectrum of Run-time Management for Modern and Next Generation Multi/Many-core Systems
Speakers:
- Amit Kumar Singh - Univ. of Essex
- Geoff V. Merrett - Univ. of Southampton
- Akash Kumar - Technische Univ. Dresden
- Amir Rahmani - Univ. of California, Irvine & Technische Univ. Wien
Organizers:
- Amit Kumar Singh - Univ. of Essex
- Geoff V. Merrett - Univ. of Southampton
- Akash Kumar - Technische Univ. Dresden
- Amir Rahmani - Univ. of California, Irvine & Technische Univ. Wien
Run-time management of multi/many-core systems is becoming extremely challenging due to several factors, e.g. increasing demand to execute concurrent applications, inefficient exploitation of heterogeneous cores, changing workload variations over time, changing run-time scenarios and desire for optimization of several metrics such as performance, energy consumption and reliability. For next generation multi/many-core systems, the challenges will further increase mainly due to higher number of cores and increased heterogeneity.
This tutorial starts with a taxonomy of run-time management approaches, providing an overview of the field and comparing approaches. The attention then shifts to focus on a range of run-time power and energy management approaches. Thereafter, approaches considering reliability as their primarily optimization goal will be addressed. Finally, run-time management approaches that leverage multiple-input, multiple-output and supervisory control theory to offer scalable, autonomous, and coordinated resource management will be covered. Depending upon the target problems, the designers can employ these methodologies to achieve efficiency in multi/many-core systems in terms of performance, energy consumption and/or reliability.
BIOGRAPHIES:
Amit Kumar Singh is a Lecturer (Assistant Professor) at University of Essex, UK. Previously, he worked as a post-doctoral researcher at University of Southampton, UK from 2016 to 2017, at University of York, UK from 2014 to 2016 and National University of Singapore (NUS) from 2013 to 2014. He received the Ph.D. degree from Nanyang Technological University (NTU), Singapore, in 2013. His current research interests include system level design-time and run-time optimizations of 2D and 3D multi-core systems with focus on performance, energy, temperature, and reliability.
Geoff V. Merrett is an Associate Professor at University of Southampton, where he is head of the Centre for Internet of Things and Pervasive Systems. He received the PhD degree in Electronic Engineering from Southampton in 2009. He is internationally known for his research into the system-level energy management of mobile and self-powered embedded systems. He is currently a Co-Investigator on over PS20M of UK-government-funded projects; for example 'PRiME' on energy-efficient many-core computing systems. He is technical director of the Arm-ECS Research Centre, an award winning industry-academia collaboration between the University of Southampton and ARM.
Akash Kumar is a Professor at Technische Universitat Dresden (TUD), Germany, where he is directing the chair for Processor Design. From 2009 to 2015, he was with the Department of Electrical and Computer Engineering, NUS. He received the joint Ph.D. degree in electrical engineering in embedded systems from University of Technology (TUe), Eindhoven and National University of Singapore (NUS), in 2009. His current research interests include design, analysis, and resource management of low-power and fault-tolerant embedded multiprocessor systems.
Amir M. Rahmani is currently Marie Curie Global Fellow at University of California Irvine (USA) and TU Wien (Austria). He is also an adjunct professor (Docent) in embedded parallel and distributed computing at the University of Turku, Finland. He received the Ph.D. degree from Department of IT, University of Turku, Finland, in 2012. He also received his MBA jointly from Turku School of Economics and European Institute of Innovation & Technology (EIT) ICT Labs, in 2014. His research interests span Self-aware Computing, Energy-efficient Many-core Systems, Runtime Resource Management, Healthcare Internet of Things, and Fog/Edge Computing.