40th Summer School of Automatic Control
Date: Sep 09, 2019 1:00 am – Sep 13, 2019 8:00 am
40th Summer School of Automatic Control
special topic on Control of Computing Systems
Grenoble, France
September, 09-13, 2019
More informations at
http://www.gipsa-lab.fr/summerschool/auto2019/home.html
Important dates
For administrative reasons, registration takes place in 2 steps:
- pre-registration
- registration
Registrants will be informed how to proceed with registration once they have made their pre-registration.
- Pre-registration deadline : July 12th, 2019
- Registration deadline : July 15th, 2019
- Summer School : September 09-13, 2019
Context and motivations
Self-managing or autonomic computing systems are answering to the need to address dynamic variations in the computing, memory or communication loads, as well as in their environment, the evolutions in their computing infrastructure (shared or subject to faults) or (re)adaptations of their initial functionalities. Their administration, usually performed by human administrators, needs to be automated in order to be efficient, safe and highly reactive. The Autonomic Computing paradigm using self-manageable closed loops emerged in the early 2000, targeting distributed system and addressing these questions from a computer science point of view. A particularly insightful way of building such control loops is to use control systems theory, which employs a large spectrum of modelling, estimation and control techniques (continuous, discrete, stochastic), classically applied mostly to electro-mechanical, physical systems, but much less usually to computing systems. .
The aim of this Summer School is to offer the opportunity of a scientific forum from control systems, informatics, distributed systems, around the various challenges and methodologies dedicated to the control of computing systems. To this end, domain experts will be present to share their expertise and cutting-edge research results.
Organization
The School will consist of a series of surveys, lectures and research talks taught in English, completed by a series of applications sessions.
Audience
The School is mainly intended for PhD students, researchers and industrial participants interested in self-managing systems, autonomic management and control of Cloud, Real-Time or High Performance Computing (HPC) systems, privacy or BigData management. Basic knowledge in automatic control and mathematics is useful.
Confirmed lecturers:
Karl-Erik Årzén (Lund University Sweden); Lydia Chen (TU Delft (IBM) Netherlands); Niklas Karlsson (Verizon Media, CA USA); Eric Kerrigan (Imperial College London, UK); Stéphane Lafortune (University of Michigan, USA); Daniel Simon (LIRMM-INRIA France)
Organization:
The School will consist of a series of surveys, lectures and research talks taught in English, completed by a series of applications sessions.
Audience:
The School is mainly intended for PhD students, researchers and industrial participants interested in self-managing systems, autonomic management and control of Cloud, Real-Time or High Performance Computing (HPC) systems, privacy or BigData management. Basic knowledge in automatic control and mathematics is useful.
Submitted by Regan Williams
on
40th Summer School of Automatic Control
special topic on Control of Computing Systems
Grenoble, France
September, 09-13, 2019
More informations at
http://www.gipsa-lab.fr/summerschool/auto2019/home.html
Important dates
For administrative reasons, registration takes place in 2 steps:
- pre-registration
- registration
Registrants will be informed how to proceed with registration once they have made their pre-registration.
- Pre-registration deadline : July 12th, 2019
- Registration deadline : July 15th, 2019
- Summer School : September 09-13, 2019
Context and motivations
Self-managing or autonomic computing systems are answering to the need to address dynamic variations in the computing, memory or communication loads, as well as in their environment, the evolutions in their computing infrastructure (shared or subject to faults) or (re)adaptations of their initial functionalities. Their administration, usually performed by human administrators, needs to be automated in order to be efficient, safe and highly reactive. The Autonomic Computing paradigm using self-manageable closed loops emerged in the early 2000, targeting distributed system and addressing these questions from a computer science point of view. A particularly insightful way of building such control loops is to use control systems theory, which employs a large spectrum of modelling, estimation and control techniques (continuous, discrete, stochastic), classically applied mostly to electro-mechanical, physical systems, but much less usually to computing systems. .
The aim of this Summer School is to offer the opportunity of a scientific forum from control systems, informatics, distributed systems, around the various challenges and methodologies dedicated to the control of computing systems. To this end, domain experts will be present to share their expertise and cutting-edge research results.
Organization
The School will consist of a series of surveys, lectures and research talks taught in English, completed by a series of applications sessions.
Audience
The School is mainly intended for PhD students, researchers and industrial participants interested in self-managing systems, autonomic management and control of Cloud, Real-Time or High Performance Computing (HPC) systems, privacy or BigData management. Basic knowledge in automatic control and mathematics is useful.
Confirmed lecturers:
Karl-Erik Årzén (Lund University Sweden); Lydia Chen (TU Delft (IBM) Netherlands); Niklas Karlsson (Verizon Media, CA USA); Eric Kerrigan (Imperial College London, UK); Stéphane Lafortune (University of Michigan, USA); Daniel Simon (LIRMM-INRIA France)
Organization:
The School will consist of a series of surveys, lectures and research talks taught in English, completed by a series of applications sessions.
Audience:
The School is mainly intended for PhD students, researchers and industrial participants interested in self-managing systems, autonomic management and control of Cloud, Real-Time or High Performance Computing (HPC) systems, privacy or BigData management. Basic knowledge in automatic control and mathematics is useful.