When multimedia meets control: use of soft real--time techniques for control design

When : Friday, April 24, 2015 - 11:00
Speaker : Luigi Palopoli
Affiliation : University of Trento
Where : Aula Magna "A. Lepschy"
Description :

Modern embedded controllers are often characterised by an important level of variability in the computation requirements for the extraction of sensor data. What is more, obviouscost reasons demand sharing hardware between different concurrent activities.These facts strain the assumptions that underlie classical flows for the designof digital controllers: constant delays and infinite availability ofcommunication and computation resources.In this setting a system design with guaranteed control performance requires:

  1. the adoption of scheduling mechanisms and of models of computation that make for the definition of accurate stochastic models for the evolution of the computing platform,
  2. the development of analysis techniques that link the choice of the scheduling parameters to the Quality of Service provided by the computing platform,
  3. the development of algorithms for the evaluation and the optimisation of the Quality of Control provided by a controller's implementation given the Quality of Service provided by the platform.

In this talk, we will show our results on each of these areas. The techniques we propose allows tackling such questions as: 1. the choice of the platformparameters that minimise the resource consumption of a control application with guaranteed levels for the Quality of Control, 2. find the best selection of theplatform parameters for a set of control application competing for the same platform.            

Kinetic Dependence Graphs

When : Monday, April 20, 2015 - 12:00
Speaker : Keshav Pingali
Affiliation : The University of Texas at Austin
Where : Sala riunioni 318 DEI/G
Description :

Task graphs or dependence graphs are used in runtime systems toschedule tasks for parallel execution. In problem domains such asdense linear algebra and signal processing, dependence graphs can begenerated from a program by static analysis.  However, in problemdomains such as discrete-event simulation and simulation usingasynchronous variational integrators, the set of tasks and thedependences between tasks in a program are complex functions ofruntime values and cannot be determined statically.In this talk, we introduce a novel approach for exploiting parallelismin such programs. This approach is based on a data structure calledthe kinetic dependence graph (KDG), which consists of a dependencegraph together with update rules that incrementally update the graphto reflect changes in the dependence structure whenever a task iscompleted. We have implemented a simple programming model that allowsprogrammers to write these applications at a high level ofabstraction, and a runtime within the Galois system that builds theKDG automatically and executes the program in parallel. On a suite ofprograms that are difficult to parallelize otherwise, we have obtainedspeedups of up to 33 on 40 cores, out-performing third-partyimplementations in some cases.This is joint work with Amber Hassaan and Donald Nguyen at UT Austin.            

Learning with Computational Regularization

When : Friday, March 27, 2015 - 11:00
Speaker : Prof. Lorenzo Rosasco
Affiliation : Universita' di Genova, MIT
Where : Aula Magna "A. Lepschy"
Description :

Abstract: Availability of large high-dimensional data-sets has urged the  development of optimization solutions for large scale learning problems.  From a theoretical perspective this has motivated the goal of better  understanding the interplay between statistics and optimization, towards developing new, more efficient  learning algorithms. Indeed,  while much theoretical work has been  devoted to study  statistical properties of estimators defined by variational schemes (a.k.a. Tikhonov regularization),  and  the  computational  properties of optimization procedures to solve the corresponding minimization problems, much less  work has  been devoted to  the integration of statistical and optimization aspects.  In this talk, we will present some recent proposals to develop machine learning algorithms which are provably efficient as well as statistically sound.  In particular, we will discuss different instances of iterative regularization methods and, if time permit,  randomized sampling techniques allowing further improvements. Short BIO: http://web.mit.edu/lrosasco/www/

Il principio di responsabilità

When : Thursday, January 22, 2015 - 16:30
Speaker : Prof. Umberto Vincenti
Affiliation : Universita' di Padova
Where : Aula Magna 'A. Lepschy'
Description :

  • Diritti e doveri
  • Etica della responsabilita'
  • Etica della sanzione
  • Responsabilita' professionale e responsabilita' sociale

Etica per una repubblica

When : Thursday, January 8, 2015 - 17:00
Speaker : Prof. Umberto Vincenti
Affiliation : Universita' di Padova
Where : Aula Magna 'A. Lepschy'
Description :

  • Costituzionalismo e repubbliche
  • Spirito pubblico e virtu' repubblicane
  • Il principio di congruenza istituzionale:
    •    il buon governante
    •    il buon giudice
    •    il buon amministratore
    •    il buon cittadino