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-------- Forwarded Message --------
Subject: [Dipartimento.di] Avviso Seminario: Leonardo Robol - Seminario
di Esperienze di Programmazione
Date: Mon, 30 Mar 2015 13:40:22 +0200
From: Gianna M. Del Corso <gianna.delcorso(a)unipi.it>
To: dipartimento(a)di.unipi.it
Nell'ambito del corso di Esperienze di Programmazione
*Mercoledi' 1 Aprile 2015* - ore 11.00
Dip. di Informatica - Aula Seminari EST
si terra' il seminario di
LEONARDO ROBOL (Scuola Normale Superiore)
INTRODUZIONE A JULIA
Sarà presentato Julia, un linguaggio per il calcolo scientifico
attualmente in fase di sviluppo. Verranno mostrate la sintassi e le
principali differenze con i linguaggi attualmente più diffusi, come
MATLAB e FORTRAN. Verrà fatta una panoramica delle principale
caratteristiche della piattaforma, come i pacchetti aggiuntivi, il
notebook IJulia, la gestione dei tipi e il raggiungimento di ottime
performance (comparabili a quelle di C e FORTRAN) grazie all'utilizzo di
LLVM come backend.
Sarà infine presentato qualche esempio per mostrare le potenzialità di
Julia per lo sviluppo di codice parallelo.
L'interprete è open source e disponibile su http://julialang.org/.
========================
Riferimento: Gianna Del Corso
Gianna M. Del Corso, PhD
Dipartimento di Informatica,
Universita' di Pisa
Largo Pontecorvo, 3 56127 Pisa, Italy
ph. +39-050-2213118
fax +39-050-2212726
Gianna M. Del Corso, PhD
Dipartimento di Informatica,
Universita' di Pisa
Largo Pontecorvo, 3 56127 Pisa, Italy
ph. +39-050-2213118
fax +39-050-2212726
In the next months we are holding a small cycle of joint seminars
between the optimization and numerical analysis groups; their purpose is
describing each other's research work, with an eye to possible new
common areas of interest.
Prof. Frangioni's seminar is the first one of the series.
Time: Thursday 2015-Mar-19 (next week), h. 10:00
Place: Sala Seminari Ovest, Dipartimento di Informatica
Speaker: Antonio Frangioni, Università di Pisa
Title: *Iterative approaches for graph-structured linear systems arising
in optimization*
Abstract: When applying Interior Point (IP) algorithm to the solution of
linear or convex separable optimization problems with strong graph
structure, like the Min Cost Flow (MCF) problem, one has to repeatedly
solve linear systems with strong graph structure. One of the two
possible approach leads to systems with a M-matrix that is basically the
weighted Laplacian of the underlying graph, where the weights (but not
the graph) change at each iteration of the IP methods and typically
become "very imbalanced" at the last ones. For this problem we have used
two different techniques: Preconditioned Conjugate Gradient (PCG)
methods, based on the idea of extracting a proper triangulated subgraph
of the original graph which strictly contains a spanning tree. We have
defined a new class of triangulated graphs, called Brother-Connected
Trees (BCT), and discuss some fast heuristics for finding BCTs of
"large" weight, starting from either the Kruskal algorithm or the Prim
one. In addition we have studied multi-iterative techniques where the
above PCG approach has been combined with specialized coarser-grid
operators which preserve the graph structure of the projected matrix at
the inner levels and smoothers, that have been completely characterized.
Quite a lot of work still remains to do for understanding which is the
best combination of preconditioning and coarsening at different stages
of the overarching IP algorithm, implementing these techniques in an
efficient solver, and extending them to "truly" interesting
graph-structured problems like Multicommodity MCF ones.
Everyone is welcome!
--
--federico poloni
Dipartimento di Informatica, Università di Pisa
http://www.di.unipi.it/~fpoloni/ tel:+39-050-2213143
Carissimi,
vi ricordo il Seminario del Prof. Jacek Gondzio (School of
Mathematics, University of Edinburgh) di venerdì prossimo (20/3) a
Firenze e, a rettifica di quanto comunicato in precedenza, preciso che
il seminario si terrà presso il PLESSO DIDATTICO MORGAGNI (Aula 223).
*********************************
Ven 20 Marzo, ore 14:00
Luogo: FIRENZE
aula: Aula 223, PLESSO DIDATTICO MORGAGNI
Viale Morgagni 40, Università di Firenze
TITOLO: "Preconditioners for higher order methods in big data
optimization"
ABSTRACT:
We address efficient preconditioning techniques for the second-order
methods applied to solve various sparse approximation problems arising
in big data optimization. The preconditioners cleverly exploit special
features of such problems and cluster the spectrum of eigenvalues
around one. The inexact Newton Conjugate Gradient method excels
in these conditions. Numerical results of solving L1-regularization
problems of unprecedented sizes will be presented.
J. Gondzio
joint work K. Fountoulakis
*********************************
Cordiali saluti,
Margherita Porcelli
--
Margherita Porcelli
Dipartimento di Matematica
Università di Bologna
Piazza di Porta S. Donato, 5
40127 - Bologna - Italy
phone : +39-051-2094423
home page: http://web.math.unifi.it/users/porcelli
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Segnalo 2 seminari che il Prof. Jacek Gondzio (School of Mathematics, University of Edinburgh) terrà
nel corso della sua visita presso il Dipartimento di Ingegneria Industriale (UNIFI) e il Dipartimento di Matematica (UNIBO).
*********************************
Ven 13 Marzo, ore 11:00
Luogo: BOLOGNA
aula: Seminario I, Dipartimento di Matematica, Università di Bologna
TITOLO: "Preconditioners for higher order methods in signal reconstruction"
ABSTRACT:
We address efficient preconditioning techniques for the inexact second-order
methods applied to solve various sparse approximation problems arising in
signal/image reconstruction.
The preconditioners exploit two features of such problems:
(i) sparsity of the solution, and
(ii) near-orthogonality of the matrices involved.
The latter originates from the restricted isometry properties frequently
assumed in such applications. Spectral analysis of the preconditioners and
their practical efficiency when solving linear systems in the Newton
Conjugate Gradient method will be presented. If time permits then a few
comments on the some other problems originating from the "Big Data" buzz
will also be given.
J. Gondzio
joint work with I. Dassios, K. Fountoulakis and P. Zhlobich
*********************************
Ven 20 Marzo, ore 14:00
Luogo: FIRENZE
aula: Aula Tricerri, Dipartimento di Matematica e Informatica 'Ulisse Dini'
Università di Firenze
TITOLO: "Preconditioners for higher order methods in big data optimization"
ABSTRACT:
We address efficient preconditioning techniques for the second-order
methods applied to solve various sparse approximation problems arising
in big data optimization. The preconditioners cleverly exploit special
features of such problems and cluster the spectrum of eigenvalues
around one. The inexact Newton Conjugate Gradient method excels
in these conditions. Numerical results of solving L1-regularization
problems of unprecedented sizes will be presented.
J. Gondzio
joint work K. Fountoulakis
*********************************
Cordiali saluti,
Margherita Porcelli
--
Margherita Porcelli
Dipartimento di Matematica
Università di Bologna
Piazza di Porta S. Donato, 5
40127 - Bologna - Italy
phone : +39-051-2094423
home page: http://web.math.unifi.it/users/porcelli