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Ph.D de

Ph.D
Group : Parallelism

Programming hierarchical and heterogenous architectures

Starts on 01/09/2008
Advisor : ETIEMBLE, Daniel

Funding : AM
Affiliation : Université Paris-Sud
Laboratory : LRI

Defended on 10/11/2011, committee :
Rapporteurs :
— M. Philippe Clauss, Professeur à l'Université de Strasbourg
— M. Frédéric Loulergue, Professeur à l'Université d'Orléans

Examinateurs :
__ M. Gaétan Hains , Professeur à l'Université Paris-Est Créteil (UPEC) , Président de jury
— M. Alain Mérigot, Professeur à l'Université Paris-Sud 11 - IEF

Directeur de thèse :
— M. Daniel Etiemble, Professeur à l'Université Paris-Sud 11 -LRI
— M. Joel Falcou, Maître de conférence à l'Université Paris-Sud 11 -LRI

Research activities :

Abstract :
Applications based on streams, ordered sequences of data values, are important
targets of program optimization because of their high computational requirements
and the diversity of their application domains: communication, embedded systems,
multimedia, etc. One of the most important and difficult problems in special purpose
stream language design and implementation is how to schedule these applications
in a fine-grain way to exploit available machine resources.
In this thesis we propose a framework for fine-grain scheduling of streaming ap-
plications and nested loops in general. First, we try to pipeline steady state phases
(inner loops), by finding the repeated kernel pattern, and executing actor occur-
rences in parallel as much as possible. Then we merge the kernel prolog and epilog
of pipelined phases to move them out of the outer loop. Merging the kernel prolog
and epilog means that we shift actor occurrences, or instructions, from one phase it-
eration to another and from one outer loop iteration to another, a multidimensional
shifting.
Experimental shows that our framework can improve performance, parallelism
extraction without increasing the code size, in streaming applications and nested
loops in general.

Ph.D. dissertations & Faculty habilitations
DECODING THE PLATFORM SOCIETY: ORGANIZATIONS, MARKETS AND NETWORKS IN THE DIGITAL ECONOMY
The original manuscript conceptualizes the recent rise of digital platforms along three main dimensions: their nature of coordination devices fueled by data, the ensuing transformations of labor, and the accompanying promises of societal innovation. The overall ambition is to unpack the coordination role of the platform and where it stands in the horizon of the classical firm – market duality. It is also to precisely understand how it uses data to do so, where it drives labor, and how it accommodates socially innovative projects. I extend this analysis to show continuity between today’s society dominated by platforms and the “organizational society”, claiming that platforms are organized structures that distribute resources, produce asymmetries of wealth and power, and push social innovation to the periphery of the system. I discuss the policy implications of these tendencies and propose avenues for follow-up research.

DISTRIBUTED COMPUTING WITH LIMITED RESOURCES


VALORISATION DES DONNéES POUR LA RECHERCHE D'EMPLO