Pablo ROTONDO defended his PhD thesis, September 2018

Pablo ROTONDO successfully defended his PhD thesis on September 27th, 2018, at Université Paris-Diderot.

Title: Probabilistic studies in Number Theory and Word Combinatorics: instances of dynamical analysis

Directors:

  • Brigitte VALLÉE, Université de Caen, France
  • Valérie BERTHÉ, IRIF, Université Paris-Diderot, France
  • Alfredo VIOLA, Universidad de la República, Uruguay

Evaluation committee:

  • Bruno SALVY     (rapporteur)
  • Pierre ARNOUX (rapporteur)
  • Cyril NICAUD     (examiner)
  • Franco ROBLEDO     (examiner)
  • Thomas STOLL     (examiner)

Abstract.
Dynamical Analysis incorporates tools from dynamical systems, namely the  Transfer Operator, into the framework of Analytic Combinatorics, permitting the analysis of numerous algorithms and objects naturally associated with an underlying dynamical system. This dissertation presents, in the integrated framework of Dynamical Analysis, the probabilistic analysis of seemingly distinct problems in a unified way: the probabilistic study of the recurrence function of Sturmian words, and the probabilistic study of the Continued Logarithm algorithm.

Sturmian words are a fundamental family of words in Word Combinatorics. They are in a precise sense the simplest infinite words that are not eventually periodic. Sturmian words have been well studied over the years, notably by Morse and Hedlund (1940) who demonstrated that they present a notable number theoretical characterization as discrete codings of lines with irrational slope, relating them naturally to dynamical systems, in particular the Euclidean dynamical system. These words have never been  studied from a probabilistic perspective.   Here, we quantify the  recurrence properties of  a “random” Sturmian word,    which  are dictated by the so-called “recurrence function”;  we perform a complete asymptotic probabilistic study of this function,  quantifying its mean and describing  its distribution  under two different probabilistic models, which present different virtues: one is a naturaly choice from an algorithmic point of view (but is innovative from the point of view of dynamical analysis), while the other allows a natural quantification of the worst-case growth of the recurrence function. We discuss  the relation between these two distinct models and their respective techniques, explaining also how the two seemingly different techniques employed could be linked through the use of the Mellin transform.  In this dissertation we also discuss our ongoing work regarding two special families of Sturmian words:  those associated with a quadratic irrational slope, and those with a rational slope (not properly Sturmian). Our work seems to show the possibility of a unified study.

The Continued Logarithm Algorithm, introduced by Gosper in Hakmem (1978) as a mutation of classical continued fractions, computes the greatest common divisor of two natural numbers by performing division-like steps involving only binary shifts and substractions. Its worst-case performance was studied recently by Shallit (2016), who showed a precise upper-bound for the number of steps and gave a family of inputs attaining this bound. In this dissertation we employ dynamical analysis to study the average running time of the algorithm, giving precise mathematical constants for the asymptotics, as well as other parameters of interest. The underlying dynamical system is akin to the Euclidean one, and was first studied by Chan (around 2005) from an ergodic, but the presence of powers of 2 in the quotients ingrains into the central parameters a dyadic flavour that cannot be grasped solely by studying this system. We thus introduce a dyadic component and deal with a two-component system. With this new mixed system at hand, we then provide a complete average-case analysis of the algorithm by Dynamical Analysis.

Course “Probabilistic Análisis of Algorithms” at UBA by J. Clement, L. Lothe, and E. Casaratto

A new course for graduate and undergraduate level will take place at Computer Science Department, School of Exact and Natural Sciences, University of Buenos Aires:
Probabilistic Análisis of Algorithms
26 October to 23 November 2018
Professors:

  • Julien Clement (Laboratoire GREYC – Université de Caen)
  • Loïck Lothe (Université de Caen)
  • Eda Cesaratto (Universidad Nacional General Sarmiento)

Elisa Orduna defends her licenciatura thesis at UBA – July 19, 2018

On July 19, 2018 Elisa Orduna defends her “Tesis de Licenciatura en Ciencias de la Computación” (eq. Masters in the EU system) at the Computer Science Department, School of Exact and Natural Sciences, University of Buenos Aires

Title: Preservation of normality in transducers.
Directors: Verónica Becher (Argentina) and Olivier Carton (France).
Evaluation committee: Sergio Abriola and Santiago Figueira

Gervasio Perez obtained his PhD

Gervasio Perez obtained his PhD in Computer Science on April 18, 2018, at Universidad de Buenos Aires under the direction of Sergio Yovine (UBA/CONICET).

Title: Specification, design and implementation of a pattern-based concurrent programming environment

Abstract: Developing correct and efficient parallel software in a cost-effective way is challenging. There are a number of pitfalls that lead to incorrect behaviors and poor performance. Pattern-based software design could help achieving correctness and scalability. However, it has several drawbacks: (a) most patterns are not broadly supported by current parallel-programming models and languages; (b) most often than not getting the appropriate pattern right is difficult; and (c) most patterns do not compose easily, thus making it hard to deal with heterogeneous parallelism.
As an attempt to overcoming these issues, the contribution of this thesis is threefold. First, it proposes a parallel-programming pattern, called PCR [43], consisting of producers, consumers, and reducers which operate concurrently on data sets. To favor correctness, the semantics of PCRs is mathematically defined in terms of the formalism FXML . PCRs are shown to be composable and to seamlessly subsume other well-known parallel-programming patterns, thus providing a framework for heterogeneous designs. Second, it formally shows how the PCR pattern can be correctly implemented in terms of a more concrete parallel execution model. Third, it proposes a platform-agnostic C++ template library to express PCRs . It briefly presents a prototype compiler based on C++ template re-writing which automatically generates distributed implementations relying on the Intel Concurrent Collections C++ library. The programming and code-generation suite is illustrated through several case studies. Overall, the proposed framework provides means to enhance parallel software quality and productivity through an automated methodology based on high-level, platform-independent programming constructs, and a compiling infrastructure to generate portable, executable code.