Parisian Master of Research in Computer Science
Master Parisien de Recherche en Informatique (MPRI)

Cours 2.18.2: Shared-Memory Distributed Computing/Algorithmique distribuée avec mémoire partagée (24h, 3ECTS)

Enseignants pour l'année 2022-23 / Teachers in charge for 2022-23

* Carole Delporte (IRIF, Université Paris Diderot) * Hugues Fauconnier (IRIF, Université Paris Diderot)

Sommaire / Summary

Distributed computing concerns designing and understanding algorithms for sets of independent computing units that have to communicate to coordinate their activities. The problem space of distributed computing is vast and it would be impossible to undertake an exhaustive study within a single course. Even a small-scale distributed system may expose an amazingly complex behavior that would make it very challenging to formally reason about. But we have to meet the challenge! Due to inherent limitations of centralized computing, all computing systems nowadays is becoming distributed, ranging from Internet-scale services to multiprocessors. Therefore, understanding the principles of distribution and concurrency is indispensable in all aspects of designing and engineering modern computing systems. The main challenge here is to balance correctness of the system's executions with its availability and efficiency, in the presence of possible misbehavior of the system components and the environment (such as faults and asynchrony).

This course discusses how to design distributed algorithms, reason about their correctness, and derive matching complexity bounds. The primary focus of the module is on understanding of the foundations of distributed computing. This course focuses on the models in which computing units communicate through a shared memory. The related course 2.18.1 deals with distributed algorithms for synchronous networks.


Lectures are given in French.


P1, Tuesdays, starting from 13/09/2020, 16h15-19h15, Bat. Sophie Germain, Room 1004

Part I

In this part, we introduce the notion of synchronization and consistency in shared-memory distributed computing and discuss different synchronization techniques

  • Introduction, theory and practice of distributed systems
  • Synchronization; mutual exclusion
Part II

In this part, we discuss nonblocking and wait-free implementation of shared-memory abstractions, the fundamental problem of consensus, and the notion of a universal construction.

  • Safe, regular, and atomic registers
  • Atomic-object implementations, atomic snapshot as an example
  • Herlihy's hierarchy of atomic objects
  • Consensus universality
Part III

In this part, we study two or three of these topics:

  • Distributed tasks: k-set agreement, renaming
  • Safe agreement
  • Random consensus
  • t-resilience
  • Failures detectors
  • Simulation of Borowsky and Gafni, with applications.
  • Byzantine failures

Planning prévisionnel/Preliminary schedule

13/09/2022 Introduction: synchronization, mutual exclusion PDF ancien PDF PDF
20/09/2022 Read-write shared memory basics; Atomic snapshot, Objects, Linearizability PDF
20/09/2022 PDF
27/09/2022 Hiérarchie, universalité impossibilité du consensus PDF
4/10/2022 immediate snapshot, task PDF PDF
11/10/2022 k-agreement, Consensus t-resilient, transmission de message PDF
18/10/2022 Consensus affaibli, Détecteurs de défaillances PDF
25/10/2022 Simulation de Borowsky-Gafni, Renaming DEVOIR A RENDRE LE 4/11 PDF
01/11/2022 férié
8/11/2022 Correction devoir, renaming, Byzantins PDF
15/11/2022 pas de cours
22/11/2022 Examen (16h15-19h15) aucun document autoriséannale

Pré-requis / Prerequisites

None, though some maturity in mathematical reasoning and algorithms is expected.

Livres conseillés / Literature

* R. Guerraoui and P. Kuznetsov. Algorithms for concurrent systems. PPUR, 2019

* Maurice Herlihy and Nir Shavit ((Victor Luchangco, Michael Spear). The art of multiprocessor programming. Morgan Kaufmann 2008 (2020).

* Hagit Attiya and Jennifer Welch. Distributed Computing: Fundamentals, Simulations, and Advanced Topics. John Wiley and Sons, Inc.

* Lynch, N: Distributed Algorithms. Morgan Kaufmann Publishers, 1996 * M. Herlihy, D. Kozlov, S. Rajsbaum: Distributed Computing Through Combinatorial Topology Morgan Kaufman 2013.

* Michel Raynal: Concurrent Programming: Algorithms, Principles and Foundations (springer)
Distributed Algorithms for Message-Passing Systems (Springer) * Michel Raynal: Fault-tolerant Message-passing Distributed Systems: An Algorithmic Approach (Springer)

Liste cohérentes de cours sur la thématique ” Algorithmes et complexité” / Related Courses

Equipe pédagogique

* Carole Delporte (Professeur, IRIF, Université Paris Cite) * Hugues Fauconnier (Professeur, IRIF, Université Paris Cité) * Pierre Fraigniaud (Directeur de Recherche CNRS, IRIF, Université Paris Cité) * Laurent Viennot (Directeur de Recherche INRIA, IRIF, Université Paris Cité)

Universités partenaires Université Paris-Diderot
Université Paris-Saclay
ENS Cachan École polytechnique Télécom ParisTech
Établissements associés Université Pierre-et-Marie-Curie CNRS INRIA CEA