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Séance de cours

Buffer en un seul endroit : Mise en oeuvre basée sur le suivi

Dans cours

CS-206: Parallelism and concurrency

Course no longer offered for new students; this edition is only a make-up course for those who repeated the year. Please log in with EPFL credentials and consult the mediaspace link below for course videos. ...

Description

Cette séance de cours couvre la mise en place d'un tampon en un seul endroit à l'aide de moniteurs dans un environnement concurrent, en discutant de concepts tels que l'attente, l'avis et l'avis All. L'instructeur explique les mécanismes de synchronisation et les problèmes potentiels comme les impasses qui peuvent survenir dans de telles implémentations.

Enseignant·e·s (3)

Sanidhya Kashyap

Sanidhya Kashyap is a systems researcher and an assistant professor at the EPFL School of Computer and Communication Sciences (IC). His research focuses on designing systems software that are performant and robust for heterogeneous hardware. He is broadly interested in the area of systems with a particular focus on operating systems, databases, concurrency, scheduling, networks, data analytics, and software testing (fuzzing).

Martin Odersky

Martin Odersky heads the programming research group at EPFL. His research interests cover fundamental as well as applied aspects of programming languages. They include semantics, type systems, programming language design, and compiler construction. The main focus if his work lies in the integration of object-oriented and functional programming. His research thesis is that the two paradigms are just two sides of the same coin and should be unified as much as possible. To prove this he has experimented a number of language designs, from Pizza to GJ to Functional Nets. He has also influenced the development of Java as a co-designer of Java generics and as the original author of the current javac reference compiler. His current work concentrates on the Scala programming language, which unifies FP and OOP, while staying completely interoperable with Java and .NET. Martin Odersky got his doctorate from ETHZ, in 1989. He held research positions at the IBM T.J. Watson Research Center from 1989 and at Yale University from 1991. He was then a professor at the University of Karlsruhe from 1993 and at the University of South Australia from 1997. He joined EPFL as full professor in 1999. He is associate editor of the Journal of Functional Programming and member of IFIP WG 2.8. He was conference chair for ICFP 2000, and program chair for ECOOP 2004 as well as ETAPS/CC 2007.

Viktor Kuncak

Viktor Kunčak joined EPFL in 2007, after receiving a PhD degree from MIT. Since then has been leading the Laboratory for Automated Reasoning and Analysis and supervised at least 12 completed PhD theses. His works on languages, algorithms and systems for verification and automated reasoning. He served as an initiator and one of the coordinators of a European network (COST action) in the area of automated reasoning, verification, and synthesis. In 2012 he received a 5-year single-investigator European Research Council (ERC) grant of 1.5M EUR. His invited talks include those at Lambda Days, Scala Days, NFM, LOPSTR, SYNT, ICALP, CSL, RV, VMCAI, and SMT. A paper on test generation he co-authored received an ACM SIGSOFT distinguished paper award at ICSE. A PLDI paper he co-authored was published in the Communications of the ACM as a Research Highlight article. His Google Scholar profile reports an over-approximate H-index of 38. He was an associate editor of ACM Transactions on Programming Languages and Systems (TOPLAS) and served as a co-chair of conferences on Computer-Aided Verification (CAV), Formal Methods in Computer Aided Design (FMCAD), Workshop on Synthesis (SYNT), and Verification, Model Checking, and Abstract Interpretation (VMCAI). At EPFL he teaches courses on functional and parallel programming, compilers, and verification. He has co-taught the MOOC "Parallel Programming" that was visited by over 100'000 learners and completed by thousands of students from all over the world.

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Concepts associés (20)

Concurrency control

In information technology and computer science, especially in the fields of computer programming, operating systems, multiprocessors, and databases, concurrency control ensures that correct results for concurrent operations are generated, while getting those results as quickly as possible. Computer systems, both software and hardware, consist of modules, or components. Each component is designed to operate correctly, i.e., to obey or to meet certain consistency rules.

Optimistic concurrency control

Optimistic concurrency control (OCC), also known as optimistic locking, is a concurrency control method applied to transactional systems such as relational database management systems and software transactional memory. OCC assumes that multiple transactions can frequently complete without interfering with each other. While running, transactions use data resources without acquiring locks on those resources. Before committing, each transaction verifies that no other transaction has modified the data it has read.

Programmation concurrente

La programmation concurrente est un paradigme de programmation tenant compte, dans un programme, de l'existence de plusieurs piles sémantiques qui peuvent être appelées threads, processus ou tâches. Elles sont matérialisées en machine par une pile d'exécution et un ensemble de données privées. La concurrence est indispensable lorsque l'on souhaite écrire des programmes interagissant avec le monde réel (qui est concurrent) ou tirant parti de multiples unités centrales (couplées, comme dans un système multiprocesseurs, ou distribuées, éventuellement en grille ou en grappe).

Multiversion Concurrency Control

Multiversion concurrency control (abrégé en MCC ou MVCC) est une méthode informatique de contrôle des accès concurrents fréquemment utilisée dans les systèmes de gestion de base de données et les langages de programmation concernant la gestion des caches en mémoire. Le principe de MVCC repose sur un verrouillage dit optimiste contrairement au verrouillage pessimiste qui consiste à bloquer préalablement les objets à des garanties de bonne fin. L'inconvénient logique est qu'une mise à jour peut être annulée du fait d'un "blocage" en fin de traitement.

Concurrency (computer science)

In computer science, concurrency is the ability of different parts or units of a program, algorithm, or problem to be executed out-of-order or in partial order, without affecting the outcome. This allows for parallel execution of the concurrent units, which can significantly improve overall speed of the execution in multi-processor and multi-core systems. In more technical terms, concurrency refers to the decomposability of a program, algorithm, or problem into order-independent or partially-ordered components or units of computation.

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Séances de cours associées (32)

Problème de philosophe de salle à manger

Présente un algorithme pour prévenir la famine et maximiser les philosophes qui mangent simultanément.

Vue d'ensemble de la concurrence

Explore l'importance de la concurrence dans l'amélioration des performances et de la réactivité du système, en mettant l'accent sur la nécessité de la synchronisation et de l'atomicité pour prévenir les conditions de course et le non-déterminisme.

Concurrence avec les contrats à terme

Explore l'avenir comme une approche structurée de la convergence, simplifiant les tâches parallèles et les opérations entrées-sorties.

Moniteurs : Synchronisation et coopération

Explore les moniteurs comme une construction de synchronisation fournissant l'exclusion mutuelle et la coopération entre les threads, avec des exemples comme le tampon d'un seul endroit.

Programmation parallèle: fondamentaux

Couvre les bases de la programmation parallèle, y compris l'exploitation du parallélisme dans les algorithmes et l'importance d'éviter les conditions de race.

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Concepts associés (20)

Concurrency control

Optimistic concurrency control

Programmation concurrente

Multiversion Concurrency Control

Concurrency (computer science)

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