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Séance de cours

Concurrent Stack: Mise en œuvre

Dans cours

CS-206: Parallelism and concurrency

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Description

Cette séance de cours présente l'implémentation de référence pour une pile concurrente, expliquant la structure des nœuds, l'utilisation des références atomiques et les opérations de push et pop. L'instructeur discute de l'importance de comparer et de définir les opérations et la nécessité de gérer les questions de concurrence.

Enseignant·e·s (3)

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 (11)

Arbre enraciné

En théorie des graphes, un arbre enraciné ou une arborescence est un graphe acyclique orienté possédant une unique racine, et tel que tous les nœuds sauf la racine ont un unique parent. En informatique, c'est également une structure de données récursive utilisée pour représenter ce type de graphes. Dans un arbre, on distingue deux catégories d'éléments : les feuilles (ou nœuds externes), éléments ne possédant pas de fils dans l'arbre ; les nœuds internes, éléments possédant des fils (sous-branches).

Arborescence

thumb|Exemple de représentation arborescente En mathématiques, plus précisément dans la théorie des graphes : une arborescence est un arbre comportant un sommet particulier , nommé racine de l'arborescence, à partir duquel il existe un chemin unique vers tous les autres sommets. En informatique, cette notion désigne souvent celle d'arbre de la théorie des graphes. Une arborescence désigne alors généralement une organisation des données en mémoire, de manière logique et hiérarchisée, utilisant une structure algorithmique d'arbre.

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.

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.

Node (computer science)

A node is a basic unit of a data structure, such as a linked list or tree data structure. Nodes contain data and also may link to other nodes. Links between nodes are often implemented by pointers. Nodes are often arranged into tree structures. A node represents the information contained in a single data structure. These nodes may contain a value or condition, or possibly serve as another independent data structure. Nodes are represented by a single parent node.

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Séances de cours associées (32)

Concurrent Stack: Mise en œuvre

Se penche sur la mise en œuvre d'une pile concurrente et l'utilisation de références atomiques.

Opérations atomiques : notions de base et applications

Couvre les bases des opérations atomiques dans la proximité et le parallélisme, y compris les opérations fournies par le matériel et les algorithmes synchronisés.

Programmation asynchrone : rappels et échecs

Couvre le concept de programmation asynchrone et comment gérer les dépendances et les échecs.

Sémantique du traitement des messages

Explore les principes de la programmation réactive et de la sémantique du traitement des messages en Akka, en mettant l'accent sur l'encapsulation des acteurs, la messagerie fiable et les garanties de livraison des messages.

Inférence de synchronisation

Explore la synthèse automatique de la synchronisation correcte et efficace dans les programmes, en mettant l'accent sur la suppression de l'atomicité redondante et l'ajout de métadonnées de synchronisation.

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Concepts associés (11)

Arbre enraciné

Arborescence

Concurrency control

Concurrency (computer science)

Node (computer science)

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