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Séance de cours

Concurrent Stack: Mise en œuvre

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 explore la mise en œuvre d'une structure de données de pile concurrente, qui suit la dernière propriété en premier. L'instructeur explique comment les opérations push et pop fonctionnent simultanément en mettant à jour le champ supérieur à l'aide des opérations de comparaison et d'échange.

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.

Source officielle

Concepts associés (12)

Compare-and-swap

Compare-and-swap (CAS) est une instruction atomique utilisée dans les systèmes multiprocesseurs ou multi-cœurs utilisant une mémoire partagée. Elle compare la valeur stockée à une adresse mémoire donnée à l'un de ses arguments et, en cas d'égalité, écrit une nouvelle valeur à cette adresse. Selon les implémentations, elle signale si l'écriture a réussi soit en renvoyant une valeur booléenne, soit en renvoyant la valeur lue en mémoire.

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).

Linearizability

In concurrent programming, an operation (or set of operations) is linearizable if it consists of an ordered list of invocation and response events, that may be extended by adding response events such that: The extended list can be re-expressed as a sequential history (is serializable). That sequential history is a subset of the original unextended list. Informally, this means that the unmodified list of events is linearizable if and only if its invocations were serializable, but some of the responses of the serial schedule have yet to return.

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.

Read–modify–write

In computer science, read–modify–write is a class of atomic operations (such as test-and-set, fetch-and-add, and compare-and-swap) that both read a memory location and write a new value into it simultaneously, either with a completely new value or some function of the previous value. These operations prevent race conditions in multi-threaded applications. Typically they are used to implement mutexes or semaphores. These atomic operations are also heavily used in non-blocking synchronization.

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Séances de cours associées (32)

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.

Verrouillages : Mise en place de mécanismes de comptabilisation des devises

Couvre la mise en œuvre des serrures en utilisant compareAndSet et le concept de serrures équitables.

Concurrent Stack: Mise en œuvre

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

Modèles de mémoire: Visibilité et sémantique

Explique le modèle Java Memory et le thread démarrent la sémantique pour les programmes simultanés.

Synchronisation primitives

Explore la conception des primitives de synchronisation et des structures de données concurrentes à l'aide d'instructions atomiques.

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Concepts associés (12)

Compare-and-swap

Programmation concurrente

Linearizability

Concurrency (computer science)

Read–modify–write

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