Lecture

Concurrent Stack: Implementation

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In course

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

This lecture explores the concept of a concurrent stack, a data structure that follows the last in first out property. The instructor explains the push and pop operations, the use of atomic references, and the compare and set operations involved in implementing a concurrent stack. The lecture also covers the reference implementation of a concurrent stack, highlighting the importance of maintaining the integrity of the data structure in a concurrent environment.

Instructors (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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Related concepts (16)

Persistent data structure

In computing, a persistent data structure or not ephemeral data structure is a data structure that always preserves the previous version of itself when it is modified. Such data structures are effectively immutable, as their operations do not (visibly) update the structure in-place, but instead always yield a new updated structure. The term was introduced in Driscoll, Sarnak, Sleator, and Tarjans' 1986 article. A data structure is partially persistent if all versions can be accessed but only the newest version can be modified.

Purely functional data structure

In computer science, a purely functional data structure is a data structure that can be directly implemented in a purely functional language. The main difference between an arbitrary data structure and a purely functional one is that the latter is (strongly) immutable. This restriction ensures the data structure possesses the advantages of immutable objects: (full) persistency, quick copy of objects, and thread safety. Efficient purely functional data structures may require the use of lazy evaluation and memoization.

Data structure

In computer science, a data structure is a data organization, management, and storage format that is usually chosen for efficient access to data. More precisely, a data structure is a collection of data values, the relationships among them, and the functions or operations that can be applied to the data, i.e., it is an algebraic structure about data. Data structures serve as the basis for abstract data types (ADT). The ADT defines the logical form of the data type. The data structure implements the physical form of the data type.

Implementation

Implementation is the realization of an application, execution of a plan, idea, model, design, specification, standard, algorithm, policy, or the administration or management of a process or objective. In computer science, an implementation is a realization of a technical specification or algorithm as a program, software component, or other computer system through computer programming and deployment. Many implementations may exist for a given specification or standard.

Multiuser DOS

Multiuser DOS is a real-time multi-user multi-tasking operating system for IBM PC-compatible microcomputers. An evolution of the older Concurrent CP/M-86, Concurrent DOS and Concurrent DOS 386 operating systems, it was originally developed by Digital Research and acquired and further developed by Novell in 1991. Its ancestry lies in the earlier Digital Research 8-bit operating systems CP/M and MP/M, and the 16-bit single-tasking CP/M-86 which evolved from CP/M.

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Atomic Operations: Basics and Applications

Covers the basics of atomic operations in concurrency and parallelism, including hardware-provided operations and synchronized algorithms.

Concurrent Stack: Implementation

Explains the reference implementation for a concurrent stack and the importance of handling concurrency issues.

New Technologies in Concurrent Algorithms: RDMA & Persistent Memory

Introduces RDMA and Persistent Memory, discussing their features, challenges, and impact on concurrent algorithms.

Model Representation: Structures and Functions

Covers the representation of mathematical models, functions, and data structures in information systems.

Concurrent Stack: Implementation

Explores the implementation of a concurrent stack data structure and how push and pop operations work concurrently.

Related concepts (16)

Persistent data structure

Purely functional data structure

Data structure

Implementation

Multiuser DOS