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A lock-free data structure can be used to improve performance. A lock-free data structure increases the amount of time spent in parallel execution rather than serial execution, improving performance on a multi-core processor, because access to the shared data structure does not need to be serialized to stay coherent. [4]
(Singly) linked lists are fundamental data structures that are widely used as is, or to build other data structures. They consist of "nodes", or "links", that are put in some order indicated by a "next" pointer on each node. The last node in the list (the "tail") has a nil next pointer.
State-based CRDTs (also called convergent replicated data types, or CvRDTs) are defined by two types, a type for local states and a type for actions on the state, together with three functions: A function to produce an initial state, a merge function of states, and a function to apply an action to update a state. State-based CRDTs simply send ...
Any lock-free data structure that uses the compare-and-swap primitive must deal with the ABA problem. For example, in a lock-free stack represented as an intrusively linked list, one thread may be attempting to pop an item from the front of the stack (A → B → C).
The POSIX pthread API provides lock support. [9] Visual C++ provides the synchronize attribute of methods to be synchronized, but this is specific to COM objects in the Windows architecture and Visual C++ compiler. [10] C and C++ can easily access any native operating system locking features.
The NIST Dictionary of Algorithms and Data Structures [1] is a reference work maintained by the U.S. National Institute of Standards and Technology. It defines a large number of terms relating to algorithms and data structures. For algorithms and data structures not necessarily mentioned here, see list of algorithms and list of data structures.
STM can be implemented as a lock-free algorithm or it can use locking. [7] There are two types of locking schemes: In encounter-time locking (Ennals, Saha, and Harris), memory writes are done by first temporarily acquiring a lock for a given location, writing the value directly, and logging it in the undo log.
This is often a stop-the-world process that traverses a whole table and rewrites it with the last version of each data item. PostgreSQL can use this approach with its VACUUM FREEZE process. Other databases split the storage blocks into two parts: the data part and an undo log. The data part always keeps the last committed version.