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In software engineering, double-checked locking (also known as "double-checked locking optimization" [1]) is a software design pattern used to reduce the overhead of acquiring a lock by testing the locking criterion (the "lock hint") before acquiring the lock. Locking occurs only if the locking criterion check indicates that locking is required.
In computing, a futex (short for "fast userspace mutex") is a kernel system call that programmers can use to implement basic locking, or as a building block for higher-level locking abstractions such as semaphores and POSIX mutexes or condition variables.
In computer architecture, the test-and-set CPU instruction (or instruction sequence) is designed to implement mutual exclusion in multiprocessor environments. Although a correct lock can be implemented with test-and-set, the test and test-and-set optimization lowers resource contention caused by bus locking, especially cache coherency protocol overhead on contended locks.
Free and open-source software portal; Lightning Memory-Mapped Database (LMDB) is an embedded transactional database in the form of a key-value store.LMDB is written in C with API bindings for several programming languages.
Some examples include: lock hierarchies, [1] lock reference-counting and preemption (either using versioning or allowing data corruption when preemption occurs); Wait-For-Graph (WFG) algorithms, which track all cycles that cause deadlocks (including temporary deadlocks); and heuristics algorithms which don't necessarily increase parallelism in ...
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.
Database caching is a process included in the design of computer applications which generate web pages on-demand (dynamically) by accessing backend databases.. When these applications are deployed on multi-tier environments that involve browser-based clients, web application servers and backend databases, [1] [2] middle-tier database caching is used to achieve high scalability and performance.
In computer science, the thundering herd problem occurs when a large number of processes or threads waiting for an event are awoken when that event occurs, but only one process is able to handle the event. When the processes wake up, they will each try to handle the event, but only one will win.