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Multithreading (computer architecture) In computer architecture, multithreading is the ability of a central processing unit (CPU) (or a single core in a multi-core processor) to provide multiple threads of execution. There are two common approaches for multi threading: parallel multithreading and concurrent multithreading.
The multiple threads of a given process may be executed concurrently (via multithreading capabilities), sharing resources such as memory, while different processes do not share these resources. In particular, the threads of a process share its executable code and the values of its dynamically allocated variables and non- thread-local global variables at any given time.
Speculative multithreading. Thread Level Speculation ( TLS ), also known as Speculative Multi-threading, or Speculative Parallelization, [1] is a technique to speculatively execute a section of computer code that is anticipated to be executed later in parallel with the normal execution on a separate independent thread.
Thread pool. In computer programming, a thread pool is a software design pattern for achieving concurrency of execution in a computer program. Often also called a replicated workers or worker-crew model, [1] a thread pool maintains multiple threads waiting for tasks to be allocated for concurrent execution by the supervising program. By ...
The Vanderbilt University Medical Center ( VUMC) is a medical provider with multiple hospitals in Nashville, Tennessee, as well as clinics and facilities throughout Middle Tennessee. VUMC is an independent non-profit organization, but maintains academic affiliations with Vanderbilt University. As of 2023, the health system had more than 3 million patient visits a year, a workforce of 40,000 ...
Concurrent data structure. In computer science, a concurrent data structure is a particular way of storing and organizing data for access by multiple computing threads (or processes) on a computer. Historically, such data structures were used on uniprocessor machines with operating systems that supported multiple computing threads (or processes ).
Distributed programming – have support for multiple autonomous computers that communicate via computer networks. Functional programming – uses evaluation of mathematical functions and avoids state and mutable data. Generic programming – uses algorithms written in terms of to-be-specified-later types that are then instantiated as needed ...
Work stealing. In parallel computing, work stealing is a scheduling strategy for multithreaded computer programs. It solves the problem of executing a dynamically multithreaded computation, one that can "spawn" new threads of execution, on a statically multithreaded computer, with a fixed number of processors (or cores ).