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Both types are listed, as concurrency is a useful tool in expressing parallelism, but it is not necessary. In both cases, the features must be part of the language syntax and not an extension such as a library (libraries such as the posix-thread library implement a parallel execution model but lack the syntax and grammar required to be a ...
The non-Python library being called to perform the CPU-intensive task is not subject to the GIL and may concurrently execute many threads on multiple processors without restriction. Concurrency of Python code can only be achieved with separate CPython interpreter processes managed by a multitasking operating system.
OpenMP (Open Multi-Processing) is an application programming interface (API) that supports multi-platform shared-memory multiprocessing programming in C, C++, and Fortran, [3] on many platforms, instruction-set architectures and operating systems, including Solaris, AIX, FreeBSD, HP-UX, Linux, macOS, and Windows.
Multiprocessing is the use of two or more central processing units (CPUs) within a single computer system. [ 1 ] [ 2 ] The term also refers to the ability of a system to support more than one processor or the ability to allocate tasks between them.
OpenVMS, often referred to as just VMS, [8] is a multi-user, multiprocessing and virtual memory-based operating system.It is designed to support time-sharing, batch processing, transaction processing and workstation applications. [9]
The term "multiprocessor" can be confused with the term "multiprocessing". While multiprocessing is a type of processing in which two or more processors work together to execute multiple programs simultaneously, multiprocessor refers to a hardware architecture that allows multiprocessing. [5]
The term multithreading is ambiguous, because not only can multiple threads be executed simultaneously on one CPU core, but also multiple tasks (with different page tables, different task state segments, different protection rings, different I/O permissions, etc.). Although running on the same core, they are completely separated from each other.
This was required due to Fedora's transition from Python 2 to Python 3, which isn't supported by YUM. [10] DNF also improves on YUM in several ways - improved performance, better resolution of dependency conflicts, and easier integration with other software applications. [11] From RHEL 8, yum is an alias for DNF. [12]