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  2. Multiprocessing - Wikipedia

    en.wikipedia.org/wiki/Multiprocessing

    Multiprocessing however means true parallel execution of multiple processes using more than one processor. [7] Multiprocessing doesn't necessarily mean that a single process or task uses more than one processor simultaneously; the term parallel processing is generally used to denote that scenario. [6]

  3. Process (computing) - Wikipedia

    en.wikipedia.org/wiki/Process_(computing)

    However, in multiprocessing systems many processes may run off of, or share, the same reentrant program at the same location in memory, but each process is said to own its own image of the program. Processes are often called "tasks" in embedded operating systems. The sense of "process" (or task) is "something that takes up time", as opposed to ...

  4. Concurrent computing - Wikipedia

    en.wikipedia.org/wiki/Concurrent_computing

    In this way, multiple processes are part-way through execution at a single instant, but only one process is being executed at that instant. [citation needed] Concurrent computations may be executed in parallel, [3] [6] for example, by assigning each process to a separate processor or processor core, or distributing a computation across a network.

  5. Computer multitasking - Wikipedia

    en.wikipedia.org/wiki/Computer_multitasking

    At any specific time, processes can be grouped into two categories: those that are waiting for input or output (called "I/O bound"), and those that are fully utilizing the CPU ("CPU bound"). In primitive systems, the software would often "poll", or "busywait" while waiting for requested input (such as disk, keyboard or network input). During ...

  6. Dask (software) - Wikipedia

    en.wikipedia.org/wiki/Dask_(software)

    Due to Python’s Global Interpreter Lock, local threads provide parallelism only when the computation is primarily non-Python code, which is the case for Pandas DataFrame, Numpy arrays or other Python/C/C++ based projects. Local process A multiprocessing scheduler leverages Python’s concurrent.futures.ProcessPoolExecutor to execute computations.

  7. CPython - Wikipedia

    en.wikipedia.org/wiki/CPython

    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.

  8. Multiprocessor system architecture - Wikipedia

    en.wikipedia.org/wiki/Multiprocessor_system...

    A cc–NUMA system is a cluster of SMP systems – each called a "node", which can have a single processor, a multi-core processor, or a mix of the two, of one or other kinds of architecture – connected via a high-speed "connection network" that can be a "link" that can be a single or double-reverse ring, or multi-ring, point-to-point ...

  9. Single program, multiple data - Wikipedia

    en.wikipedia.org/wiki/Single_program,_multiple_data

    The (IBM) SPMD programming model assumes a multiplicity of processors which operate cooperatively, all executing the same program but can take different paths through the program based on parallelization directives embedded in the program; and specifically as stated in [6] [5] [4] [9] [10] “all processes participating in the parallel ...