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  2. File:Non-Programmer's Tutorial for Python 3.pdf - Wikipedia

    en.wikipedia.org/wiki/File:Non-Programmer's...

    You are free: to share – to copy, distribute and transmit the work; to remix – to adapt the work; Under the following conditions: attribution – You must give appropriate credit, provide a link to the license, and indicate if changes were made.

  3. 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.

  4. Linda (coordination language) - Wikipedia

    en.wikipedia.org/wiki/Linda_(coordination_language)

    Python: PyLinda; Ruby: Rinda; Swift: pSpaces; Some of the more notable Linda implementations include: C-Linda or TCP-Linda - the earliest commercial and a widespread implementation of virtual shared memory for supercomputers and clustered systems from Scientific Computing Associates, founded by Martin Schultz.

  5. OpenBLAS - Wikipedia

    en.wikipedia.org/wiki/OpenBLAS

    OpenBLAS is an open-source implementation of the BLAS (Basic Linear Algebra Subprograms) and LAPACK APIs with many hand-crafted optimizations for specific processor types. It is developed at the Lab of Parallel Software and Computational Science, ISCAS.

  6. Multiprocessing - Wikipedia

    en.wikipedia.org/wiki/Multiprocessing

    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.

  7. Fork–join model - Wikipedia

    en.wikipedia.org/wiki/Fork–join_model

    Implementations of the fork–join model will typically fork tasks, fibers or lightweight threads, not operating-system-level "heavyweight" threads or processes, and use a thread pool to execute these tasks: the fork primitive allows the programmer to specify potential parallelism, which the implementation then maps onto actual parallel execution. [1]

  8. Single program, multiple data - Wikipedia

    en.wikipedia.org/wiki/Single_program,_multiple_data

    In computing, single program, multiple data (SPMD) is a term that has been used to refer to computational models for exploiting parallelism whereby multiple processors cooperate in the execution of a program in order to obtain results faster.

  9. Thread (computing) - Wikipedia

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

    A process with two threads of execution, running on one processor Program vs. Process vs. Thread Scheduling, Preemption, Context Switching. In computer science, a thread of execution is the smallest sequence of programmed instructions that can be managed independently by a scheduler, which is typically a part of the operating system. [1]