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  2. Parallel task scheduling - Wikipedia

    en.wikipedia.org/wiki/Parallel_task_scheduling

    To schedule a job , an algorithm has to choose a machine count and assign j to a starting time and to machines during the time interval [, +,). A usual assumption for this kind of problem is that the total workload of a job, which is defined as d ⋅ p j , d {\displaystyle d\cdot p_{j,d}} , is non-increasing for an increasing number of machines.

  3. Automatic parallelization - Wikipedia

    en.wikipedia.org/wiki/Automatic_parallelization

    The scheduler will generate a list of all the tasks and the details of the cores on which they will execute along with the time that they will execute for. The code Generator will insert special constructs in the code that will be read during execution by the scheduler.

  4. Job-shop scheduling - Wikipedia

    en.wikipedia.org/wiki/Job-shop_scheduling

    The basic form of the problem of scheduling jobs with multiple (M) operations, over M machines, such that all of the first operations must be done on the first machine, all of the second operations on the second, etc., and a single job cannot be performed in parallel, is known as the flow-shop scheduling problem.

  5. Optimal job scheduling - Wikipedia

    en.wikipedia.org/wiki/Optimal_job_scheduling

    Optimal job scheduling is a class of optimization problems related to scheduling. The inputs to such problems are a list of jobs (also called processes or tasks) and a list of machines (also called processors or workers). The required output is a schedule – an assignment of jobs to machines. The schedule should optimize a certain objective ...

  6. Fork–join model - Wikipedia

    en.wikipedia.org/wiki/Fork–join_model

    Fork–join is the main model of parallel execution in the OpenMP framework, although OpenMP implementations may or may not support nesting of parallel sections. [6] It is also supported by the Java concurrency framework, [7] the Task Parallel Library for .NET, [8] and Intel's Threading Building Blocks (TBB). [1]

  7. Task parallelism - Wikipedia

    en.wikipedia.org/wiki/Task_parallelism

    Task parallelism (also known as function parallelism and control parallelism) is a form of parallelization of computer code across multiple processors in parallel computing environments. Task parallelism focuses on distributing tasks —concurrently performed by processes or threads —across different processors.

  8. Concurrency (computer science) - Wikipedia

    en.wikipedia.org/wiki/Concurrency_(computer_science)

    The parallel random-access machine [10] The actor model; Computational bridging models such as the bulk synchronous parallel (BSP) model; Petri nets; Process calculi. Calculus of communicating systems (CCS) Communicating sequential processes (CSP) model; π-calculus; Tuple spaces, e.g., Linda; Simple Concurrent Object-Oriented Programming (SCOOP)

  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 ...