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Parallel task scheduling (also called parallel job scheduling [1] [2] or parallel processing scheduling [3]) is an optimization problem in computer science and operations research. It is a variant of optimal job scheduling .
In computer science, gang scheduling is a scheduling algorithm for parallel systems that schedules related threads or processes to run simultaneously on different processors. Usually these will be threads all belonging to the same process, but they may also be from different processes, where the processes could have a producer-consumer ...
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 ]
In single-stage job scheduling problems, there are four main categories of machine environments: 1: Single-machine scheduling. There is a single machine. P: Identical-machines scheduling. There are parallel machines, and they are identical. Job takes time on any machine it is scheduled to.
"Embarrassingly" is used here to refer to parallelization problems which are "embarrassingly easy". [4] The term may imply embarrassment on the part of developers or compilers: "Because so many important problems remain unsolved mainly due to their intrinsic computational complexity, it would be embarrassing not to develop parallel implementations of polynomial homotopy continuation methods."
Modules can be nested using the two tier model, where the outer level is composed of task parallel skeletons, while data parallel skeletons may be used in the inner level [64]. Type verification is performed at the data flow level, when the programmer explicitly specifies the type of the input and output streams, and by specifying the flow of ...
The randomized variant due to Blumofe and Leiserson executes a parallel computation in expected time / + on processors; here, is the work, or the amount of time required to run the computation on a serial computer, and is the span, the amount of time required on an infinitely parallel machine. [note 2] This means that, in expectation, the time ...
In computer science, a parallel algorithm, as opposed to a traditional serial algorithm, is an algorithm which can do multiple operations in a given time. It has been a tradition of computer science to describe serial algorithms in abstract machine models, often the one known as random-access machine.