Loop scheduling
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In parallel computing, loop scheduling is the problem of assigning proper iterations of parallelizable loops among n processors to achieve load balancing and maintain data locality with minimum dispatch overhead. Typical loop scheduling methods are: * static even scheduling: evenly divide loop iteration space into n chunks and assign each chunk to a processor * dynamic scheduling: a chunk of loop iteration is dispatched at runtime by an idle processor. When the chunk size is 1 iteration, it is also called self-scheduling. * guided scheduling: similar to dynamic scheduling, but the chunk sizes per dispatch keep shrinking until reaching a preset value.
In parallel computing, loop scheduling is the problem of assigning proper iterations of parallelizable loops among n processors to achieve load balancing and maintain data locality with minimum dispatch overhead. Typical loop scheduling methods are: static even scheduling: evenly divide loop iteration space into n chunks and assign each chunk to a processor dynamic scheduling: a chunk of loop iteration is dispatched at runtime by an idle processor. When the chunk size is 1 iteration, it is also called self-scheduling. guided scheduling: similar to dynamic scheduling, but the chunk sizes per dispatch keep shrinking until reaching a preset value. ==See also== OpenMP Automatic parallelization Loop nest optimization
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