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Dependencies among tasks have a major impact on the emerging algorithm design There are two categories of dependencies, ordering constraints and dependencies related t shared data o For this pattern, ordering constraints apply to task groups and can be handled by forcing the groups to execute in the required order For example, in a task parallel multidimensional Fast Fourier Transform, there is a group of tasks for each dimension of the transform, and synchronization or other program constructs are used to make sure computation on one dimension completes before the next dimension begins Alternatively, we could simply think of such a problem as a sequential composition of task parallel computations, one for each task group Shared data dependencies are potentially more complicated In the simplest case, there are no dependencies among the tasks A surprisingly large number of problems can be cast into this form Such problems are often called embarrassingly parallel Their solutions are among the simplest of parallel programs; the main considerations are how the tasks are defined (as discussed previously) and scheduled (as discussed later) When data is shared among tasks, the algorithm can be much more complicated, although there are still some common cases that can be dealt with relatively easily We can categorize dependencies as follows how to write pdf file in asp.net c# How to Easily Create a PDF Document in ASP . NET Core Web API
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