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You haven't shown anything to

You haven't shown anything to indicate why there should be a problem with your first version (unlike the second).  Most OpenMP implementations keep the thread pool active for a while after a parallel...

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My comment is Not related to

My comment is Not related to your questions and it is rather about possible performance issues.You could have a problem with indx=1,N and indx=1,M statements if your processing is done on different...

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Extending Sergey's comment

Extending Sergey's comment further. If in the case where Task1 and Task2 are both run .AND. outputs are independent .AND. inputs are somewhat the same, then consider something along the line of!$omp...

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Thank you all for your

Thank you all for your responses.  Task1 and Task2 process two independent and large data sets.  Jim, I will try your suggestion. Thanks again.Jon

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Jon,

Jon,The suggestion I made will help when the input data for the two tasks are shared (either completely or partially). Essentially the technique is attempting to re-use data in cache in Task2 that was...

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You haven't shown anything to

You haven't shown anything to indicate why there should be a problem with your first version (unlike the second).  Most OpenMP implementations keep the thread pool active for a while after a parallel...

View Article

My comment is Not related to

My comment is Not related to your questions and it is rather about possible performance issues.You could have a problem with indx=1,N and indx=1,M statements if your processing is done on different...

View Article

Extending Sergey's comment

Extending Sergey's comment further. If in the case where Task1 and Task2 are both run .AND. outputs are independent .AND. inputs are somewhat the same, then consider something along the line of!$omp...

View Article


Thank you all for your

Thank you all for your responses.  Task1 and Task2 process two independent and large data sets.  Jim, I will try your suggestion. Thanks again.Jon

View Article


Jon,

Jon,The suggestion I made will help when the input data for the two tasks are shared (either completely or partially). Essentially the technique is attempting to re-use data in cache in Task2 that was...

View Article
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