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The second most important environment variable is probably <tt>OMP_SCHEDULE</tt>. This one controls how loops (and, more generally, parallel sections) are distributed. The default value depends on the compiler, and can also be added into the source code. Possible values are | The second most important environment variable is probably <tt>OMP_SCHEDULE</tt>. This one controls how loops (and, more generally, parallel sections) are distributed. The default value depends on the compiler, and can also be added into the source code. Possible values are | ||
''static,n'', ''dynamic,n'', ''guided,n'' or ''auto''. For the first three cases, ''n'' corresponds to the number of iterations managed by each thread. For the ''static'' case, the number of iterations is fixed, and iterations are distributed at the beginning of the parallel section. For the ''dynamic'' case, the number of iterations is fixed, but they are distributed during execution, as a function of the time required by each thread to execute its iterations. For the ''guided'' case, ''n'' corresponds to the minimal number of iterations. The number of iterations is first chosen to be "large", but dynamically shrinks gradually as the remaining number of iterations diminishes. For the ''auto'' mode, the compiler and the library are free to choose what to do. | '''''static,n''''', '''''dynamic,n''''', '''''guided,n''''' or ''auto''. For the first three cases, ''n'' corresponds to the number of iterations managed by each thread. For the ''static'' case, the number of iterations is fixed, and iterations are distributed at the beginning of the parallel section. For the ''dynamic'' case, the number of iterations is fixed, but they are distributed during execution, as a function of the time required by each thread to execute its iterations. For the ''guided'' case, ''n'' corresponds to the minimal number of iterations. The number of iterations is first chosen to be "large", but dynamically shrinks gradually as the remaining number of iterations diminishes. For the ''auto'' mode, the compiler and the library are free to choose what to do. | ||
The advantage of the cases ''dynamic'', ''guided'' and ''auto'', is that they theoretically allow a better load-balancing of the threads as they dynamically adjust the work assigned to each thread. Their disadvantage is that the programmer does not know in advance on which core a certain thread executes, and which memory it will need to access. Hence, with this kind of scheduling, it is impossible to predict the affinity between memory and the executing core. This can be particularly problematic in a | The advantage of the cases ''dynamic'', ''guided'' and ''auto'', is that they theoretically allow a better load-balancing of the threads as they dynamically adjust the work assigned to each thread. Their disadvantage is that the programmer does not know in advance on which core a certain thread executes, and which memory it will need to access. Hence, with this kind of scheduling, it is impossible to predict the affinity between memory and the executing core. This can be particularly problematic in a | ||