Programming with Auto-parallelization
The auto-parallelization feature implements
of OpenMP*,such as the worksharing construct (with the
directive). This section provides details on auto-parallelization.
Guidelines for Effective Auto-parallelization Usage
A loop can be parallelized if it meets the following criteria:
- The loop is countable at compile time: This means that an expression representing how many times the loop will execute (loop trip count) can be generated just before entering the loop.
- There are noFLOW(READafterWRITE),OUTPUT(WRITEafterWRITE) orANTI(WRITEafterREAD) loop-carried data dependencies. A loop-carried data dependency occurs when the same memory location is referenced in different iterations of the loop. At the compiler's discretion, a loop may be parallelized if any assumed inhibiting loop-carried dependencies can be resolved by run-time dependency testing.
The compiler may generate a run-time test for the profitability of executing in parallel for loop, with loop parameters that are not compile-time constants.
Enhance the power and effectiveness of the auto-parallelizer by following these coding guidelines:
- Expose the trip count of loops whenever possible; use constants where the trip count is known and save loop parameters in local variables.
- Avoid placing structures inside loop bodies that the compiler may assume to carry dependent data, for example, procedure calls, ambiguous indirect references or global references.