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Note: Incorrect specification of a reduction function (for example, specifying MIN instead of MAX) is not detected by this method. Use the trace comparison method to detect such errors.
3.1.5Checking usage of remote access buffer
The remote data buffer is used for pre-loading of non-local elements required for the each processor. The same verifications are performed for a remote data buffer and for a distributed array. But there are few exclusions:
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Verifying the data dependencies in a parallel construction takes into account that the remote data buffer is used instead of distributed array.
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Verifying the array initialization is performed both for remote data buffer elements and elements of related distributed array. The initialization of remote data buffer is copying of distributed array elements to remote data buffer.
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Only read operations are allowed for elements of the remote data buffer.
3.2The “Comparing execution results” method
3.2.1Trace accumulation
The following trace information is accumulated in a trace file:
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Values of all variables accessed for reading.
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Values of all variables accessed for writing.
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Results of reduction operations.
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Beginning of a task region or parallel and sequential loop.
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Beginning of iteration or parallel task.
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End of a task region or parallel and sequential loop.
Each record in the trace file has reference to a line of the source program.
Since this method requires considerable overhead the means to control trace detailing are provided.
The content of a special file (trace configuration file) determines detailing of the trace. This file contains description of all program loops and task regions.
To decrease trace size the following accumulation levels are provided:
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No trace information.
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Only the information about loops, task regions, tasks and iterations are accumulated.
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In addition to the previous level the information about variable modifications are accumulated.
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In addition to the previous level the information about all usage of the variables are accumulated.
Furthermore, you can specify for each loop an iteration range and for each task region an task range, which the information about variable usage will be accumulated for.
3.2.2Trace comparing
In the comparing mode the trace-file is read into the memory before program startup. The structure of trace in the memory is formed by the same functions that are used in the accumulation mode. As result, we have the same trace structure in the memory both after accumulating and after reading the trace.
Then during program execution the occurred events are compared with reference ones.
There are the following singularities of parallel program execution:
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Values of reduction variables inside a parallel construction can be different in the sequential and parallel modes. Therefore comparing values of reduction variables inside a parallel constructions isn’t performed.
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In the parallel mode an order of parallel loop iterations and parallel tasks can be changed. Therefore at the iteration and task beginning the corresponding reference trace record is searched for and set as current.
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In the parallel mode a sequential branch can miss statements, which calculate and assign values to non-local elements of distributed arrays.
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Inside the parallel construction some references to variables used for calculation of reduction maximum or minimum may be missed in the sequential or parallel modes.
3.2.3Checking reduction operations
Reduction variable accumulation has a special implementation. The values of reduction variables inside a parallel constructions aren’t compared with reference ones. Comparison is performed only for reduction result.
There are two ways to calculate a reduction operation. The first way is a standard method of reduction performance. Program statements inside an iteration or task perform all computations of a reduction variable on the its own processor. The final result of reduction operation between processors is computed by Lib-DVM. If a program is performed on a single processor only program statements will compute the reduction.
The second way is emulation of performing each iteration and parallel task on a separate processor. At the beginning of iteration and task the initial value is assigned to reduction variable. The initial value is stored before parallel construction beginning. Upon end of iteration and task the reduction is performed by Lib-DVM according to specified reduction function.
To perform reduction checking the comparing of program execution results is performed for each method that described above. If a program specify the reduction function correctly the reduction results will be the same for both ways. Otherwise the error of differences of reduction results will be reported for user.
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