2.14 Correcting KAP Problems

The following are some problems you may encounter when using KAP and possible fixes and workarounds:

• KAP works best on programs that are CPU-intensive, that spend a great deal of time doing floating-point calculations, and that have large loop bounds.

  The two most common reasons KAP is unable to achieve performance improvement in applications code are the following:

  • A program with small loop limits or too few loops to work with will cause KAP vectorization setup overhead to outweigh the speedup.

  • A program that is I/O bound is not likely to achieve much performance improvement because no amount of improvement to the computation sections will change execution time significantly. However, in the case of a C program, I/O strength reduction can improve I/O performance. Profiling information may provide clues to either problem. You may need to insert additional print statements to verify loop limits.

• If the program is correct but the output is significantly different when KAP is run on the program, try reducing the setting on the /optimize qualifier.

• Nonsensical or nonrepeatable values in the output can be the result of the program violating declared array bounds. Try compiling the original source code with array bounds checking enabled. If the program is violating array bounds, you may be able to work around the problem by using /assume=b or the assertion C*$* assert bounds violation . Nonsensical or nonrepeatable values in the output may also be the result of unstable algorithms. Try setting /roundoff=0 .

  For Fortran programs, also try /save=all in case the save statements you have supplied in the code are incorrect or insufficient for the compiler you are using.

• If you get incorrect results from a large program with a few routines run through KAP, or a small program run through KAP, or a program with a few routines inlined by KAP, you may be able to determine the source of the problem by means of binary chop.

  For example, suppose you have five routines, a, b, c, d, and e. When all five are processed with KAP, the program produces incorrect results or dies. Try running KAP again, but only on routines a and b. If they succeed, then the problem is in c, d, or e. If they fail, try with just routine a, and so on. By breaking the list of suspects into approximate halves for each test, you can fairly quickly identify which routine or routines cause the failure. Leave the problematic routines out of future KAP runs.

• If you have link errors, ensure that the link step loaded all the libraries needed for all parts of the program. A link failure may also occur because KAP failed while processing a file, and the routines that came after the point of failure in that file were not copied to the compile file. Determine the reason that KAP failed, and try relinking.

• If the compiler issues a syntax error on a transformed program, compare the source code with the transformed code. KAP detects and flags some run-time errors, especially in I/O statements, at compilation time.

• Insufficient memory for KAP to run can sometimes be fixed by placing fewer names on the /inline_and_copy qualifier or by reducing the /eiifg and /miifg settings. To compensate for insufficient memory, you can also break up a source file into smaller logical units and run KAP on the separate units.

• If you receive the messages Preprocessor Failed or Translator Error, try lowering qualifier values, especially /scalaropt .