Abstract#R##N##R##N#Many scientific codes can achieve significant performance improvement when executed on a computer equipped with a vector processor. Vector constructs in source code should be recognized by a vectorizing compiler or preprocessor. This paper discusses, from a general point of view, how a vectorizing compiler/preprocessor can be evaluated. The areas discussed include data dependence analysis, IF loop analysis, nested loops, loop interchanging, loop collapsing, indirect addressing, use of temporary storage, and order of arithmetic. The ideas presented are based on vectorization of over a million lines of production codes and an extensive test suite developed to evaluate preprocessors under varying degrees of code complexity. Areas for future research are also discussed.
['Glenn R. Luecke', 'Wagar Haque', 'Jim Hoekstra', 'Howard W. Jespersen', 'James Coyle']
Evaluation of Fortran vector compilers and preprocessors