Compilers for distributed-memory systems generate code that is based on runtime analysis techniques and is only efficient if, in addition, aggressive compile-time optimizations are applied. Vienna Fortran, a machine-independent language extension to Fortran which allows the user to write programs for distributed-memory systems using global addresses, provides the forall-loop construct for specifying irregular computations that do not cause inter-iteration dependences.

SVM Support in the Vienna Fortran Compilation Systemīrezany, Peter Gerndt, Michael Sipkova, Viera We achieve a 3.8Ã- speedup in the case study below. For some projects on some machines, it can be advantageous to compile in two passes: The first pass generates the module files, quickly the second pass produces the object files, in parallel. As it happens, this option usually runs much faster than the object code generation and optimization phases. Some Fortran compilers (Intel ifort, GNU gfortran and IBM xlf, at least) offer an option to â€˜â€˜verify syntaxâ€™â€™, with the side effect of also producing any associated Fortran module files.

If file A depends on file B, (A uses a module defined by B), you must finish compiling B before you can begin compiling A. (LLNL), Livermore, CA (United States)įortran modules tend to serialize compilation of large Fortran projects, by introducing dependencies among the source files. Energy Technology Data Exchange (ETDEWEB)īusby, L.

Compaq Visual Fortran 6.6 Standard