Distributed memory multiprocessor systems can provide the computing power necessary for large-scale scientific applications. A critical performance issue for a number of these applications is the efficient transfer of data to secondary storage. Recently several research groups have proposed FORTRAN language extensions for exploiting the data parallelism of such scientific codes on distributed memory architectures. However, few of these high performance FORTRANs provide appropriate constructs for controlling the use of ...
This document presents the syntax and semantics of Vienna Fortran, a machine-independent language extension to FORTRAN 77, which allows the user to write programs for distributed-memory systems using global addresses. Vienna Fortran includes high level features for specifying virtual processor structures, distributing data across sets of processors, dynamically modifying distributions, and formulating explicitly parallel loops. The language is based upon the Single-Program-Multiple-Data (SPMD) paradigm, which exploits the parallelism inherent in ...
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