Abstract High‐Performance Fortran (HPF) has been designed to provide portable performance on distributed memory machines. An important aspect of portable performance is the behavior of the available HPF compilers. Ideally, a programmer may expect comparable performance between different HPF compilers, given the same program and the same machine. To test the performance portability between compilers, we have designed a special benchmark suite, called the TNO HPF benchmark suite. It consists of a set of HPF programs that test various aspects of efficient parallel code generation. The benchmark suite consists of a number of template programs that are used to generate test programs with different array sizes, alignments, distributions, and iteration spaces. It ranges from very simple assignments to more complex assignments such as triangular iteration spaces, convex iteration spaces, coupled subscripts, and indirection arrays. We have run the TNO HPF benchmark suite on three compilers: the PREPARE prototype compiler, the PGI‐HPF compiler, and the GMD Adaptor HPF compiler. Results show performance differences that can be quite large (up to two orders of magnitude for the same test program). Closer inspection reveals that the origin of most of the differences in performance is due to differences in local enumeration and storage of distributed array elements. Copyright © 2002 John Wiley & Sons, Ltd.

In this paper, we analyze the efficiency of three local enumeration and three storage compression schemes for cyclic(m) data distributions in High Performance Fortran (HPF).We show that for linear array access sequences, efficient enumeration and storage compression schemes can be derived.Furthermore, local enumeration and storage techniques are shown to be orthogonal, if the local storage compression scheme is collapsible.Performance figures of the methods are given for a number of different processors.

Data parallel languages, like High Performance Fortran (HPF), support the notion of distributed arrays. However, the implementation of such distributed array structures and their access on message passing computers is not straightforward. This holds especially for distributed arrays that are aligned to each other and given a block-cyclic distribution. In this paper, an implementation framework is presented for HPF distributed arrays on message passing computers. Methods are presented for efficient (in space and time) local index enumeration, local storage, and communication. Techniques for local set enumeration provide the basis for constructing local iteration sets and communication sets. It is shown that both local set enumeration and local storage schemes can be derived from the same equation. Local set enumeration and local storage schemes are shown to be orthogonal, i.e., they can be freely combined. Moreover, for linear access sequences generated by our enumeration methods, the local address calculations can be moved out of the enumeration loop, yielding efficient local memory address generation. The local set enumeration methods are implemented by using a relatively simple general transformation rule for absorbing ownership tests. This transformation rule can be repeatedly applied to absorb multiple ownership tests. Performance figures are presented for local iteration overhead, a simple communication pattern, and storage efficiency.