Abstract

This paper compares two data parallel languages, ZPL and HPF, in terms of programming style and performance. The results show that for eight programs from a number of standard benchmark suites, ZPL generally outperforms HPF, and ZPL expresses problems at higher levels of abstraction, yielding programs that are shorter, less error prone and easier to maintain. ZPL's better performance comes from its clean expression of parallelism that allows for better compiler analysis. 1 Introduction ZPL is a new data parallel array language designed at the University of Washington to provide high performance parallel computation for all MIMD parallel computers [7]. HPF was recently defined by the High Performance Fortran Forum to provide "data parallel programming" and "top performance on MIMD and SIMD computers" [4, p.1]. With such similar ambitions, it is natural to compare the two languages. This paper compares ZPL and HPF, concentrating on performance and programming style. Though their high-le...

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