SIMPLE performance results in ZPL

Lin, Calvin; Snyder, Lawrence

doi:10.1007/bfb0025890

Cited by 8 publications

(4 citation statements)

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“…The first step towards achieving good parallel performance is to achieve good performance on a single node. Experiments on sequential computers have shown that ZPL is competitive-typically within a few percent-with languages such as C and Fortran [36,32,20]. Comparisons against hand-coded message passing programs [13,36] show similar success.…”

Section: Empirical Evidence Of Successmentioning

confidence: 99%

“…Experiments on sequential computers have shown that ZPL is competitive-typically within a few percent-with languages such as C and Fortran [36,32,20]. Comparisons against hand-coded message passing programs [13,36] show similar success. For example, Figure 5 shows that for 64 processors on the IBM SP-2, a ZPL implementation of the SIMPLE fluid dynamics benchmark [21] is about 16% slower than the same program written using C and MPI.…”

Section: Empirical Evidence Of Successmentioning

confidence: 99%

“…Several core concepts of ZPL were developed and announced in 1993 [35]. The first portability and performance measurements for the base language were reported in 1994 [36], and these were followed by additional comparisons in 1995 [33]. The language was substantially enhanced over the next two years, and in July 1997, ZPL was packaged with appropriate support software and documentation and released to the public.…”

Section: Introductionmentioning

confidence: 99%

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ZPL: a machine independent programming language for parallel computers

Chamberlain

Choi

Lewis

et al. 2000

IIEEE Trans. Software Eng.

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The goal of producing architecture-independent parallel programs is complicated by the competing need for high performance. The ZPL programming language achieves both goals by building upon an abstract parallel machine and by providing programming constructs that allow the programmer to "see" this underlying machine. This paper describes ZPL and provides a comprehensive evaluation of the language with respect to its goals of performance, portability, and programming convenience. In particular, we describe ZPL's machine-independent performance model, describe the programming benefits of ZPL's region-based constructs, summarize the compilation benefits of the language's high-level semantics, and summarize empirical evidence that ZPL has achieved both high performance and portability on diverse machines such as the IBM SP-2, Cray T3E, and SGI Power Challenge.

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Section: Empirical Evidence Of Successmentioning

confidence: 99%

Section: Empirical Evidence Of Successmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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ZPL: a machine independent programming language for parallel computers

Chamberlain

Choi

Lewis

et al. 2000

IIEEE Trans. Software Eng.

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“…ZPL generally outperforms HPF and has proven to be competitive with hand-coded C and message passing [10,9]. Applications from a variety of disciplines have been written using ZPL [4,7,14], and the language was released for widespread use in July, 1997.…”

Section: Introduction To Zplmentioning

confidence: 99%

ZPL's WYSIWYG performance model

Chamberlain

Lin

Choi

et al.

Proceedings Third International Workshop on High-Level Parallel Programming Models and Supportive Environments

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ZPL is a parallel array language designed for high performance scientific and engineering computations. Unlike other parallel languages, ZPL is founded on a machine model (the CTA) that accurately abstracts contemporary MIMD parallel computers. This makes it possible to correlate ZPL programs with machine behavior. As a result, programmers can reason about how code will perform on a typical parallel machine and thereby make informed decisions between alternative programming solutions. This paper describes ZPL's performance model and its syntactic cues for conveying operation cost. The what-you-seeis-what-you-get (WYSIWYG) nature of ZPL operations is demonstrated on the IBM SP-2, Intel Paragon, SGI Power Challenge, and Cray T3E. Additionally, the model is used to evaluate two algorithms for matrix multiplication. Experiments show that the performance model correctly predicts the faster solution on all four platforms for a range of problem sizes.

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