A comparative analysis of parallel programming language complexity and performance

被引：0
|
作者：
Vanderwiel, SP
Nathanson, D
Lilja, DJ
机构：
[1] Univ Minnesota, Dept Elect & Comp Engn, Minneapolis, MN 55455 USA
[2] Iowa State Univ, Dept Elect & Comp Engn, Ames, IA 50010 USA
来源：
CONCURRENCY-PRACTICE AND EXPERIENCE | 1998年 / 10卷 / 10期
关键词：
D O I：
10.1002/(SICI)1096-9128(19980825)10:10<807::AID-CPE376>3.0.CO;2-2
中图分类号：
TP31 [计算机软件];
学科分类号：
081202 ; 0835 ;
摘要：
Several parallel programming languages, libraries and environments have been developed to ease the task of writing programs for multiprocessors. Proponents of each approach often point out various language features that are designed to provide the programmer with a simple programming interface. However, virtually no data exist that quantitatively evaluate the relative ease of use of different parallel programming languages. The paper borrows techniques from the software engineering field to quantify the complexity of three predominant programming models: shared-memory, message-passing and high-performance Fortran, It is concluded that traditional software complexity metrics are effective indicators of the relative complexity of parallel programming languages. The impact of complexity on run-time performance is also discussed in the context of message-passing vs. HPF on an IBM SP2. (C) 1998 John Wiley & Sons, Ltd.
引用
收藏
页码：807 / 820
页数：14
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