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    Abstract:

    In this paper, task tree is introduced to model a parallel functional program on distributed and message passing platform. Based on this model, the main issues of task partition, such as task size and parallelism, are analyzed with speedup as the performance measure. An optimized partition algorithm is given, and an implemented system——PARLisp's performance data is supplied as an example.

    Reference
    1  Donaldson Val, Berman Francine, Paturi Ramamohan. Program speedup in a heterogeneous computing network. Journal of Parallel and Distributed Computing, 1994,21(3):316~312 2  Yuen C K, Feng M D, Wang W F et al. Parallel Lisp Systems. Singapore: Chapman and Hall, 1993 3  周一萍.基于分布存储及消息传递系统的分布式智能软件开发环境——PARLISP的设计与实现[硕士论文].西安交通大学,1996 (Zhou Yi-ping. Design and implementation of PARLISP——a distributed AI programming environment based on distributed memory and message passing platform[M.S. Thesis]. Xi'an Jiaotong University, 1996) 4  Halstead Robert H. Multilisp: a language for concurrent symbolic computation. ACM Transactions on Programming Languages and Systems, 1985,7(4):501~538 5  Almasi G S, Gottlieb A. Highly Parallel Computing. Redwood City, CA: Benjamin/Cummingsm Publishing, 1989
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周一萍,郑守淇,白英彩.函数型程序的并行计算模型及任务划分.软件学报,1998,9(12):932-936

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History
  • Received:July 25,1997
  • Revised:December 18,1997
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