Low-cost process creation and dynamic partitioning in Qlisp

  • Joseph D. Pehoushek
  • Joseph S. Weening
Part I Parallel Lisp Languages and Programming Models
Part of the Lecture Notes in Computer Science book series (LNCS, volume 441)


Our experiments with Qlisp have led to two ways of improving the performance of parallel Lisp programs. One is to reduce the cost of process creation and scheduling; the other is to use a dynamic partitioning and scheduling method. We describe these techniques and present the results of several experiments that use them. We also present an analysis of the dynamic partitioning method to explain the reasons for its success.


Idle Time Process Creation Computation Tree Queue Size Partitioning Method 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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    Richard P. Gabriel and John McCarthy. Queue-based multiprocessing Lisp. In Conference Record of the 1984 ACM Symposium on Lisp and Functional Programming, pages 25–44, Austin, Texas, August 1984.Google Scholar
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    Ron Goldman, Richard P. Gabriel, and Carol Sexton. Qlisp: Parallel processing in Lisp. In Proceedings of the US/Japan Workshop on Parallel Lisp, June 1989.Google Scholar
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    Robert H. Halstead, Jr. Multilisp: A language for concurrent symbolic computation. ACM Transactions on Programming Languages and Systems, 7(4):501–538, October 1985.Google Scholar
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    Joseph S. Weening. Parallel execution of Lisp programs. Technical Report STANCS-89-1265, Stanford University, Stanford, California, June 1989.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1990

Authors and Affiliations

  • Joseph D. Pehoushek
    • 1
  • Joseph S. Weening
    • 1
  1. 1.Stanford UniversityStanford

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