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Experience with parallel symbolic applications in Orca

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Parallel Symbolic Languages and Systems (PSLS 1995)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1068))

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Abstract

Orca is a simple, imperative parallel programming language, based on a form of distributed shared memory called shared data-objects. This paper discusses the suitability of Orca for parallel symbolic programming. Orca was not designed specifically for this application area, and it lacks several features supported in many languages for symbolic parallel computing, such as futures, automatic load balancing, and automatic garbage collection. On the other hand, Orca does give high-level support for sharing global state. Also, its implementation automatically distributes shared data (stored in shared objects).

We first give a comparison between Orca and two other models: imperative message-passing systems and functional languages. We do so by looking at several key issues in parallel programming and by studying how each of the three paradigms deals with these issues. Next, we describe our experiences with writing parallel symbolic applications in Orca. This work indicates that Orca is quite suitable for such applications.

This research is supported in part by a PIONIER grant from the Netherlands Organization for Scientific Research (N.W.O.).

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Authors and Affiliations

  1. Dept. of Mathematics and Computer Science, Vrije Universiteit, Amsterdam, The Netherlands

    Henri Bal, Koen Langendoen & Raoul Bhoedjang

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  1. Henri Bal
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  2. Koen Langendoen
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  3. Raoul Bhoedjang
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Editor information

Takayasu Ito Robert H. Halstead Jr. Christian Queinnec

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© 1996 Springer-Verlag Berlin Heidelberg

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Bal, H., Langendoen, K., Bhoedjang, R. (1996). Experience with parallel symbolic applications in Orca. In: Ito, T., Halstead, R.H., Queinnec, C. (eds) Parallel Symbolic Languages and Systems. PSLS 1995. Lecture Notes in Computer Science, vol 1068. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0023067

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  • DOI: https://doi.org/10.1007/BFb0023067

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  • Print ISBN: 978-3-540-61143-1

  • Online ISBN: 978-3-540-68332-2

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