Distributed programming with shared data

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Distributed programming with shared data (1988)

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by Henri E. Bal , Andrew S. Tanenbaum

Venue:	Computer Languages
Citations:	84 - 16 self

BibTeX

@INPROCEEDINGS{Bal88distributedprogramming,
    author = {Henri E. Bal and Andrew S. Tanenbaum},
    title = {Distributed programming with shared data},
    booktitle = {Computer Languages},
    year = {1988},
    pages = {82--91}
}

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Abstract

Until recently, at least one thing was clear about parallel programming: tightly coupled (shared memory) machines were programmed in a language based on shared variables and loosely coupled (distributed) systems were programmed using message passing. The explosive growth of research on distributed systems and their languages, however, has led to several new methodologies that blur this simple distinction. Operating system primitives (e.g., problem-oriented shared memory, Shared Virtual Memory, the Agora shared memory) and languages (e.g., Concurrent Prolog, Linda, Emerald) for programming distributed systems have been proposed that support the shared variable paradigm without the presence of physical shared memory. In this paper we will look at the reasons for this evolution, the resemblances and differences among these new proposals, and the key issues in their design and implementation. It turns out that many implementations are based on replication of data. We take this idea one step further, and discuss how automatic replication (initiated by the run time system) can be used as a basis for a new model, called the shared data-object model, whose semantics are similar to the shared variable model. Finally, we discuss the design of a new language for distributed programming, Orca, based on the shared data-object model. 1.

Keyphrases

data-object model distributed system physical shared memory key issue explosive growth new model variable model parallel programming automatic replication new language distributed programming new proposal shared memory simple distinction system primitive variable paradigm run time system message passing several new methodology many implementation concurrent prolog shared virtual memory