Experience With Distributed Programming In Orca

Orca is a language for programming parallel applications on distributed computing systems. Although processors in such systems communicate only through message passing and not through shared memory, Orca provides a communication model based on logically shared data. Programmers can define abstract d...

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Main Authors: Henri Bal, M. Frans Kaashoek, Andrew S. Tanenbaum
Other Authors: The Pennsylvania State University CiteSeerX Archives
Format: Text
Language:English
Published: 1990
Subjects:
Online Access:http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.38.4883
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spelling ftciteseerx:oai:CiteSeerX.psu:10.1.1.38.4883 2023-05-15T17:53:07+02:00 Experience With Distributed Programming In Orca Henri Bal M. Frans Kaashoek Andrew S. Tanenbaum The Pennsylvania State University CiteSeerX Archives 1990 application/postscript http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.38.4883 en eng http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.38.4883 Metadata may be used without restrictions as long as the oai identifier remains attached to it. ftp://gatekeeper.dec.com/pub/doc/amoeba/ps/17.ps.Z text 1990 ftciteseerx 2016-09-18T00:19:14Z Orca is a language for programming parallel applications on distributed computing systems. Although processors in such systems communicate only through message passing and not through shared memory, Orca provides a communication model based on logically shared data. Programmers can define abstract data types and create instances (objects) of these types, which may be shared among processes. All operations on shared objects are executed atomically. Orca's shared objects are implemented by replicating them in the local memories of the processors. Read operations use the local copies of the object, without doing any interprocess communication. Write operations update all copies using an efficient reliable broadcast protocol. In this paper, we briefly describe the language and its implementation and then report on our experiences in using Orca for three parallel applications: the Traveling Salesman Problem, the All-pairs Shortest Paths problem, and Successive Overrelaxation. These applica. Text Orca Unknown
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description Orca is a language for programming parallel applications on distributed computing systems. Although processors in such systems communicate only through message passing and not through shared memory, Orca provides a communication model based on logically shared data. Programmers can define abstract data types and create instances (objects) of these types, which may be shared among processes. All operations on shared objects are executed atomically. Orca's shared objects are implemented by replicating them in the local memories of the processors. Read operations use the local copies of the object, without doing any interprocess communication. Write operations update all copies using an efficient reliable broadcast protocol. In this paper, we briefly describe the language and its implementation and then report on our experiences in using Orca for three parallel applications: the Traveling Salesman Problem, the All-pairs Shortest Paths problem, and Successive Overrelaxation. These applica.
author2 The Pennsylvania State University CiteSeerX Archives
format Text
author Henri Bal
M. Frans Kaashoek
Andrew S. Tanenbaum
spellingShingle Henri Bal
M. Frans Kaashoek
Andrew S. Tanenbaum
Experience With Distributed Programming In Orca
author_facet Henri Bal
M. Frans Kaashoek
Andrew S. Tanenbaum
author_sort Henri Bal
title Experience With Distributed Programming In Orca
title_short Experience With Distributed Programming In Orca
title_full Experience With Distributed Programming In Orca
title_fullStr Experience With Distributed Programming In Orca
title_full_unstemmed Experience With Distributed Programming In Orca
title_sort experience with distributed programming in orca
publishDate 1990
url http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.38.4883
genre Orca
genre_facet Orca
op_source ftp://gatekeeper.dec.com/pub/doc/amoeba/ps/17.ps.Z
op_relation http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.38.4883
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