Replication Techniques For Speeding Up Parallel Applications On Distributed Systems
Traditional programming methods for loosely-coupled systems are based on message-passing. More recently, methods have emerged based for "virtually" sharing data. These methods simplify distributed programming, but are hard to implement efficiently, as loosely-coupled systems do not contain...
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ftciteseerx:oai:CiteSeerX.psu:10.1.1.37.8521 2023-05-15T17:53:43+02:00 Replication Techniques For Speeding Up Parallel Applications On Distributed Systems Henri E. Bal M. Frans Kaashoek Andrew S. Tanenbaum Jack Jansen The Pennsylvania State University CiteSeerX Archives 1992 application/postscript http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.37.8521 en eng http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.37.8521 Metadata may be used without restrictions as long as the oai identifier remains attached to it. ftp://gatekeeper.dec.com/pub/doc/amoeba/ps/14.ps.Z Index terms Amoeba distributed systems multicast Orca parallel programming replication shared data-object text 1992 ftciteseerx 2016-01-08T01:15:33Z Traditional programming methods for loosely-coupled systems are based on message-passing. More recently, methods have emerged based for "virtually" sharing data. These methods simplify distributed programming, but are hard to implement efficiently, as loosely-coupled systems do not contain physical shared memory. We introduce a new model, the shared data-object model, that eases the implementation of parallel applications on looselycoupled systems, but can still be implemented efficiently. In the shared data-object model, shared data are encapsulated in data objects, which are variables of userdefined abstract data types. To speed up access to shared data, data objects are replicated. This paper discusses the design choices involved in replicating objects and their effect on performance. We have implemented several options to determine which strategy is most efficient. Text Orca Unknown |
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Index terms Amoeba distributed systems multicast Orca parallel programming replication shared data-object |
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Index terms Amoeba distributed systems multicast Orca parallel programming replication shared data-object Henri E. Bal M. Frans Kaashoek Andrew S. Tanenbaum Jack Jansen Replication Techniques For Speeding Up Parallel Applications On Distributed Systems |
topic_facet |
Index terms Amoeba distributed systems multicast Orca parallel programming replication shared data-object |
description |
Traditional programming methods for loosely-coupled systems are based on message-passing. More recently, methods have emerged based for "virtually" sharing data. These methods simplify distributed programming, but are hard to implement efficiently, as loosely-coupled systems do not contain physical shared memory. We introduce a new model, the shared data-object model, that eases the implementation of parallel applications on looselycoupled systems, but can still be implemented efficiently. In the shared data-object model, shared data are encapsulated in data objects, which are variables of userdefined abstract data types. To speed up access to shared data, data objects are replicated. This paper discusses the design choices involved in replicating objects and their effect on performance. We have implemented several options to determine which strategy is most efficient. |
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The Pennsylvania State University CiteSeerX Archives |
format |
Text |
author |
Henri E. Bal M. Frans Kaashoek Andrew S. Tanenbaum Jack Jansen |
author_facet |
Henri E. Bal M. Frans Kaashoek Andrew S. Tanenbaum Jack Jansen |
author_sort |
Henri E. Bal |
title |
Replication Techniques For Speeding Up Parallel Applications On Distributed Systems |
title_short |
Replication Techniques For Speeding Up Parallel Applications On Distributed Systems |
title_full |
Replication Techniques For Speeding Up Parallel Applications On Distributed Systems |
title_fullStr |
Replication Techniques For Speeding Up Parallel Applications On Distributed Systems |
title_full_unstemmed |
Replication Techniques For Speeding Up Parallel Applications On Distributed Systems |
title_sort |
replication techniques for speeding up parallel applications on distributed systems |
publishDate |
1992 |
url |
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.37.8521 |
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Orca |
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ftp://gatekeeper.dec.com/pub/doc/amoeba/ps/14.ps.Z |
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http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.37.8521 |
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Metadata may be used without restrictions as long as the oai identifier remains attached to it. |
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1766161424809197568 |