A comparison of two paradigms for distributed shared memory
This paper compares two paradigms for Distributed Shared Memory on loosely coupled computing systems: the shared data-object model as used in Orca, a programming language specially designed for loosely coupled computing systems and the Shared Virtual Memory model. For both paradigms two systems are...
| Main Authors: | , , , |
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| Other Authors: | |
| Format: | Text |
| Language: | English |
| Published: |
1992
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| Subjects: | |
| Online Access: | http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.143.3684 http://www.cs.vu.nl/~ast/publications/spe-1992.pdf |
| Summary: | This paper compares two paradigms for Distributed Shared Memory on loosely coupled computing systems: the shared data-object model as used in Orca, a programming language specially designed for loosely coupled computing systems and the Shared Virtual Memory model. For both paradigms two systems are described, one using only point-to-point messages, the other using broadcasting as well. The two paradigms and their implementations are described briefly. Their performances on four applications are compared: the travelling-salesman problem, alpha-beta search, matrix multiplication and the all-pairs shortest paths problem. The relevant measurements were obtained on a system consisting of 10 MC68020 processors connected by an Ethernet. For comparison purposes, the applications have also been run on a system with physical shared memory. In addition, the paper gives measurements for the first two applications above when Remote Procedure Call is used as the communication mechanism. The measurements show that both paradigms can be used efficiently for programming large-grain parallel applications, with significant speed-ups. The structured shared data-object model achieves the highest speed-ups and is easiest to program and to debug. KEYWORDS: Amoeba Distributed shared memory Distributed programming Orca |
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