A Comparison of Two Paradigms for Distributed Shared Memory

• Published in: Software: Practice and Experience
• Main Authors: Levelt, W.G., Kaashoek, M.F., Bal, H.E., Tanenbaum, A.S.
• Format: Article in Journal/Newspaper
• Language: English
• Published: 1992
• Subjects: Amoeba; Distributed programming; Distributed shared memory; Orca; Shared data‐objects; Shared virtual memory
• Online Access: https://research.vu.nl/en/publications/075c27da-0970-4423-97ee-1cca6d239ea9; https://doi.org/10.1002/spe.4380221105; http://hdl.handle.net/1871.1/075c27da-0970-4423-97ee-1cca6d239ea9; http://www.scopus.com/inward/record.url?scp=0026945291&partnerID=8YFLogxK; http://www.scopus.com/inward/citedby.url?scp=0026945291&partnerID=8YFLogxK

Two paradigms for distributed shared memory on loosely‐coupled computing systems are compared: 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 are compared on four applications: the travelling‐salesman problem, alpha‐beta search, matrix multiplication and the all‐pairs shortest‐paths problem. 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. Copyright © 1992 John Wiley & Sons, Ltd