Treadmarks: Shared memory computing on networks of workstations

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Treadmarks: Shared memory computing on networks of workstations (1996)

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by Cristiana Amza , Alan L. Cox , Hya Dwarkadas , Pete Keleher , Honghui Lu , Ramakrishnan Rajamony , Weimin Yu , Willy Zwaenepoel

Venue:	Computer
Citations:	487 - 37 self

BibTeX

@ARTICLE{Amza96treadmarks:shared,
    author = {Cristiana Amza and Alan L. Cox and Hya Dwarkadas and Pete Keleher and Honghui Lu and Ramakrishnan Rajamony and Weimin Yu and Willy Zwaenepoel},
    title = {Treadmarks: Shared memory computing on networks of workstations},
    journal = {Computer},
    year = {1996}
}

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Abstract

TreadMarks supports parallel computing on networks of workstations by providing the application with a shared memory abstraction. Shared memory facilitates the transition from sequential to parallel programs. After identifying possible sources of parallelism in the code, most of the data structures can be retained without change, and only synchronization needs to be added to achieve a correct shared memory parallel program. Additional transformations may be necessary to optimize performance, but this can be done in an incremental fashion. We discuss the techniques used in TreadMarks to provide e cient shared memory, and our experience with two large applications, mixed integer programming and genetic linkage analysis. 1

Keyphrases

shared memory data structure synchronization need mixed integer programming parallel program genetic linkage analysis incremental fashion shared memory abstraction memory parallel program treadmarks support possible source large application additional transformation