TreadMarks: Shared Memory Computing on Networks of Workstations (1996)
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| Venue: | IEEE Computer |
| Citations: | 405 - 36 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 = {IEEE Computer},
year = {1996},
volume = {29},
pages = {18--28}
}
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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 efficient shared memory, and our experience with two large applications, mixed integer programming and genetic linkage analysis. 1 Introduction High-speed networks and rapidly improving microprocessor performance make networks of workstations an increasingly appealing vehicle for parallel computing. By relying solely on commodity hardware and software, networks of workstations offer parallel p...
