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FTL: a multithreaded environment for parallel computation
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Proceedings of the 1994 conference of the Centre for Advanced Studies on Collaborative research table of contents
Toronto, Ontario, Canada
Page: 33  
Year of Publication: 1994
Authors
Ivan Kalas  Centre for Advanced Studies, IBM Canada Ltd., 21/894, 844 Don Mills Rd., North York, Ontario M3C 1W3
Eshrat Arjomandi  Department of Computer Science, York University, North York, Ontario, M3J-1P3
Guang R. Gao
Bill O'Farrell  Centre for Advanced Studies, IBM Canada Ltd., 21/894, 844 Don Mills Rd., North York, Ontario M3C 1W3
Sponsors
NRC : National Research Council - Canada
: Natural Sciences and Engineering Research Council
: Industry Canada
IBM Canada : IBM Canada
Publisher
IBM Press 
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ABSTRACT

The arrival of high-performance "killer micros" and the availability of high-performance networks (e.g., ATM) offer potential for building clusters of workstations with a significantly higher level of scalability than before. A promising approach to exploiting parallel computation on these systems is to use multithreading to overlap computation and communication while offering a simple programming model that smoothly integrates these two functions.This paper describes the design and implementation of a portable software platform for multithreaded computation in distributed memory systems. The goal is to provide a runtime environment that efficiently integrates computation and communication, and runs on off-the-shelf workstations without any hardware or operating system modifications. The target configurations are networked clusters of UNIX workstations, such as workstation farms and high-speed interconnect clusters. The FTL software platform is being implemented as a runtime library that can be used either directly by a programmer, or by a compiler. Portability and programmability are among the important objectives in our design.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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Collaborative Colleagues:
Ivan Kalas: colleagues
Eshrat Arjomandi: colleagues
Guang R. Gao: colleagues
Bill O'Farrell: colleagues