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Data communication estimation and reduction for reconfigurable systems
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Source Annual ACM IEEE Design Automation Conference archive
Proceedings of the 40th annual Design Automation Conference table of contents
Anaheim, CA, USA
SESSION: Compilation techniques for reconfigurable devices table of contents
Pages: 616 - 621  
Year of Publication: 2003
ISBN:1-58113-688-9
Authors
Adam Kaplan  University of California, Los Angeles
Philip Brisk  University of California, Los Angeles
Ryan Kastner  University of California, Santa Barbara
Sponsor
ACM: Association for Computing Machinery
Publisher
ACM  New York, NY, USA
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Downloads (6 Weeks): 4,   Downloads (12 Months): 21,   Citation Count: 3
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ABSTRACT

Widespread adoption of reconfigurable devices requires system level synthesis techniques to take an application written in a high level language and map it to the reconfigurable device. This paper describes methods for synthesizing the internal representation of a compiler into a hardware description language in order to program reconfigurable hardware devices. We demonstrate the usefulness of static single assignment (SSA) in reducing the amount of data communication in the hardware. However, the placement of Φ-nodes by current SSA algorithms is not optimal in terms of minimizing data communication. We propose a new algorithm which optimally places Φ-nodes, further decreasing area and communication latency. Our algorithm reduces the data communication (measured as total edge weight in a control data flow graph) by as much as 20% for some applications as compared to the best-known SSA algorithm - the pruned algorithm. We also describe future modifications to our model that should increase the effectiveness of our methods.


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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M. Hall et al., "DEFACTO: A Design Environment for Adaptive Computing Technology", Proceedings of the 6th Reconfigurable Architectures Workshop, Springer-Verlag, 1999.
 
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R. Cytron et al., "Efficiently Computing Φ-nodes On-the-Fly", ACM Transactions on Programming Languages and Systems, October 1991.
 
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K. Kennedy. "A Survey of Data Flow Analysis Techniques", Program Flow Analysis: Theory and Applications, Prentice-Hall, 1981.
 
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M. D. Smith and G. Holloway, An Introduction to Machine SUIF and its Portable Libraries for Analysis and Optimization, Division of Engineering and Applied Sciences, Harvard University,
 
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P. Briggs, T. Harvey and L. Simpson, Static Single Assignment Construction, Implementation documentation, 1996.
 
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A. Smith et al., "PRISM II Compiler and Architecture", Proceedings of IEEE Workshop on FPGA-based Custom Computing Machines, April, 1993.
 
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Collaborative Colleagues:
Adam Kaplan: colleagues
Philip Brisk: colleagues
Ryan Kastner: colleagues