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Customizing computation accelerators for extensible multi-issue processors with effective optimization techniques
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Source Annual ACM IEEE Design Automation Conference archive
Proceedings of the 45th annual Design Automation Conference table of contents
Anaheim, California
SESSION: Application mapping and power efficiency table of contents
Pages 197-200  
Year of Publication: 2008
ISBN ~ ISSN:0738-100X , 978-1-60558-115-6
Authors
Ya-shuai Lü  National University of Defense Technology, Changsha, Hunan, China
Li Shen  National University of Defense Technology, Changsha, Hunan, China
Li-bo Huang  National University of Defense Technology, Changsha, Hunan, China
Zhi-ying Wang  National University of Defense Technology, Changsha, Hunan, China
Nong Xiao  National University of Defense Technology, Changsha, Hunan, China
Sponsors
SIGDA: ACM Special Interest Group on Design Automation
: IEEE/CASS/CANDE/CEDA
: The EDA Consortium
Publisher
ACM  New York, NY, USA
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ABSTRACT

Compared with single-issue general purpose processors (GPPs), extensible multi-issue/VLIW processors can exploit instruction-level parallelism, which are more suitable for computation intensive tasks. Moreover, they offer the ability of customizing computation accelerators for an application domain. In this paper, we present an automated methodology that customizes computation accelerators for the multi-issue/VLIW extensible processors, where several techniques are also proposed to optimize the design of an accelerator.


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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A. Peymandoust, L. Pozzi, P. Ienne, G. De Micheli: 'Automatic Instruction Set Extension and Utilization for Embedded Processors'. In ASAP, Hague, Netherlands, June 2003, pp. 108--118
 
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Xiaoyong Chen, Douglas Maskell and Yang Sun, Fast Identification of Custom Instructions for Extensible Processors, IEEE TCAD, Feb 2007
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Collaborative Colleagues:
Ya-shuai Lü: colleagues
Li Shen: colleagues
Li-bo Huang: colleagues
Zhi-ying Wang: colleagues
Nong Xiao: colleagues