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Application-specific instruction generation for configurable processor architectures
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Proceedings of the 2004 ACM/SIGDA 12th international symposium on Field programmable gate arrays table of contents
Monterey, California, USA
SESSION: Reconfigurable computing: architectures and applications table of contents
Pages: 183 - 189  
Year of Publication: 2004
ISBN:1-58113-829-6
Authors
Jason Cong  University of California, Los Angeles, Los Angeles, CA
Yiping Fan  University of California, Los Angeles, Los Angeles, CA
Guoling Han  University of California, Los Angeles, Los Angeles, CA
Zhiru Zhang  University of California, Los Angeles, Los Angeles, CA
Sponsors
SIGDA: ACM Special Interest Group on Design Automation
ACM: Association for Computing Machinery
Publisher
ACM  New York, NY, USA
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Downloads (6 Weeks): 9,   Downloads (12 Months): 101,   Citation Count: 31
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ABSTRACT

Designing an application-specific embedded system in nanometer technologies has become more difficult than ever due to the rapid increase in design complexity and manufacturing cost. Efficiency and flexibility must be carefully balanced to meet different application requirements. The recently emerged configurable and extensible processor architectures offer a favorable tradeoff between efficiency and flexibility, and a promising way to minimize certain important metrics (e.g., execution time, code size, etc.) of the embedded processors. This paper addresses the problem of generating the application-specific instructions to improve the execution speed for configurable processors. A set of algorithms, including pattern generation, pattern selection, and application mapping, are proposed to efficiently utilize the instruction set extensibility of the target configurable processor. Applications of our approach to several real-life benchmarks on the Altera Nios processor show encouraging performance speedup (2.75X on average and up to 3.73X in some cases).


REFERENCES

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CITED BY  32

Collaborative Colleagues:
Jason Cong: colleagues
Yiping Fan: colleagues
Guoling Han: colleagues
Zhiru Zhang: colleagues