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The input-aware dynamic adaptation of area and performance for reconfigurable accelerator
Source
International Symposium on Field Programmable Gate Arrays archive
Proceeding of the ACM/SIGDA international symposium on Field programmable gate arrays table of contents
Monterey, California, USA
POSTER SESSION: Applications table of contents
Pages 281-281  
Year of Publication: 2009
ISBN:978-1-60558-410-2
Authors
Like Yan  ZJU-Intel Technology Center, College of Computer Science, Zhejiang University, Hangzhou, China
Gang Wang  ZJU-Intel Technology Center, College of Computer Science, Zhejiang University, Hangzhou, China
Tianzhou Chen  ZJU-Intel Technology Center, College of Computer Science, Zhejiang University, Hangzhou, China
Sponsors
SIGDA: ACM Special Interest Group on Design Automation
ACM: Association for Computing Machinery
Publisher
ACM  New York, NY, USA
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ABSTRACT

Attaching reconfigurable loop accelerator to a processor is a promising way to improve the performance and efficiency of the system. It's usually to unroll a loop to increase the parallelism of a loop accelerator. While the higher degree a loop is unrolled, the more reconfigurable area is needed. However, an observation is that the utilization of the loop accelerator is relative to the input. Focusing on the area and performance balance, a dynamically adaptive reconfigurable accelerator framework is proposed on CPU/RA architecture in the paper. Firstly, the inputs are classified into certain predefined types. At run-time the input of the application will be monitored and then the accelerator will be reconfigured to accomplish the area-performance dynamic adaption. An accelerator selection model is also presented to choose an accelerator at run-time according to the predefined input types. And a bzip2 case study is presented, the experimental results demonstrated the feasibility of the approach, and shown that up to 93.6% reconfigurable area is saved at a cost of 1.6% performance lost in a best case.


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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Intel® QuickAssist Technology Overview. http://www.intel.com/technology/platforms/quickassist/index.htm, 2008-05-09
 
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Intel Corp. Intel® QuickAssist Technology White Paper. 2007.
 
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Intel Corp. Intel® QuickAssist Technology Accelerator Abstraction Layer (AAL) White Paper. 2007.
 
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Xilinx Inc., Virtex-5 Family Overview LX, LXT, and SXT Platforms, 2007.
 
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Bzip2 homepage, http://www.bzip.org/.
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Seng Lin Sheey, Sri Parameswarany and Newton Cheungz. Novel Architecture for Loop Acceleration: A Case Study.

Collaborative Colleagues:
Like Yan: colleagues
Gang Wang: colleagues
Tianzhou Chen: colleagues