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The pipeline decomposition tree:: an analysis tool for multiprocessor implementation of image processing applications
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Source International Conference on Hardware Software Codesign archive
Proceedings of the 4th international conference on Hardware/software codesign and system synthesis table of contents
Seoul, Korea
SESSION: System-level performance issues table of contents
Pages: 52 - 57  
Year of Publication: 2006
ISBN:1-59593-370-0
Authors
Dong-Ik Ko  University of Maryland, College Park, USA
Shuvra S. Bhattacharyya  University of Maryland, College Park, USA
Sponsors
SIGDA: ACM Special Interest Group on Design Automation
ACM: Association for Computing Machinery
SIGBED: ACM Special Interest Group on Embedded Systems
SIGMICRO: ACM Special Interest Group on Microarchitectural Research and Processing
Publisher
ACM  New York, NY, USA
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ABSTRACT

Modern embedded systems for image processing involve increasingly complex levels of functionality under real-time and resource-related constraints. As this complexity increases, the application of single-chip multiprocessor technology is attractive. To address the challenges of mapping image processing applications onto embedded multiprocessor platforms, this paper presents a novel data structure called the pipeline decomposition tree (PDT), and an associated scheduling framework, which we refer to as PDT scheduling. PDT scheduling exploits both heterogeneous data parallelism and task-level parallelism, which are important considerations for scheduling image processing applications. This paper develops the PDT representation for system synthesis, and presents methods using the PDT to derive customized pipelined architectures that are streamlined for the given implementation constraints.


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:
Dong-Ik Ko: colleagues
Shuvra S. Bhattacharyya: colleagues