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MAGELLAN: multiway hardware-software partitioning and scheduling for latency minimization of hierarchical control-dataflow task graphs
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Source International Conference on Hardware Software Codesign archive
Proceedings of the ninth international symposium on Hardware/software codesign table of contents
Copenhagen, Denmark
Pages: 42 - 47  
Year of Publication: 2001
ISBN:1-58113-364-2
Authors
Karam S. Chatha  Department of ECECS, ML 30, University of Cincinnati, Cincinnati, OH
Ranga Vemuri  Department of ECECS, ML 30, University of Cincinnati, Cincinnati, OH
Sponsors
IEEE-ComSoc : Communications Society
IFIP WG 10.5 : IFIP WG 10.5
SIGSOFT: ACM Special Interest Group on Software Engineering
SIGDA: ACM Special Interest Group on Design Automation
Publisher
ACM  New York, NY, USA
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Downloads (6 Weeks): 8,   Downloads (12 Months): 24,   Citation Count: 7
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ABSTRACT

The paper presents MAGELLAN, a heuristic technique for mapping hierarchical control-dataflow task graph specifications on heterogeneous architecture templates. The architecture can consist of multiple hardware and software processing elements as specified by the user. The objective of the technique is to minimize the worst case latency of the task graph subject to the area constraints on the architecture. The technique uses an iterative approach consisting of closely linked hardware-software partitioner and scheduler. Both the partitioner and scheduler operate on the task graph in a hierarchical top down manner. The technique optimizes deterministic loop constructs by applying clustering, unrolling and pipelining. The technique considers speculative execution for conditional constructs. The number of actual hardware/software implementations of a function in the task graph are also optimized by the technique. The effectiveness of the technique is demonstrated by a case study of an image compression algorithm.


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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R. Ernst et al. "The COSYMA environment for hardwaro/softvmre cosynthesis of small embedded systems". Journal of Microprocessors ond Microsgstems, 20, 1996.
 
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J: Jeon and K. Cboi. Loop Pipelining in Herdware-Software Partitioning". In Proceedings of ASPDAC, 1998.
 
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B.P. Dave and N.K. Jha. "COHRA: Herdware-Software Co-Synthesis of Hierarchical Heterogenous Distributed Embedded Systems". 17(10), October 1998.
 
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B..P. Dick end N.K. Jh&. "MOGAC: A Multiobjective Genetic Algorithm for Hardwaro-Softwere Cosynthesis of Distributed Embedded Systems". 17(10), October 1998.
 
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F. Ba}arln, L. Lavegno, P. Murthy, end A. Sangiovanni-Vincentelli. "Scheduling for Embedded tteal-Time Systems". January-Mereh 1998.
 
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K.S. Chatha and R. Vemuri. "An Iterative Algorithm for Hardware-Software Partitioning, Hardware Design Space Exploration and Scheduling. "Design Automation for Embedded Systems , (5):281-293, 2000.

CITED BY  7

Collaborative Colleagues:
Karam S. Chatha: colleagues
Ranga Vemuri: colleagues