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Evaluation of on-chip networks using deflection routing
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Source Great Lakes Symposium on VLSI archive
Proceedings of the 16th ACM Great Lakes symposium on VLSI table of contents
Philadelphia, PA, USA
POSTER SESSION: Poster session 2 table of contents
Pages: 296 - 301  
Year of Publication: 2006
ISBN:1-59593-347-6
Authors
Zhonghai Lu  Royal Institute of Technology in Sweden
Mingchen Zhong  Royal Institute of Technology in Sweden
Axel Jantsch  Royal Institute of Technology in Sweden
Sponsors
ACM: Association for Computing Machinery
SIGDA: ACM Special Interest Group on Design Automation
Publisher
ACM  New York, NY, USA
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ABSTRACT

Deflection routing is being proposed for networks on chips since it is simple and adaptive. A deflection switch can be much smaller and faster than a wormhole or virtual cut-through switch. A deflection-routed network has three orthogonal characteristics: topology, routing algorithm and deflection policy. In this paper we evaluate deflection networks with different topologies such as mesh, torus and Manhattan Street Network, different routing algorithms such as random, dimension XY, delta XY and minimum deflection, as well as different deflection policies such as non-priority, weighted priority and straight-through policies. Our results suggest that the performance of a deflection network is more sensitive to its topology than the other two parameters. It is less sensitive to its routing algorithm, but a routing algorithm should be minimal. A priority-based deflection policy that uses global and history-related criterion can achieve both better average-case and worst-case performance than a non-priority or priority policy that uses local and stateless criterion. These findings are important since they can guide designers to make right decisions on the deflection network architecture, for instance, selecting a routing algorithm or deflection policy which has potentially low cost and high speed for hardware implementation.


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:
Zhonghai Lu: colleagues
Mingchen Zhong: colleagues
Axel Jantsch: colleagues