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Physical-level synthesis for digital lab-on-a-chip considering variation, contamination and defect

Physical-level synthesis for digital lab-on-a-chip considering variation, contamination and defect
Physical-level synthesis for digital lab-on-a-chip considering variation, contamination and defect
Microfluidic lab-on-a-chips have been widely utilized in biochemical analysis and human health studies due to high detection accuracy, high timing efficiency, and low cost. The increasing design complexity of lab-on-a-chips necessitates the computer-aided design (CAD) methodology in contrast to the classical manual design methodology. A key part in lab-on-a-chip CAD is physical-level synthesis. It includes the lab-on-a-chip placement and routing, where placement is to determine the physical location and the starting time of each operation and routing is to transport each droplet from the source to the destination. In the lab-on-a-chip design, variation, contamination, and defect need to be considered. This work designs a physical-level synthesis flow which simultaneously considers variation, contamination, and defect of the lab-on-a-chip design. It proposes a maze routing based, variation, contamination, and defect aware droplet routing technique, which is seamlessly integrated into an existing placement technique. The proposed technique improves the placement solution for routing and achieves the placement and routing co-optimization to handle variation, contamination, and defect. The simulation results demonstrate that our technique does not use any defective/contaminated grids, while the technique without considering contamination and defect uses 17.0% of the defective/contaminated grids on average. In addition, our routing variation aware technique significantly improves the average routing yield by 51.2% with only 3.5% increase in completion time compared to a routing variation unaware technique.
1536-1241
3-11
Liao, Chen
1fea98f5-fe88-41c6-8663-276745e4c0fb
Hu, Shiyan
19bb09b2-bf52-4bd7-818a-63e8da474072
Liao, Chen
1fea98f5-fe88-41c6-8663-276745e4c0fb
Hu, Shiyan
19bb09b2-bf52-4bd7-818a-63e8da474072

Liao, Chen and Hu, Shiyan (2014) Physical-level synthesis for digital lab-on-a-chip considering variation, contamination and defect. IEEE Transactions on Nanobioscience, 13 (1), 3-11. (doi:10.1109/TNB.2013.2294943).

Record type: Article

Abstract

Microfluidic lab-on-a-chips have been widely utilized in biochemical analysis and human health studies due to high detection accuracy, high timing efficiency, and low cost. The increasing design complexity of lab-on-a-chips necessitates the computer-aided design (CAD) methodology in contrast to the classical manual design methodology. A key part in lab-on-a-chip CAD is physical-level synthesis. It includes the lab-on-a-chip placement and routing, where placement is to determine the physical location and the starting time of each operation and routing is to transport each droplet from the source to the destination. In the lab-on-a-chip design, variation, contamination, and defect need to be considered. This work designs a physical-level synthesis flow which simultaneously considers variation, contamination, and defect of the lab-on-a-chip design. It proposes a maze routing based, variation, contamination, and defect aware droplet routing technique, which is seamlessly integrated into an existing placement technique. The proposed technique improves the placement solution for routing and achieves the placement and routing co-optimization to handle variation, contamination, and defect. The simulation results demonstrate that our technique does not use any defective/contaminated grids, while the technique without considering contamination and defect uses 17.0% of the defective/contaminated grids on average. In addition, our routing variation aware technique significantly improves the average routing yield by 51.2% with only 3.5% increase in completion time compared to a routing variation unaware technique.

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More information

e-pub ahead of print date: 27 February 2014
Published date: March 2014

Identifiers

Local EPrints ID: 438339
URI: http://eprints.soton.ac.uk/id/eprint/438339
ISSN: 1536-1241
PURE UUID: ef7d7012-f7da-4a88-959e-06e16d2b61a6

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Date deposited: 06 Mar 2020 17:30
Last modified: 03 Jul 2020 16:38

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