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URBER: Ultrafast Rule-Based Escape Routing Method for Large-Scale Sample Delivery Biochips.

Authors :
Weng, Jiayi
Ho, Tsung-Yi
Ji, Weiqing
Liu, Peng
Bao, Mengdi
Yao, Hailong
Source :
IEEE Transactions on Computer-Aided Design of Integrated Circuits & Systems; Jan2020, Vol. 39 Issue 1, p157-170, 14p
Publication Year :
2020

Abstract

In high-throughput drug screening applications, as manual drug sample delivery is time-consuming and error-prone, there is an urgent need for accurate and efficient drug sample delivery biochip for large-scale microwell arrays. This paper proposes a new microfluidic biochip architecture, where drugs are automatically prepared with different concentration values, and then delivered into multiple microwells. For large-scale drug sample delivery biochips, the routing of drug sample delivery channels is a very challenging task without effective routing solutions. This paper proposes an ultrafast rule-based escape routing method, called URBER, to address the large-scale routing of drug sample delivery channels, which scales well in both runtime and memory even for a very large problem size. URBER runs very fast because it routes channels based on a set of predefined rules, which avoids runtime consumed in solution space exploration. All benchmarks for 30 ${\le }~{N}$ , ${M} {\le }~100$ have been tested, where ${N}$ and ${M}$ are the number of columns and rows of the terminal array. Among these benchmarks, about ~91.9% are routed with optimal solutions, and the runtime is order of magnitudes faster than optimal min-cost flow-based methods (speedup is from ~600 to ~340 k). Specifically, for all benchmarks with (${M}/{N}$) ${\in }$ ((3/4), (4/3)), optimal routing solutions are always obtained. URBER also shows promise of routing large-scale designs with up to 500 k terminals efficiently. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
02780070
Volume :
39
Issue :
1
Database :
Complementary Index
Journal :
IEEE Transactions on Computer-Aided Design of Integrated Circuits & Systems
Publication Type :
Academic Journal
Accession number :
143315590
Full Text :
https://doi.org/10.1109/TCAD.2018.2883908