Browsing by Author "Song, Ling-Yen"

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A Structure-Based Methodology for Analog Layout Generation
(2019-01-01)
Chen, Yu-Hsien
;
Chi, Hao-Yu
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Song, Ling-Yen
;
Liu, Chien-Nan Jimmy
;
Chen, Hung-Ming
In order to speed up analog design cycles, analog layout automation is a popular research in recent years. However, most previous works assume that the required design constraints are given by users manually. Designers still take a lot of time to fill-in the required design information. Template-based layout generation is another approach to consider the design constraints, but considerable development efforts are required for each new design and each new technology. In this paper, we propose a structure-based methodology for analog layout generation. This methodology starts from a structure analysis that divides the circuit netlist into several building blocks automatically. It can help to reduce the dependence on users' input and generate corresponding design constraints for the succeeding layout steps. With the help from structure analysis, the layouts of those analog structures are generated, placed, and routed automatically with proper constraints. As shown in the demo cases, the proposed flow is able to generate the required layout accurately without users' intervention and still keeps the post-layout performance within specifications.
Forecast-Based Sample Preparation Algorithm for Unbalanced Splitting Correction on DMFBs
(2019-01-01)
Song, Ling-Yen
;
Chen, Yi-Ling
;
Lei, Yung-Chun
;
Huang, Juinn-Dar
;
電子工程學系及電子研究所
Sample preparation is regarded as one of essential processing steps in most biochemical assays. In the past decade, numerous techniques have been presented to deal with sample preparation under the (1:1) mixing model on digital microfluidic biochips (DMFBs) for various optimization goals. However, most of previous works assumed that mixing-then-splitting would get two identical output droplets, which is not always true due to unbalanced splitting. As a consequence, those works may fail to provide correct solutions at the presence of unbalanced splitting. Several methods have been proposed to deal with this issue. Nevertheless, some of them rely on hypotheses that may not be practical, while the others demand extra reactants or special hardware. In this paper, we propose a new probability-based sample preparation algorithm for unbalanced splitting correction. Our new algorithm not only guarantees a correct solution, but requires neither extra reactants nor on-chip special hardware. Experimental results show that the effect of unbalanced splitting can be eliminated only at the cost of 20% more operation steps. That is, the proposed algorithm is both reliable and efficient.
Time-Constrained Sample Preparation Algorithm for Reactant Minimization on Digital Microfluidic Biochips
(2019-01-01)
Song, Ling-Yen
;
Li, Yu-Ying
;
Lei, Yung-Chun
;
Huang, Juinn-Dar
;
電子工程學系及電子研究所
Sample preparation is one of the essential processes for most biochemical assays on biochips. Many studies have been conducted for dealing with the reactant minimization problem during sample preparation. Nevertheless, those approaches try to minimize reactant consumption at the cost of more extra operations, which may lead to deterioration of reactant and even wrong results. In this paper, we propose a time-constrained sample preparation algorithm for reactant minimization on digital microfluidic biochips (DMFBs). Starting from a given reactant-minimized solution, the proposed algorithm tries to incrementally reduce the operation count at the cost of more reactant consumption to meet the given timing constraint. The experimental results show that our algorithm achieves a 33% reactant reduction over a delay-optimal method with the same operation time. Meanwhile, the proposed method can save 5% operation count as compared with a state-of-the-art reactant minimization algorithm under the same reactant consumption.