Download Hardware/Software Co-Design and Optimization for by Yan Luo, Krishnendu Chakrabarty, Tsung-Yi Ho PDF

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By Yan Luo, Krishnendu Chakrabarty, Tsung-Yi Ho

This e-book describes a accomplished framework for hardware/software co-design, optimization, and use of strong, inexpensive, and cyberphysical electronic microfluidic structures. Readers with a historical past in digital layout automation will locate this booklet to be a worthy reference for leveraging traditional VLSI CAD suggestions for rising applied sciences, e.g., biochips or bioMEMS. Readers from the circuit/system layout neighborhood will reap the benefits of equipment provided to increase layout and trying out innovations from microelectronics to mixed-technology microsystems. For readers from the microfluidics area, this e-book offers a brand new layout and improvement procedure for cyberphysical microfluidics-based biochips appropriate for large-scale bioassay applications.

• Takes a transformative, “cyberphysical” strategy in the direction of reaching closed-loop and sensor feedback-driven biochip operation lower than software control;
• provides a “physically-aware” method reconfiguration approach that makes use of sensor information at intermediate checkpoints to dynamically reconfigure biochips;
• allows readers to simplify the constitution of biochips, whereas facilitating the “general-purpose” use of electronic microfluidic biochips for a much broader diversity of applications.

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Additional info for Hardware/Software Co-Design and Optimization for Cyberphysical Integration in Digital Microfluidic Biochips

Sample text

The procedure for automatical search of the droplets can be described as a “template matching” problem. Here a pattern can be represented as the image of a “typical” droplet. During the matching process, we move the template image to all possible positions in the image of the entire array and crop a sub-image that has the same size as the template image. Then the control software computes the correlation index, which measures the similarity between the template and the “cropped image”. The correlation factor is calculated on a pixelby-pixel basis, and this process is shown in Fig.

1007/978-3-319-09006-1__2 27 28 2 Error-Recovery in Cyberphysical Biochips Due to the complex and randomness component interactions that are ubiquitous in biological/chemical processes, predictive modeling and accuracy control become difficult [5, 6]. In addition to manufacturing defects and imperfections, various faults may also arise during bioassay execution. For example, DNA fouling may lead to malfunction of multiple electrodes in the biochip and excessive actuation voltage applied to an electrode may lead to breakdown of electrodes and charge trapping [7–9].

T. Xu and K. Chakrabarty, “Integrated droplet routing in the synthesis of microfluidic biochips”, Proc. IEEE/ACM Design Automation Conference, pp. 948–953, 2007. 43. T. Xu and K. Chakrabarty, “Broadcast electrode-addressing for pin-constrained multifunctional digital microfluidic biochips”, Proc. IEEE/ACM Design Automation Conference, pp. 173–178, 2008. 44. Y. Zhao and K. Chakrabarty, “Simultaneous optimization of droplet routing and control-pin mapping to electrodes in digital microfluidic biochips”, IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, vol.

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