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Hardware/Software Co-Design and Optimization for Cyberphysical Integration in Digital Microfluidic Biochips 2015 ed. [Kõva köide]

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  • Formaat: Hardback, 197 pages, kõrgus x laius: 235x155 mm, kaal: 4823 g, 60 Illustrations, color; 38 Illustrations, black and white; XII, 197 p. 98 illus., 60 illus. in color., 1 Hardback
  • Ilmumisaeg: 22-Aug-2014
  • Kirjastus: Springer International Publishing AG
  • ISBN-10: 3319090054
  • ISBN-13: 9783319090054
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Hardware/Software Co-Design and Optimization for Cyberphysical Integration in Digital Microfluidic Biochips 2015 ed.Suurem pilt
  • Formaat: Hardback, 197 pages, kõrgus x laius: 235x155 mm, kaal: 4823 g, 60 Illustrations, color; 38 Illustrations, black and white; XII, 197 p. 98 illus., 60 illus. in color., 1 Hardback
  • Ilmumisaeg: 22-Aug-2014
  • Kirjastus: Springer International Publishing AG
  • ISBN-10: 3319090054
  • ISBN-13: 9783319090054
Teised raamatud teemal:
Püsilink: https://www.kriso.ee/db/9783319090054.html
Märksõnad:

This book describes a comprehensive framework for hardware/software co-design, optimization, and use of robust, low-cost, and cyberphysical digital microfluidic systems. Readers with a background in electronic design automation will find this book to be a valuable reference for leveraging conventional VLSI CAD techniques for emerging technologies, e.g., biochips or bioMEMS. Readers from the circuit/system design community will benefit from methods presented to extend design and testing techniques from microelectronics to mixed-technology microsystems. For readers from the microfluidics domain, this book presents a new design and development strategy for cyberphysical microfluidics-based biochips suitable for large-scale bioassay applications.

• Takes a transformative, “cyberphysical” approach towards achieving closed-loop and sensor feedback-driven biochip operation under program control;
• Presents a “physically-aware” system reconfiguration technique that uses sensor data at intermediate checkpoints to dynamically reconfigure biochips;
• Enables readers to simplify the structure of biochips, while facilitating the “general-purpose” use of digital microfluidic biochips for a wider range of applications.

1 Introduction
1(26)
1.1 Overview of Digital Microfluidics
4(10)
1.1.1 Theory of Electrowetting-on-Dielectric
4(3)
1.1.2 Hardware Platform
7(1)
1.1.3 Sensing Systems
8(4)
1.1.4 Fault Models
12(2)
1.2 Computer-Aided Design and Optimization
14(9)
1.2.1 Design Flow for Digital Microfluidic Biochips
14(2)
1.2.2 Testing Techniques
16(2)
1.2.3 Error Recovery
18(1)
1.2.4 Pin-Assignment Methods
18(3)
1.2.5 Chip-Level Design
21(2)
1.3 Outline of the Book
23(4)
References
24(3)
2 Error-Recovery in Cyberphysical Biochips
27(34)
2.1 Motivation and Related Prior Work
27(3)
2.2 Overview of Cyberphysical Biochips
30(6)
2.2.1 Sensing Systems
30(4)
2.2.2 "Physical-Aware" Software
34(1)
2.2.3 Interfaces Between Biochip and Control Software
34(2)
2.3 Reliability-Driven Error-Recovery
36(7)
2.3.1 Error Recovery Strategies
36(3)
2.3.2 Reliability Consideration in Error-Recovery
39(2)
2.3.3 Comparison Between Two Sensing Schemes
41(2)
2.4 Error Recovery and Dynamic Re-synthesis
43(9)
2.4.1 Off-Line Data Preparation Before Bioassay Execution
44(1)
2.4.2 On-Line Monitoring of Droplets and Re-synthesis of the Bioassay
45(7)
2.5 Simulation Results
52(6)
2.5.1 Preparation of Plasmid DNA
52(3)
2.5.2 Protein Assays: Interpolating Mixing and Exponential Dilution
55(3)
2.6
Chapter Summary and Conclusions
58(3)
References
59(2)
3 Real-Time Error Recovery Using a Compact Dictionary
61(34)
3.1 Motivation and Related Prior Work
61(3)
3.2 Generation of the Error Dictionary
64(5)
3.2.1 Dictionary Entry for Error-Free Case
65(2)
3.2.2 Dictionary Entries for Single-Operation Errors
67(1)
3.2.3 Dictionary Entries for Multiple-Operation Errors
68(1)
3.2.4 Consideration of Error-Recovery Cost and Reduction in the Number of Dictionary Entries
68(1)
3.3 Actuation Matrix
69(3)
3.4 Estimation for the Percentage of Non-zero Elements in Actuation Matrices
72(2)
3.5 Compaction of the Error Dictionary
74(2)
3.5.1 Compaction of the Actuation Matrix
74(1)
3.5.2 De-Compaction of the Error Dictionary
75(1)
3.6 Implementation of Dictionary-Based Error Recovery on FPGA
76(4)
3.6.1 Sensing Module
77(1)
3.6.2 Memory for Storage of the Error Dictionary
78(1)
3.6.3 FSM Module
79(1)
3.6.4 De-Compaction Module
79(1)
3.6.5 Resource Report for Synthesized Modules
79(1)
3.7 Fault Simulation in the Presence of Chip-Parameter Variations
80(2)
3.8 Simulation Results
82(10)
3.8.1 Exponential Dilution of a Protein Sample
82(6)
3.8.2 Interpolation Dilution of a Protein Sample
88(1)
3.8.3 Mixing Tree Bioassay
89(1)
3.8.4 PCR Bioassay
90(1)
3.8.5 Flash Chemistry
91(1)
3.9
Chapter Summary and Conclusions
92(3)
References
93(2)
4 Biochemistry Synthesis Under Completion-Time Uncertainties in Fluidic Operations
95(22)
4.1 Introduction
95(2)
4.2 Biochips with Multiple Clock Frequencies
97(3)
4.3 Operation-Dependency-Aware Synthesis
100(5)
4.3.1 Synthesis for Sequencing Graphs with Directed Tree Structure
101(2)
4.3.2 Synthesis for Sequencing Graphs in General Cases
103(2)
4.4 Droplet-Routing Procedure
105(4)
4.4.1 Routability Analysis
106(2)
4.4.2 Searching Droplet-Routing Paths
108(1)
4.4.3 Online Decision-Making for Droplet-Routing
108(1)
4.5 Simulation Results
109(5)
4.5.1 Comparisons Between the Proposed Synthesis Algorithm and Previous Algorithms
109(1)
4.5.2 Number of Droplets Consumed
109(4)
4.5.3 Results Derived by the Operation-Interdependency- Aware Synthesis Approach
113(1)
4.5.4 Completion Time with Multiple Clock Frequencies
114(1)
4.6
Chapter Summary and Conclusions
114(3)
References
115(2)
5 Optimization of On-Chip Polymerase Chain Reaction
117(30)
5.1 Introduction
117(3)
5.2 Cyberphysical Biochip with On-line Decision Making
120(3)
5.2.1 Statistical Model for the Number of DNA Strands in a Droplet
121(1)
5.2.2 A Simplified Statistical Model for Amplification of DNA
121(1)
5.2.3 An Improved Statistical Model for Amplification of DNA
122(1)
5.3 Optimized Resource Placement Under Proximity Constraints
123(7)
5.3.1 Device-Proximity Constraints on a PCR Biochip
124(1)
5.3.2 Objective Function for Device Placement
125(1)
5.3.3 Device Placement on a PCR Biochip
126(2)
5.3.4 Optimization of Device Placement Results
128(2)
5.4 Bioassay-Specific Reservoir Allocation for PCR Biochip
130(5)
5.4.1 Electrode Ring on Low-Cost Biochips
130(1)
5.4.2 Droplet Routing on Low-Cost PCR Biochip
131(2)
5.4.3 Bioassay-Specific Reservoir Allocation
133(2)
5.5 Visibility-Aware Droplet Detection
135(3)
5.6 Experimental Results
138(6)
5.6.1 Probabilistic Control of DNA Amplification
138(2)
5.6.2 Layout Design for PCR Biochips
140(3)
5.6.3 Defect Tolerance of Layouts for PCR Biochips
143(1)
5.7 Conclusion
144(3)
References
145(2)
6 Pin-Count Minimization for Application-Independent Chips
147(38)
6.1 Motivation and Related Prior Work
147(2)
6.2 Analysis of Pin-Assignment
149(6)
6.2.1 Pin-Actuation Conflicts
149(1)
6.2.2 Control-Pin Sharing and Concurrent Movement of Droplets
150(5)
6.3 ILP Model for Pin-Assignment
155(1)
6.4 Heuristic Optimization Method
156(10)
6.5 Manipulation of Large Droplets
166(4)
6.5.1 Transportation of 2× Droplets
166(2)
6.5.2 Influence of Diagonal Electrodes
168(2)
6.6 Scheduling of Fluid-Handling Operations
170(3)
6.7 Simulation Results
173(9)
6.7.1 Commercial Biochips
174(3)
6.7.2 Experimental Biochips
177(3)
6.7.3 Simulation Results on Regular Array
180(2)
6.8
Chapter Summary and Conclusions
182(3)
References
182(3)
7 Pin-Limited Cyberphysical Microfluidic Biochip
185(10)
7.1 Introduction
185(2)
7.2 Wire Routing for General-Purpose Pin-Limited Biochips
187(3)
7.3 Design Flow for Pin-Limited Cyberphysical Biochips
190(1)
7.4 Simulation Results
191(2)
7.4.1 Results Derived by the Operation-Interdependency- Aware Synthesis Approach
191(1)
7.4.2 Completion Time with Multiple Clock Frequencies on Pin-Limited Biochip
192(1)
7.5
Chapter Summary and Conclusions
193(2)
References
193(2)
8 Conclusions
195
Yan Luo received the Bachelor degree from Tsinghua University,Beijing, in 2010, and the Master and Ph.D. degrees from Duke University in North Carolina, in 2012 and 2013, respectively. Dr.Luo's research interests include hardware/software co-design for cyber-physical system, engineering data analysis and design/implementation of high-volume, fault-tolerant, scalable backend systems that process and manage petabytes of engineering data. Since obtaining her Ph.D. degree, Dr. Luo has worked in the IT industry in Silicon Valley. Currently as a Research Scientist at Sumo Logic Inc., Dr. Luo applies her expertise and talents of cyber-physical systems in the hybrid software and system research and machine data analytics with real-time monitor and control capabilities, creating next-generation large-scale computing systems and IT environment with high performance, scalability, and reliability. Dr. Luo has published 10 papers in refereed journals and conferences and authored one book chapter. Dr. Luo was invited as technique committee members and reviewers for more than 20 international conferences and journals.

Krishnendu Chakrabarty is the William H. Younger Distinguished Chair Professor of Engineering in the Department of Professor of Electrical and Computer Engineering and Professor of Computer Science at Duke University. He is a recipient of the National Science Foundation Early Faculty (CAREER) award, the Office of Naval Research Young Investigator award, the Humboldt Research Award from the Alexander von Humboldt Foundation, Germany, and 10 best paper awards at major IEEE conferences. Prof. Chakrabartys current research projects include: testing and design-for-testability of integrated circuits; digital microfluidics, biochips, and cyberphysical systems; optimization of digital print and enterprise systems. He is a Fellow of ACM, a Fellow of IEEE, and a Golden Core Member of the IEEE Computer Society.

Tsung-Yi Horeceived his Ph.D. degrees in Electrical Engineering from National Taiwan University, Taipei, Taiwan, ROC, in 2005. Since 2007, he has been with the Department of Computer Science and Information Engineering, National Cheng Kung University, Tainan, Taiwan, ROC, where he is currently an Associate Professor. His research interests include design automation for microfluidic biochips and nanometer integrated circuits. He has published several papers in top journals and conferences such as IEEE TCAD, ACM TODAES, ACM/IEEE DAC, IEEE/ACM ICCAD, ACM ISPD, and etc. He presented 8 tutorials and contributed 4 special sessions in ACM/IEEE conferences, all in design automations on biochips. He was the recipient of many research awards, such as Dr. Wu Ta-You Memorial Award of National Science Council (NSC) of Taiwan (the most prestigious award from NSC for junior researchers), Distinguished Young Scholar Award of Taiwan IC Design Society, Outstanding Young Electrical Engineer Award of Chinese Institute of Electrical Engineering, K. T. Li Research Award of Delta Electronics, ACM Taipei Chapter Young Researcher Award, IEEE Tainan Chapter Gold Member Award, the Invitational Fellowship of the Japan Society for the Promotion of Science (JSPS), Japan, and the Humboldt Research Fellowship from the Alexander von Humboldt Foundation, Germany. Currently, he serves as a Distinguished Visitor of the IEEE Computer Society, the Chair of IEEE Computer Society Tainan Chapter and an Associate Editor of ACM Journal on Emerging Technologies in Computing Systems and IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems. He is a senior member of IEEE.