VLSI/PCB placement with obstacles based on sequence-pair
Proceedings of the 1997 international symposium on Physical design
An analytical algorithm for placement of arbitrarily sized rectangular blocks
DAC '85 Proceedings of the 22nd ACM/IEEE Design Automation Conference
Chemical and Biological Applications of Digital-Microfluidic Devices
IEEE Design & Test
High-level synthesis of digital microfluidic biochips
ACM Journal on Emerging Technologies in Computing Systems (JETC)
Algorithms in c, part 5: graph algorithms, third edition
Algorithms in c, part 5: graph algorithms, third edition
ACM Journal on Emerging Technologies in Computing Systems (JETC)
Routing-based synthesis of digital microfluidic biochips
CASES '10 Proceedings of the 2010 international conference on Compilers, architectures and synthesis for embedded systems
A contamination aware droplet routing algorithm for the synthesis of digital microfluidic biochips
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Model and solution strategy for placement of rectangular blocks in the Euclidean plane
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Proceedings of the Conference on Design, Automation and Test in Europe
Optimization of polymerase chain reaction on a cyberphysical digital microfluidic biochip
Proceedings of the International Conference on Computer-Aided Design
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Droplet-based "digital" microfluidics technology has now come of age and software-controlled biochips for healthcare applications are starting to emerge. However, today's digital microfluidic biochips suffer from the drawback that there is no feedback to the control software from the underlying hardware platform. Due to the lack of precision inherent in biochemical experiments, errors are likely during droplet manipulation, but error recovery based on the repetition of experiments leads to wastage of expensive reagents and hard-to-prepare samples. By exploiting recent advances in the integration of optical detectors (sensors) in a digital microfluidics biochip, we present a "physical-aware" system reconfiguration technique that uses sensor data at checkpoints to dynamically reconfigure the biochip. A re-synthesis technique is used to recompute electrode-actuation sequences, thereby deriving new schedules, module placement, and droplet routing pathways, with minimum impact on the time-to-response.