Tsung-Yi Ho

Error Recovery in Cyberphysical Digital Microfluidic Biochips

Droplet-based digital microfluidics technology has now come of age, and software-controlled biochips for healthcare applications are starting to emerge. However, todays 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; 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) into a digital microfluidics biochip, we present a physical-aware system reconfiguration technique that uses sensor data at intermediate checkpoints to dynamically reconfigure the biochip. A cyberphysical resynthesis 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.

Digital microfluidic biochips: a vision for functional diversity and more than Moore

Advances in droplet-based digital microfluidics have led to the emergence of biochips for automating laboratory procedures in biochemistry and molecular biology. These devices enable the precise control of microliter of nanoliter volumes of biochemical samples and reagents. They combine electronics with biology, and integrate various bioassay operations, such as sample preparation, analysis, separation, and detection. Compared to conventional laboratory procedures, which are cumbersome and expensive, miniaturized digital microfluidic biochips (DMFBs) offer the advantages of higher sensitivity, lower cost, system integration, and less likelihood of human error. This tutorial paper provides an overview of DMFBs and describes emerging computer-aided design (CAD) tools for the automated synthesis and optimization of biochips, from physical modeling to fluidic-level synthesis and then to chip-level design. By efficiently utilizing the electronic design automation (EDA) technique on emerging CAD tools, users can concentrate on the development of nanoscale bioas-says, leaving chip optimization and implementation details to design-automation tools.

A Fast Crosstalk- and Performance-Driven Multilevel Routing System

In this paper, we propose a novel framework for fast multilevelrouting considering crosstalk and performance optimization. To handlethe crosstalk minimization problem, we incorporate an intermediatestage of layer/track assignment into the multilevel routing framework.For performance-driven routing, we propose a novel minimum-radiusminimum-cost spanning-tree (MRMCST) heuristic for global routing.Compared with the state-of-the-art multilevel routing, the experimentalresults show that our approach achieved a 6.7X runtime speedup, reducedthe respective maximum and average crosstalk (coupling length)by about 30% and 24%, reduced the respective maximum and averagedelay by about 15% and 5%, and resulted in fewer failed nets.

A Reagent-Saving Mixing Algorithm for Preparing Multiple-Target Biochemical Samples Using Digital Microfluidics

Recent advances in digital microfluidics have led to the promise of miniaturized laboratories, with the associated advantages of high sensitivity and less human-induced errors. Front-end operations such as sample preparation play a pivotal role in biochemical laboratories, and in applications in biomedical engineering and life science. For fast and high-throughput biochemical applications, preparing samples of multiple target concentrations sequentially is inefficient and time-consuming. Therefore, it is critical to concurrently prepare samples of multiple target concentrations. In addition, since reagents used in biochemical reactions are expensive, reagent-saving has become an important consideration in sample preparation. Prior work in this area does not address the problem of reagent-saving and concurrent sample preparation for multiple target concentrations. In this paper, we propose the first reagent-saving mixing algorithm for biochemical samples of multiple target concentrations. The proposed algorithm not only minimizes the consumption of reagents, but it also reduces the number of waste droplets and the sample preparation time by preparing the target concentrations concurrently. The proposed algorithm is evaluated on both real biochemical experiments and synthetic test cases to demonstrate its effectiveness and efficiency. Compared to prior work, the proposed algorithm can achieve up to 41% reduction in the number of reagent droplets and waste droplets, and up to 50% reduction in sample preparation time.

A Contamination Aware Droplet Routing Algorithm for the Synthesis of Digital Microfluidic Biochips

Recent advances of digital microfluidic biochips (DMFBs) have revolutionized the traditional laboratory procedures. By providing the droplet-based system, DMFB can perform real-time biological analysis and safety-critical biomedical applications. However, different droplets being transported and manipulated on the DMFB may introduce the contamination problem caused by liquid residue between different biomolecules. To overcome this problem, a wash droplet is introduced to clean the contaminations on the surface of the microfluidic array. However, current scheduling of wash droplet does not restrict the extra used cells and execution time of bioassay, thereby degrading the reliability and fault-tolerance significantly. In this paper, we propose a contamination aware droplet routing algorithm for DMFBs. To reduce the routing complexity and the used cells, we first construct preferred routing tracks by analyzing the global moving vector of droplets to guide the droplet routing. To cope with contaminations within one subproblem, we first apply a k -shortest path routing technique to minimize the contaminated spots. Then, to take advantage of multiple wash droplets, we adopt a minimum cost circulation (MCC) algorithm for optimal wash-droplet routing to simultaneously minimize used cells and the cleaning time. Since the droplet routing problem consists of several subproblems, a look-ahead prediction technique is further used to determine the contaminations between successive subproblems. After that, we can simultaneously clean both contaminations within one subproblem and those between successive subproblems by using the MCC-based algorithm to reduce the execution time and the used cells significantly. Based on four widely used bioassays, our algorithm reduces the used cells and the execution time significantly compared with the state-of-the-art algorithm.

Crosstalk- and performance-driven multilevel full-chip routing

In this paper, we propose a novel framework for fast multilevel routing considering crosstalk and performance optimization. To handle the crosstalk minimization problem, we incorporate an intermediate stage of layer/track assignment into the multilevel routing framework. For performance-driven routing, we propose a novel minimum-radius minimum-cost spanning tree heuristic for global routing. Compared with the state-of-the-art multilevel routing with the routability mode, the experimental results show that our router achieved a 6.7X runtime speedup, reduced the respective maximum and average crosstalk (coupling length) by about 30% and 24%, reduced the respective maximum and average delay by about 15% and 5%. Compared with the timing-driven mode, the experimental results show that our router still achieved a 5.9X runtime speedup, reduced the respective maximum and average crosstalk by about 35% and 23%, reduced the respective maximum and average delay by about 7% and 10% in comparable routability, and resulted in fewer failed nets.

Multilevel routing with antenna avoidance

As technology advances into the nanometer territory, the antenna problem has caused significant impact on routing tools. The antenna effect is a phenomenon of plasma-induced gate oxide degradation caused by charge accumulation on conductors. It directly influences manufacturability and yield of VLSI circuits, especially in deep-submicron technology using high density plasma. Furthermore, the continuous increase of the problem size of IC routing is also a great challenge to existing routing algorithms. In this paper, we propose a novel framework for multilevel full-chip routing with antenna avoidance using a built-in jumper insertion approach. Experimental results show that our approach reduced antenna-violated gates by about 98% and also achieved 100% routing completion for all circuits.

Multilevel full-chip routing for the X-based architecture

As technology advances into the nanometer territory, the interconnect delay has become a first-order effect on chip performance. To handle this effect, the X-architecture has been proposed for high-performance integrated circuits. The X-architecture presents a new way of orienting a chips microscopic interconnect wires with the pervasive use of diagonal routes. It can reduce the wire-length and via count, and thus improve performance and routability. Furthermore, the continuous increase of the problem size of IC routing is also a great challenge to existing routing algorithms. In this paper, we present the first multilevel framework for full-chip routing using the X-architecture. To take full advantage of the X-architecture, we explore the optimal routing for three-terminal nets on the X-architecture and develop a general X-Steiner tree algorithm based on the Delaunay triangulation approach for the X-architecture. The multilevel routing framework adopts a two-stage technique of coarsening followed by uncoarsening, with a trapezoid-shaped track assignment embedded between the two stages to assign long, straight diagonal segments for wirelength reduction. Compared with the state-of-the-art multilevel routing for the Manhattan architecture, experimental results show that our approach reduced wirelength by 18.7% and average delay by 8.8% with similar routing completion rates and via counts.

A cyberphysical synthesis approach for error recovery in digital microfluidic biochips

Droplet-based “digital” microfluidics technology has now come of age and software-controlled biochips for healthcare applications are starting to emerge. However, todays 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.

Reliability-oriented broadcast electrode-addressing for pin-constrained digital microfluidic biochips

Designs for pin-constrained digital microfluidic biochips (PDMFBs) are receiving much attention because they simplify chip fabrication and packaging, and reduce product cost. To reduce the pin count, broadcast addressing, by minimally grouping electrode sets with non-conflict signal merging, has emerged as a promising solution. Nevertheless, naive signal merging has the potential to cause excessive electrode actuations, which has been reported to have direct and adverse effect on chip reliability. According to recent studies, reliability is an important attribute for PDMFBs particularly developed for medical applications as it directly affects the final medical decision making. However, no research findings have been reported on the reliability problem in pin-constrained designs. To make PDMFBs more feasible for practical applications, we propose in this paper the first matching-based reliability-oriented broadcast-addressing algorithm for PDMFBs. We identify the factors that affect reliability and incorporate into the design-technique attributes that enhance reliability. Experimental results demonstrate the effectiveness of the proposed algorithm.