Mirela Alistar

Synthesis of biochemical applications on digital microfluidic biochips with operation execution time variability

Microfluidic-based biochips are replacing the conventional biochemical analyzers, and are able to integrate all the necessary functions for biochemical analysis. The digital microfluidic biochips are based on the manipulation of liquids not as a continuous flow, but as discrete droplets. Several approaches have been proposed for the synthesis of digital microfluidic biochips, which, starting from a biochemical application and a given biochip architecture, determine the allocation, resource binding, scheduling, placement and routing of the operations in the application. Researchers have assumed that each biochemical operation in an application is characterized by a worst-case execution time (wcet). However, during the execution of the application, due to variability and randomness in biochemical reactions, operations may finish earlier than their wcets , resulting in unexploited slack in the schedule. In this paper, we first propose an online synthesis strategy that re-synthesizes the application at runtime when operations experience variability in their execution time, exploiting thus the slack to obtain shorter application completion times. We also propose a quasi-static synthesis strategy that determines offline a database of alternative implementations. During the execution of the application, several implementations are selected based on the current execution scenario with operation execution time variability. The proposed strategies have been evaluated using several benchmarks and compared to related work.

Application-specific fault-tolerant architecture synthesis for digital microfluidic biochips

Microfluidic-based biochips are replacing the conventional biochemical analyzers, and are able to integrate onchip all the necessary functions for biochemical analysis using microfluidics. The digital microfluidic biochips are based on the manipulation of liquids not as a continuous flow, but as discrete droplets on an array of electrodes. Microfluidic operations, such as transport, mixing, split, are performed on this array by routing the corresponding droplets on a series of electrodes. Researchers have proposed several approaches for the synthesis of digital microfluidic biochips. All previous work assumes that the biochip architecture is given, and most approaches consider a rectangular shape for the electrode array. However, non-regular application-specific architectures are common in practice. Hence, in this paper, we propose an approach to the application-specific architecture synthesis. Our approach can also help the designer to increase the yield by introducing redundant electrodes to tolerate permanent faults. The proposed architecture synthesis algorithm has been evaluated using several benchmarks.

Synthesis of Application-Specific Fault-Tolerant Digital Microfluidic Biochip Architectures

Digital microfluidic biochips (DMBs) are microfluidic devices that manipulate droplets on an array of electrodes. Microfluidic operations, such as transport, mixing, and split, are performed on the electrode array to perform a biochemical application. All previous work assumes that the DMB architecture is given and most approaches consider a rectangular shape for the electrode array. However, nonrectangular application-specific architectures are common in practice. Hence, in this paper, we propose an approach to the synthesis of application-specific architectures, such that the cost of the architecture is minimized and the timing constraints of the biochemical application are satisfied. DMBs can be affected by permanent faults, which may lead to the failure of the biochemical application. Our approach introduces redundant electrodes to synthesize fault-tolerant architectures aiming at increasing the yield of DMBs. We have used a tabu search metaheuristic for this architecture synthesis problem. We have proposed a technique to evaluate the architecture alternatives visited during the search, in terms of their impact on the timing constraints of the application. The proposed architecture synthesis approach has been evaluated using several benchmarks.

Towards droplet size-aware biochemical application compilation for AM-EWOD biochips

Microfluidic-based biochips are replacing the conventional biochemical analyzers, and are able to integrate onchip all the necessary functions for biochemical analysis using microfluidics. The digital microfluidic biochips are based on the manipulation of liquids not as a continuous flow, but as discrete droplets on an array of electrodes. Microfluidic operations, such as transport, mixing, split, are performed on this array by routing the corresponding droplets on a series of electrodes. Several approaches have been proposed for the compilation of digital microfluidic biochips, which, starting from a biochemical application and a given biochip architecture, determine the allocation, resource binding, scheduling, placement and routing of the operations in the application. To simplify the compilation problem, researchers have assumed an abstract droplet size of one electrode. However, the droplet size abstraction is not realistic and it impacts negatively the execution of the biochemical application, leading in most cases to its failure. Hence the existing compilation approaches have to be revisited to consider the size of the droplets. In this paper we take the first step towards a droplet size-aware compilation by proposing a routing algorithm that considers the droplet size. Our routing algorithm is developed for a novel digital microfluidic biochip architecture based on Active Matrix Electrowetting on Dielectric, which uses a thin film transistor array for the electrodes. We also implement a simulator that allows us to perform the needed adaptations and to validate the proposed routing algorithm.

Design Methodology for Digital Microfluidic Biochips

This chapter presents an overview of the digital biochip design process, highlighting the main design tasks, with a focus on fault-tolerant biochips. The purpose is to explain how the methods presented in this book are used within a design methodology and to define the main design tasks. We highlight the difference between the “compilation” and “synthesis” terms used throughout the book. We discuss in more detail the compilation task, which is covered by Parts II and III, and its constituent subtasks. The architecture synthesis tasks are covered in Part IV. This chapter is intended to help in understanding how the methods presented in the book interact with each other. This chapter also presents the related work in the area of compilation and architecture synthesis approaches for digital microfluidic biochips.

Fault-Tolerant Digital Microfluidic Biochips: Compilation and Synthesis

This book describes for researchers in the fields of compiler technology, design and test, and electronic design automation the new area of digital microfluidic biochips (DMBs), and thus offers a new application area for their methods. The authors present a routing-based model of operation execution, along with several associated compilation approaches, which progressively relax the assumption that operations execute inside fixed rectangular modules. Since operations can experience transient faults during the execution of a bioassay, the authors show how to use both offline (design time) and online (runtime) recovery strategies. The book also presents methods for the synthesis of fault-tolerant application-specific DMB architectures. · Presents the current models used for the research on compilation and synthesis techniques of DMBs in a tutorial fashion; · Includes a set of benchmarks , which are presented in great detail and includes the source code of most of the techniques presented, including solutions to the basic compilation and synthesis problems; · Discusses several new research problems in detail, using numerous examples.

Biochemical Application Model

This chapter presents the models we use for biochemical applications. We give an informal presentation of the syntax and semantics of the high-level protocol language and define the biochemical application model used in the book. The purpose of the high-level protocol language is to describe biochemical assays in a precise and unambiguous way to allow automatic extraction of the biochemical application. The biochemical application model represents the microfluidic operations of an assay and their interdependencies in terms of input and output relations. We first present a high-level protocol language called Aqua, which serves as the basis for the high-level language we consider in this book. Then, we present a sequencing graph model that captures the behavior of the biochemical protocol. Each node in the graph represents an operation and the edges represent fluid transport. The next chapter presents how the high-level language is compiled into the graph representation. The graph model is used as an input to several of the design tasks addressed in the book.

The Compilation Problem

This chapter presents in detail the compilation task, which, given the biochemical application and biochip architecture models as inputs, produces the electrode actuation sequence required to run the application on the given biochip. Each of the compilation subtasks, such as, allocation, binding, placement, scheduling and routing are discussed in a corresponding subsection. These subtasks have a high computational complexity, and we have used a heuristic algorithm called “List Scheduling” as a starting point for providing solutions to them. Hence, this chapter also covers the “List Scheduling” heuristic. The compilation task also takes as input a “library of modules” on which the operations on the biochemical applications have to execute. We present a method to determine a library of “circular-route modules”, which will be used in Part IV of the book, to support application-specific architectures. To simplify the presentation, this chapter presents the compilation task assuming that an operation executes on a static rectangular “module”. However, as discussed in Chap. 3, we also consider other operation execution models in the book; these will be covered in the next chapters related to the compilation task.

Biochip Architecture Model

This chapter presents in detail how digital microfluidic biochips work, and introduces the architecture model we use in the book. Digital microfluidic biochips are organized as an array of electrodes, each of which can hold one droplet, and move the droplets of fluid using electrokinetics. We present the key ideas behind electrowetting-on-dielectric, the fluid propulsion method used in these biochips. We discuss the basic microfluidic operations, such as transport, splitting, dispensing, mixing, and detection, focusing on the reconfigurable operations, which are characteristic to droplet-based biochips. The reconfigurable operations are typically performed inside “virtual modules”, which are created by grouping adjacent cells. During module-based operation execution, all cells inside the module are considered occupied, although the droplet uses only one cell at a time, which is inefficient. Therefore, we introduce a new, “routing-based”, model of operation execution and propose an analytical method for determining the completion time of an operation on any given route. The chapter also presents the typical faults affecting digital microfluidic biochips and the fault models considered in this book, as well as a detailed discussion of how these faults can affect the operation execution.

Module-Based Compilation with Reconfigurable Operation Execution

This chapter also proposes a solution to the compilation of biochemical applications on a given biochip architecture. The compilation problem proposed in the previous chapter has assumed that reconfigurable operations are performed inside rectangular modules whose location and shape remain fixed throughout the execution of operations. However, as discussed in Sect. 3.4, reconfigurable operations can be performed anywhere on the array, by simply routing the corresponding droplets on a sequence of electrodes. In this chapter, we propose two models for operation execution inside virtual devices, which take into consideration the reconfigurability of microfluidic operations: (1) moving a module during the operation execution and (2) changing the shape of the device on which an operation is bound during its execution. These operation execution models aim at reducing the fragmentation of the free space on the microfluidic array during the placement step of the compilation process. In this context, we revisit the compilation problem and present an extension to the Tabu Search metaheuristic optimization solution introduced earlier, with a focus on a new dynamic module placement algorithm. The advantages of the new operation execution models are evaluated using extensive experiments.