Unified high-level synthesis and module placement for defect-tolerant microfluidic biochips

Su, Fei; Chakrabarty, Krishnendu

doi:10.1145/1065579.1065797

Cited by 155 publications

(136 citation statements)

References 14 publications

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“…Su et al represent protocols as acyclic sequence graphs and map them to droplet-based processors using automatic scheduling [Su and Chakrabarty, 2004] and module placement [Su and Chakrabarty, 2005].…”

Section: Related Workmentioning

confidence: 99%

Abstraction layers for scalable microfluidic biocomputing

et al. 2007

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Microfluidic devices are emerging as an attractive technology for automatically orchestrating the reactions needed in a biological computer. Thousands of microfluidic primitives have already been integrated on a single chip, and recent trends indicate that the hardware complexity is increasing at rates comparable to Moore's Law. As in the case of silicon, it will be critical to develop abstraction layerssuch as programming languages and Instruction Set Architectures (ISAs)-that decouple software development from changes in the underlying device technology.Towards this end, this paper presents BioStream, a portable language for describing biology protocols, and the Fluidic ISA, a stable interface for microfluidic chip designers. A novel algorithm translates microfluidic mixing operations from the BioStream layer to the Fluidic ISA. To demonstrate the benefits of these abstraction layers, we build two microfluidic chips that can both execute BioStream code despite significant differences at the device level. We consider this to be an important step towards building scalable biological computers.

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Section: Related Workmentioning

confidence: 99%

Abstraction layers for scalable microfluidic biocomputing

et al. 2007

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“…Su and Chakrabarty [10] developed a genetic algorithm that performs scheduling, module selection, and placement concurrently. The runtime of this algorithm is too large for use in an online context; however, it illustrates the importance of module selection during synthesis.…”

Section: Related Workmentioning

confidence: 99%

Path scheduling on digital microfluidic biochips

Grissom

Brisk

2012

Proceedings of the 49th Annual Design Automation Conference

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Since the inception of digital microfluidics, the synthesis problems of scheduling, placement and routing have been performed offline (before runtime) due to their algorithmic complexity. However, with the increasing maturity of digital microfluidic research, online synthesis is becoming a realistic possibility that can bring new benefits in the areas of dynamic scheduling, control-flow, fault-tolerance and live-feedback. This paper contributes to the digital microfluidic synthesis process by introducing a fast, novel path-based scheduling algorithm that produces better schedules than list scheduler for assays with high fan-out; path scheduler computes schedules in milliseconds, making it suitable for both offline and online synthesis.

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“…Placement determines the specific location on the DMFB where each assay operation will start, at the times computed by the scheduler [6][15] [16]. The placer annotates each node in the DAG with the location of the module, and outputs a .dot file, as shown in Fig.…”

Section: ) Placement Visualizationmentioning

confidence: 99%

“…Assays are specified as directed acyclic graphs (DAGs). Synthesis involves three steps: scheduling the operations [7][9] [10][12] [14], placing modules onto the device [6][15] [16], and routing droplets [13] [19]; algorithms that perform multiple steps at once, to synergize cross-boundary optimization, have also been proposed [16].…”

Section: Introductionmentioning

confidence: 99%

A digital microfluidic biochip synthesis framework

Grissom¹,

O’Neal²,

Preciado³

et al. 2012

2012 IEEE/IFIP 20th International Conference on VLSI and System-on-Chip (VLSI-SoC)

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Abstract-Synthesis of digital microfluidic biochips (DMFBs) is a crucial to the advancement and realization of miniaturized, automated, programmable biochemistry solutions; synthesis is performed in three steps: scheduling, placement and routing. In principle, algorithms for specific steps should be interchangeable with one another; however, different research groups typically develop algorithms for each step in isolation from one another. Thus, it is difficult to compare algorithms against one another, or to determine which algorithms for different steps share synergies.We introduce an open source DMFB synthesis framework to encourage collaboration between researchers working in the area. We introduce a common interface and describe the internal data structures that must be updated to ensure that the interfaces are adhered to. We also present and describe a number of highquality 2D and 3D debugging tools that provide graphical output for each stage of synthesis.

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Unified high-level synthesis and module placement for defect-tolerant microfluidic biochips

Cited by 155 publications

References 14 publications

Abstraction layers for scalable microfluidic biocomputing

Abstraction layers for scalable microfluidic biocomputing

Path scheduling on digital microfluidic biochips

A digital microfluidic biochip synthesis framework

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