Path scheduling on digital microfluidic biochips

Grissom, Daniel; Brisk, Philip

doi:10.1145/2228360.2228367

Cited by 60 publications

(62 citation statements)

References 12 publications

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“…LS-based syntheses have been proposed previously for online error recovery [1], [8], [5] and the comparisons to the approaches based on metaheuristics show that LS provides good results in a short time [1].…”

Section: Online Synthesis Strategy (Ons)mentioning

confidence: 99%

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Online synthesis for operation execution time variability on digital microfluidic biochips

Alistar

Pop

2014

2014 International Symposium on Integrated Circuits (ISIC)

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Abstract-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. In this paper we propose an online synthesis strategy that re-synthesizes the application at runtime when operations experience variability in their execution time, obtaining thus shorter application execution times. The proposed strategy has been evaluated using several benchmarks.

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Section: Online Synthesis Strategy (Ons)mentioning

confidence: 99%

“…To be executed on a DMB, a biochemical application has to be synthesized [5], [3], [9]. All synthesis strategies proposed so far in related research (the only exception is [7]) consider a given module library L, which contains for each operation its worst-case execution time (wcet).…”

Section: Introductionmentioning

confidence: 99%

Online synthesis for operation execution time variability on digital microfluidic biochips

Alistar

Pop

2014

2014 International Symposium on Integrated Circuits (ISIC)

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“…We are aware of two heuristics, Modified List Scheduling (MLS) [11] and Path Scheduling (PS) [3], two genetic algorithms (GA-1, GA-2) [9][11], and two optimal integer linear programming (ILP) formulations [2][11].…”

Section: Related Workmentioning

confidence: 99%

“…PS [3] is based on the observation that storing droplets on-chip reduces the availability of resources for other operations. This is important for assays with a large fanout in their DAG representation.…”

Section: Related Workmentioning

confidence: 99%

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Force-Directed List Scheduling for Digital Microfluidic Biochips

O’Neal

Grissom

Brisk

2012

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

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Abstract-We introduce a Force-directed List Scheduling (FDLS) algorithm for resource-constrained assay compilation targeting Digital Microfluidic Biochips (DMFBs). This algorithm has been used in the past for high-level synthesis of digital signal processing systems, and is now applied to DMFB synthesis. The results show improvements compared to List Scheduling (LS) and Path Scheduling (PS), the most efficient heuristics that have been proposed, to date, for DMFBs. FDLS was also competitive with longer-running iterative improvement DMFB scheduling algorithms based on genetic algorithms.

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A hybrid artificial bee colony algorithm for scheduling of digital microfluidic biochip operations

Rajesh

Pyne

2021

Concurrency and Computation

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Summary Digital microfluidic biochips (DMFBs) are designed to efficiently carry out biochemical and biomedical analysis in a miniaturized way. DMFBs offer various advantages over traditional laboratory techniques and reduces cost, and increases automation and software programmability. Scheduling of microfluidic operations is the first and essential step in the fluidic‐level synthesis of DMFBs, while the other two are the module placement and droplet routing. Scheduling DMFB operations is a multiconstrained optimization problem, and the particular decision problem is NP‐complete. We propose a hybrid artificial bee colony (ABC) algorithm using generalized N‐point crossover (GNX) based scheduling of DMFB operations. Proposed ABC‐GNX perturbs through search space, evaluates various schedules possible, and returns the best schedule among the evaluated schedules. Simple list scheduling based heuristic algorithms can explore a single schedule based on the sequence generated by the priority function. Iterative improvement based search algorithms explore the search space and evaluate more schedules, but the proposed ABC‐GNX algorithm produces optimal solutions in shorter execution times. Simulation results show that the proposed ABC‐GNX produces a higher number of optimal completion times and faster execution times than existing algorithms.

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Path scheduling on digital microfluidic biochips

Cited by 60 publications

References 12 publications

Online synthesis for operation execution time variability on digital microfluidic biochips

Online synthesis for operation execution time variability on digital microfluidic biochips

Force-Directed List Scheduling for Digital Microfluidic Biochips

A hybrid artificial bee colony algorithm for scheduling of digital microfluidic biochip operations

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