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Author Su, Fei ♦ Chakrabarty, Krishnendu
Source ACM Digital Library
Content type Text
Publisher Association for Computing Machinery (ACM)
File Format PDF
Copyright Year ©2008
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science
Subject Keyword High-level synthesis ♦ Biochips ♦ Microfluidics ♦ Scheduling ♦ System-on-chip
Abstract Microfluidic biochips offer a promising platform for massively parallel DNA analysis, automated drug discovery, and real-time biomolecular recognition. Current techniques for full-custom design of droplet-based “digital” biochips do not scale well for concurrent assays and for next-generation system-on-chip (SOC) designs that are expected to include microfluidic components. We propose a system design methodology that attempts to apply classical high-level synthesis techniques to the design of digital microfluidic biochips. We focus here on the problem of scheduling bioassay functions under resource constraints. We first develop an optimal scheduling strategy based on integer linear programming. However, because the scheduling problem is NP-complete, we also develop two heuristic techniques that scale well for large problem instances. A clinical diagnostic procedure, namely multiplexed in-vitro diagnostics on human physiological fluids, is first used to illustrate and evaluate the proposed method. Next, the synthesis approach is applied to a protein assay, which serves as a more complex bioassay application. The proposed synthesis approach is expected to reduce human effort and design cycle time, and it will facilitate the integration of microfluidic components with microelectronic components in next-generation SOCs.
ISSN 15504832
Age Range 18 to 22 years ♦ above 22 year
Educational Use Research
Education Level UG and PG
Learning Resource Type Article
Publisher Date 2008-01-01
Publisher Place New York
e-ISSN 15504840
Journal ACM Journal on Emerging Technologies in Computing Systems (JETC)
Volume Number 3
Issue Number 4
Page Count 32
Starting Page 1
Ending Page 32

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Source: ACM Digital Library