Description
The growth in speed and density of programmable logic devices, such as Field programmable gate arrays (FPGA), enables sophisticated designs to be created within a short time frame. The flexibility of a programmable device alleviates the difficulty of the integration of a design with a wide range of components on a single chip. FPGAs bring both performance and power efficiency, especially for compute or data-intensive applications. Efficient and accurate mRNA quantification is an essential step for molecular signature identification, disease outcome prediction, and drug development, which is a typical compute- and data-intensive compute workload. In this work, I propose to accelerate mRNA quantification with FPGA implementation. I analyze the performance of mRNA Quantification with FPGA, which shows better or similar performance compared to that of CPU implementation.
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Details
Title
- Accelerating Genome Quantification in FPGA
Contributors
- Kim, Kiju (Author)
- Fan, Deliang (Thesis advisor)
- Cao, Kevin (Committee member)
- Zhang, Wei (Committee member)
- Arizona State University (Publisher)
Date Created
The date the item was original created (prior to any relationship with the ASU Digital Repositories.)
2022
Subjects
Resource Type
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Note
- Partial requirement for: M.S., Arizona State University, 2022
- Field of study: Electrical Engineering