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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

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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    Title
    • Accelerating Genome Quantification in FPGA
    Contributors
    Date Created
    2022
    Resource Type
  • Text
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    Note
    • Partial requirement for: M.S., Arizona State University, 2022
    • Field of study: Electrical Engineering

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