Full metadata
Title
Accelerating Genome Quantification in FPGA
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.
Date Created
2022
Contributors
- Kim, Kiju (Author)
- Fan, Deliang (Thesis advisor)
- Cao, Kevin (Committee member)
- Zhang, Wei (Committee member)
- Arizona State University (Publisher)
Topical Subject
Resource Type
Extent
38 pages
Language
eng
Copyright Statement
In Copyright
Primary Member of
Peer-reviewed
No
Open Access
No
Handle
https://hdl.handle.net/2286/R.2.N.168366
Level of coding
minimal
Cataloging Standards
Note
Partial requirement for: M.S., Arizona State University, 2022
Field of study: Electrical Engineering
System Created
- 2022-08-22 02:41:05
System Modified
- 2022-08-22 02:41:31
- 2 years 3 months ago
Additional Formats