Summary
The high demand for addressing the required processing power of today's big-data and compute-intensive applications and the cost of powerful processing units have led end-devices to move most of their data processing to clouds, edges, and datacenters. In clouds, edges, and datacenters, hardware accelerators are exploited to drastically augment the processing power of multi-core processors. Among hardware accelerators, Field Programmable Gate Arrays (FPGAs) have attracted significant attention due to their prominent performance and power efficiency. There are two main challenges in exploiting FPGAs as hardware platforms for acceleration: how to design efficient accelerators to gain high performance?, and how to efficiently enable software applications to access FPGA accelerators? In this dissertation, my focus is on the second challenge, where I show the importance of FPGA-based acceleration management on the total gained performance.
Read More ↓Edition Statements
- Publication Date:2020
Thesis Information
- Degree:Ph.D.
- University:University of California, Irvine
- Advisor/Supervisor:Bozorgzadeh, Eli
- Pages:119
Publication Statements
- Language:eng
- Publication Date:2020
Edition Identifiers
- proquest:2557256037
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