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Using FPGAs for Accelerating Machine Learning Applications
Project Objective
Evaluate performance of FPGA-based Machine Learning (ML) accelerators when used for real-time inference and/or signal processing.
Reading Material
- Xilinx Alveo 200 Cards
- Xilinx Machine Learning Suite
- Overview of FPGA architecture (especially for Xilinx devices), and comparison between FPGA and CPU
Week 1 Activites
- Get ORBIT/COSMOS account and familiarize oneself with the testbed procedures
- Learn about FPGAs
- Run simple perceptron model in Python
Note:
See TracWiki
for help on using the wiki.