= 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 ==

* [https://www.xilinx.com/products/boards-and-kits/alveo/u200.html Xilinx Alveo 200 Cards]
* [https://www.xilinx.com/products/acceleration-solutions/xilinx-machine-learning-suite.html Xilinx Machine Learning Suite]
* [https://www.xilinx.com/support/documentation/sw_manuals/ug998-vivado-intro-fpga-design-hls.pdf  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 
* [https://machinelearningmastery.com/implement-perceptron-algorithm-scratch-python/ Run simple perceptron model in Python]