I will deploy a k8s clusters on three pine64 A+ boards, all boards are installed opensuse tumbleweed, and one as k8s-master
two as k8s-minions. The whole cluster will use TLS and BRAC security mechanism.
Current Jetson Nano image is based on Ubuntu distro, This project will try to deploy a opensuse version. Furthermore, I will take a closer look on deep learning framework, and learn how they use hardware accelerator.
First, boot up Jeston nano with Ubuntu, and deploy Tensorflow(Keras), Pytorch(Caffee2), MXNet, the most popular DL framework today, on it. Understand how those frameworks take advantage of hardware accelerator.
As we know, hardware accelerator is more and more important to AI/Machine Learning today, FPGA also comes to the front line beside with GPU. It is really helpful to understand its mechanism before deploying in a cloud environment.
I will go back to on my AC620 board, A Cyclone IV FPGA, and It has been a while since last time. As part of my FPGA virtualization Project, I will continue work on some simulation, refresh my verilog skill.