In the previous blog post we learned how to integrate Xilinx Vivado with Docker and Jenkins to build automatically (or with a single button) the FPGA bitstream.
During the project life span, the FPGA bitstream is going to be built a large number of times. Wouldn’t be interesting to collect metrics from each build and track them?
In this blog post of the series “FPGA meets DevOps” I am going show you how to get metrics from a Xilinx Vivado build and track them in Jenkins using the Plot plugin.
In particular we are going to track resource usage (i.e. LUT, FF, DSP and memory). This gives you insight on how the resource usage evolved during the project life span and if the FPGA is getting too full.
In this second blog post of the series “FPGA meets DevOps” I am going show you how to integrate Xilinx Vivado with Docker and Jenkins.
Docker provides a lightweight operating system level virtualisation. It allows developers to package up an application with all the parts it needs in a container, and then ship it out as one package. A container image is described by a file (Dockerfile) which contains a sequence of commands to create the image itself (i.e.: packages to install, configuration tasks, etc) and it is all you need to replicate the exact build environment on another machine.
The objective is to create a container that will run Vivado in headless mode (without user interface) to build the FPGA image.