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Companion Notebooks

Environment

To run these Jupyter notebooks, you will need an environment with JupyterLab and pynq installed, the best way to accomplish this is to create a Python virtual environment or to create a Conda environment.

The steps to Install Conda and get the environment setup are here.

Distributed Alveo cards

The Dask class and Notebooks that use such class are only intended for systems where the Alveo cards are located in different systems, either different servers or different VMs.

For these type of scenarios you can use the Notebooks as it.

Multiple Alveo cards in the same system

If you have multiple Alveo cards in the same system you can still reuse the Notebooks, but, some modifications are needed.

To begin with, we will use pynq to identify how many Alveo cards are present in the system and their id.

import pynq
for i in range(len(pynq.Device.devices)):
    print("{} {}".format(i, pynq.Device.devices[i].name))

An example output should look like this, where the first column is the id and the second one is the Alveo shell

0 xilinx_u280_xdma_201920_3
1 xilinx_u250_xdma_201830_2
2 xilinx_u280_xdma_201920_3

In this case, three cards are available. We are only interested in the Alveo U280. To use them the Overlay class in pynq allows us to specify the device where the xclbin file is downloaded.

In the companion Notebooks discard everything before Download xclbin to workers* and use this code to configure the Alveo cards. Replace Alveo id accordingly.

from vnx_utils import *
import pynq
import numpy as np

xclbin = <xclbin filename replace>
ol_w0 = pynq.Overlay(xclbin, device=pynq.Device.devices[0])
ol_w1 = pynq.Overlay(xclbin, device=pynq.Device.devices[2])

You can reuse the rest of the Notebook after this point.

Getting Started with these Notebooks

To use these notebooks you need pynq installed in your system. pynq is available in PYPI, hence you can install it using pip install pynq. However, for a smoother and more iterative experience, we recommend to use JupyterLab. As described in the Environment section, the easiest way to accomplish this is to use a Conda environment.

Once pynq and JupyterLab are installed you can start using these notebooks.

Launch JupyterLab

It is recommended to launch JupyterLab directly from the Notebooks directory.

jupyter lab

This will launch a JupyterLab on a web browser.

Double click in any of the notebooks you want to use --- files with extension *.ipynb. Learn more about JupyterLab here.

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