Graph Shaders for Visualizing Large Graphs

This repository contains the code to visualize large graphs using Graph Shader Programs (.GSP).

The Graph Shaders (GS) system architecture is comprised of three main pieces:

• The GS Engine is a C++ program that loads graph data from disk and configures OpenGL to render specially designed shaders.

• The GS Transpiler is a Python program that parses .GSP programs and is configured using #pragma statements.

• The GS Server is a Python program that provides an HTTP API to render graphs from a web browser.

The remainder of this repository is a set of example scripts.

Building

In the simplest case, the GS Engine can be compiled using CMake like any other CMake program.

$ cmake -Bbuild
$ cmake --build build
$ cmake --install build

We also provide a Dockerfile for making setup easier. It can be accessed directly by calling docker, but we also have a helper script go.sh that simplifies some of the repeated arguments.

$ ./go.sh docker build
$ ./go.sh docker start
$
$ ./go.sh docker exec ./go.sh gs configure
$ ./go.sh docker exec ./go.sh gs build
$ ./go.sh docker exec ./go.sh gs install

Examples

We provide several example GS Programs. The data can be downloaded from our server.

$ wget -O examples/JS-Deps/JS-Deps.data.tar.gz https://accona.eecs.utk.edu/JS-Deps.data.tar.gz
$ wget -O examples/SO-Answers/SO-Answers.data.tar.gz https://accona.eecs.utk.edu/SO-Answers.data.tar.gz
$ wget -O examples/NBER-Patents/NBER-Patents.data.tar.gz https://accona.eecs.utk.edu/NBER-Patents.data.tar.gz
$
$ (cd examples/JS-Deps && tar xvf JS-Deps.data.tar.gz)
$ (cd examples/SO-Answers && tar xvf SO-Answers.data.tar.gz)
$ (cd examples/NBER-Patents && tar xvf NBER-Patents.data.tar.gz)

If you are using our go.sh scripts, then you can execute our example scripts:

$ ./go.sh docker exec ./go.sh gs exec ./examples/JS-Deps/JS-Deps.sh
$ ./go.sh docker exec ./go.sh gs exec ./examples/SO-Answers/SO-Answers.sh
$ ./go.sh docker exec ./go.sh gs exec ./examples/NBER-Patents/NBER-Patents.sh

Otherwise, you should make sure that GraphShaderEngine and GraphShaderTranspiler.py are within your path.

Example: JS-Deps

Example: SO-Answers

Example: NBER-Patents

Running the GS Server

The GS Server requires the flask and flask-cors libraries to be installed.

These can be installed using:

$ ./go.sh docker exec ./go.sh gs exec python3 -m virtualenv venv
$ ./go.sh docker exec ./go.sh gs exec venv/bin/python3 -m pip install flask flask-cors

The server is designed to only load one dataset at a time. This functionality is based on replacing the GS Transpiler executable that the server calls, to a shell script that calls the GS Transpiler with some file paths.

$ ./go.sh docker exec ./go.sh gs exec venv/bin/python3 -u src/GraphShaderServer.py --gst-executable ./examples/JS-Deps/JS-Deps.sh

Running the server outside of a Docker environment is left as an exercise to the reader 😅

Two frontends are provided for the GS Server.

• A very simplistic HTML page in src/index.html that renders a single image tile at a time from the text box on the page.

• A more advanced library in the ObservableHQ notebook environment that supports stitching multiple tiles into a single image. Available here