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Node graph architecture

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Node graph architecture is a software design structured around the concept of a node graph. The source code for the software application is organized into atomic functional units called nodes. This is typically done using classes derived from a base class for all nodes. Each node can have inputs and outputs, which are typically implemented using classes derived from a base class for all inputs and outputs. Outputs and inputs can be connected to each other, typically by holding pointers to instances of outputs and inputs. When a node executes its functionality, it retrieves its inputs by following the pointers stored in its inputs to retrieve data output by other nodes. The node then executes its operation on these inputs to produce its own outputs. The ability to link nodes together in this way allows complex tasks or problems to be broken down into atomic nodal units that are easier to understand.


Visual History

There is an ongoing effort by Eric Hosick on Twitter to collect snapshots of all node graph user interfaces in all software applications. The effort attempts to document the evolution and explosion of node graph user interfaces starting from the very first known use. This visual history is hosted on his blog page called Visual Programming Languages - Snapshots.


Ivan Sutherland's Sketchpad program, 1963

Some of the earliest uses of node graph architectures started back in the 1960s with the work of Ivan Sutherland and Alan Kay.


Blender node graph, 2006

Some of the more recent uses of node graph architectures started around 2005. Node graphs in this time frame start to develop paradigms to deal with complexity in the node graph. The complexity arose as the number of nodes and links in the graph increased. One of the main ideas dealing with complexity was the concept of a group or package node which hid nodes inside of itself, only exposing the inputs and outputs into the group.


Visual Programming Debate

Node graph architecture is a subset of the broader class of visual programming languages. Node graphs allow you to design programs in a visual and structured way instead of through the authoring of source code. In the film and video game industries node graphs are synonymous with visual programming. There is currently some debate on the power, abstraction, and need of node graphs and visual programming languages.

  • Advocates of visual programming generally emphasize how it simplifies programming because it abstracts away many details and only exposes controls that are necessary. These controls are the parameters on the nodes which control their behavior and the links between nodes.
  • Critics of visual programming generally emphasize how it does not offer enough control, and how for more complex tasks it becomes necessary to author source code. However, these more complex tasks often fall outside the intended usage or domain of the node graph.


This remains an active area of debate with new discussions occurring in open forums to this day.


Research studies tend to lean in favor of critics of node graphs. They indicate that node graphs and visual programming are easy to understand for new users, but as the users move to more complex tasks they often need to resort to authoring textual source code. However, in well-defined domains such as the film and video game industries, node graphs remain the default user interface for most digital content creation tools.

Node Graph

Nodes encapsulate some executable functionality and will often take inputs and produce outputs. A simple example is a node that adds two numbers together. The inputs are the two numbers to add and the output is the sum of the two numbers. The inputs and outputs of different nodes can be connected together. This allows the output from one node to flow to the input of another node. Nodes can also have parameters that modify their functionality. For example, in our simple example of an addition node, there could be a parameter on the node called bias, which adds another bias factor to the sum.


Example directed acyclic graph


When nodes are connected together in this way they form a graph, and many theoretical results from graph theory can be applied to the evaluation, update, and maintenance of node graphs. Nodes are linked together to form graphs. One particular area of concern during node graph evaluation is cycles. When cycles are present in the node graph, the evaluation never ends as nodes are continually revisited by following links. To avoid these problems many node graphs architectures restrict themselves to a subset of graphs known as directed acyclic graphs.


Different types of nodes working together


There are often many different node types participating in the node graph. For example, Nuke, a popular visual effects compositing program, includes hundreds of nodes.[1] each performing specific tasks. For example, Nuke's Merge node produces an output image in which a number of input images have been layered. By connecting many different node types together complex image effects can be produced.

The node graph architecture often allows the grouping of nodes inside other group nodes. This hides complexity inside of the group nodes, and limits their coupling with other nodes outside the group. This leads to a hierarchy where smaller graphs are embedded in group nodes.

In the paper Hierarchical Small Worlds in Software Architecture[2] author Sergi Valverde argues that most large software systems are built in a modular and hierarchical fashion, and that node graphs can be used to analyze large software systems. Many other software analysis papers often use node graphs to analyze large software systems suggesting that node graphs are good models of the internal structure and operation of the software[3].


User Interface

An example of a node graph based user interface

Software applications using node graph architecture will typically expose the node graph visually to the user, allowing the user to make changes to the node graph. Users will be able to visualize new nodes that they create and also manually drag links to connect nodes together using the mouse. In the image above the node graph is displayed in the mid-left panel of the image. The other panels show some of the effects of evaluating the node graph.

With the increasing usage of node graphs, there is currently increased attention on creating user-friendly interfaces. Often these new interfaces are being designed by user interface specialists and graphical designers. The following are some user interfaces designed by artists and designers.


Use in Computer Graphics

An example of a node graph based user interface


The use of node graph architecture in software design is especially popular in the film and video game industries. The diagram above shows a simplified user interface for an artistic tool for editing and creating videos. The nodes are represented as rectangles and are connected to each other through curved lines (Bezier curves). In this software's operational model, a video sequence is being passed through the lines onto the next node, and each node performs some additional modifications to the video sequence. In this example one video is translated in 2D, another is pixelated, and finally, both streams are merged together.

The following are some examples of software using node graph architecture in the film and video game industries.

Use in Machine Learning

Simple neural network layers


The use of node graph architecture in software design has recently become very popular in machine learning applications. The diagram above shows a simple neural network composed of 3 layers. The 3 layers are the input layer, the hidden layer, and the output layer. The elements in each layer are weights and are connected to weights in other layers. During inference, the machine learning algorithm evaluates the weights in the output layer through a sequence of functional evaluations over the weights from previous layers. During training, the machine learning algorithm uses optimization to minimize a loss function, where the loss function depends on the difference between the weights in the output layer and the expected values. Node graphs are used to visualize, configure and debug these neural network layers.

The following are examples of machine learning software using node graph architecture without a graphical interface for the node graphs.

The following are some examples of machine learning software using node graph architecture.


References

  1. ^ "Nuke Reference Guide". learn.foundry.com. Retrieved 2020-12-21.
  2. ^ Valverde, Sergi; Sole, Ricard V. (11 July 2003). "Hierarchical Small Worlds in Software Architecture". arXiv:cond-mat/0307278.
  3. ^ "Representation and Analysis of Software". CiteSeerX 10.1.1.394.4865. {{cite journal}}: Cite journal requires |journal= (help)
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