Tutorial Node: Attributes With CUDA Data

This is a tutorial node. It performs different functions on the GPU to illustrate different types of data access. The first adds inputs ‘a’ and ‘b’ to yield output ‘sum’, all of which are on the GPU. The second is a sample expansion deformation that multiplies every point on a set of input points, stored on the GPU, by a constant value, stored on the CPU, to yield a set of output points, also on the GPU. The third is an assortment of different data types illustrating how different data is passed to the GPU. This particular node uses CUDA for its GPU computations, as indicated in the memory type value. Normal use case for GPU compute is large amounts of data. For testing purposes this node only handles a very small amount but the principle is the same.

Installation

To use this node enable omni.graph.tutorials in the Extension Manager.

Inputs

Name

Type

Descripton

Default

A (inputs:a)

float

First value to be added in algorithm 1

0.0

B (inputs:b)

float

Second value to be added in algorithm 1

0.0

Color (inputs:color)

colord[3]

Input with three doubles as a color for algorithm 3

[1.0, 0.5, 1.0]

Half (inputs:half)

half

Input of type half for algorithm 3

1.0

Matrix (inputs:matrix)

matrixd[4]

Input with 16 doubles interpreted as a double-precision 4d matrix

[[1.0, 0.0, 0.0, 0.0], [0.0, 1.0, 0.0, 0.0], [0.0, 0.0, 1.0, 0.0], [0.0, 0.0, 0.0, 1.0]]

Multiplier (inputs:multiplier)

float[3]

Amplitude of the expansion for the input points in algorithm 2

[1.0, 1.0, 1.0]

Points (inputs:points)

float[3][]

Points to be moved by algorithm 2

[]

Outputs

Name

Type

Descripton

Default

Color (outputs:color)

colord[3]

Output with three doubles as a color for algorithm 3

None

Half (outputs:half)

half

Output of type half for algorithm 3

None

Matrix (outputs:matrix)

matrixd[4]

Output with 16 doubles interpreted as a double-precision 4d matrix

None

Points (outputs:points)

float[3][]

Final positions of points from algorithm 2

None

Sum (outputs:sum)

float

Sum of the two inputs from algorithm 1

None

Metadata

Name

Value

Unique ID

omni.graph.tutorials.CudaData

Version

1

Extension

omni.graph.tutorials

Icon

ogn/icons/omni.graph.tutorials.CudaData.svg

Has State?

False

Implementation Language

C++

Default Memory Type

cuda

Generated Code Exclusions

None

uiName

Tutorial Node: Attributes With CUDA Data

__memoryType

cuda

Categories

tutorials

Generated Class Name

OgnTutorialCudaDataDatabase

Python Module

omni.graph.tutorials

See the accompanying tutorial and annotated code at Tutorial 8 - GPU Data Node