6.5.3 Data division examples

You can process one-, two-, or three-dimensional data with OpenCL.


The examples map the problems into the NDRanges that have the same number of dimensions. OpenCL does not require that you do this. You can for example, map a one-dimensional problem onto a two-, or three-dimensional NDRange.

One-dimensional data

An example of one-dimensional data is audio. Audio is represented as a series of samples. Changing the volume of the audio is a parallel task, because the operation is performed independently per sample.

In this case, the NDRange is the total number of samples in the audio. Each work-item can be one sample and a work-group is a collection of samples.

Audio can also be processed with vectors. If your audio samples are 16-bit, you can make a work-item represent eight samples and process eight of them at a time with vector instructions.

Two-dimensional data

An image is a natural fit for OpenCL, because you can process a 1,600 by 1,200 pixel image by mapping it onto a two-dimensional NDRange of 1,600 by 1,200.The total number of work-items is the total number of pixels in the image, that is, 1,920,000.

The NDRange is divided into work-groups where each work-group is also a two-dimensional array. The number of work-groups must divide into the NDRange exactly.

If each work-item processes a single pixel, a work-group size of 8 by 16 has the size of 128. This work-group size fits exactly into the NDRange on both the x and y axis. To process the image, you require 15,000 work-groups of 128 work-items each.

You can vectorize this example by processing all the color channels in a single vector. If the channels are 8-bit values, you can process multiple pixels in a single vector. If each vector processes four pixels, this means each work-item processes four pixels and you require four times fewer work-items to process the entire image. This means that your NDRange can be reduced to 400 by 1,200 and you only require 3,750 work-groups to process the image.

Three-dimensional data

You can use three-dimensional data to model the behavior of materials in the real world. For example, you can model the behavior of concrete for building by simulating the stresses in a three-dimensional data set.

You can use the data produced to determine the size and design of the structure you require to hold a specific load.

You can use this technique in games to model the physics of objects. When an object is broken, the physics simulation makes the process of breaking more realistic.

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