GPU Computing

Run image processing code on a graphics processing unit (GPU)

To take advantage of the performance benefits offered by a modern graphics processing unit (GPU), certain Image Processing Toolbox™ functions can perform image processing operations on a GPU. These functions provide GPU acceleration for complicated image processing workflows.

Functions

`gather`	Transfer distributed array, `Composite` object, or `gpuArray` object to local workspace
`gpuArray`	Array stored on GPU

Topics

Image Processing on a GPU
Take advantage of graphics processing unit (GPU) acceleration for complicated image processing workflows.
Parallel Block Processing on Large Image Files
If you have a Parallel Computing Toolbox™ license, you can take advantage of multiple processor cores on your machine to improve the performance of blockproc.
Functions Supporting GPU Computing

Related Information

GPU Computing in MATLAB

Featured Examples

Perform Pixel-Based Operations on GPU

Perform pixel-based operations on a GPU by using functions that send both the data and the operations to the GPU for processing. This method is most effective for element-wise operations that require two or more data sets.

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Perform Thresholding and Morphological Operations on GPU

Perform image processing operations on a GPU. The example uses filtering to highlight the watery areas in an aerial photograph.

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