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Merge branch 'master' of code.opencv.org:opencv

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Vladislav Vinogradov
2012-08-07 16:09:04 +04:00
parent 76d46e20de ce9b97c78c
commit cd58b7e154
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modules/gpu/doc/introduction.rst
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@@ -42,7 +42,7 @@ You can always determine at runtime whether the OpenCV GPU-built binaries (or PT
Utilizing Multiple GPUs
-----------------------
In the current version, each of the OpenCV GPU algorithms can use only a single GPU. So, to utilize multiple GPUs, you have to manually distribute the work between GPUs.
In the current version, each of the OpenCV GPU algorithms can use only a single GPU. So, to utilize multiple GPUs, you have to manually distribute the work between GPUs.
Switching active devie can be done using :ocv:func:`gpu::setDevice()` function. For more details please read Cuda C Programing Guide.
While developing algorithms for multiple GPUs, note a data passing overhead. For primitive functions and small images, it can be significant, which may eliminate all the advantages of having multiple GPUs. But for high-level algorithms, consider using multi-GPU acceleration. For example, the Stereo Block Matching algorithm has been successfully parallelized using the following algorithm:
@@ -59,5 +59,5 @@ While developing algorithms for multiple GPUs, note a data passing overhead. For
With this algorithm, a dual GPU gave a 180
%
performance increase comparing to the single Fermi GPU. For a source code example, see
http://code.opencv.org/svn/opencv/trunk/opencv/samples/gpu/.
http://code.opencv.org/projects/opencv/repository/revisions/master/entry/samples/gpu/.