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Merge pull request #2553 from ilya-lavrenov:typo

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Andrey Pavlenko
2014-03-31 23:21:06 +04:00
committed by OpenCV Buildbot
parent 97eac3f394 9b9769169f
commit 0d5ffec521
7 changed files with 8 additions and 8 deletions
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modules/gpu/doc/introduction.rst
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@@ -43,7 +43,7 @@ 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.
Switching active devie can be done using :ocv:func:`gpu::setDevice()` function. For more details please read Cuda C Programing Guide.
Switching active devie can be done using :ocv:func:`gpu::setDevice()` function. For more details please read Cuda C Programming 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: