CODEWITHSUNDEEP
pythontensorflow
Amin Darestani
Amin Darestani

Reputation: 1

Using GPU cores for parallel computing in Tensorflow

I am working on tensorflow-gpu and pyqt5 for an object detection system.

I have developed a project based on neural network model which is trained by tensorflow and it is good but I need to speed up the detection rate.

My GPU is GTX 1060 and CPU is Corei7.

How can I use CUDA cores to divide my computations ?

I have searched a lot of articles and I have asked it several times in *stack** overflow* but there is no response.

How can I use tensorflow-gpu with programming CUDA cores by libraries like PYCUDA or numba or CUPY?

I have asked this question in several manners but I am looking for a right approach to use CUDA for programming GPU cores( GTX1060 has 1280 CUDA cores but Corei7 has 8 core and by giving computations to GPU , program will speed up in a large scale)

Upvotes: 0

Views: 404

Answers (1)

pierresegonne
pierresegonne

Reputation: 446

See here for installation of tensorflow-gpu. In a script, tensorflow automatically uses GPU if available, but you can check this for more information to check the number of available cores or select some manually etc

Upvotes: 1

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