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I am working on my master's project which uses keras and tensorflow backend .I have intel(r) hd graphics 520 ,So I am not able to use tensorflow-gpu. The cpu version is working fine .Is there any way to use tensorflow-gpu with the intel(r) hd graphics 520?
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Tensorflow can be now activated on Intel-gpus as well..
Yes, You Can Run NVIDIA CUDA On Intel GPUs And Libraries For It Have Hit Github. Using a graphics processor or GPU for tasks beyond just rendering 3D graphics is how NVIDIA has made billions in the datacenter space.
If a TensorFlow operation has no corresponding GPU implementation, then the operation falls back to the CPU device. For example, since tf. cast only has a CPU kernel, on a system with devices CPU:0 and GPU:0 , the CPU:0 device is selected to run tf. cast , even if requested to run on the GPU:0 device.
Intel added a technology called Deep Link, to allow intelligent power-sharing between the CPU and GPU of the computer to boost its performance for machine learning tasks. Hence, the accelerated performance is much faster at processing AI workloads compared to processors with comparably energy consumption.
Tensorflow GPU support needs Nvidia Cuda and CuDNN packages installed. For GPU accelerated training you will need a dedicated GPU. Intel onboard graphics can't be used for that purpose.
You can see full requirements for tensorflow-gpu here
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I saw this page just now (published on Sep 2020). Accordingly, it is possible to run Tensorflow on DirectX 12 compatible GPUs using DirectML library. It is called TensorFlow-DirectML.
TensorFlow is an end-to-end open source platform for machine learning. This repository is a fork of tensorflow that leverages DirectML to provide cross-vendor hardware acceleration on Windows 10 and the Windows Subsystem for Linux (WSL). TensorFlow with DirectML enables training and inference of complex machine learning models on a wide range of DirectX 12-compatible hardware.
There are some other discussion about OpenCL here.
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