The GTX 745 and the tensorflow – gpu installation on Windows
Authoress: Eleonora Bernasconi
NVIDIA GeForce GTX 745 Graphics Card specifications
Specifications:https://www.geforce.com/hardware/desktop-gpus/geforce-gtx-745-oem/specifications
CUDA Cores: 384
Base Clock (MHz): 1033
Memory Clock: 1.8 Gbps
Standard Memory Config: 4 GB
Memory Interface: DDR3
Memory Bandwidth (GB/sec): 28.8
Figure 01 – nvidia-smi for GPU monitoring
Open the command prompt and insert:
cd C:\Program Files\NVIDIA Corporation\NVSMI
nvidia-smi
N.B. The percentage of use of the GPU ranges between 92% and 94%, in the Windows Task Manager it remains at 70%.
Installing TensorFlow with GPU on Windows 10
Requirements
Python 3.5
Nvidia CUDA GPU. Make sure you do have a CUDA-capable NVIDIA GPU on your system.
Setting up the Nvidia GPU card
Install Cuda Toolkit 8.0 e cuDNN v5.1.
Download and install CUDA Toolkit
Toolkit 8.0 https://developer.nvidia.com/cuda-downloads
Example installation directory: C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v8.0
Download and install cuDNN
Install cuDNN version 5.1 for Windows 10:https://developer.nvidia.com/cudnn
Extract the cuDNN files and enter them in the Toolkit directory.
Environment variables
Make sure after installing CUDA toolkit, that CUDA_HOME is set in the environment variables, otherwise add them manually.
Figure 02 – Environmet variables CUDA_HOME parte 01
Figure 03 – Environmet variables CUDA_HOME parte 02
Install Anaconda
Download : https://www.anaconda.com/download/
Create a new environment with the name tensorflow-gpu and the python version 3.5.2
conda create -n tensorflow-gpu python=3.5.2
N.B. If you find that you have incompatible versions, turn on these commands to resolve the problem:
conda install -c conda-forge tensorflow-gpu
Anaconda will automatically install the required versions of cuda, cudNN and other packages.
Figure 04 – conda install -c conda-forge tensorflow-gpu
activate tensorflow-gpu
Figure 05 – activate tensorflow-gpu
Install tensorFlow
pip install tensorflow-gpu
Figure 06 – pip install tensorflow-gpu
Now you are done and you have successfully installed tensorflow with the GPU!
Remember to activate the command: activate tensorflow-gpu to get into GPU mode!
Test GPU
python
import tensorflow as tf
sess = tf.Session(config=tf.ConfigProto(log_device_placement=True))
Figure 07 – test GPU
Test on CIFAR-10 with 10 epochs
Average Training Time per epoch:150 sec
Total time: 25 min
Figure 08 – Test on CIFAR-10 with 10 epochs
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