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