Tensorflow Doesn't Allocate Full Gpu Memory

Tensorflow allocates all of GPU memory per default, but my new settings actually only are 9588 MiB / 11264 MiB. I expected around 11.000MiB like my old settings. Tensorflow informa

Solution 1:

It is necessary to use the TCC driver to avoid windows reserving some of the VRAM. You may be using the WDDM driver.

Here is the page on TCC: https://docs.nvidia.com/gameworks/content/developertools/desktop/nsight/tesla_compute_cluster.htm

Here is a related question: How can I use 100% of VRAM on a secondary GPU from a single process on windows 10?

Solution 2:

import tensorflow as tf
gpu_options = tf.GPUOptions(per_process_gpu_memory_fraction=0.2)
sess = tf.Session(config=tf.ConfigProto(gpu_options=gpu_options))
from keras import backend as K
import tensorflow as tf
config = tf.ConfigProto()
config.gpu_options.per_process_gpu_memory_fraction = 0.2
session = tf.Session(config=config)
K.set_session(session)

This works well for my case