If you perform the following : nvidia-smi -q you will see the following:
Processes
Process ID : 6564
Type : C+G
Name : C:\Windows\explorer.exe
Used GPU Memory : Not available in WDDM driver model
Not available in WDDM driver model => WDDM stand for Windows Display Driver Model. You can switch to TCC and obtain the information with the command: nvidia-smi -dm 1, however this operation can only performed if you do not have any display attached to the GPU. So... It's mostly impossible...
By the way, don't worry about a high memory usage, Tensorflow reserve as much GPU memory as it can to speed up its processes. If you prefer a finer grained control on the memory taken use the following (it may slow down a little bit your computations):
config = tf.ConfigProto()
config.gpu_options.allow_growth = True
sess = tf.Session(config=config)
You can create a dual boot on Ubuntu or just forget about this.
