Differnt GPU's in one System

Talk about Hardware used for Deep Learning
Post Reply
User avatar
tochan
Posts: 8
Joined: Sun Sep 22, 2019 8:17 am

Differnt GPU's in one System

Post by tochan » Fri Oct 11, 2019 4:15 pm

Hi,

last month my 1080 died so i buy a 2080 for the warrenty time ;). Now the fixed 1080 is back and i plug the 2 Cards in my Sys butt the Training speed is not faster or bigger batches are possible. The Clock speed of card 1 and 2 are high and not in the idl but the Temp from the second GPU is very low.

Gpus found in the output Systen information.

In the Analysis the EGs/sec are much lower with one GPU (2080).
Can some help here? Need i 2 same cards with a SLI bridge?

Thanks

Sys info:

============ System Information ============
encoding: cp1252
git_branch: master
git_commits: 5887cb5 GUI Bugfix: Fix csv saving in analysis tab. fb34e17 Merge branch 'staging' of https://github.com/deepfakes/faceswap into staging. 7a70ac6 GUI: Fix disappearing columns on resize. c63b080 Add non-fixed items to session item in state.json. e0b0bc8 Increase count_frames_and_secs timeout
gpu_cuda: 9.0
gpu_cudnn: 7.0.5
gpu_devices: GPU_0: GeForce RTX 2080, GPU_1: GeForce GTX 1080
gpu_devices_active: GPU_0, GPU_1
gpu_driver: 436.48
gpu_vram: GPU_0: 8192MB, GPU_1: 8192MB
os_machine: AMD64
os_platform: Windows-10-10.0.18362-SP0
os_release: 10
py_command: C:\Users\denni\faceswap/faceswap.py gui
py_conda_version: conda 4.5.12
py_implementation: CPython
py_version: 3.6.8
py_virtual_env: True
sys_cores: 16
sys_processor: AMD64 Family 23 Model 1 Stepping 1, AuthenticAMD
sys_ram: Total: 65467MB, Available: 48840MB, Used: 16626MB, Free: 48840MB

=============== Pip Packages ===============
absl-py==0.7.0
astor==0.7.1
certifi==2019.6.16
Click==7.0
cloudpickle==0.8.0
cmake==3.13.3
cycler==0.10.0
cytoolz==0.9.0.1
dask==1.1.4
decorator==4.3.2
dlib==19.16.99
face-recognition==1.2.3
face-recognition-models==0.3.0
fastcluster==1.1.25
ffmpy==0.2.2
gast==0.2.2
grpcio==1.16.1
h5py==2.9.0
imageio==2.5.0
imageio-ffmpeg==0.3.0
Keras==2.2.4
Keras-Applications==1.0.7
Keras-Preprocessing==1.0.9
kiwisolver==1.0.1
Markdown==3.0.1
matplotlib==2.2.2
mkl-fft==1.0.10
mkl-random==1.0.2
mock==2.0.0
networkx==2.2
numpy==1.16.2
nvidia-ml-py3==7.352.1
olefile==0.46
opencv-python==4.1.1.26
pathlib==1.0.1
pbr==5.1.3
Pillow==6.1.0
protobuf==3.6.1
psutil==5.6.1
pyparsing==2.3.1
pyreadline==2.1
python-dateutil==2.8.0
pytz==2018.9
PyWavelets==1.0.2
pywin32==224
PyYAML==3.13
scikit-image==0.14.2
scikit-learn==0.20.3
scipy==1.2.1
six==1.12.0
tensorboard==1.12.2
tensorflow==1.12.0
tensorflow-estimator==1.13.0
termcolor==1.1.0
toolz==0.9.0
toposort==1.5
tornado==6.0.1
tqdm==4.31.1
Werkzeug==0.14.1
wincertstore==0.2

============== Conda Packages ==============
# packages in environment at C:\Users\denni\MiniConda3\envs\faceswap:
#
# Name Version Build Channel
_tflow_select 2.1.0 gpu
absl-py 0.7.0 py36_0
astor 0.7.1 py36_0
blas 1.0 mkl
ca-certificates 2019.5.15 0
certifi 2019.6.16 py36_1
Click 7.0 <pip>
cloudpickle 0.8.0 py36_0
cmake 3.13.3 <pip>
cudatoolkit 9.0 1
cudnn 7.3.1 cuda9.0_0
cycler 0.10.0 py36h009560c_0
cytoolz 0.9.0.1 py36hfa6e2cd_1
dask-core 1.1.4 py_0
decorator 4.3.2 py36_0
dlib 19.16.99 <pip>
face-recognition 1.2.3 <pip>
face-recognition-models 0.3.0 <pip>
fastcluster 1.1.25 py36h830ac7b_1000 conda-forge
ffmpeg 4.1 h6538335_1002 conda-forge
ffmpy 0.2.2 <pip>
freetype 2.9.1 ha9979f8_1
gast 0.2.2 py36_0
grpcio 1.16.1 py36h351948d_1
h5py 2.9.0 py36h5e291fa_0
hdf5 1.10.4 h7ebc959_0
icc_rt 2019.0.0 h0cc432a_1
icu 58.2 ha66f8fd_1
imageio 2.5.0 py36_0
imageio-ffmpeg 0.3.0 <pip>
intel-openmp 2019.1 144
jpeg 9c hfa6e2cd_1001 conda-forge
keras 2.2.4 0
keras-applications 1.0.7 py_0
keras-base 2.2.4 py36_0
keras-preprocessing 1.0.9 py_0
kiwisolver 1.0.1 py36h6538335_0
libblas 3.8.0 8_mkl conda-forge
libcblas 3.8.0 8_mkl conda-forge
liblapack 3.8.0 8_mkl conda-forge
liblapacke 3.8.0 8_mkl conda-forge
libmklml 2019.0.3 0
libpng 1.6.36 h2a8f88b_0
libprotobuf 3.6.1 h7bd577a_0
libtiff 4.0.10 hb898794_2
libwebp 1.0.2 hfa6e2cd_2 conda-forge
markdown 3.0.1 py36_0
matplotlib 2.2.2 py36had4c4a9_2
mkl 2019.1 144
mkl_fft 1.0.10 py36h14836fe_0
mkl_random 1.0.2 py36h343c172_0
mock 2.0.0 py36h9086845_0
networkx 2.2 py36_1
numpy 1.16.2 py36h19fb1c0_0
numpy-base 1.16.2 py36hc3f5095_0
nvidia-ml-py3 7.352.1 <pip>
olefile 0.46 py36_0
opencv 4.1.0 py36hb4945ee_5 conda-forge
opencv-python 4.0.0.21 <pip>
opencv-python 4.1.1.26 <pip>
openssl 1.1.1c he774522_1
pathlib 1.0.1 py36_1
pbr 5.1.3 py_0
pillow 6.1.0 py36hdc69c19_0
pip 19.0.3 py36_0
protobuf 3.6.1 py36h33f27b4_0
psutil 5.6.1 py36he774522_0
pyparsing 2.3.1 py36_0
pyqt 5.9.2 py36h6538335_2
pyreadline 2.1 py36_1
python 3.6.8 h9f7ef89_7
python-dateutil 2.8.0 py36_0
pytz 2018.9 py36_0
pywavelets 1.0.2 py36h8c2d366_0
pywin32 224 <pip>
pyyaml 3.13 py36hfa6e2cd_0
qt 5.9.7 vc14h73c81de_0
scikit-image 0.14.2 py36ha925a31_0
scikit-learn 0.20.3 py36h343c172_0
scipy 1.2.1 py36h29ff71c_0
setuptools 40.8.0 py36_0
sip 4.19.8 py36h6538335_0
six 1.12.0 py36_0
sqlite 3.27.2 he774522_0
tensorboard 1.12.2 py36h33f27b4_0
tensorflow 1.12.0 gpu_py36ha5f9131_0
tensorflow-base 1.12.0 gpu_py36h6e53903_0
tensorflow-estimator 1.13.0 py_0
tensorflow-gpu 1.12.0 h0d30ee6_0
termcolor 1.1.0 py36_1
tk 8.6.8 hfa6e2cd_0
toolz 0.9.0 py36_0
toposort 1.5 <pip>
tornado 6.0.1 py36he774522_0
tqdm 4.31.1 py_0
vc 14.1 h0510ff6_4
vs2015_runtime 14.15.26706 h3a45250_0
werkzeug 0.14.1 py36_0
wheel 0.33.1 py36_0
wincertstore 0.2 py36h7fe50ca_0
xz 5.2.4 h2fa13f4_4
yaml 0.1.7 hc54c509_2
zlib 1.2.11 h62dcd97_3
zstd 1.3.7 h508b16e_0

User avatar
bryanlyon
Site Admin
Posts: 74
Joined: Fri Jul 12, 2019 12:49 am
Answers: 9
Location: San Francisco
Has thanked: 3 times
Been thanked: 14 times
Contact:

Re: Differnt GPU's in one System

Post by bryanlyon » Fri Oct 11, 2019 4:16 pm

To use 2 GPUs, you should set GPU in the GUI or CLI to "2" and then increase the BS accordingly.

User avatar
tochan
Posts: 8
Joined: Sun Sep 22, 2019 8:17 am

Re: Differnt GPU's in one System

Post by tochan » Fri Oct 11, 2019 4:33 pm

I do this but only the freqency from the 1080 go high an "a little bit the Temps". with select one GPU the 1080 freqency is in idle. Need i Linux for this?

Post Reply