How to enable NVIDIA T4 GPU with podman
We will enable GPU with Podman on a RHEL 8.1 system with a NVIDIA Tesla T4:
Take a RHEL 8.1 system:
[egallen@lab0 ~]$ cat /etc/redhat-release
Red Hat Enterprise Linux release 8.1 (Ootpa)
Enable sudo passwordless:
[egallen@lab0 ~]$ echo "egallen ALL=(root) NOPASSWD:ALL" | sudo tee -a /etc/sudoers.d/egallen
Register your node:
[egallen@lab0 ~]$ sudo subscription-manager register --username rhnuser
[egallen@lab0 ~]$ sudo subscription-manager attach --pool=XXXXXXXXX
[egallen@lab0 ~]$ sudo subscription-manager repos --enable=rhel-8-for-x86_64-baseos-rpms --enable=rhel-8-for-x86_64-appstream-rpms
The NVIDIA Tesla T4 PCI device is available:
[egallen@lab0 ~]$ sudo dnf install pciutils -y
[egallen@lab0 ~]$ lspci -nn | grep -i nvidia
01:00.0 3D controller [0302]: NVIDIA Corporation TU104GL [Tesla T4] [10de:1eb8] (rev a1)
Check the hardware:
[egallen@lab0 ~]$ sudo lshw -numeric -C display
*-display
description: 3D controller
product: TU104GL [Tesla T4] [10DE:1EB8]
vendor: NVIDIA Corporation [10DE]
physical id: 0
bus info: pci@0000:01:00.0
version: a1
width: 64 bits
clock: 33MHz
capabilities: pm bus_master cap_list
configuration: driver=nvidia latency=0
resources: irq:16 memory:f6000000-f6ffffff memory:e0000000-efffffff memory:f0000000-f1ffffff
*-display
description: VGA compatible controller
product: HD Graphics 630 [8086:5912]
vendor: Intel Corporation [8086]
physical id: 2
bus info: pci@0000:00:02.0
version: 04
width: 64 bits
clock: 33MHz
capabilities: pciexpress msi pm vga_controller bus_master cap_list rom
configuration: driver=i915 latency=0
resources: irq:137 memory:f5000000-f5ffffff memory:d0000000-dfffffff ioport:f000(size=64) memory:c0000-dffff
Enable EPEL repositories:
[egallen@lab0 ~]$ sudo dnf install https://dl.fedoraproject.org/pub/epel/epel-release-latest-8.noarch.rpm -y
Get the last updates:
[egallen@instance0 ~]$ sudo dnf upgrade -y
Install kernel-devel:
[egallen@lab0 ~]$ sudo dnf install kernel-devel -y
Reboot the node:
[egallen@lab0 ~]$ sudo systemctl reboot
Nouveau kernel module is enabled and will be disabled by the NVIDIA install:
[egallen@lab0 ~]$ sudo lsmod | grep nouveau
nouveau 2215936 0
mxm_wmi 16384 1 nouveau
ttm 110592 1 nouveau
i2c_algo_bit 16384 2 i915,nouveau
drm_kms_helper 217088 2 i915,nouveau
drm 524288 5 drm_kms_helper,i915,ttm,nouveau
wmi 32768 2 mxm_wmi,nouveau
video 45056 2 i915,nouveau
Enable NVIDIA repositories:
[egallen@lab0 ~]$ sudo dnf config-manager --add-repo http://developer.download.nvidia.com/compute/cuda/repos/rhel8/x86_64/cuda-rhel8.repo
Updating Subscription Management repositories.
Adding repo from: http://developer.download.nvidia.com/compute/cuda/repos/rhel8/x86_64/cuda-rhel8.repo
Install cuda and cuda-drivers:
[egallen@lab0 ~]$ sudo dnf install cuda -y
Updating Subscription Management repositories.
Last metadata expiration check: 0:00:35 ago on Sun 15 Dec 2019 04:02:27 PM CET.
Dependencies resolved.
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Package Architecture Version Repository Size
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Installing:
cuda x86_64 10.2.89-1 cuda 6.1 k
Installing dependencies:
nsight-systems-2019.5.2 x86_64 2019.5.2.16_b54ef97-0 cuda 109 M
cuda-10-2 x86_64 10.2.89-1 cuda 6.1 k
cuda-command-line-tools-10-2 x86_64 10.2.89-1 cuda 6.2 k
cuda-compiler-10-2 x86_64 10.2.89-1 cuda 6.1 k
cuda-cudart-10-2 x86_64 10.2.89-1 cuda 151 k
cuda-cudart-dev-10-2 x86_64 10.2.89-1 cuda 861 k
cuda-cufft-10-2 x86_64 10.2.89-1 cuda 108 M
cuda-cufft-dev-10-2 x86_64 10.2.89-1 cuda 206 M
cuda-cuobjdump-10-2 x86_64 10.2.89-1 cuda 106 k
cuda-cupti-10-2 x86_64 10.2.89-1 cuda 15 M
cuda-curand-10-2 x86_64 10.2.89-1 cuda 42 M
cuda-curand-dev-10-2 x86_64 10.2.89-1 cuda 43 M
cuda-cusolver-10-2 x86_64 10.2.89-1 cuda 129 M
cuda-cusolver-dev-10-2 x86_64 10.2.89-1 cuda 29 M
cuda-cusparse-10-2 x86_64 10.2.89-1 cuda 79 M
cuda-cusparse-dev-10-2 x86_64 10.2.89-1 cuda 159 M
cuda-demo-suite-10-2 x86_64 10.2.89-1 cuda 4.7 M
cuda-documentation-10-2 x86_64 10.2.89-1 cuda 132 M
cuda-driver-dev-10-2 x86_64 10.2.89-1 cuda 20 k
cuda-drivers x86_64 440.33.01-1 cuda 6.8 k
cuda-gdb-10-2 x86_64 10.2.89-1 cuda 3.5 M
cuda-libraries-10-2 x86_64 10.2.89-1 cuda 6.3 k
cuda-libraries-dev-10-2 x86_64 10.2.89-1 cuda 6.4 k
cuda-license-10-2 x86_64 10.2.89-1 cuda 22 k
cuda-memcheck-10-2 x86_64 10.2.89-1 cuda 180 k
cuda-misc-headers-10-2 x86_64 10.2.89-1 cuda 1.7 M
cuda-npp-10-2 x86_64 10.2.89-1 cuda 86 M
cuda-npp-dev-10-2 x86_64 10.2.89-1 cuda 86 M
cuda-nsight-10-2 x86_64 10.2.89-1 cuda 268 M
cuda-nsight-compute-10-2 x86_64 10.2.89-1 cuda 7.8 k
cuda-nsight-systems-10-2 x86_64 10.2.89-1 cuda 7.3 k
cuda-nvcc-10-2 x86_64 10.2.89-1 cuda 48 M
cuda-nvdisasm-10-2 x86_64 10.2.89-1 cuda 21 M
cuda-nvgraph-10-2 x86_64 10.2.89-1 cuda 97 M
cuda-nvgraph-dev-10-2 x86_64 10.2.89-1 cuda 57 M
cuda-nvjpeg-10-2 x86_64 10.2.89-1 cuda 1.7 M
cuda-nvjpeg-dev-10-2 x86_64 10.2.89-1 cuda 1.8 M
cuda-nvml-dev-10-2 x86_64 10.2.89-1 cuda 71 k
cuda-nvprof-10-2 x86_64 10.2.89-1 cuda 3.8 M
cuda-nvprune-10-2 x86_64 10.2.89-1 cuda 49 k
cuda-nvrtc-10-2 x86_64 10.2.89-1 cuda 8.9 M
cuda-nvrtc-dev-10-2 x86_64 10.2.89-1 cuda 14 k
cuda-nvtx-10-2 x86_64 10.2.89-1 cuda 68 k
cuda-nvvp-10-2 x86_64 10.2.89-1 cuda 114 M
cuda-runtime-10-2 x86_64 10.2.89-1 cuda 6.1 k
cuda-samples-10-2 x86_64 10.2.89-1 cuda 89 M
cuda-sanitizer-api-10-2 x86_64 10.2.89-1 cuda 3.5 M
cuda-toolkit-10-2 x86_64 10.2.89-1 cuda 6.7 k
cuda-tools-10-2 x86_64 10.2.89-1 cuda 6.0 k
cuda-visual-tools-10-2 x86_64 10.2.89-1 cuda 6.8 k
dnf-plugin-nvidia noarch 1.1-1.el8 cuda 8.5 k
kmod-nvidia-latest-dkms x86_64 3:440.33.01-1.el8 cuda 14 M
libcublas-devel x86_64 10.2.2.89-1 cuda 60 M
libcublas10 x86_64 10.2.2.89-1 cuda 58 M
nsight-compute-2019.4.0 x86_64 2019.4.0.12-1 cuda 257 M
nvidia-driver x86_64 3:440.33.01-1.el8 cuda 5.3 M
nvidia-driver-NVML x86_64 3:440.33.01-1.el8 cuda 523 k
nvidia-driver-NvFBCOpenGL x86_64 3:440.33.01-1.el8 cuda 136 k
nvidia-driver-cuda x86_64 3:440.33.01-1.el8 cuda 392 k
nvidia-driver-cuda-libs x86_64 3:440.33.01-1.el8 cuda 34 M
nvidia-driver-devel x86_64 3:440.33.01-1.el8 cuda 12 k
nvidia-driver-libs x86_64 3:440.33.01-1.el8 cuda 80 M
nvidia-kmod-common noarch 3:440.33.01-1.el8 cuda 9.8 k
nvidia-libXNVCtrl x86_64 3:440.33.01-1.el8 cuda 58 k
nvidia-libXNVCtrl-devel x86_64 3:440.33.01-1.el8 cuda 60 k
nvidia-modprobe x86_64 3:440.33.01-1.el8 cuda 77 k
nvidia-persistenced x86_64 3:440.33.01-1.el8 cuda 111 k
nvidia-settings x86_64 3:440.33.01-1.el8 cuda 2.3 M
nvidia-xconfig x86_64 3:440.33.01-1.el8 cuda 319 k
dkms noarch 2.7.1-2.el8 epel 79 k
make x86_64 1:4.2.1-9.el8 rhel-8-for-x86_64-baseos-rpms 498 k
libpkgconf x86_64 1.4.2-1.el8 rhel-8-for-x86_64-baseos-rpms 35 k
libmodman x86_64 2.0.1-17.el8 rhel-8-for-x86_64-baseos-rpms 36 k
pkgconf-m4 noarch 1.4.2-1.el8 rhel-8-for-x86_64-baseos-rpms 17 k
pkgconf x86_64 1.4.2-1.el8 rhel-8-for-x86_64-baseos-rpms 38 k
libproxy x86_64 0.4.15-5.2.el8 rhel-8-for-x86_64-baseos-rpms 74 k
glib-networking x86_64 2.56.1-1.1.el8 rhel-8-for-x86_64-baseos-rpms 155 k
avahi-libs x86_64 0.7-19.el8 rhel-8-for-x86_64-baseos-rpms 63 k
libxcrypt-devel x86_64 4.1.1-4.el8 rhel-8-for-x86_64-baseos-rpms 25 k
libsoup x86_64 2.62.3-1.el8 rhel-8-for-x86_64-baseos-rpms 424 k
fontpackages-filesystem noarch 1.44-22.el8 rhel-8-for-x86_64-baseos-rpms 16 k
libgusb x86_64 0.3.0-1.el8 rhel-8-for-x86_64-baseos-rpms 49 k
tar x86_64 2:1.30-4.el8 rhel-8-for-x86_64-baseos-rpms 838 k
lksctp-tools x86_64 1.0.18-3.el8 rhel-8-for-x86_64-baseos-rpms 100 k
libpciaccess x86_64 0.14-1.el8 rhel-8-for-x86_64-baseos-rpms 32 k
fontconfig x86_64 2.13.1-3.el8 rhel-8-for-x86_64-baseos-rpms 275 k
zlib-devel x86_64 1.2.11-10.el8 rhel-8-for-x86_64-baseos-rpms 56 k
binutils x86_64 2.30-58.el8 rhel-8-for-x86_64-baseos-rpms 5.7 M
elfutils-libelf-devel x86_64 0.176-5.el8 rhel-8-for-x86_64-baseos-rpms 54 k
gdk-pixbuf2 x86_64 2.36.12-5.el8 rhel-8-for-x86_64-baseos-rpms 467 k
gsettings-desktop-schemas x86_64 3.32.0-3.el8 rhel-8-for-x86_64-baseos-rpms 632 k
glibc-devel x86_64 2.28-72.el8 rhel-8-for-x86_64-baseos-rpms 1.0 M
pkgconf-pkg-config x86_64 1.4.2-1.el8 rhel-8-for-x86_64-baseos-rpms 15 k
cups-libs x86_64 1:2.2.6-28.el8 rhel-8-for-x86_64-baseos-rpms 433 k
glibc-headers x86_64 2.28-72.el8 rhel-8-for-x86_64-baseos-rpms 469 k
kernel-headers x86_64 4.18.0-147.0.3.el8_1 rhel-8-for-x86_64-baseos-rpms 2.7 M
libX11-common noarch 1.6.7-1.el8 rhel-8-for-x86_64-appstream-rpms 157 k
adwaita-icon-theme noarch 3.28.0-2.el8 rhel-8-for-x86_64-appstream-rpms 11 M
opencl-filesystem noarch 1.0-6.el8 rhel-8-for-x86_64-appstream-rpms 8.5 k
adwaita-cursor-theme noarch 3.28.0-2.el8 rhel-8-for-x86_64-appstream-rpms 647 k
xorg-x11-proto-devel noarch 2018.4-1.el8 rhel-8-for-x86_64-appstream-rpms 283 k
javapackages-filesystem noarch 5.3.0-1.module+el8+2447+6f56d9a6 rhel-8-for-x86_64-appstream-rpms 30 k
abattis-cantarell-fonts noarch 0.0.25-4.el8 rhel-8-for-x86_64-appstream-rpms 155 k
libXdmcp x86_64 1.1.2-11.el8 rhel-8-for-x86_64-appstream-rpms 40 k
libglvnd-opengl x86_64 1:1.0.1-0.9.git5baa1e5.el8 rhel-8-for-x86_64-appstream-rpms 48 k
xorg-x11-fonts-Type1 noarch 7.5-19.el8 rhel-8-for-x86_64-appstream-rpms 522 k
copy-jdk-configs noarch 3.7-1.el8 rhel-8-for-x86_64-appstream-rpms 27 k
hicolor-icon-theme noarch 0.17-2.el8 rhel-8-for-x86_64-appstream-rpms 48 k
libxcb x86_64 1.13-5.el8 rhel-8-for-x86_64-appstream-rpms 230 k
libwacom-data noarch 0.31-1.el8 rhel-8-for-x86_64-appstream-rpms 76 k
gl-manpages noarch 1.1-15.20161227.el8 rhel-8-for-x86_64-appstream-rpms 1.2 M
lcms2 x86_64 2.9-2.el8 rhel-8-for-x86_64-appstream-rpms 165 k
mesa-libGLU-devel x86_64 9.0.0-15.el8 rhel-8-for-x86_64-appstream-rpms 15 k
libXdamage-devel x86_64 1.1.4-14.el8 rhel-8-for-x86_64-appstream-rpms 15 k
jbigkit-libs x86_64 2.1-14.el8 rhel-8-for-x86_64-appstream-rpms 55 k
libXi-devel x86_64 1.7.9-7.el8 rhel-8-for-x86_64-appstream-rpms 111 k
libXi x86_64 1.7.9-7.el8 rhel-8-for-x86_64-appstream-rpms 49 k
libXext x86_64 1.3.3-9.el8 rhel-8-for-x86_64-appstream-rpms 45 k
ocl-icd x86_64 2.2.12-1.el8 rhel-8-for-x86_64-appstream-rpms 51 k
libXtst x86_64 1.2.3-7.el8 rhel-8-for-x86_64-appstream-rpms 22 k
libXinerama x86_64 1.1.4-1.el8 rhel-8-for-x86_64-appstream-rpms 16 k
libglvnd-egl x86_64 1:1.0.1-0.9.git5baa1e5.el8 rhel-8-for-x86_64-appstream-rpms 50 k
libmpc x86_64 1.0.2-9.el8 rhel-8-for-x86_64-appstream-rpms 59 k
libglvnd-core-devel x86_64 1:1.0.1-0.9.git5baa1e5.el8 rhel-8-for-x86_64-appstream-rpms 24 k
xorg-x11-xkb-utils x86_64 7.7-27.el8 rhel-8-for-x86_64-appstream-rpms 114 k
libvdpau x86_64 1.1.1-7.el8 rhel-8-for-x86_64-appstream-rpms 40 k
at-spi2-core x86_64 2.28.0-1.el8 rhel-8-for-x86_64-appstream-rpms 169 k
ttmkfdir x86_64 3.0.9-54.el8 rhel-8-for-x86_64-appstream-rpms 62 k
graphite2 x86_64 1.3.10-10.el8 rhel-8-for-x86_64-appstream-rpms 122 k
libXfixes-devel x86_64 5.0.3-7.el8 rhel-8-for-x86_64-appstream-rpms 19 k
libXcursor x86_64 1.1.15-3.el8 rhel-8-for-x86_64-appstream-rpms 36 k
libXrandr x86_64 1.5.1-7.el8 rhel-8-for-x86_64-appstream-rpms 33 k
at-spi2-atk x86_64 2.26.2-1.el8 rhel-8-for-x86_64-appstream-rpms 89 k
xorg-x11-drv-libinput x86_64 0.28.0-2.el8 rhel-8-for-x86_64-appstream-rpms 50 k
libwayland-egl x86_64 1.15.0-1.el8 rhel-8-for-x86_64-appstream-rpms 19 k
libX11-devel x86_64 1.6.7-1.el8 rhel-8-for-x86_64-appstream-rpms 977 k
libXfont2 x86_64 2.0.3-2.el8 rhel-8-for-x86_64-appstream-rpms 149 k
jasper-libs x86_64 2.0.14-4.el8 rhel-8-for-x86_64-appstream-rpms 167 k
libSM x86_64 1.2.3-1.el8 rhel-8-for-x86_64-appstream-rpms 48 k
libwayland-server x86_64 1.15.0-1.el8 rhel-8-for-x86_64-appstream-rpms 45 k
libwayland-cursor x86_64 1.15.0-1.el8 rhel-8-for-x86_64-appstream-rpms 26 k
libXft x86_64 2.3.2-10.el8 rhel-8-for-x86_64-appstream-rpms 66 k
libxkbfile x86_64 1.0.9-9.el8 rhel-8-for-x86_64-appstream-rpms 86 k
libXfixes x86_64 5.0.3-7.el8 rhel-8-for-x86_64-appstream-rpms 25 k
libglvnd x86_64 1:1.0.1-0.9.git5baa1e5.el8 rhel-8-for-x86_64-appstream-rpms 96 k
cairo-gobject x86_64 1.15.12-3.el8 rhel-8-for-x86_64-appstream-rpms 33 k
libglvnd-gles x86_64 1:1.0.1-0.9.git5baa1e5.el8 rhel-8-for-x86_64-appstream-rpms 41 k
libXau x86_64 1.0.8-13.el8 rhel-8-for-x86_64-appstream-rpms 36 k
freeglut x86_64 3.0.0-8.el8 rhel-8-for-x86_64-appstream-rpms 191 k
libepoxy x86_64 1.5.2-1.el8 rhel-8-for-x86_64-appstream-rpms 225 k
freeglut-devel x86_64 3.0.0-8.el8 rhel-8-for-x86_64-appstream-rpms 121 k
egl-wayland x86_64 1.1.2-1.el8 rhel-8-for-x86_64-appstream-rpms 33 k
xorg-x11-drv-vesa x86_64 2.4.0-3.el8 rhel-8-for-x86_64-appstream-rpms 31 k
libwacom x86_64 0.31-1.el8 rhel-8-for-x86_64-appstream-rpms 42 k
libXxf86vm x86_64 1.1.4-9.el8 rhel-8-for-x86_64-appstream-rpms 19 k
xorg-x11-drv-fbdev x86_64 0.5.0-2.el8 rhel-8-for-x86_64-appstream-rpms 27 k
libthai x86_64 0.1.27-2.el8 rhel-8-for-x86_64-appstream-rpms 203 k
colord-libs x86_64 1.4.2-1.el8 rhel-8-for-x86_64-appstream-rpms 236 k
rest x86_64 0.8.1-2.el8 rhel-8-for-x86_64-appstream-rpms 71 k
libXdamage x86_64 1.1.4-14.el8 rhel-8-for-x86_64-appstream-rpms 27 k
libXmu-devel x86_64 1.1.2-12.el8 rhel-8-for-x86_64-appstream-rpms 25 k
libSM-devel x86_64 1.2.3-1.el8 rhel-8-for-x86_64-appstream-rpms 18 k
cairo x86_64 1.15.12-3.el8 rhel-8-for-x86_64-appstream-rpms 721 k
harfbuzz x86_64 1.7.5-3.el8 rhel-8-for-x86_64-appstream-rpms 294 k
libXxf86vm-devel x86_64 1.1.4-9.el8 rhel-8-for-x86_64-appstream-rpms 20 k
mesa-libGLU x86_64 9.0.0-15.el8 rhel-8-for-x86_64-appstream-rpms 185 k
libXcomposite x86_64 0.4.4-14.el8 rhel-8-for-x86_64-appstream-rpms 29 k
libfontenc x86_64 1.1.3-8.el8 rhel-8-for-x86_64-appstream-rpms 37 k
libwayland-client x86_64 1.15.0-1.el8 rhel-8-for-x86_64-appstream-rpms 39 k
libX11-xcb x86_64 1.6.7-1.el8 rhel-8-for-x86_64-appstream-rpms 14 k
libxcb-devel x86_64 1.13-5.el8 rhel-8-for-x86_64-appstream-rpms 1.1 M
libX11 x86_64 1.6.7-1.el8 rhel-8-for-x86_64-appstream-rpms 612 k
fribidi x86_64 1.0.4-6.el8 rhel-8-for-x86_64-appstream-rpms 89 k
libXrender x86_64 0.9.10-7.el8 rhel-8-for-x86_64-appstream-rpms 33 k
atk x86_64 2.28.1-1.el8 rhel-8-for-x86_64-appstream-rpms 272 k
libdatrie x86_64 0.2.9-7.el8 rhel-8-for-x86_64-appstream-rpms 33 k
libxshmfence x86_64 1.3-2.el8 rhel-8-for-x86_64-appstream-rpms 13 k
giflib x86_64 5.1.4-3.el8 rhel-8-for-x86_64-appstream-rpms 51 k
libXext-devel x86_64 1.3.3-9.el8 rhel-8-for-x86_64-appstream-rpms 80 k
libevdev x86_64 1.5.9-5.el8 rhel-8-for-x86_64-appstream-rpms 42 k
isl x86_64 0.16.1-6.el8 rhel-8-for-x86_64-appstream-rpms 841 k
libXau-devel x86_64 1.0.8-13.el8 rhel-8-for-x86_64-appstream-rpms 20 k
pixman x86_64 0.36.0-1.el8 rhel-8-for-x86_64-appstream-rpms 257 k
libXmu x86_64 1.1.2-12.el8 rhel-8-for-x86_64-appstream-rpms 74 k
mtdev x86_64 1.1.5-12.el8 rhel-8-for-x86_64-appstream-rpms 24 k
xorg-x11-font-utils x86_64 1:7.5-40.el8 rhel-8-for-x86_64-appstream-rpms 103 k
libglvnd-glx x86_64 1:1.0.1-0.9.git5baa1e5.el8 rhel-8-for-x86_64-appstream-rpms 131 k
libglvnd-devel x86_64 1:1.0.1-0.9.git5baa1e5.el8 rhel-8-for-x86_64-appstream-rpms 16 k
libXt x86_64 1.1.5-12.el8 rhel-8-for-x86_64-appstream-rpms 185 k
tzdata-java noarch 2019c-1.el8 rhel-8-for-x86_64-appstream-rpms 189 k
gcc x86_64 8.3.1-4.5.el8 rhel-8-for-x86_64-appstream-rpms 23 M
mesa-libEGL x86_64 19.1.4-2.el8 rhel-8-for-x86_64-appstream-rpms 131 k
mesa-libGL-devel x86_64 19.1.4-2.el8 rhel-8-for-x86_64-appstream-rpms 177 k
libjpeg-turbo x86_64 1.5.3-10.el8 rhel-8-for-x86_64-appstream-rpms 156 k
mesa-vulkan-drivers x86_64 19.1.4-2.el8 rhel-8-for-x86_64-appstream-rpms 2.6 M
mesa-libglapi x86_64 19.1.4-2.el8 rhel-8-for-x86_64-appstream-rpms 61 k
alsa-lib x86_64 1.1.9-4.el8 rhel-8-for-x86_64-appstream-rpms 429 k
gcc-c++ x86_64 8.3.1-4.5.el8 rhel-8-for-x86_64-appstream-rpms 12 M
libXt-devel x86_64 1.1.5-12.el8 rhel-8-for-x86_64-appstream-rpms 452 k
xorg-x11-server-common x86_64 1.20.3-11.el8 rhel-8-for-x86_64-appstream-rpms 40 k
xorg-x11-server-Xorg x86_64 1.20.3-11.el8 rhel-8-for-x86_64-appstream-rpms 1.5 M
cpp x86_64 8.3.1-4.5.el8 rhel-8-for-x86_64-appstream-rpms 10 M
gtk-update-icon-cache x86_64 3.22.30-4.el8 rhel-8-for-x86_64-appstream-rpms 33 k
pango x86_64 1.42.4-6.el8 rhel-8-for-x86_64-appstream-rpms 298 k
libtiff x86_64 4.0.9-15.el8 rhel-8-for-x86_64-appstream-rpms 188 k
mesa-libgbm x86_64 19.1.4-2.el8 rhel-8-for-x86_64-appstream-rpms 55 k
libdrm x86_64 2.4.98-2.el8 rhel-8-for-x86_64-appstream-rpms 165 k
lua x86_64 5.3.4-11.el8 rhel-8-for-x86_64-appstream-rpms 193 k
libICE-devel x86_64 1.0.9-15.el8 rhel-8-for-x86_64-appstream-rpms 55 k
mesa-khr-devel x86_64 19.1.4-2.el8 rhel-8-for-x86_64-appstream-rpms 33 k
libdrm-devel x86_64 2.4.98-2.el8 rhel-8-for-x86_64-appstream-rpms 156 k
vulkan-loader x86_64 1.1.114.0-3.el8 rhel-8-for-x86_64-appstream-rpms 113 k
java-1.8.0-openjdk x86_64 1:1.8.0.232.b09-2.el8_1 rhel-8-for-x86_64-appstream-rpms 317 k
gdk-pixbuf2-modules x86_64 2.36.12-5.el8 rhel-8-for-x86_64-appstream-rpms 109 k
mesa-libGL x86_64 19.1.4-2.el8 rhel-8-for-x86_64-appstream-rpms 184 k
gtk3 x86_64 3.22.30-4.el8 rhel-8-for-x86_64-appstream-rpms 4.5 M
java-1.8.0-openjdk-headless x86_64 1:1.8.0.232.b09-2.el8_1 rhel-8-for-x86_64-appstream-rpms 33 M
llvm-libs x86_64 8.0.1-1.module+el8.1.0+3866+6be7f4d8 rhel-8-for-x86_64-appstream-rpms 18 M
libstdc++-devel x86_64 8.3.1-4.5.el8 rhel-8-for-x86_64-appstream-rpms 2.0 M
libinput x86_64 1.13.2-1.el8 rhel-8-for-x86_64-appstream-rpms 198 k
libICE x86_64 1.0.9-15.el8 rhel-8-for-x86_64-appstream-rpms 74 k
Installing weak dependencies:
dconf x86_64 0.28.0-3.el8 rhel-8-for-x86_64-appstream-rpms 109 k
gtk2 x86_64 2.24.32-4.el8 rhel-8-for-x86_64-appstream-rpms 3.4 M
Enabling module streams:
javapackages-runtime 201801
llvm-toolset rhel8
nvidia-driver latest-dkms
Transaction Summary
========================================================================================================================================================================================
Install 224 Packages
Total download size: 2.6 G
Installed size: 5.1 G
Downloading Packages:
(1/224): cuda-10-2-10.2.89-1.x86_64.rpm 330 kB/s | 6.1 kB 00:00
(2/224): cuda-10.2.89-1.x86_64.rpm 322 kB/s | 6.1 kB 00:00
(3/224): cuda-compiler-10-2-10.2.89-1.x86_64.rpm 603 kB/s | 6.1 kB 00:00
(4/224): cuda-command-line-tools-10-2-10.2.89-1.x86_64.rpm 567 kB/s | 6.2 kB 00:00
(5/224): cuda-cudart-10-2-10.2.89-1.x86_64.rpm 5.6 MB/s | 151 kB 00:00
(6/224): cuda-cudart-dev-10-2-10.2.89-1.x86_64.rpm 9.4 MB/s | 861 kB 00:00
(7/224): NsightSystems-linux-public-2019.5.2.16-b54ef97.rpm 55 MB/s | 109 MB 00:01
(8/224): cuda-cuobjdump-10-2-10.2.89-1.x86_64.rpm 7.8 MB/s | 106 kB 00:00
(9/224): cuda-cupti-10-2-10.2.89-1.x86_64.rpm 45 MB/s | 15 MB 00:00
(10/224): cuda-curand-10-2-10.2.89-1.x86_64.rpm 45 MB/s | 42 MB 00:00
(11/224): cuda-curand-dev-10-2-10.2.89-1.x86_64.rpm 39 MB/s | 43 MB 00:01
(12/224): cuda-cufft-10-2-10.2.89-1.x86_64.rpm 22 MB/s | 108 MB 00:05
(13/224): cuda-cusolver-dev-10-2-10.2.89-1.x86_64.rpm 36 MB/s | 29 MB 00:00
(14/224): cuda-cufft-dev-10-2-10.2.89-1.x86_64.rpm 27 MB/s | 206 MB 00:07
(15/224): cuda-cusolver-10-2-10.2.89-1.x86_64.rpm 31 MB/s | 129 MB 00:04
(16/224): cuda-cusparse-10-2-10.2.89-1.x86_64.rpm 28 MB/s | 79 MB 00:02
(17/224): cuda-demo-suite-10-2-10.2.89-1.x86_64.rpm 16 MB/s | 4.7 MB 00:00
(18/224): cuda-driver-dev-10-2-10.2.89-1.x86_64.rpm 1.6 MB/s | 20 kB 00:00
(19/224): cuda-drivers-440.33.01-1.x86_64.rpm 621 kB/s | 6.8 kB 00:00
(20/224): cuda-gdb-10-2-10.2.89-1.x86_64.rpm 31 MB/s | 3.5 MB 00:00
(21/224): cuda-libraries-10-2-10.2.89-1.x86_64.rpm 615 kB/s | 6.3 kB 00:00
(22/224): cuda-libraries-dev-10-2-10.2.89-1.x86_64.rpm 627 kB/s | 6.4 kB 00:00
(23/224): cuda-license-10-2-10.2.89-1.x86_64.rpm 2.0 MB/s | 22 kB 00:00
(24/224): cuda-memcheck-10-2-10.2.89-1.x86_64.rpm 421 kB/s | 180 kB 00:00
(25/224): cuda-misc-headers-10-2-10.2.89-1.x86_64.rpm 27 MB/s | 1.7 MB 00:00
(26/224): cuda-cusparse-dev-10-2-10.2.89-1.x86_64.rpm 36 MB/s | 159 MB 00:04
(27/224): cuda-npp-10-2-10.2.89-1.x86_64.rpm 26 MB/s | 86 MB 00:03
(28/224): cuda-documentation-10-2-10.2.89-1.x86_64.rpm 29 MB/s | 132 MB 00:04
(29/224): cuda-nsight-compute-10-2-10.2.89-1.x86_64.rpm 697 kB/s | 7.8 kB 00:00
(30/224): cuda-nsight-systems-10-2-10.2.89-1.x86_64.rpm 691 kB/s | 7.3 kB 00:00
(31/224): cuda-nvcc-10-2-10.2.89-1.x86_64.rpm 41 MB/s | 48 MB 00:01
(32/224): cuda-nvdisasm-10-2-10.2.89-1.x86_64.rpm 41 MB/s | 21 MB 00:00
(33/224): cuda-npp-dev-10-2-10.2.89-1.x86_64.rpm 28 MB/s | 86 MB 00:03
(34/224): cuda-nvgraph-dev-10-2-10.2.89-1.x86_64.rpm 32 MB/s | 57 MB 00:01
(35/224): cuda-nvgraph-10-2-10.2.89-1.x86_64.rpm 35 MB/s | 97 MB 00:02
(36/224): cuda-nvjpeg-dev-10-2-10.2.89-1.x86_64.rpm 37 MB/s | 1.8 MB 00:00
(37/224): cuda-nvml-dev-10-2-10.2.89-1.x86_64.rpm 6.0 MB/s | 71 kB 00:00
(38/224): cuda-nvjpeg-10-2-10.2.89-1.x86_64.rpm 2.4 MB/s | 1.7 MB 00:00
(39/224): cuda-nvprune-10-2-10.2.89-1.x86_64.rpm 3.7 MB/s | 49 kB 00:00
(40/224): cuda-nvprof-10-2-10.2.89-1.x86_64.rpm 35 MB/s | 3.8 MB 00:00
(41/224): cuda-nvrtc-dev-10-2-10.2.89-1.x86_64.rpm 1.0 MB/s | 14 kB 00:00
(42/224): cuda-nvtx-10-2-10.2.89-1.x86_64.rpm 5.6 MB/s | 68 kB 00:00
(43/224): cuda-nvrtc-10-2-10.2.89-1.x86_64.rpm 39 MB/s | 8.9 MB 00:00
(44/224): cuda-runtime-10-2-10.2.89-1.x86_64.rpm 551 kB/s | 6.1 kB 00:00
(45/224): cuda-samples-10-2-10.2.89-1.x86_64.rpm 44 MB/s | 89 MB 00:02
(46/224): cuda-sanitizer-api-10-2-10.2.89-1.x86_64.rpm 38 MB/s | 3.5 MB 00:00
(47/224): cuda-toolkit-10-2-10.2.89-1.x86_64.rpm 536 kB/s | 6.7 kB 00:00
(48/224): cuda-tools-10-2-10.2.89-1.x86_64.rpm 628 kB/s | 6.0 kB 00:00
(49/224): cuda-visual-tools-10-2-10.2.89-1.x86_64.rpm 603 kB/s | 6.8 kB 00:00
(50/224): dnf-plugin-nvidia-1.1-1.el8.noarch.rpm 766 kB/s | 8.5 kB 00:00
(51/224): kmod-nvidia-latest-dkms-440.33.01-1.el8.x86_64.rpm 41 MB/s | 14 MB 00:00
(52/224): cuda-nsight-10-2-10.2.89-1.x86_64.rpm 31 MB/s | 268 MB 00:08
(53/224): libcublas10-10.2.2.89-1.x86_64.rpm 39 MB/s | 58 MB 00:01
(54/224): libcublas-devel-10.2.2.89-1.x86_64.rpm 19 MB/s | 60 MB 00:03
(55/224): cuda-nvvp-10-2-10.2.89-1.x86_64.rpm 19 MB/s | 114 MB 00:06
(56/224): nvidia-driver-440.33.01-1.el8.x86_64.rpm 17 MB/s | 5.3 MB 00:00
(57/224): nvidia-driver-NVML-440.33.01-1.el8.x86_64.rpm 16 MB/s | 523 kB 00:00
(58/224): nvidia-driver-NvFBCOpenGL-440.33.01-1.el8.x86_64.rpm 11 MB/s | 136 kB 00:00
(59/224): nvidia-driver-cuda-440.33.01-1.el8.x86_64.rpm 723 kB/s | 392 kB 00:00
(60/224): nvidia-driver-devel-440.33.01-1.el8.x86_64.rpm 1.1 MB/s | 12 kB 00:00
(61/224): nvidia-driver-cuda-libs-440.33.01-1.el8.x86_64.rpm 54 MB/s | 34 MB 00:00
(62/224): nvidia-kmod-common-440.33.01-1.el8.noarch.rpm 703 kB/s | 9.8 kB 00:00
(63/224): nvidia-libXNVCtrl-440.33.01-1.el8.x86_64.rpm 5.0 MB/s | 58 kB 00:00
(64/224): nvidia-libXNVCtrl-devel-440.33.01-1.el8.x86_64.rpm 5.3 MB/s | 60 kB 00:00
(65/224): nvidia-modprobe-440.33.01-1.el8.x86_64.rpm 6.4 MB/s | 77 kB 00:00
(66/224): nvidia-persistenced-440.33.01-1.el8.x86_64.rpm 9.0 MB/s | 111 kB 00:00
(67/224): nvidia-settings-440.33.01-1.el8.x86_64.rpm 2.0 MB/s | 2.3 MB 00:01
(68/224): nvidia-xconfig-440.33.01-1.el8.x86_64.rpm 15 MB/s | 319 kB 00:00
(69/224): dkms-2.7.1-2.el8.noarch.rpm 788 kB/s | 79 kB 00:00
(70/224): nvidia-driver-libs-440.33.01-1.el8.x86_64.rpm 48 MB/s | 80 MB 00:01
(71/224): make-4.2.1-9.el8.x86_64.rpm 1.3 MB/s | 498 kB 00:00
(72/224): libpkgconf-1.4.2-1.el8.x86_64.rpm 106 kB/s | 35 kB 00:00
(73/224): libmodman-2.0.1-17.el8.x86_64.rpm 71 kB/s | 36 kB 00:00
(74/224): pkgconf-m4-1.4.2-1.el8.noarch.rpm 50 kB/s | 17 kB 00:00
(75/224): pkgconf-1.4.2-1.el8.x86_64.rpm 102 kB/s | 38 kB 00:00
(76/224): libproxy-0.4.15-5.2.el8.x86_64.rpm 219 kB/s | 74 kB 00:00
(77/224): avahi-libs-0.7-19.el8.x86_64.rpm 208 kB/s | 63 kB 00:00
(78/224): glib-networking-2.56.1-1.1.el8.x86_64.rpm 408 kB/s | 155 kB 00:00
(79/224): libxcrypt-devel-4.1.1-4.el8.x86_64.rpm 84 kB/s | 25 kB 00:00
(80/224): libsoup-2.62.3-1.el8.x86_64.rpm 904 kB/s | 424 kB 00:00
(81/224): nsight-compute-2019.4.0-2019.4.0.12-1.x86_64.rpm 47 MB/s | 257 MB 00:05
(82/224): fontpackages-filesystem-1.44-22.el8.noarch.rpm 21 kB/s | 16 kB 00:00
(83/224): libgusb-0.3.0-1.el8.x86_64.rpm 88 kB/s | 49 kB 00:00
(84/224): libpciaccess-0.14-1.el8.x86_64.rpm 111 kB/s | 32 kB 00:00
(85/224): lksctp-tools-1.0.18-3.el8.x86_64.rpm 309 kB/s | 100 kB 00:00
(86/224): tar-1.30-4.el8.x86_64.rpm 2.1 MB/s | 838 kB 00:00
(87/224): fontconfig-2.13.1-3.el8.x86_64.rpm 849 kB/s | 275 kB 00:00
(88/224): zlib-devel-1.2.11-10.el8.x86_64.rpm 173 kB/s | 56 kB 00:00
(89/224): binutils-2.30-58.el8.x86_64.rpm 15 MB/s | 5.7 MB 00:00
(90/224): elfutils-libelf-devel-0.176-5.el8.x86_64.rpm 178 kB/s | 54 kB 00:00
(91/224): gdk-pixbuf2-2.36.12-5.el8.x86_64.rpm 1.4 MB/s | 467 kB 00:00
(92/224): gsettings-desktop-schemas-3.32.0-3.el8.x86_64.rpm 1.9 MB/s | 632 kB 00:00
(93/224): glibc-devel-2.28-72.el8.x86_64.rpm 2.9 MB/s | 1.0 MB 00:00
(94/224): pkgconf-pkg-config-1.4.2-1.el8.x86_64.rpm 38 kB/s | 15 kB 00:00
(95/224): cups-libs-2.2.6-28.el8.x86_64.rpm 1.3 MB/s | 433 kB 00:00
(96/224): glibc-headers-2.28-72.el8.x86_64.rpm 1.4 MB/s | 469 kB 00:00
(97/224): kernel-headers-4.18.0-147.0.3.el8_1.x86_64.rpm 6.9 MB/s | 2.7 MB 00:00
(98/224): libX11-common-1.6.7-1.el8.noarch.rpm 298 kB/s | 157 kB 00:00
(99/224): opencl-filesystem-1.0-6.el8.noarch.rpm 26 kB/s | 8.5 kB 00:00
(100/224): adwaita-icon-theme-3.28.0-2.el8.noarch.rpm 20 MB/s | 11 MB 00:00
(101/224): adwaita-cursor-theme-3.28.0-2.el8.noarch.rpm 2.1 MB/s | 647 kB 00:00
(102/224): xorg-x11-proto-devel-2018.4-1.el8.noarch.rpm 716 kB/s | 283 kB 00:00
(103/224): javapackages-filesystem-5.3.0-1.module+el8+2447+6f56d9a6.noarch.rpm 90 kB/s | 30 kB 00:00
(104/224): abattis-cantarell-fonts-0.0.25-4.el8.noarch.rpm 524 kB/s | 155 kB 00:00
(105/224): libXdmcp-1.1.2-11.el8.x86_64.rpm 125 kB/s | 40 kB 00:00
(106/224): xorg-x11-fonts-Type1-7.5-19.el8.noarch.rpm 1.5 MB/s | 522 kB 00:00
(107/224): libglvnd-opengl-1.0.1-0.9.git5baa1e5.el8.x86_64.rpm 88 kB/s | 48 kB 00:00
(108/224): copy-jdk-configs-3.7-1.el8.noarch.rpm 93 kB/s | 27 kB 00:00
(109/224): hicolor-icon-theme-0.17-2.el8.noarch.rpm 125 kB/s | 48 kB 00:00
(110/224): libwacom-data-0.31-1.el8.noarch.rpm 222 kB/s | 76 kB 00:00
(111/224): libxcb-1.13-5.el8.x86_64.rpm 563 kB/s | 230 kB 00:00
(112/224): lcms2-2.9-2.el8.x86_64.rpm 463 kB/s | 165 kB 00:00
(113/224): mesa-libGLU-devel-9.0.0-15.el8.x86_64.rpm 45 kB/s | 15 kB 00:00
(114/224): gl-manpages-1.1-15.20161227.el8.noarch.rpm 2.2 MB/s | 1.2 MB 00:00
(115/224): libXi-devel-1.7.9-7.el8.x86_64.rpm 383 kB/s | 111 kB 00:00
(116/224): libXdamage-devel-1.1.4-14.el8.x86_64.rpm 46 kB/s | 15 kB 00:00
(117/224): jbigkit-libs-2.1-14.el8.x86_64.rpm 147 kB/s | 55 kB 00:00
(118/224): libXext-1.3.3-9.el8.x86_64.rpm 153 kB/s | 45 kB 00:00
(119/224): libXi-1.7.9-7.el8.x86_64.rpm 148 kB/s | 49 kB 00:00
(120/224): ocl-icd-2.2.12-1.el8.x86_64.rpm 134 kB/s | 51 kB 00:00
(121/224): libXtst-1.2.3-7.el8.x86_64.rpm 75 kB/s | 22 kB 00:00
(122/224): libXinerama-1.1.4-1.el8.x86_64.rpm 46 kB/s | 16 kB 00:00
(123/224): libglvnd-egl-1.0.1-0.9.git5baa1e5.el8.x86_64.rpm 139 kB/s | 50 kB 00:00
(124/224): libglvnd-core-devel-1.0.1-0.9.git5baa1e5.el8.x86_64.rpm 88 kB/s | 24 kB 00:00
(125/224): libmpc-1.0.2-9.el8.x86_64.rpm 157 kB/s | 59 kB 00:00
(126/224): xorg-x11-xkb-utils-7.7-27.el8.x86_64.rpm 371 kB/s | 114 kB 00:00
(127/224): libvdpau-1.1.1-7.el8.x86_64.rpm 131 kB/s | 40 kB 00:00
(128/224): at-spi2-core-2.28.0-1.el8.x86_64.rpm 396 kB/s | 169 kB 00:00
(129/224): ttmkfdir-3.0.9-54.el8.x86_64.rpm 194 kB/s | 62 kB 00:00
(130/224): graphite2-1.3.10-10.el8.x86_64.rpm 392 kB/s | 122 kB 00:00
(131/224): libXfixes-devel-5.0.3-7.el8.x86_64.rpm 65 kB/s | 19 kB 00:00
(132/224): libXrandr-1.5.1-7.el8.x86_64.rpm 110 kB/s | 33 kB 00:00
(133/224): libXcursor-1.1.15-3.el8.x86_64.rpm 71 kB/s | 36 kB 00:00
(134/224): at-spi2-atk-2.26.2-1.el8.x86_64.rpm 221 kB/s | 89 kB 00:00
(135/224): xorg-x11-drv-libinput-0.28.0-2.el8.x86_64.rpm 161 kB/s | 50 kB 00:00
(136/224): libwayland-egl-1.15.0-1.el8.x86_64.rpm 54 kB/s | 19 kB 00:00
(137/224): libX11-devel-1.6.7-1.el8.x86_64.rpm 2.7 MB/s | 977 kB 00:00
(138/224): libXfont2-2.0.3-2.el8.x86_64.rpm 487 kB/s | 149 kB 00:00
(139/224): jasper-libs-2.0.14-4.el8.x86_64.rpm 519 kB/s | 167 kB 00:00
(140/224): libSM-1.2.3-1.el8.x86_64.rpm 152 kB/s | 48 kB 00:00
(141/224): libwayland-server-1.15.0-1.el8.x86_64.rpm 152 kB/s | 45 kB 00:00
(142/224): libwayland-cursor-1.15.0-1.el8.x86_64.rpm 81 kB/s | 26 kB 00:00
(143/224): libxkbfile-1.0.9-9.el8.x86_64.rpm 263 kB/s | 86 kB 00:00
(144/224): libXft-2.3.2-10.el8.x86_64.rpm 189 kB/s | 66 kB 00:00
(145/224): libXfixes-5.0.3-7.el8.x86_64.rpm 82 kB/s | 25 kB 00:00
(146/224): cairo-gobject-1.15.12-3.el8.x86_64.rpm 113 kB/s | 33 kB 00:00
(147/224): libglvnd-1.0.1-0.9.git5baa1e5.el8.x86_64.rpm 302 kB/s | 96 kB 00:00
(148/224): dconf-0.28.0-3.el8.x86_64.rpm 231 kB/s | 109 kB 00:00
(149/224): libXau-1.0.8-13.el8.x86_64.rpm 111 kB/s | 36 kB 00:00
(150/224): libglvnd-gles-1.0.1-0.9.git5baa1e5.el8.x86_64.rpm 88 kB/s | 41 kB 00:00
(151/224): freeglut-3.0.0-8.el8.x86_64.rpm 507 kB/s | 191 kB 00:00
(152/224): libepoxy-1.5.2-1.el8.x86_64.rpm 498 kB/s | 225 kB 00:00
(153/224): freeglut-devel-3.0.0-8.el8.x86_64.rpm 327 kB/s | 121 kB 00:00
(154/224): egl-wayland-1.1.2-1.el8.x86_64.rpm 87 kB/s | 33 kB 00:00
(155/224): xorg-x11-drv-vesa-2.4.0-3.el8.x86_64.rpm 103 kB/s | 31 kB 00:00
(156/224): libwacom-0.31-1.el8.x86_64.rpm 127 kB/s | 42 kB 00:00
(157/224): libXxf86vm-1.1.4-9.el8.x86_64.rpm 56 kB/s | 19 kB 00:00
(158/224): xorg-x11-drv-fbdev-0.5.0-2.el8.x86_64.rpm 56 kB/s | 27 kB 00:00
(159/224): libthai-0.1.27-2.el8.x86_64.rpm 459 kB/s | 203 kB 00:00
(160/224): colord-libs-1.4.2-1.el8.x86_64.rpm 741 kB/s | 236 kB 00:00
(161/224): rest-0.8.1-2.el8.x86_64.rpm 207 kB/s | 71 kB 00:00
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(165/224): cairo-1.15.12-3.el8.x86_64.rpm 2.1 MB/s | 721 kB 00:00
(166/224): harfbuzz-1.7.5-3.el8.x86_64.rpm 742 kB/s | 294 kB 00:00
(167/224): libXxf86vm-devel-1.1.4-9.el8.x86_64.rpm 53 kB/s | 20 kB 00:00
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(176/224): libXrender-0.9.10-7.el8.x86_64.rpm 94 kB/s | 33 kB 00:00
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(179/224): libxshmfence-1.3-2.el8.x86_64.rpm 43 kB/s | 13 kB 00:00
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(185/224): libXau-devel-1.0.8-13.el8.x86_64.rpm 54 kB/s | 20 kB 00:00
(186/224): libXmu-1.1.2-12.el8.x86_64.rpm 197 kB/s | 74 kB 00:00
(187/224): pixman-0.36.0-1.el8.x86_64.rpm 556 kB/s | 257 kB 00:00
(188/224): mtdev-1.1.5-12.el8.x86_64.rpm 72 kB/s | 24 kB 00:00
(189/224): libglvnd-glx-1.0.1-0.9.git5baa1e5.el8.x86_64.rpm 391 kB/s | 131 kB 00:00
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(191/224): libglvnd-devel-1.0.1-0.9.git5baa1e5.el8.x86_64.rpm 38 kB/s | 16 kB 00:00
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(194/224): mesa-libEGL-19.1.4-2.el8.x86_64.rpm 449 kB/s | 131 kB 00:00
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(197/224): mesa-vulkan-drivers-19.1.4-2.el8.x86_64.rpm 7.1 MB/s | 2.6 MB 00:00
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(203/224): gcc-c++-8.3.1-4.5.el8.x86_64.rpm 15 MB/s | 12 MB 00:00
(204/224): xorg-x11-server-Xorg-1.20.3-11.el8.x86_64.rpm 3.3 MB/s | 1.5 MB 00:00
(205/224): cpp-8.3.1-4.5.el8.x86_64.rpm 20 MB/s | 10 MB 00:00
(206/224): pango-1.42.4-6.el8.x86_64.rpm 937 kB/s | 298 kB 00:00
(207/224): gtk-update-icon-cache-3.22.30-4.el8.x86_64.rpm 95 kB/s | 33 kB 00:00
(208/224): libtiff-4.0.9-15.el8.x86_64.rpm 594 kB/s | 188 kB 00:00
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(210/224): libdrm-2.4.98-2.el8.x86_64.rpm 530 kB/s | 165 kB 00:00
(211/224): lua-5.3.4-11.el8.x86_64.rpm 674 kB/s | 193 kB 00:00
(212/224): libICE-devel-1.0.9-15.el8.x86_64.rpm 193 kB/s | 55 kB 00:00
(213/224): mesa-khr-devel-19.1.4-2.el8.x86_64.rpm 107 kB/s | 33 kB 00:00
(214/224): libdrm-devel-2.4.98-2.el8.x86_64.rpm 479 kB/s | 156 kB 00:00
(215/224): vulkan-loader-1.1.114.0-3.el8.x86_64.rpm 389 kB/s | 113 kB 00:00
(216/224): java-1.8.0-openjdk-1.8.0.232.b09-2.el8_1.x86_64.rpm 963 kB/s | 317 kB 00:00
(217/224): gdk-pixbuf2-modules-2.36.12-5.el8.x86_64.rpm 390 kB/s | 109 kB 00:00
(218/224): mesa-libGL-19.1.4-2.el8.x86_64.rpm 552 kB/s | 184 kB 00:00
(219/224): llvm-libs-8.0.1-1.module+el8.1.0+3866+6be7f4d8.x86_64.rpm 23 MB/s | 18 MB 00:00
(220/224): gtk3-3.22.30-4.el8.x86_64.rpm 4.4 MB/s | 4.5 MB 00:01
(221/224): java-1.8.0-openjdk-headless-1.8.0.232.b09-2.el8_1.x86_64.rpm 28 MB/s | 33 MB 00:01
(222/224): libinput-1.13.2-1.el8.x86_64.rpm 639 kB/s | 198 kB 00:00
(223/224): libstdc++-devel-8.3.1-4.5.el8.x86_64.rpm 4.4 MB/s | 2.0 MB 00:00
(224/224): libICE-1.0.9-15.el8.x86_64.rpm 138 kB/s | 74 kB 00:00
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Total 55 MB/s | 2.6 GB 00:47
warning: /var/cache/dnf/cuda-3a207caebcd365bb/packages/NsightSystems-linux-public-2019.5.2.16-b54ef97.rpm: Header V4 RSA/SHA512 Signature, key ID 7fa2af80: NOKEY
cuda 88 kB/s | 1.6 kB 00:00
Importing GPG key 0x7FA2AF80:
Userid : "cudatools <cudatools@nvidia.com>"
Fingerprint: AE09 FE4B BD22 3A84 B2CC FCE3 F60F 4B3D 7FA2 AF80
From : http://developer.download.nvidia.com/compute/cuda/repos/rhel8/x86_64/7fa2af80.pub
Key imported successfully
warning: /var/cache/dnf/epel-fafd94c310c51e1e/packages/dkms-2.7.1-2.el8.noarch.rpm: Header V3 RSA/SHA256 Signature, key ID 2f86d6a1: NOKEY
Extra Packages for Enterprise Linux 8 - x86_64 1.6 MB/s | 1.6 kB 00:00
Importing GPG key 0x2F86D6A1:
Userid : "Fedora EPEL (8) <epel@fedoraproject.org>"
Fingerprint: 94E2 79EB 8D8F 25B2 1810 ADF1 21EA 45AB 2F86 D6A1
From : /etc/pki/rpm-gpg/RPM-GPG-KEY-EPEL-8
Key imported successfully
Running transaction check
Transaction check succeeded.
Running transaction test
Transaction test succeeded.
Running transaction
Running scriptlet: copy-jdk-configs-3.7-1.el8.noarch 1/1
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Running scriptlet: cuda-drivers-440.33.01-1.x86_64 1/1
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*** LICENSE AGREEMENT ***
By using this software you agree to fully comply with the terms and
conditions of the EULA (End User License Agreement). The EULA is located
at /usr/local/cuda-10.2/doc/EULA.txt. The EULA can also be found at
http://docs.nvidia.com/cuda/eula/index.html. If you do not agree to the
terms and conditions of the EULA, do not use the software.
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Error in POSTTRANS scriptlet in rpm package nsight-compute-2019.4.0
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Verifying : ttmkfdir-3.0.9-54.el8.x86_64 129/224
Verifying : graphite2-1.3.10-10.el8.x86_64 130/224
Verifying : libXfixes-devel-5.0.3-7.el8.x86_64 131/224
Verifying : libXcursor-1.1.15-3.el8.x86_64 132/224
Verifying : libXrandr-1.5.1-7.el8.x86_64 133/224
Verifying : at-spi2-atk-2.26.2-1.el8.x86_64 134/224
Verifying : xorg-x11-drv-libinput-0.28.0-2.el8.x86_64 135/224
Verifying : libwayland-egl-1.15.0-1.el8.x86_64 136/224
Verifying : libX11-devel-1.6.7-1.el8.x86_64 137/224
Verifying : libXfont2-2.0.3-2.el8.x86_64 138/224
Verifying : jasper-libs-2.0.14-4.el8.x86_64 139/224
Verifying : libSM-1.2.3-1.el8.x86_64 140/224
Verifying : libwayland-server-1.15.0-1.el8.x86_64 141/224
Verifying : libwayland-cursor-1.15.0-1.el8.x86_64 142/224
Verifying : libXft-2.3.2-10.el8.x86_64 143/224
Verifying : libxkbfile-1.0.9-9.el8.x86_64 144/224
Verifying : libXfixes-5.0.3-7.el8.x86_64 145/224
Verifying : libglvnd-1:1.0.1-0.9.git5baa1e5.el8.x86_64 146/224
Verifying : cairo-gobject-1.15.12-3.el8.x86_64 147/224
Verifying : dconf-0.28.0-3.el8.x86_64 148/224
Verifying : libglvnd-gles-1:1.0.1-0.9.git5baa1e5.el8.x86_64 149/224
Verifying : libXau-1.0.8-13.el8.x86_64 150/224
Verifying : freeglut-3.0.0-8.el8.x86_64 151/224
Verifying : libepoxy-1.5.2-1.el8.x86_64 152/224
Verifying : freeglut-devel-3.0.0-8.el8.x86_64 153/224
Verifying : egl-wayland-1.1.2-1.el8.x86_64 154/224
Verifying : xorg-x11-drv-vesa-2.4.0-3.el8.x86_64 155/224
Verifying : libwacom-0.31-1.el8.x86_64 156/224
Verifying : libXxf86vm-1.1.4-9.el8.x86_64 157/224
Verifying : xorg-x11-drv-fbdev-0.5.0-2.el8.x86_64 158/224
Verifying : libthai-0.1.27-2.el8.x86_64 159/224
Verifying : colord-libs-1.4.2-1.el8.x86_64 160/224
Verifying : rest-0.8.1-2.el8.x86_64 161/224
Verifying : libXdamage-1.1.4-14.el8.x86_64 162/224
Verifying : libXmu-devel-1.1.2-12.el8.x86_64 163/224
Verifying : libSM-devel-1.2.3-1.el8.x86_64 164/224
Verifying : cairo-1.15.12-3.el8.x86_64 165/224
Verifying : harfbuzz-1.7.5-3.el8.x86_64 166/224
Verifying : libXxf86vm-devel-1.1.4-9.el8.x86_64 167/224
Verifying : mesa-libGLU-9.0.0-15.el8.x86_64 168/224
Verifying : libXcomposite-0.4.4-14.el8.x86_64 169/224
Verifying : libfontenc-1.1.3-8.el8.x86_64 170/224
Verifying : libwayland-client-1.15.0-1.el8.x86_64 171/224
Verifying : libX11-xcb-1.6.7-1.el8.x86_64 172/224
Verifying : libxcb-devel-1.13-5.el8.x86_64 173/224
Verifying : libX11-1.6.7-1.el8.x86_64 174/224
Verifying : fribidi-1.0.4-6.el8.x86_64 175/224
Verifying : libXrender-0.9.10-7.el8.x86_64 176/224
Verifying : atk-2.28.1-1.el8.x86_64 177/224
Verifying : libdatrie-0.2.9-7.el8.x86_64 178/224
Verifying : gtk2-2.24.32-4.el8.x86_64 179/224
Verifying : libxshmfence-1.3-2.el8.x86_64 180/224
Verifying : giflib-5.1.4-3.el8.x86_64 181/224
Verifying : libXext-devel-1.3.3-9.el8.x86_64 182/224
Verifying : libevdev-1.5.9-5.el8.x86_64 183/224
Verifying : isl-0.16.1-6.el8.x86_64 184/224
Verifying : libXau-devel-1.0.8-13.el8.x86_64 185/224
Verifying : pixman-0.36.0-1.el8.x86_64 186/224
Verifying : libXmu-1.1.2-12.el8.x86_64 187/224
Verifying : mtdev-1.1.5-12.el8.x86_64 188/224
Verifying : xorg-x11-font-utils-1:7.5-40.el8.x86_64 189/224
Verifying : libglvnd-glx-1:1.0.1-0.9.git5baa1e5.el8.x86_64 190/224
Verifying : libglvnd-devel-1:1.0.1-0.9.git5baa1e5.el8.x86_64 191/224
Verifying : libXt-1.1.5-12.el8.x86_64 192/224
Verifying : tzdata-java-2019c-1.el8.noarch 193/224
Verifying : gcc-8.3.1-4.5.el8.x86_64 194/224
Verifying : mesa-libEGL-19.1.4-2.el8.x86_64 195/224
Verifying : mesa-libGL-devel-19.1.4-2.el8.x86_64 196/224
Verifying : libjpeg-turbo-1.5.3-10.el8.x86_64 197/224
Verifying : mesa-vulkan-drivers-19.1.4-2.el8.x86_64 198/224
Verifying : mesa-libglapi-19.1.4-2.el8.x86_64 199/224
Verifying : alsa-lib-1.1.9-4.el8.x86_64 200/224
Verifying : gcc-c++-8.3.1-4.5.el8.x86_64 201/224
Verifying : libXt-devel-1.1.5-12.el8.x86_64 202/224
Verifying : xorg-x11-server-common-1.20.3-11.el8.x86_64 203/224
Verifying : xorg-x11-server-Xorg-1.20.3-11.el8.x86_64 204/224
Verifying : cpp-8.3.1-4.5.el8.x86_64 205/224
Verifying : gtk-update-icon-cache-3.22.30-4.el8.x86_64 206/224
Verifying : pango-1.42.4-6.el8.x86_64 207/224
Verifying : libtiff-4.0.9-15.el8.x86_64 208/224
Verifying : mesa-libgbm-19.1.4-2.el8.x86_64 209/224
Verifying : libdrm-2.4.98-2.el8.x86_64 210/224
Verifying : lua-5.3.4-11.el8.x86_64 211/224
Verifying : libICE-devel-1.0.9-15.el8.x86_64 212/224
Verifying : mesa-khr-devel-19.1.4-2.el8.x86_64 213/224
Verifying : libdrm-devel-2.4.98-2.el8.x86_64 214/224
Verifying : vulkan-loader-1.1.114.0-3.el8.x86_64 215/224
Verifying : java-1.8.0-openjdk-1:1.8.0.232.b09-2.el8_1.x86_64 216/224
Verifying : gdk-pixbuf2-modules-2.36.12-5.el8.x86_64 217/224
Verifying : mesa-libGL-19.1.4-2.el8.x86_64 218/224
Verifying : gtk3-3.22.30-4.el8.x86_64 219/224
Verifying : java-1.8.0-openjdk-headless-1:1.8.0.232.b09-2.el8_1.x86_64 220/224
Verifying : llvm-libs-8.0.1-1.module+el8.1.0+3866+6be7f4d8.x86_64 221/224
Verifying : libstdc++-devel-8.3.1-4.5.el8.x86_64 222/224
Verifying : libinput-1.13.2-1.el8.x86_64 223/224
Verifying : libICE-1.0.9-15.el8.x86_64 224/224
Installed products updated.
Installed:
cuda-10.2.89-1.x86_64 dconf-0.28.0-3.el8.x86_64 gtk2-2.24.32-4.el8.x86_64
nsight-systems-2019.5.2-2019.5.2.16_b54ef97-0.x86_64 cuda-10-2-10.2.89-1.x86_64 cuda-command-line-tools-10-2-10.2.89-1.x86_64
cuda-compiler-10-2-10.2.89-1.x86_64 cuda-cudart-10-2-10.2.89-1.x86_64 cuda-cudart-dev-10-2-10.2.89-1.x86_64
cuda-cufft-10-2-10.2.89-1.x86_64 cuda-cufft-dev-10-2-10.2.89-1.x86_64 cuda-cuobjdump-10-2-10.2.89-1.x86_64
cuda-cupti-10-2-10.2.89-1.x86_64 cuda-curand-10-2-10.2.89-1.x86_64 cuda-curand-dev-10-2-10.2.89-1.x86_64
cuda-cusolver-10-2-10.2.89-1.x86_64 cuda-cusolver-dev-10-2-10.2.89-1.x86_64 cuda-cusparse-10-2-10.2.89-1.x86_64
cuda-cusparse-dev-10-2-10.2.89-1.x86_64 cuda-demo-suite-10-2-10.2.89-1.x86_64 cuda-documentation-10-2-10.2.89-1.x86_64
cuda-driver-dev-10-2-10.2.89-1.x86_64 cuda-drivers-440.33.01-1.x86_64 cuda-gdb-10-2-10.2.89-1.x86_64
cuda-libraries-10-2-10.2.89-1.x86_64 cuda-libraries-dev-10-2-10.2.89-1.x86_64 cuda-license-10-2-10.2.89-1.x86_64
cuda-memcheck-10-2-10.2.89-1.x86_64 cuda-misc-headers-10-2-10.2.89-1.x86_64 cuda-npp-10-2-10.2.89-1.x86_64
cuda-npp-dev-10-2-10.2.89-1.x86_64 cuda-nsight-10-2-10.2.89-1.x86_64 cuda-nsight-compute-10-2-10.2.89-1.x86_64
cuda-nsight-systems-10-2-10.2.89-1.x86_64 cuda-nvcc-10-2-10.2.89-1.x86_64 cuda-nvdisasm-10-2-10.2.89-1.x86_64
cuda-nvgraph-10-2-10.2.89-1.x86_64 cuda-nvgraph-dev-10-2-10.2.89-1.x86_64 cuda-nvjpeg-10-2-10.2.89-1.x86_64
cuda-nvjpeg-dev-10-2-10.2.89-1.x86_64 cuda-nvml-dev-10-2-10.2.89-1.x86_64 cuda-nvprof-10-2-10.2.89-1.x86_64
cuda-nvprune-10-2-10.2.89-1.x86_64 cuda-nvrtc-10-2-10.2.89-1.x86_64 cuda-nvrtc-dev-10-2-10.2.89-1.x86_64
cuda-nvtx-10-2-10.2.89-1.x86_64 cuda-nvvp-10-2-10.2.89-1.x86_64 cuda-runtime-10-2-10.2.89-1.x86_64
cuda-samples-10-2-10.2.89-1.x86_64 cuda-sanitizer-api-10-2-10.2.89-1.x86_64 cuda-toolkit-10-2-10.2.89-1.x86_64
cuda-tools-10-2-10.2.89-1.x86_64 cuda-visual-tools-10-2-10.2.89-1.x86_64 dnf-plugin-nvidia-1.1-1.el8.noarch
kmod-nvidia-latest-dkms-3:440.33.01-1.el8.x86_64 libcublas-devel-10.2.2.89-1.x86_64 libcublas10-10.2.2.89-1.x86_64
nsight-compute-2019.4.0-2019.4.0.12-1.x86_64 nvidia-driver-3:440.33.01-1.el8.x86_64 nvidia-driver-NVML-3:440.33.01-1.el8.x86_64
nvidia-driver-NvFBCOpenGL-3:440.33.01-1.el8.x86_64 nvidia-driver-cuda-3:440.33.01-1.el8.x86_64 nvidia-driver-cuda-libs-3:440.33.01-1.el8.x86_64
nvidia-driver-devel-3:440.33.01-1.el8.x86_64 nvidia-driver-libs-3:440.33.01-1.el8.x86_64 nvidia-kmod-common-3:440.33.01-1.el8.noarch
nvidia-libXNVCtrl-3:440.33.01-1.el8.x86_64 nvidia-libXNVCtrl-devel-3:440.33.01-1.el8.x86_64 nvidia-modprobe-3:440.33.01-1.el8.x86_64
nvidia-persistenced-3:440.33.01-1.el8.x86_64 nvidia-settings-3:440.33.01-1.el8.x86_64 nvidia-xconfig-3:440.33.01-1.el8.x86_64
dkms-2.7.1-2.el8.noarch make-1:4.2.1-9.el8.x86_64 libpkgconf-1.4.2-1.el8.x86_64
libmodman-2.0.1-17.el8.x86_64 pkgconf-m4-1.4.2-1.el8.noarch pkgconf-1.4.2-1.el8.x86_64
libproxy-0.4.15-5.2.el8.x86_64 glib-networking-2.56.1-1.1.el8.x86_64 avahi-libs-0.7-19.el8.x86_64
libxcrypt-devel-4.1.1-4.el8.x86_64 libsoup-2.62.3-1.el8.x86_64 fontpackages-filesystem-1.44-22.el8.noarch
libgusb-0.3.0-1.el8.x86_64 tar-2:1.30-4.el8.x86_64 lksctp-tools-1.0.18-3.el8.x86_64
libpciaccess-0.14-1.el8.x86_64 fontconfig-2.13.1-3.el8.x86_64 zlib-devel-1.2.11-10.el8.x86_64
binutils-2.30-58.el8.x86_64 elfutils-libelf-devel-0.176-5.el8.x86_64 gdk-pixbuf2-2.36.12-5.el8.x86_64
gsettings-desktop-schemas-3.32.0-3.el8.x86_64 glibc-devel-2.28-72.el8.x86_64 pkgconf-pkg-config-1.4.2-1.el8.x86_64
cups-libs-1:2.2.6-28.el8.x86_64 glibc-headers-2.28-72.el8.x86_64 kernel-headers-4.18.0-147.0.3.el8_1.x86_64
libX11-common-1.6.7-1.el8.noarch adwaita-icon-theme-3.28.0-2.el8.noarch opencl-filesystem-1.0-6.el8.noarch
adwaita-cursor-theme-3.28.0-2.el8.noarch xorg-x11-proto-devel-2018.4-1.el8.noarch javapackages-filesystem-5.3.0-1.module+el8+2447+6f56d9a6.noarch
abattis-cantarell-fonts-0.0.25-4.el8.noarch libXdmcp-1.1.2-11.el8.x86_64 libglvnd-opengl-1:1.0.1-0.9.git5baa1e5.el8.x86_64
xorg-x11-fonts-Type1-7.5-19.el8.noarch copy-jdk-configs-3.7-1.el8.noarch hicolor-icon-theme-0.17-2.el8.noarch
libxcb-1.13-5.el8.x86_64 libwacom-data-0.31-1.el8.noarch gl-manpages-1.1-15.20161227.el8.noarch
lcms2-2.9-2.el8.x86_64 mesa-libGLU-devel-9.0.0-15.el8.x86_64 libXdamage-devel-1.1.4-14.el8.x86_64
jbigkit-libs-2.1-14.el8.x86_64 libXi-devel-1.7.9-7.el8.x86_64 libXi-1.7.9-7.el8.x86_64
libXext-1.3.3-9.el8.x86_64 ocl-icd-2.2.12-1.el8.x86_64 libXtst-1.2.3-7.el8.x86_64
libXinerama-1.1.4-1.el8.x86_64 libglvnd-egl-1:1.0.1-0.9.git5baa1e5.el8.x86_64 libmpc-1.0.2-9.el8.x86_64
libglvnd-core-devel-1:1.0.1-0.9.git5baa1e5.el8.x86_64 xorg-x11-xkb-utils-7.7-27.el8.x86_64 libvdpau-1.1.1-7.el8.x86_64
at-spi2-core-2.28.0-1.el8.x86_64 ttmkfdir-3.0.9-54.el8.x86_64 graphite2-1.3.10-10.el8.x86_64
libXfixes-devel-5.0.3-7.el8.x86_64 libXcursor-1.1.15-3.el8.x86_64 libXrandr-1.5.1-7.el8.x86_64
at-spi2-atk-2.26.2-1.el8.x86_64 xorg-x11-drv-libinput-0.28.0-2.el8.x86_64 libwayland-egl-1.15.0-1.el8.x86_64
libX11-devel-1.6.7-1.el8.x86_64 libXfont2-2.0.3-2.el8.x86_64 jasper-libs-2.0.14-4.el8.x86_64
libSM-1.2.3-1.el8.x86_64 libwayland-server-1.15.0-1.el8.x86_64 libwayland-cursor-1.15.0-1.el8.x86_64
libXft-2.3.2-10.el8.x86_64 libxkbfile-1.0.9-9.el8.x86_64 libXfixes-5.0.3-7.el8.x86_64
libglvnd-1:1.0.1-0.9.git5baa1e5.el8.x86_64 cairo-gobject-1.15.12-3.el8.x86_64 libglvnd-gles-1:1.0.1-0.9.git5baa1e5.el8.x86_64
libXau-1.0.8-13.el8.x86_64 freeglut-3.0.0-8.el8.x86_64 libepoxy-1.5.2-1.el8.x86_64
freeglut-devel-3.0.0-8.el8.x86_64 egl-wayland-1.1.2-1.el8.x86_64 xorg-x11-drv-vesa-2.4.0-3.el8.x86_64
libwacom-0.31-1.el8.x86_64 libXxf86vm-1.1.4-9.el8.x86_64 xorg-x11-drv-fbdev-0.5.0-2.el8.x86_64
libthai-0.1.27-2.el8.x86_64 colord-libs-1.4.2-1.el8.x86_64 rest-0.8.1-2.el8.x86_64
libXdamage-1.1.4-14.el8.x86_64 libXmu-devel-1.1.2-12.el8.x86_64 libSM-devel-1.2.3-1.el8.x86_64
cairo-1.15.12-3.el8.x86_64 harfbuzz-1.7.5-3.el8.x86_64 libXxf86vm-devel-1.1.4-9.el8.x86_64
mesa-libGLU-9.0.0-15.el8.x86_64 libXcomposite-0.4.4-14.el8.x86_64 libfontenc-1.1.3-8.el8.x86_64
libwayland-client-1.15.0-1.el8.x86_64 libX11-xcb-1.6.7-1.el8.x86_64 libxcb-devel-1.13-5.el8.x86_64
libX11-1.6.7-1.el8.x86_64 fribidi-1.0.4-6.el8.x86_64 libXrender-0.9.10-7.el8.x86_64
atk-2.28.1-1.el8.x86_64 libdatrie-0.2.9-7.el8.x86_64 libxshmfence-1.3-2.el8.x86_64
giflib-5.1.4-3.el8.x86_64 libXext-devel-1.3.3-9.el8.x86_64 libevdev-1.5.9-5.el8.x86_64
isl-0.16.1-6.el8.x86_64 libXau-devel-1.0.8-13.el8.x86_64 pixman-0.36.0-1.el8.x86_64
libXmu-1.1.2-12.el8.x86_64 mtdev-1.1.5-12.el8.x86_64 xorg-x11-font-utils-1:7.5-40.el8.x86_64
libglvnd-glx-1:1.0.1-0.9.git5baa1e5.el8.x86_64 libglvnd-devel-1:1.0.1-0.9.git5baa1e5.el8.x86_64 libXt-1.1.5-12.el8.x86_64
tzdata-java-2019c-1.el8.noarch gcc-8.3.1-4.5.el8.x86_64 mesa-libEGL-19.1.4-2.el8.x86_64
mesa-libGL-devel-19.1.4-2.el8.x86_64 libjpeg-turbo-1.5.3-10.el8.x86_64 mesa-vulkan-drivers-19.1.4-2.el8.x86_64
mesa-libglapi-19.1.4-2.el8.x86_64 alsa-lib-1.1.9-4.el8.x86_64 gcc-c++-8.3.1-4.5.el8.x86_64
libXt-devel-1.1.5-12.el8.x86_64 xorg-x11-server-common-1.20.3-11.el8.x86_64 xorg-x11-server-Xorg-1.20.3-11.el8.x86_64
cpp-8.3.1-4.5.el8.x86_64 gtk-update-icon-cache-3.22.30-4.el8.x86_64 pango-1.42.4-6.el8.x86_64
libtiff-4.0.9-15.el8.x86_64 mesa-libgbm-19.1.4-2.el8.x86_64 libdrm-2.4.98-2.el8.x86_64
lua-5.3.4-11.el8.x86_64 libICE-devel-1.0.9-15.el8.x86_64 mesa-khr-devel-19.1.4-2.el8.x86_64
libdrm-devel-2.4.98-2.el8.x86_64 vulkan-loader-1.1.114.0-3.el8.x86_64 java-1.8.0-openjdk-1:1.8.0.232.b09-2.el8_1.x86_64
gdk-pixbuf2-modules-2.36.12-5.el8.x86_64 mesa-libGL-19.1.4-2.el8.x86_64 gtk3-3.22.30-4.el8.x86_64
java-1.8.0-openjdk-headless-1:1.8.0.232.b09-2.el8_1.x86_64 llvm-libs-8.0.1-1.module+el8.1.0+3866+6be7f4d8.x86_64 libstdc++-devel-8.3.1-4.5.el8.x86_64
libinput-1.13.2-1.el8.x86_64 libICE-1.0.9-15.el8.x86_64
Complete!
Reboot your node:
[egallen@lab0 ~]$ sudo systemctl reboot
Success the drivers are installed and the NVIDIA System Management Interface is reporting a positive status:
[egallen@lab0 ~]$ nvidia-smi
Sun Dec 15 16:09:04 2019
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 440.33.01 Driver Version: 440.33.01 CUDA Version: 10.2 |
|-------------------------------+----------------------+----------------------+
| GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |
|===============================+======================+======================|
| 0 Tesla T4 Off | 00000000:01:00.0 Off | 0 |
| N/A 38C P0 20W / 70W | 0MiB / 15109MiB | 0% Default |
+-------------------------------+----------------------+----------------------+
+-----------------------------------------------------------------------------+
| Processes: GPU Memory |
| GPU PID Type Process name Usage |
|=============================================================================|
| No running processes found |
+-----------------------------------------------------------------------------+
Monitor interactively the driver status:
[egallen@lab0 ~]$ nvidia-smi -q -g 0 -d UTILIZATION -l
==============NVSMI LOG==============
Timestamp : Sun Dec 15 17:20:16 2019
Driver Version : 440.33.01
CUDA Version : 10.2
Attached GPUs : 1
GPU 00000000:01:00.0
Utilization
Gpu : 0 %
Memory : 0 %
Encoder : 0 %
Decoder : 0 %
GPU Utilization Samples
Duration : 9.84 sec
Number of Samples : 50
Max : 4 %
Min : 0 %
Avg : 0 %
Memory Utilization Samples
Duration : 9.84 sec
Number of Samples : 50
Max : 0 %
Min : 0 %
Avg : 0 %
ENC Utilization Samples
Duration : 9.84 sec
Number of Samples : 50
Max : 0 %
Min : 0 %
Avg : 0 %
DEC Utilization Samples
Duration : 9.84 sec
Number of Samples : 50
Max : 0 %
Min : 0 %
Avg : 0 %
The nvidia modules are available:
[egallen@lab0 ~]$ lsmod | grep -i nvidia
nvidia_drm 49152 0
nvidia_modeset 1114112 1 nvidia_drm
nvidia 19927040 1 nvidia_modeset
ipmi_msghandler 110592 1 nvidia
drm_kms_helper 217088 2 nvidia_drm,i915
drm 524288 4 drm_kms_helper,nvidia_drm,i915
Nouveau modules are removed:
[egallen@lab0 ~]$ lsmod | grep -i nouveau
[egallen@lab0 ~]$
Nouveau is disabled in the grub configuration:
[root@lab0 etc]# cat /etc/default/grub | grep nouveau
GRUB_CMDLINE_LINUX="crashkernel=auto resume=/dev/mapper/rhel-swap rd.lvm.lv=rhel/root rd.lvm.lv=rhel/swap rhgb quiet rd.driver.blacklist=nouveau"
dkms nvidia is installed:
[egallen@lab0 ~]$ dkms status
nvidia, 440.33.01, 4.18.0-147.0.3.el8_1.x86_64, x86_64: installed
A DKMS log file is available to check action done during installation:
[egallen@lab0 ~]$ cat /var/lib/dkms/nvidia/440.33.01/4.18.0-147.0.3.el8_1.x86_64/x86_64/log/make.log
DKMS make.log for nvidia-440.33.01 for kernel 4.18.0-147.0.3.el8_1.x86_64 (x86_64)
Sun Dec 15 16:05:16 CET 2019
make[1]: Entering directory '/usr/src/kernels/4.18.0-147.0.3.el8_1.x86_64'
SYMLINK /var/lib/dkms/nvidia/440.33.01/build/nvidia/nv-kernel.o
SYMLINK /var/lib/dkms/nvidia/440.33.01/build/nvidia-modeset/nv-modeset-kernel.o
CONFTEST: hash__remap_4k_pfn
CONFTEST: set_pages_uc
CONFTEST: list_is_first
CONFTEST: set_memory_uc
CONFTEST: set_memory_array_uc
CONFTEST: acquire_console_sem
CONFTEST: console_lock
CONFTEST: ioremap_cache
CONFTEST: ioremap_wc
CONFTEST: acpi_walk_namespace
CONFTEST: sg_alloc_table
CONFTEST: pci_get_domain_bus_and_slot
CONFTEST: get_num_physpages
CONFTEST: efi_enabled
CONFTEST: pde_data
CONFTEST: proc_remove
CONFTEST: pm_vt_switch_required
CONFTEST: xen_ioemu_inject_msi
CONFTEST: phys_to_dma
CONFTEST: get_dma_ops
CONFTEST: write_cr4
CONFTEST: of_get_property
CONFTEST: of_find_node_by_phandle
CONFTEST: of_node_to_nid
CONFTEST: pnv_pci_get_npu_dev
CONFTEST: of_get_ibm_chip_id
CONFTEST: node_end_pfn
CONFTEST: pci_bus_address
CONFTEST: pci_stop_and_remove_bus_device
CONFTEST: pci_remove_bus_device
CONFTEST: register_cpu_notifier
CONFTEST: cpuhp_setup_state
CONFTEST: dma_map_resource
CONFTEST: backlight_device_register
CONFTEST: timer_setup
CONFTEST: pci_enable_msix_range
CONFTEST: do_gettimeofday
CONFTEST: kernel_read
CONFTEST: kernel_write
CONFTEST: kthread_create_on_node
CONFTEST: of_find_matching_node
CONFTEST: dev_is_pci
CONFTEST: dma_direct_map_resource
CONFTEST: tegra_get_platform
CONFTEST: flush_cache_all
CONFTEST: vmf_insert_pfn
CONFTEST: address_space_init_once
CONFTEST: kbasename
CONFTEST: vzalloc
CONFTEST: wait_on_bit_lock_argument_count
CONFTEST: bitmap_clear
CONFTEST: usleep_range
CONFTEST: radix_tree_empty
CONFTEST: radix_tree_replace_slot
CONFTEST: pnv_npu2_init_context
CONFTEST: cpumask_of_node
CONFTEST: drm_dev_unref
CONFTEST: drm_reinit_primary_mode_group
CONFTEST: get_user_pages_remote
CONFTEST: get_user_pages
CONFTEST: drm_gem_object_lookup
CONFTEST: drm_atomic_state_ref_counting
CONFTEST: drm_driver_has_gem_prime_res_obj
CONFTEST: drm_atomic_helper_connector_dpms
CONFTEST: drm_connector_funcs_have_mode_in_name
CONFTEST: drm_framebuffer_get
CONFTEST: drm_gem_object_get
CONFTEST: drm_dev_put
CONFTEST: is_export_symbol_gpl_of_node_to_nid
CONFTEST: is_export_symbol_present_swiotlb_map_sg_attrs
CONFTEST: is_export_symbol_present_swiotlb_dma_ops
CONFTEST: is_export_symbol_present_kthread_create_on_node
CONFTEST: acpi_op_remove
CONFTEST: outer_flush_all
CONFTEST: file_operations
CONFTEST: file_inode
CONFTEST: kuid_t
CONFTEST: dma_ops
CONFTEST: swiotlb_dma_ops
CONFTEST: noncoherent_swiotlb_dma_ops
CONFTEST: vm_fault_has_address
CONFTEST: backlight_properties_type
CONFTEST: vm_insert_pfn_prot
CONFTEST: vmf_insert_pfn_prot
CONFTEST: vm_ops_fault_removed_vma_arg
CONFTEST: vmbus_channel_has_ringbuffer_page
CONFTEST: device_driver_of_match_table
CONFTEST: device_of_node
CONFTEST: node_states_n_memory
CONFTEST: kmem_cache_has_kobj_remove_work
CONFTEST: sysfs_slab_unlink
CONFTEST: address_space
CONFTEST: backing_dev_info
CONFTEST: mm_context_t
CONFTEST: drm_bus_present
CONFTEST: drm_bus_has_bus_type
CONFTEST: drm_bus_has_get_irq
CONFTEST: drm_bus_has_get_name
CONFTEST: drm_driver_has_legacy_dev_list
CONFTEST: drm_driver_has_set_busid
CONFTEST: drm_crtc_state_has_connectors_changed
CONFTEST: drm_init_function_args
CONFTEST: drm_helper_mode_fill_fb_struct
CONFTEST: drm_master_drop_has_from_release_arg
CONFTEST: drm_driver_unload_has_int_return_type
CONFTEST: drm_atomic_helper_crtc_destroy_state_has_crtc_arg
CONFTEST: drm_crtc_helper_funcs_has_atomic_enable
CONFTEST: drm_mode_object_find_has_file_priv_arg
CONFTEST: dma_buf_owner
CONFTEST: drm_connector_list_iter
CONFTEST: drm_atomic_helper_swap_state_has_stall_arg
CONFTEST: drm_driver_prime_flag_present
CONFTEST: dom0_kernel_present
CONFTEST: nvidia_vgpu_hyperv_available
CONFTEST: nvidia_vgpu_kvm_build
CONFTEST: nvidia_grid_build
CONFTEST: nvidia_grid_csp_build
CONFTEST: pm_runtime_available
CONFTEST: drm_available
CONFTEST: drm_atomic_available
CONFTEST: is_export_symbol_gpl_refcount_inc
CONFTEST: is_export_symbol_gpl_refcount_dec_and_test
CONFTEST: drm_alpha_blending_available
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia/nv-frontend.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia/nv.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia/nv-pci.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia/nv-acpi.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia/nv-cray.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia/nv-dma.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia/nv-i2c.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia/nv-mempool.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia/nv-mmap.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia/nv-p2p.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia/nv-pat.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia/nv-procfs.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia/nv-usermap.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia/nv-vm.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia/nv-vtophys.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia/os-interface.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia/os-mlock.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia/os-pci.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia/os-registry.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia/os-usermap.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia/nv-modeset-interface.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia/nv-pci-table.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia/nv-kthread-q.o
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CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia/nv_uvm_interface.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia/nvlink_linux.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia/linux_nvswitch.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm_utils.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm_common.o
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CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/nvstatus.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/nvCpuUuid.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/nv-kthread-q.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/nv-kthread-q-selftest.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_tools.o
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CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_procfs.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_va_space.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_va_space_mm.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_gpu_semaphore.o
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CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_lock.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_hal.o
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CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_va_range.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_va_block.o
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CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_gpu_access_counters.o
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CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_mmu.o
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CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_tlb_batch.o
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CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_pushbuffer.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_thread_context.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_tracker.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_kepler.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_kepler_ce.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_kepler_host.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_kepler_mmu.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_maxwell.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_maxwell_host.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_pascal.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_pascal_ce.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_pascal_host.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_pascal_mmu.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_pascal_fault_buffer.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_volta_host.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_volta_mmu.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_volta.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_volta_fault_buffer.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_volta_access_counter_buffer.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_turing.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_turing_mmu.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_turing_host.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_policy.o
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CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_kvmalloc.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_pmm_sysmem.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_pmm_gpu.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_migrate.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_populate_pageable.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_migrate_pageable.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_map_external.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_user_channel.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_hmm.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_perf_heuristics.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_perf_thrashing.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_perf_prefetch.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_ats_ibm.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_ats_faults.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_test.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_test_rng.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_range_tree_test.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_range_allocator_test.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_gpu_semaphore_test.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_mem_test.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_rm_mem_test.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_page_tree_test.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_tracker_test.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_push_test.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_channel_test.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_ce_test.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_lock_test.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_perf_utils_test.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_kvmalloc_test.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_pmm_test.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_pmm_sysmem_test.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_perf_events_test.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_perf_module_test.o
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CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-drm/nvidia-drm-gem.o
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CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-drm/nv-pci-table.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-drm/nvidia-drm-gem-nvkms-memory.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-drm/nvidia-drm-gem-user-memory.o
ld -r -o /var/lib/dkms/nvidia/440.33.01/build/nvidia/nv-interface.o /var/lib/dkms/nvidia/440.33.01/build/nvidia/nv-frontend.o /var/lib/dkms/nvidia/440.33.01/build/nvidia/nv.o /var/lib/dkms/nvidia/440.33.01/build/nvidia/nv-pci.o /var/lib/dkms/nvidia/440.33.01/build/nvidia/nv-acpi.o /var/lib/dkms/nvidia/440.33.01/build/nvidia/nv-cray.o /var/lib/dkms/nvidia/440.33.01/build/nvidia/nv-dma.o /var/lib/dkms/nvidia/440.33.01/build/nvidia/nv-i2c.o /var/lib/dkms/nvidia/440.33.01/build/nvidia/nv-mempool.o /var/lib/dkms/nvidia/440.33.01/build/nvidia/nv-mmap.o /var/lib/dkms/nvidia/440.33.01/build/nvidia/nv-p2p.o /var/lib/dkms/nvidia/440.33.01/build/nvidia/nv-pat.o /var/lib/dkms/nvidia/440.33.01/build/nvidia/nv-procfs.o /var/lib/dkms/nvidia/440.33.01/build/nvidia/nv-usermap.o /var/lib/dkms/nvidia/440.33.01/build/nvidia/nv-vm.o /var/lib/dkms/nvidia/440.33.01/build/nvidia/nv-vtophys.o /var/lib/dkms/nvidia/440.33.01/build/nvidia/os-interface.o /var/lib/dkms/nvidia/440.33.01/build/nvidia/os-mlock.o /var/lib/dkms/nvidia/440.33.01/build/nvidia/os-pci.o /var/lib/dkms/nvidia/440.33.01/build/nvidia/os-registry.o /var/lib/dkms/nvidia/440.33.01/build/nvidia/os-usermap.o /var/lib/dkms/nvidia/440.33.01/build/nvidia/nv-modeset-interface.o /var/lib/dkms/nvidia/440.33.01/build/nvidia/nv-pci-table.o /var/lib/dkms/nvidia/440.33.01/build/nvidia/nv-kthread-q.o /var/lib/dkms/nvidia/440.33.01/build/nvidia/nv-memdbg.o /var/lib/dkms/nvidia/440.33.01/build/nvidia/nv-ibmnpu.o /var/lib/dkms/nvidia/440.33.01/build/nvidia/nv-report-err.o /var/lib/dkms/nvidia/440.33.01/build/nvidia/nv-rsync.o /var/lib/dkms/nvidia/440.33.01/build/nvidia/nv-msi.o /var/lib/dkms/nvidia/440.33.01/build/nvidia/nv_uvm_interface.o /var/lib/dkms/nvidia/440.33.01/build/nvidia/nvlink_linux.o /var/lib/dkms/nvidia/440.33.01/build/nvidia/linux_nvswitch.o
ld -r -o /var/lib/dkms/nvidia/440.33.01/build/nvidia-modeset/nv-modeset-interface.o /var/lib/dkms/nvidia/440.33.01/build/nvidia-modeset/nvidia-modeset-linux.o /var/lib/dkms/nvidia/440.33.01/build/nvidia-modeset/nv-kthread-q.o
LD [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia.o
LD [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm.o
LD [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-modeset.o
LD [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-drm.o
Building modules, stage 2.
MODPOST 4 modules
CC /var/lib/dkms/nvidia/440.33.01/build/nvidia-drm.mod.o
CC /var/lib/dkms/nvidia/440.33.01/build/nvidia-modeset.mod.o
CC /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm.mod.o
CC /var/lib/dkms/nvidia/440.33.01/build/nvidia.mod.o
LD [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-drm.ko
LD [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-modeset.ko
LD [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm.ko
LD [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia.ko
make[1]: Leaving directory '/usr/src/kernels/4.18.0-147.0.3.el8_1.x86_64'
[egallen@lab0 ~]$ cat /var/lib/dkms/nvidia/440.33.01/4.18.0-147.0.3.el8_1.x86_64/x86_64/log/make.log | wc -l
292
[egallen@lab0 ~]$ cat /var/lib/dkms/nvidia/440.33.01/4.18.0-147.0.3.el8_1.x86_64/x86_64/log/make.log
DKMS make.log for nvidia-440.33.01 for kernel 4.18.0-147.0.3.el8_1.x86_64 (x86_64)
Sun Dec 15 16:05:16 CET 2019
make[1]: Entering directory '/usr/src/kernels/4.18.0-147.0.3.el8_1.x86_64'
SYMLINK /var/lib/dkms/nvidia/440.33.01/build/nvidia/nv-kernel.o
SYMLINK /var/lib/dkms/nvidia/440.33.01/build/nvidia-modeset/nv-modeset-kernel.o
CONFTEST: hash__remap_4k_pfn
CONFTEST: set_pages_uc
CONFTEST: list_is_first
CONFTEST: set_memory_uc
CONFTEST: set_memory_array_uc
CONFTEST: acquire_console_sem
CONFTEST: console_lock
CONFTEST: ioremap_cache
CONFTEST: ioremap_wc
CONFTEST: acpi_walk_namespace
CONFTEST: sg_alloc_table
CONFTEST: pci_get_domain_bus_and_slot
CONFTEST: get_num_physpages
CONFTEST: efi_enabled
CONFTEST: pde_data
CONFTEST: proc_remove
CONFTEST: pm_vt_switch_required
CONFTEST: xen_ioemu_inject_msi
CONFTEST: phys_to_dma
CONFTEST: get_dma_ops
CONFTEST: write_cr4
CONFTEST: of_get_property
CONFTEST: of_find_node_by_phandle
CONFTEST: of_node_to_nid
CONFTEST: pnv_pci_get_npu_dev
CONFTEST: of_get_ibm_chip_id
CONFTEST: node_end_pfn
CONFTEST: pci_bus_address
CONFTEST: pci_stop_and_remove_bus_device
CONFTEST: pci_remove_bus_device
CONFTEST: register_cpu_notifier
CONFTEST: cpuhp_setup_state
CONFTEST: dma_map_resource
CONFTEST: backlight_device_register
CONFTEST: timer_setup
CONFTEST: pci_enable_msix_range
CONFTEST: do_gettimeofday
CONFTEST: kernel_read
CONFTEST: kernel_write
CONFTEST: kthread_create_on_node
CONFTEST: of_find_matching_node
CONFTEST: dev_is_pci
CONFTEST: dma_direct_map_resource
CONFTEST: tegra_get_platform
CONFTEST: flush_cache_all
CONFTEST: vmf_insert_pfn
CONFTEST: address_space_init_once
CONFTEST: kbasename
CONFTEST: vzalloc
CONFTEST: wait_on_bit_lock_argument_count
CONFTEST: bitmap_clear
CONFTEST: usleep_range
CONFTEST: radix_tree_empty
CONFTEST: radix_tree_replace_slot
CONFTEST: pnv_npu2_init_context
CONFTEST: cpumask_of_node
CONFTEST: drm_dev_unref
CONFTEST: drm_reinit_primary_mode_group
CONFTEST: get_user_pages_remote
CONFTEST: get_user_pages
CONFTEST: drm_gem_object_lookup
CONFTEST: drm_atomic_state_ref_counting
CONFTEST: drm_driver_has_gem_prime_res_obj
CONFTEST: drm_atomic_helper_connector_dpms
CONFTEST: drm_connector_funcs_have_mode_in_name
CONFTEST: drm_framebuffer_get
CONFTEST: drm_gem_object_get
CONFTEST: drm_dev_put
CONFTEST: is_export_symbol_gpl_of_node_to_nid
CONFTEST: is_export_symbol_present_swiotlb_map_sg_attrs
CONFTEST: is_export_symbol_present_swiotlb_dma_ops
CONFTEST: is_export_symbol_present_kthread_create_on_node
CONFTEST: acpi_op_remove
CONFTEST: outer_flush_all
CONFTEST: file_operations
CONFTEST: file_inode
CONFTEST: kuid_t
CONFTEST: dma_ops
CONFTEST: swiotlb_dma_ops
CONFTEST: noncoherent_swiotlb_dma_ops
CONFTEST: vm_fault_has_address
CONFTEST: backlight_properties_type
CONFTEST: vm_insert_pfn_prot
CONFTEST: vmf_insert_pfn_prot
CONFTEST: vm_ops_fault_removed_vma_arg
CONFTEST: vmbus_channel_has_ringbuffer_page
CONFTEST: device_driver_of_match_table
CONFTEST: device_of_node
CONFTEST: node_states_n_memory
CONFTEST: kmem_cache_has_kobj_remove_work
CONFTEST: sysfs_slab_unlink
CONFTEST: address_space
CONFTEST: backing_dev_info
CONFTEST: mm_context_t
CONFTEST: drm_bus_present
CONFTEST: drm_bus_has_bus_type
CONFTEST: drm_bus_has_get_irq
CONFTEST: drm_bus_has_get_name
CONFTEST: drm_driver_has_legacy_dev_list
CONFTEST: drm_driver_has_set_busid
CONFTEST: drm_crtc_state_has_connectors_changed
CONFTEST: drm_init_function_args
CONFTEST: drm_helper_mode_fill_fb_struct
CONFTEST: drm_master_drop_has_from_release_arg
CONFTEST: drm_driver_unload_has_int_return_type
CONFTEST: drm_atomic_helper_crtc_destroy_state_has_crtc_arg
CONFTEST: drm_crtc_helper_funcs_has_atomic_enable
CONFTEST: drm_mode_object_find_has_file_priv_arg
CONFTEST: dma_buf_owner
CONFTEST: drm_connector_list_iter
CONFTEST: drm_atomic_helper_swap_state_has_stall_arg
CONFTEST: drm_driver_prime_flag_present
CONFTEST: dom0_kernel_present
CONFTEST: nvidia_vgpu_hyperv_available
CONFTEST: nvidia_vgpu_kvm_build
CONFTEST: nvidia_grid_build
CONFTEST: nvidia_grid_csp_build
CONFTEST: pm_runtime_available
CONFTEST: drm_available
CONFTEST: drm_atomic_available
CONFTEST: is_export_symbol_gpl_refcount_inc
CONFTEST: is_export_symbol_gpl_refcount_dec_and_test
CONFTEST: drm_alpha_blending_available
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia/nv-frontend.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia/nv.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia/nv-pci.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia/nv-acpi.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia/nv-cray.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia/nv-dma.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia/nv-i2c.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia/nv-mempool.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia/nv-mmap.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia/nv-p2p.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia/nv-pat.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia/nv-procfs.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia/nv-usermap.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia/nv-vm.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia/nv-vtophys.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia/os-interface.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia/os-mlock.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia/os-pci.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia/os-registry.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia/os-usermap.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia/nv-modeset-interface.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia/nv-pci-table.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia/nv-kthread-q.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia/nv-memdbg.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia/nv-ibmnpu.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia/nv-report-err.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia/nv-rsync.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia/nv-msi.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia/nv_uvm_interface.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia/nvlink_linux.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia/linux_nvswitch.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm_utils.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm_common.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm_linux.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/nvstatus.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/nvCpuUuid.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/nv-kthread-q.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/nv-kthread-q-selftest.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_tools.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_global.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_gpu.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_gpu_isr.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_procfs.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_va_space.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_va_space_mm.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_gpu_semaphore.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_mem.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_rm_mem.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_channel.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_lock.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_hal.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_range_tree.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_range_allocator.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_va_range.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_va_block.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_range_group.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_gpu_replayable_faults.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_gpu_non_replayable_faults.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_gpu_access_counters.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_perf_events.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_perf_module.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_mmu.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_pte_batch.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_tlb_batch.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_push.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_pushbuffer.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_thread_context.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_tracker.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_kepler.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_kepler_ce.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_kepler_host.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_kepler_mmu.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_maxwell.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_maxwell_host.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_pascal.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_pascal_ce.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_pascal_host.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_pascal_mmu.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_pascal_fault_buffer.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_volta_host.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_volta_mmu.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_volta.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_volta_fault_buffer.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_volta_access_counter_buffer.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_turing.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_turing_mmu.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_turing_host.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_policy.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_perf_utils.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_kvmalloc.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_pmm_sysmem.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_pmm_gpu.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_migrate.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_populate_pageable.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_migrate_pageable.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_map_external.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_user_channel.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_hmm.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_perf_heuristics.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_perf_thrashing.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_perf_prefetch.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_ats_ibm.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_ats_faults.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_test.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_test_rng.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_range_tree_test.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_range_allocator_test.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_gpu_semaphore_test.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_mem_test.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_rm_mem_test.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_page_tree_test.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_tracker_test.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_push_test.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_channel_test.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_ce_test.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_lock_test.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_perf_utils_test.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_kvmalloc_test.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_pmm_test.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_pmm_sysmem_test.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_perf_events_test.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_perf_module_test.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_get_rm_ptes_test.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_fault_buffer_flush_test.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_mmu_test.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_peer_identity_mappings_test.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_va_block_test.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_range_group_tree_test.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm/uvm8_thread_context_test.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-modeset/nvidia-modeset-linux.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-modeset/nv-kthread-q.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-drm/nvidia-drm.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-drm/nvidia-drm-drv.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-drm/nvidia-drm-utils.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-drm/nvidia-drm-crtc.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-drm/nvidia-drm-encoder.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-drm/nvidia-drm-connector.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-drm/nvidia-drm-gem.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-drm/nvidia-drm-fb.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-drm/nvidia-drm-modeset.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-drm/nvidia-drm-prime-fence.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-drm/nvidia-drm-linux.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-drm/nvidia-drm-helper.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-drm/nv-pci-table.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-drm/nvidia-drm-gem-nvkms-memory.o
CC [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-drm/nvidia-drm-gem-user-memory.o
ld -r -o /var/lib/dkms/nvidia/440.33.01/build/nvidia/nv-interface.o /var/lib/dkms/nvidia/440.33.01/build/nvidia/nv-frontend.o /var/lib/dkms/nvidia/440.33.01/build/nvidia/nv.o /var/lib/dkms/nvidia/440.33.01/build/nvidia/nv-pci.o /var/lib/dkms/nvidia/440.33.01/build/nvidia/nv-acpi.o /var/lib/dkms/nvidia/440.33.01/build/nvidia/nv-cray.o /var/lib/dkms/nvidia/440.33.01/build/nvidia/nv-dma.o /var/lib/dkms/nvidia/440.33.01/build/nvidia/nv-i2c.o /var/lib/dkms/nvidia/440.33.01/build/nvidia/nv-mempool.o /var/lib/dkms/nvidia/440.33.01/build/nvidia/nv-mmap.o /var/lib/dkms/nvidia/440.33.01/build/nvidia/nv-p2p.o /var/lib/dkms/nvidia/440.33.01/build/nvidia/nv-pat.o /var/lib/dkms/nvidia/440.33.01/build/nvidia/nv-procfs.o /var/lib/dkms/nvidia/440.33.01/build/nvidia/nv-usermap.o /var/lib/dkms/nvidia/440.33.01/build/nvidia/nv-vm.o /var/lib/dkms/nvidia/440.33.01/build/nvidia/nv-vtophys.o /var/lib/dkms/nvidia/440.33.01/build/nvidia/os-interface.o /var/lib/dkms/nvidia/440.33.01/build/nvidia/os-mlock.o /var/lib/dkms/nvidia/440.33.01/build/nvidia/os-pci.o /var/lib/dkms/nvidia/440.33.01/build/nvidia/os-registry.o /var/lib/dkms/nvidia/440.33.01/build/nvidia/os-usermap.o /var/lib/dkms/nvidia/440.33.01/build/nvidia/nv-modeset-interface.o /var/lib/dkms/nvidia/440.33.01/build/nvidia/nv-pci-table.o /var/lib/dkms/nvidia/440.33.01/build/nvidia/nv-kthread-q.o /var/lib/dkms/nvidia/440.33.01/build/nvidia/nv-memdbg.o /var/lib/dkms/nvidia/440.33.01/build/nvidia/nv-ibmnpu.o /var/lib/dkms/nvidia/440.33.01/build/nvidia/nv-report-err.o /var/lib/dkms/nvidia/440.33.01/build/nvidia/nv-rsync.o /var/lib/dkms/nvidia/440.33.01/build/nvidia/nv-msi.o /var/lib/dkms/nvidia/440.33.01/build/nvidia/nv_uvm_interface.o /var/lib/dkms/nvidia/440.33.01/build/nvidia/nvlink_linux.o /var/lib/dkms/nvidia/440.33.01/build/nvidia/linux_nvswitch.o
ld -r -o /var/lib/dkms/nvidia/440.33.01/build/nvidia-modeset/nv-modeset-interface.o /var/lib/dkms/nvidia/440.33.01/build/nvidia-modeset/nvidia-modeset-linux.o /var/lib/dkms/nvidia/440.33.01/build/nvidia-modeset/nv-kthread-q.o
LD [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia.o
LD [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm.o
LD [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-modeset.o
LD [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-drm.o
Building modules, stage 2.
MODPOST 4 modules
CC /var/lib/dkms/nvidia/440.33.01/build/nvidia-drm.mod.o
CC /var/lib/dkms/nvidia/440.33.01/build/nvidia-modeset.mod.o
CC /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm.mod.o
CC /var/lib/dkms/nvidia/440.33.01/build/nvidia.mod.o
LD [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-drm.ko
LD [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-modeset.ko
LD [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia-uvm.ko
LD [M] /var/lib/dkms/nvidia/440.33.01/build/nvidia.ko
make[1]: Leaving directory '/usr/src/kernels/4.18.0-147.0.3.el8_1.x86_64'
Check nvidia and cuda packages installed:
[egallen@lab0 ~]$ dnf list installed | grep -E 'nvidia|cuda'
cuda.x86_64 10.2.89-1 @cuda
cuda-10-2.x86_64 10.2.89-1 @cuda
cuda-command-line-tools-10-2.x86_64 10.2.89-1 @cuda
cuda-compiler-10-2.x86_64 10.2.89-1 @cuda
cuda-cudart-10-2.x86_64 10.2.89-1 @cuda
cuda-cudart-dev-10-2.x86_64 10.2.89-1 @cuda
cuda-cufft-10-2.x86_64 10.2.89-1 @cuda
cuda-cufft-dev-10-2.x86_64 10.2.89-1 @cuda
cuda-cuobjdump-10-2.x86_64 10.2.89-1 @cuda
cuda-cupti-10-2.x86_64 10.2.89-1 @cuda
cuda-curand-10-2.x86_64 10.2.89-1 @cuda
cuda-curand-dev-10-2.x86_64 10.2.89-1 @cuda
cuda-cusolver-10-2.x86_64 10.2.89-1 @cuda
cuda-cusolver-dev-10-2.x86_64 10.2.89-1 @cuda
cuda-cusparse-10-2.x86_64 10.2.89-1 @cuda
cuda-cusparse-dev-10-2.x86_64 10.2.89-1 @cuda
cuda-demo-suite-10-2.x86_64 10.2.89-1 @cuda
cuda-documentation-10-2.x86_64 10.2.89-1 @cuda
cuda-driver-dev-10-2.x86_64 10.2.89-1 @cuda
cuda-drivers.x86_64 440.33.01-1 @cuda
cuda-gdb-10-2.x86_64 10.2.89-1 @cuda
cuda-libraries-10-2.x86_64 10.2.89-1 @cuda
cuda-libraries-dev-10-2.x86_64 10.2.89-1 @cuda
cuda-license-10-2.x86_64 10.2.89-1 @cuda
cuda-memcheck-10-2.x86_64 10.2.89-1 @cuda
cuda-misc-headers-10-2.x86_64 10.2.89-1 @cuda
cuda-npp-10-2.x86_64 10.2.89-1 @cuda
cuda-npp-dev-10-2.x86_64 10.2.89-1 @cuda
cuda-nsight-10-2.x86_64 10.2.89-1 @cuda
cuda-nsight-compute-10-2.x86_64 10.2.89-1 @cuda
cuda-nsight-systems-10-2.x86_64 10.2.89-1 @cuda
cuda-nvcc-10-2.x86_64 10.2.89-1 @cuda
cuda-nvdisasm-10-2.x86_64 10.2.89-1 @cuda
cuda-nvgraph-10-2.x86_64 10.2.89-1 @cuda
cuda-nvgraph-dev-10-2.x86_64 10.2.89-1 @cuda
cuda-nvjpeg-10-2.x86_64 10.2.89-1 @cuda
cuda-nvjpeg-dev-10-2.x86_64 10.2.89-1 @cuda
cuda-nvml-dev-10-2.x86_64 10.2.89-1 @cuda
cuda-nvprof-10-2.x86_64 10.2.89-1 @cuda
cuda-nvprune-10-2.x86_64 10.2.89-1 @cuda
cuda-nvrtc-10-2.x86_64 10.2.89-1 @cuda
cuda-nvrtc-dev-10-2.x86_64 10.2.89-1 @cuda
cuda-nvtx-10-2.x86_64 10.2.89-1 @cuda
cuda-nvvp-10-2.x86_64 10.2.89-1 @cuda
cuda-runtime-10-2.x86_64 10.2.89-1 @cuda
cuda-samples-10-2.x86_64 10.2.89-1 @cuda
cuda-sanitizer-api-10-2.x86_64 10.2.89-1 @cuda
cuda-toolkit-10-2.x86_64 10.2.89-1 @cuda
cuda-tools-10-2.x86_64 10.2.89-1 @cuda
cuda-visual-tools-10-2.x86_64 10.2.89-1 @cuda
dnf-plugin-nvidia.noarch 1.1-1.el8 @cuda
kmod-nvidia-latest-dkms.x86_64 3:440.33.01-1.el8 @cuda
libcublas-devel.x86_64 10.2.2.89-1 @cuda
libcublas10.x86_64 10.2.2.89-1 @cuda
nsight-compute-2019.4.0.x86_64 2019.4.0.12-1 @cuda
nsight-systems-2019.5.2.x86_64 2019.5.2.16_b54ef97-0 @cuda
nvidia-driver.x86_64 3:440.33.01-1.el8 @cuda
nvidia-driver-NVML.x86_64 3:440.33.01-1.el8 @cuda
nvidia-driver-NvFBCOpenGL.x86_64 3:440.33.01-1.el8 @cuda
nvidia-driver-cuda.x86_64 3:440.33.01-1.el8 @cuda
nvidia-driver-cuda-libs.x86_64 3:440.33.01-1.el8 @cuda
nvidia-driver-devel.x86_64 3:440.33.01-1.el8 @cuda
nvidia-driver-libs.x86_64 3:440.33.01-1.el8 @cuda
nvidia-kmod-common.noarch 3:440.33.01-1.el8 @cuda
nvidia-libXNVCtrl.x86_64 3:440.33.01-1.el8 @cuda
nvidia-libXNVCtrl-devel.x86_64 3:440.33.01-1.el8 @cuda
nvidia-modprobe.x86_64 3:440.33.01-1.el8 @cuda
nvidia-persistenced.x86_64 3:440.33.01-1.el8 @cuda
nvidia-settings.x86_64 3:440.33.01-1.el8 @cuda
nvidia-xconfig.x86_64 3:440.33.01-1.el8 @cuda
Check kernel modules installed:
[egallen@lab0 ~]$ dnf list installed|grep 'kernel'
kernel.x86_64 4.18.0-147.el8 @anaconda
kernel.x86_64 4.18.0-147.0.3.el8_1 @rhel-8-for-x86_64-baseos-rpms
kernel-core.x86_64 4.18.0-147.el8 @anaconda
kernel-core.x86_64 4.18.0-147.0.3.el8_1 @rhel-8-for-x86_64-baseos-rpms
kernel-devel.x86_64 4.18.0-147.0.3.el8_1 @rhel-8-for-x86_64-baseos-rpms
kernel-headers.x86_64 4.18.0-147.0.3.el8_1 @rhel-8-for-x86_64-baseos-rpms
kernel-modules.x86_64 4.18.0-147.el8 @anaconda
kernel-modules.x86_64 4.18.0-147.0.3.el8_1 @rhel-8-for-x86_64-baseos-rpms
kernel-tools.x86_64 4.18.0-147.0.3.el8_1 @rhel-8-for-x86_64-baseos-rpms
kernel-tools-libs.x86_64 4.18.0-147.0.3.el8_1 @rhel-8-for-x86_64-baseos-rpms
SELinux is enabled:
[egallen@lab0 ~]$ getenforce
Enforcing
Enable GPU with podman
Now we will install podman, offical documentation: https://access.redhat.com/solutions/3650231
Since RHEL 8, the podman container engine is included in a module called container-tools. Instead of using a classic “dnf install” command we will use the container-tools module:
[egallen@lab0 ~]$ sudo dnf module install container-tools -y
Updating Subscription Management repositories.
Last metadata expiration check: 0:04:18 ago on Sun 15 Dec 2019 05:21:08 PM CET.
Dependencies resolved.
========================================================================================================================================================================================
Package Architecture Version Repository Size
========================================================================================================================================================================================
Installing group/module packages:
oci-umount x86_64 2:2.3.4-2.git87f9237.module+el8+2769+577ad176 rhel-8-for-x86_64-appstream-rpms 38 k
oci-systemd-hook x86_64 1:0.1.15-2.git2d0b8a3.module+el8+2769+577ad176 rhel-8-for-x86_64-appstream-rpms 39 k
slirp4netns x86_64 0.3.0-4.module+el8.1.0+4306+1d917805 rhel-8-for-x86_64-appstream-rpms 83 k
skopeo x86_64 1:0.1.37-5.module+el8.1.0+4240+893c1ab8 rhel-8-for-x86_64-appstream-rpms 5.3 M
podman x86_64 1.4.2-5.module+el8.1.0+4240+893c1ab8 rhel-8-for-x86_64-appstream-rpms 11 M
buildah x86_64 1.9.0-5.module+el8.1.0+4240+893c1ab8 rhel-8-for-x86_64-appstream-rpms 6.4 M
runc x86_64 1.0.0-60.rc8.module+el8.1.0+4081+b29780af rhel-8-for-x86_64-appstream-rpms 2.5 M
fuse-overlayfs x86_64 0.4.1-1.module+el8.1.0+4081+b29780af rhel-8-for-x86_64-appstream-rpms 50 k
container-selinux noarch 2:2.107-2.module+el8.1.0+4081+b29780af rhel-8-for-x86_64-appstream-rpms 44 k
containernetworking-plugins x86_64 0.8.1-2.module+el8.1.0+4081+b29780af rhel-8-for-x86_64-appstream-rpms 20 M
Installing dependencies:
fuse3-libs x86_64 3.2.1-12.el8 rhel-8-for-x86_64-baseos-rpms 94 k
python3-setools x86_64 4.2.2-1.el8 rhel-8-for-x86_64-baseos-rpms 600 k
python3-audit x86_64 3.0-0.13.20190507gitf58ec40.el8 rhel-8-for-x86_64-baseos-rpms 85 k
policycoreutils-python-utils noarch 2.9-3.el8 rhel-8-for-x86_64-baseos-rpms 250 k
python3-policycoreutils noarch 2.9-3.el8 rhel-8-for-x86_64-baseos-rpms 2.2 M
checkpolicy x86_64 2.9-1.el8 rhel-8-for-x86_64-baseos-rpms 346 k
python3-libsemanage x86_64 2.9-1.el8 rhel-8-for-x86_64-baseos-rpms 127 k
libnet x86_64 1.1.6-15.el8 rhel-8-for-x86_64-appstream-rpms 67 k
yajl x86_64 2.1.0-10.el8 rhel-8-for-x86_64-appstream-rpms 41 k
protobuf-c x86_64 1.3.0-4.el8 rhel-8-for-x86_64-appstream-rpms 37 k
containers-common x86_64 1:0.1.37-5.module+el8.1.0+4240+893c1ab8 rhel-8-for-x86_64-appstream-rpms 32 k
podman-manpages noarch 1.4.2-5.module+el8.1.0+4240+893c1ab8 rhel-8-for-x86_64-appstream-rpms 180 k
ostree-libs x86_64 2019.2-1.el8 rhel-8-for-x86_64-appstream-rpms 389 k
criu x86_64 3.12-9.el8 rhel-8-for-x86_64-appstream-rpms 482 k
Installing weak dependencies:
libvarlink x86_64 18-3.el8 rhel-8-for-x86_64-baseos-rpms 44 k
Installing module profiles:
container-tools/common
Enabling module streams:
container-tools rhel8
Transaction Summary
========================================================================================================================================================================================
Install 25 Packages
Total download size: 51 M
Installed size: 189 M
Downloading Packages:
(1/25): python3-audit-3.0-0.13.20190507gitf58ec40.el8.x86_64.rpm 225 kB/s | 85 kB 00:00
(2/25): fuse3-libs-3.2.1-12.el8.x86_64.rpm 231 kB/s | 94 kB 00:00
(3/25): python3-setools-4.2.2-1.el8.x86_64.rpm 1.2 MB/s | 600 kB 00:00
(4/25): policycoreutils-python-utils-2.9-3.el8.noarch.rpm 751 kB/s | 250 kB 00:00
(5/25): python3-policycoreutils-2.9-3.el8.noarch.rpm 6.6 MB/s | 2.2 MB 00:00
(6/25): checkpolicy-2.9-1.el8.x86_64.rpm 772 kB/s | 346 kB 00:00
(7/25): python3-libsemanage-2.9-1.el8.x86_64.rpm 402 kB/s | 127 kB 00:00
(8/25): libvarlink-18-3.el8.x86_64.rpm 149 kB/s | 44 kB 00:00
(9/25): libnet-1.1.6-15.el8.x86_64.rpm 217 kB/s | 67 kB 00:00
(10/25): protobuf-c-1.3.0-4.el8.x86_64.rpm 121 kB/s | 37 kB 00:00
(11/25): yajl-2.1.0-10.el8.x86_64.rpm 96 kB/s | 41 kB 00:00
(12/25): oci-systemd-hook-0.1.15-2.git2d0b8a3.module+el8+2769+577ad176.x86_64.rpm 133 kB/s | 39 kB 00:00
(13/25): slirp4netns-0.3.0-4.module+el8.1.0+4306+1d917805.x86_64.rpm 248 kB/s | 83 kB 00:00
(14/25): containers-common-0.1.37-5.module+el8.1.0+4240+893c1ab8.x86_64.rpm 105 kB/s | 32 kB 00:00
(15/25): skopeo-0.1.37-5.module+el8.1.0+4240+893c1ab8.x86_64.rpm 8.0 MB/s | 5.3 MB 00:00
(16/25): podman-1.4.2-5.module+el8.1.0+4240+893c1ab8.x86_64.rpm 19 MB/s | 11 MB 00:00
(17/25): buildah-1.9.0-5.module+el8.1.0+4240+893c1ab8.x86_64.rpm 11 MB/s | 6.4 MB 00:00
(18/25): oci-umount-2.3.4-2.git87f9237.module+el8+2769+577ad176.x86_64.rpm 20 kB/s | 38 kB 00:01
(19/25): runc-1.0.0-60.rc8.module+el8.1.0+4081+b29780af.x86_64.rpm 5.7 MB/s | 2.5 MB 00:00
(20/25): podman-manpages-1.4.2-5.module+el8.1.0+4240+893c1ab8.noarch.rpm 573 kB/s | 180 kB 00:00
(21/25): ostree-libs-2019.2-1.el8.x86_64.rpm 1.3 MB/s | 389 kB 00:00
(22/25): fuse-overlayfs-0.4.1-1.module+el8.1.0+4081+b29780af.x86_64.rpm 155 kB/s | 50 kB 00:00
(23/25): container-selinux-2.107-2.module+el8.1.0+4081+b29780af.noarch.rpm 128 kB/s | 44 kB 00:00
(24/25): criu-3.12-9.el8.x86_64.rpm 1.4 MB/s | 482 kB 00:00
(25/25): containernetworking-plugins-0.8.1-2.module+el8.1.0+4081+b29780af.x86_64.rpm 8.5 MB/s | 20 MB 00:02
----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
Total 8.8 MB/s | 51 MB 00:05
Running transaction check
Transaction check succeeded.
Running transaction test
Transaction test succeeded.
Running transaction
Preparing : 1/1
Installing : ostree-libs-2019.2-1.el8.x86_64 1/25
Installing : slirp4netns-0.3.0-4.module+el8.1.0+4306+1d917805.x86_64 2/25
Installing : yajl-2.1.0-10.el8.x86_64 3/25
Installing : oci-systemd-hook-1:0.1.15-2.git2d0b8a3.module+el8+2769+577ad176.x86_64 4/25
Installing : containernetworking-plugins-0.8.1-2.module+el8.1.0+4081+b29780af.x86_64 5/25
Installing : podman-manpages-1.4.2-5.module+el8.1.0+4240+893c1ab8.noarch 6/25
Installing : protobuf-c-1.3.0-4.el8.x86_64 7/25
Installing : libnet-1.1.6-15.el8.x86_64 8/25
Running scriptlet: libnet-1.1.6-15.el8.x86_64 8/25
Installing : criu-3.12-9.el8.x86_64 9/25
Installing : libvarlink-18-3.el8.x86_64 10/25
Running scriptlet: libvarlink-18-3.el8.x86_64 10/25
Installing : python3-libsemanage-2.9-1.el8.x86_64 11/25
Installing : checkpolicy-2.9-1.el8.x86_64 12/25
Installing : python3-audit-3.0-0.13.20190507gitf58ec40.el8.x86_64 13/25
Installing : python3-setools-4.2.2-1.el8.x86_64 14/25
Installing : python3-policycoreutils-2.9-3.el8.noarch 15/25
Installing : policycoreutils-python-utils-2.9-3.el8.noarch 16/25
Installing : container-selinux-2:2.107-2.module+el8.1.0+4081+b29780af.noarch 17/25
Running scriptlet: container-selinux-2:2.107-2.module+el8.1.0+4081+b29780af.noarch 17/25
Installing : runc-1.0.0-60.rc8.module+el8.1.0+4081+b29780af.x86_64 18/25
Installing : fuse3-libs-3.2.1-12.el8.x86_64 19/25
Running scriptlet: fuse3-libs-3.2.1-12.el8.x86_64 19/25
Installing : fuse-overlayfs-0.4.1-1.module+el8.1.0+4081+b29780af.x86_64 20/25
Installing : containers-common-1:0.1.37-5.module+el8.1.0+4240+893c1ab8.x86_64 21/25
Installing : skopeo-1:0.1.37-5.module+el8.1.0+4240+893c1ab8.x86_64 22/25
Installing : podman-1.4.2-5.module+el8.1.0+4240+893c1ab8.x86_64 23/25
Installing : buildah-1.9.0-5.module+el8.1.0+4240+893c1ab8.x86_64 24/25
Installing : oci-umount-2:2.3.4-2.git87f9237.module+el8+2769+577ad176.x86_64 25/25
Running scriptlet: oci-umount-2:2.3.4-2.git87f9237.module+el8+2769+577ad176.x86_64 25/25
Verifying : fuse3-libs-3.2.1-12.el8.x86_64 1/25
Verifying : python3-setools-4.2.2-1.el8.x86_64 2/25
Verifying : python3-audit-3.0-0.13.20190507gitf58ec40.el8.x86_64 3/25
Verifying : policycoreutils-python-utils-2.9-3.el8.noarch 4/25
Verifying : python3-policycoreutils-2.9-3.el8.noarch 5/25
Verifying : checkpolicy-2.9-1.el8.x86_64 6/25
Verifying : python3-libsemanage-2.9-1.el8.x86_64 7/25
Verifying : libvarlink-18-3.el8.x86_64 8/25
Verifying : libnet-1.1.6-15.el8.x86_64 9/25
Verifying : yajl-2.1.0-10.el8.x86_64 10/25
Verifying : protobuf-c-1.3.0-4.el8.x86_64 11/25
Verifying : oci-umount-2:2.3.4-2.git87f9237.module+el8+2769+577ad176.x86_64 12/25
Verifying : oci-systemd-hook-1:0.1.15-2.git2d0b8a3.module+el8+2769+577ad176.x86_64 13/25
Verifying : slirp4netns-0.3.0-4.module+el8.1.0+4306+1d917805.x86_64 14/25
Verifying : skopeo-1:0.1.37-5.module+el8.1.0+4240+893c1ab8.x86_64 15/25
Verifying : containers-common-1:0.1.37-5.module+el8.1.0+4240+893c1ab8.x86_64 16/25
Verifying : podman-1.4.2-5.module+el8.1.0+4240+893c1ab8.x86_64 17/25
Verifying : buildah-1.9.0-5.module+el8.1.0+4240+893c1ab8.x86_64 18/25
Verifying : runc-1.0.0-60.rc8.module+el8.1.0+4081+b29780af.x86_64 19/25
Verifying : podman-manpages-1.4.2-5.module+el8.1.0+4240+893c1ab8.noarch 20/25
Verifying : fuse-overlayfs-0.4.1-1.module+el8.1.0+4081+b29780af.x86_64 21/25
Verifying : ostree-libs-2019.2-1.el8.x86_64 22/25
Verifying : container-selinux-2:2.107-2.module+el8.1.0+4081+b29780af.noarch 23/25
Verifying : criu-3.12-9.el8.x86_64 24/25
Verifying : containernetworking-plugins-0.8.1-2.module+el8.1.0+4081+b29780af.x86_64 25/25
Installed products updated.
Installed:
oci-umount-2:2.3.4-2.git87f9237.module+el8+2769+577ad176.x86_64 oci-systemd-hook-1:0.1.15-2.git2d0b8a3.module+el8+2769+577ad176.x86_64
slirp4netns-0.3.0-4.module+el8.1.0+4306+1d917805.x86_64 skopeo-1:0.1.37-5.module+el8.1.0+4240+893c1ab8.x86_64
podman-1.4.2-5.module+el8.1.0+4240+893c1ab8.x86_64 buildah-1.9.0-5.module+el8.1.0+4240+893c1ab8.x86_64
runc-1.0.0-60.rc8.module+el8.1.0+4081+b29780af.x86_64 fuse-overlayfs-0.4.1-1.module+el8.1.0+4081+b29780af.x86_64
container-selinux-2:2.107-2.module+el8.1.0+4081+b29780af.noarch containernetworking-plugins-0.8.1-2.module+el8.1.0+4081+b29780af.x86_64
libvarlink-18-3.el8.x86_64 fuse3-libs-3.2.1-12.el8.x86_64
python3-setools-4.2.2-1.el8.x86_64 python3-audit-3.0-0.13.20190507gitf58ec40.el8.x86_64
policycoreutils-python-utils-2.9-3.el8.noarch python3-policycoreutils-2.9-3.el8.noarch
checkpolicy-2.9-1.el8.x86_64 python3-libsemanage-2.9-1.el8.x86_64
libnet-1.1.6-15.el8.x86_64 yajl-2.1.0-10.el8.x86_64
protobuf-c-1.3.0-4.el8.x86_64 containers-common-1:0.1.37-5.module+el8.1.0+4240+893c1ab8.x86_64
podman-manpages-1.4.2-5.module+el8.1.0+4240+893c1ab8.noarch ostree-libs-2019.2-1.el8.x86_64
criu-3.12-9.el8.x86_64
Complete!
Podman is installed:
[egallen@lab0 ~]$ podman --version
podman version 1.4.2-stable2
Run the basic hello-world:
[egallen@lab0 ~]$ sudo podman run hello-world
Hello from Docker!
This message shows that your installation appears to be working correctly.
To generate this message, Docker took the following steps:
1. The Docker client contacted the Docker daemon.
2. The Docker daemon pulled the "hello-world" image from the Docker Hub.
(amd64)
3. The Docker daemon created a new container from that image which runs the
executable that produces the output you are currently reading.
4. The Docker daemon streamed that output to the Docker client, which sent it
to your terminal.
To try something more ambitious, you can run an Ubuntu container with:
$ docker run -it ubuntu bash
Share images, automate workflows, and more with a free Docker ID:
https://hub.docker.com/
For more examples and ideas, visit:
https://docs.docker.com/get-started/
Go to https://ngc.nvidia.com/catalog/containers/nvidia:cuda/tags to get a NGC registry CUDA tag, we can take 10.2-runtime-ubi8:
We need to enable the runtime hook, by default configuration containers cannot use the GPU:
[egallen@lab0 ~]$ sudo podman run --rm nvcr.io/nvidia/cuda:10.2-runtime-ubi8 nvidia-smi
Error: container_linux.go:345: starting container process caused "exec: \"nvidia-smi\": executable file not found in $PATH"
: OCI runtime error
Here we can download the nvidia-container-runtime https://nvidia.github.io/nvidia-container-runtime/.
Enable nvidia-container-runtime-hook repository:
[egallen@lab0 ~]$ distribution=$(. /etc/os-release;echo $ID$VERSION_ID)
[egallen@lab0 ~]$ echo $distribution
rhel8.1
[egallen@lab0 ~]$ curl -s -L https://nvidia.github.io/nvidia-container-runtime/$distribution/nvidia-container-runtime.repo | sudo tee /etc/yum.repos.d/nvidia-container-runtime.repo
[libnvidia-container]
name=libnvidia-container
baseurl=https://nvidia.github.io/libnvidia-container/centos7/$basearch
repo_gpgcheck=1
gpgcheck=0
enabled=1
gpgkey=https://nvidia.github.io/libnvidia-container/gpgkey
sslverify=1
sslcacert=/etc/pki/tls/certs/ca-bundle.crt
[nvidia-container-runtime]
name=nvidia-container-runtime
baseurl=https://nvidia.github.io/nvidia-container-runtime/centos7/$basearch
repo_gpgcheck=1
gpgcheck=0
enabled=1
gpgkey=https://nvidia.github.io/nvidia-container-runtime/gpgkey
sslverify=1
sslcacert=/etc/pki/tls/certs/ca-bundle.crt
Install NVIDIA container runtime hook:
[egallen@lab0 ~]$ sudo dnf install nvidia-container-runtime-hook
Updating Subscription Management repositories.
libnvidia-container
nvidia-container-runtime 21 kB/s | 11 kB 00:00
Dependencies resolved.
========================================================================================================================================================================================
Package Architecture Version Repository Size
========================================================================================================================================================================================
Installing:
nvidia-container-toolkit x86_64 1.0.5-2 nvidia-container-runtime 616 k
Installing dependencies:
libnvidia-container-tools x86_64 1.0.5-1 libnvidia-container 36 k
libnvidia-container1 x86_64 1.0.5-1 libnvidia-container 77 k
Transaction Summary
========================================================================================================================================================================================
Install 3 Packages
Total download size: 729 k
Installed size: 2.1 M
Is this ok [y/N]: y
Downloading Packages:
(1/3): libnvidia-container-tools-1.0.5-1.x86_64.rpm 120 kB/s | 36 kB 00:00
(2/3): libnvidia-container1-1.0.5-1.x86_64.rpm 230 kB/s | 77 kB 00:00
(3/3): nvidia-container-toolkit-1.0.5-2.x86_64.rpm 1.4 MB/s | 616 kB 00:00
----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
Total 1.7 MB/s | 729 kB 00:00
Running transaction check
Transaction check succeeded.
Running transaction test
Transaction test succeeded.
Running transaction
Preparing : 1/1
Installing : libnvidia-container1-1.0.5-1.x86_64 1/3
Running scriptlet: libnvidia-container1-1.0.5-1.x86_64 1/3
Installing : libnvidia-container-tools-1.0.5-1.x86_64 2/3
Installing : nvidia-container-toolkit-1.0.5-2.x86_64 3/3
Running scriptlet: nvidia-container-toolkit-1.0.5-2.x86_64 3/3
Verifying : libnvidia-container-tools-1.0.5-1.x86_64 1/3
Verifying : libnvidia-container1-1.0.5-1.x86_64 2/3
Verifying : nvidia-container-toolkit-1.0.5-2.x86_64 3/3
Installed products updated.
Installed:
nvidia-container-toolkit-1.0.5-2.x86_64 libnvidia-container-tools-1.0.5-1.x86_64 libnvidia-container1-1.0.5-1.x86_64
Complete!
Success podman is ready to run Artificial Intelligence and Machine Learning workloads:
[egallen@lab0 ~]$ sudo podman run --rm nvcr.io/nvidia/cuda:10.2-runtime-ubi8 nvidia-smi
Sun Dec 15 17:23:54 2019
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 440.33.01 Driver Version: 440.33.01 CUDA Version: 10.2 |
|-------------------------------+----------------------+----------------------+
| GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |
|===============================+======================+======================|
| 0 Tesla T4 Off | 00000000:01:00.0 Off | 0 |
| N/A 34C P0 16W / 70W | 0MiB / 15109MiB | 0% Default |
+-------------------------------+----------------------+----------------------+
+-----------------------------------------------------------------------------+
| Processes: GPU Memory |
| GPU PID Type Process name Usage |
|=============================================================================|
| No running processes found |
+-----------------------------------------------------------------------------+
NVIDIA Tesla T4 idle temperatures is at 34C with this motherboard and “custom” cooling.
[egallen@lab0 ~]$ sudo podman image ls -a
REPOSITORY TAG IMAGE ID CREATED SIZE
nvcr.io/nvidia/cuda 10.2-runtime-ubi8 7c056c682a7b 9 days ago 1.41 GB
docker.io/library/hello-world latest fce289e99eb9 11 months ago 6.14 kB
Try a TensorFlow run
Let’s make a burn with NGC TensorFlow 19.11.
Clone TensorFlow benchmarks:
[egallen@lab0 ~]$ sudo mkdir /data
[egallen@lab0 ~]$ sudo chown egallen:egallen /data
[egallen@lab0 data]$ cd /data
[egallen@lab0 data]$ git clone https://github.com/tensorflow/benchmarks.git
We can use NGC TensorFlow container from NVIDIA, we can pick the proper tag here, we will use 19.11-tf1-py3: https://ngc.nvidia.com/catalog/containers/nvidia:tensorflow
By default, tf_cnn_benchmarks will use all cores of all CPUs on the system if we pass –device=cpu (/cpu:0 represents all the CPUs). Run a Tensorflow benchmark with all the CPUs of the node:
[egallen@lab0 data]$ time sudo podman run --volume /data:/data -it nvcr.io/nvidia/tensorflow:19.11-tf1-py3 python3 /data/benchmarks/scripts/tf_cnn_benchmarks/tf_cnn_benchmarks.py --device=cpu --data_format=NHWC --batch_size=32 --model=resnet50 --variable_update=parameter_server
================
== TensorFlow ==
================
NVIDIA Release 19.11-tf1 (build 8788896)
TensorFlow Version 1.15.0
Container image Copyright (c) 2019, NVIDIA CORPORATION. All rights reserved.
Copyright 2017-2019 The TensorFlow Authors. All rights reserved.
Various files include modifications (c) NVIDIA CORPORATION. All rights reserved.
NVIDIA modifications are covered by the license terms that apply to the underlying project or file.
NOTE: MOFED driver for multi-node communication was not detected.
Multi-node communication performance may be reduced.
2019-12-16 08:39:35.105993: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.2
WARNING:tensorflow:
The TensorFlow contrib module will not be included in TensorFlow 2.0.
For more information, please see:
* https://github.com/tensorflow/community/blob/master/rfcs/20180907-contrib-sunset.md
* https://github.com/tensorflow/addons
* https://github.com/tensorflow/io (for I/O related ops)
If you depend on functionality not listed there, please file an issue.
WARNING:tensorflow:From /data/benchmarks/scripts/tf_cnn_benchmarks/models/mobilenet.py:388: The name tf.nn.avg_pool is deprecated. Please use tf.nn.avg_pool2d instead.
WARNING:tensorflow:From /data/benchmarks/scripts/tf_cnn_benchmarks/models/experimental/deepspeech.py:131: The name tf.nn.rnn_cell.RNNCell is deprecated. Please use tf.compat.v1.nn.rnn_cell.RNNCell instead.
WARNING:tensorflow:From /data/benchmarks/scripts/tf_cnn_benchmarks/benchmark_cnn.py:737: The name tf.ConfigProto is deprecated. Please use tf.compat.v1.ConfigProto instead.
W1216 08:39:36.597405 139914130491200 module_wrapper.py:139] From /data/benchmarks/scripts/tf_cnn_benchmarks/benchmark_cnn.py:737: The name tf.ConfigProto is deprecated. Please use tf.compat.v1.ConfigProto instead.
WARNING:tensorflow:From /data/benchmarks/scripts/tf_cnn_benchmarks/benchmark_cnn.py:3531: The name tf.Session is deprecated. Please use tf.compat.v1.Session instead.
W1216 08:39:36.597609 139914130491200 module_wrapper.py:139] From /data/benchmarks/scripts/tf_cnn_benchmarks/benchmark_cnn.py:3531: The name tf.Session is deprecated. Please use tf.compat.v1.Session instead.
2019-12-16 08:39:36.613408: I tensorflow/core/platform/profile_utils/cpu_utils.cc:94] CPU Frequency: 4200000000 Hz
2019-12-16 08:39:36.614010: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x5354b50 initialized for platform Host (this does not guarantee that XLA will be used). Devices:
2019-12-16 08:39:36.614021: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): Host, Default Version
2019-12-16 08:39:36.615399: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcuda.so.1
2019-12-16 08:39:37.126960: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:983] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2019-12-16 08:39:37.127440: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x5351ec0 initialized for platform CUDA (this does not guarantee that XLA will be used). Devices:
2019-12-16 08:39:37.127453: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): Tesla T4, Compute Capability 7.5
2019-12-16 08:39:37.127581: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:983] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2019-12-16 08:39:37.127966: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1618] Found device 0 with properties:
name: Tesla T4 major: 7 minor: 5 memoryClockRate(GHz): 1.59
pciBusID: 0000:01:00.0
2019-12-16 08:39:37.127984: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.2
2019-12-16 08:39:37.129228: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10
2019-12-16 08:39:37.130391: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10
2019-12-16 08:39:37.130592: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10
2019-12-16 08:39:37.131930: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10
2019-12-16 08:39:37.132681: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10
2019-12-16 08:39:37.135357: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7
2019-12-16 08:39:37.135466: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:983] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2019-12-16 08:39:37.135924: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:983] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2019-12-16 08:39:37.136349: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1746] Adding visible gpu devices: 0
2019-12-16 08:39:37.136384: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.2
2019-12-16 08:39:37.381441: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1159] Device interconnect StreamExecutor with strength 1 edge matrix:
2019-12-16 08:39:37.381481: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1165] 0
2019-12-16 08:39:37.381486: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1178] 0: N
2019-12-16 08:39:37.381642: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:983] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2019-12-16 08:39:37.382084: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:983] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2019-12-16 08:39:37.382488: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1304] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 14003 MB memory) -> physical GPU (device: 0, name: Tesla T4, pci bus id: 0000:01:00.0, compute capability: 7.5)
TensorFlow: 1.15
Model: resnet50
Dataset: imagenet (synthetic)
Mode: training
SingleSess: False
Batch size: 32 global
32 per device
Num batches: 100
Num epochs: 0.00
Devices: ['/cpu:0']
NUMA bind: False
Data format: NHWC
Optimizer: sgd
Variables: parameter_server
==========
WARNING:tensorflow:From /data/benchmarks/scripts/tf_cnn_benchmarks/benchmark_cnn.py:2790: The name tf.set_random_seed is deprecated. Please use tf.compat.v1.set_random_seed instead.
W1216 08:39:37.384276 139914130491200 module_wrapper.py:139] From /data/benchmarks/scripts/tf_cnn_benchmarks/benchmark_cnn.py:2790: The name tf.set_random_seed is deprecated. Please use tf.compat.v1.set_random_seed instead.
Generating training model
WARNING:tensorflow:From /data/benchmarks/scripts/tf_cnn_benchmarks/benchmark_cnn.py:2810: The name tf.train.get_or_create_global_step is deprecated. Please use tf.compat.v1.train.get_or_create_global_step instead.
W1216 08:39:37.384566 139914130491200 module_wrapper.py:139] From /data/benchmarks/scripts/tf_cnn_benchmarks/benchmark_cnn.py:2810: The name tf.train.get_or_create_global_step is deprecated. Please use tf.compat.v1.train.get_or_create_global_step instead.
WARNING:tensorflow:From /data/benchmarks/scripts/tf_cnn_benchmarks/variable_mgr.py:220: The name tf.variable_scope is deprecated. Please use tf.compat.v1.variable_scope instead.
W1216 08:39:37.388102 139914130491200 module_wrapper.py:139] From /data/benchmarks/scripts/tf_cnn_benchmarks/variable_mgr.py:220: The name tf.variable_scope is deprecated. Please use tf.compat.v1.variable_scope instead.
WARNING:tensorflow:From /data/benchmarks/scripts/tf_cnn_benchmarks/models/model.py:245: The name tf.truncated_normal is deprecated. Please use tf.random.truncated_normal instead.
W1216 08:39:37.388331 139914130491200 module_wrapper.py:139] From /data/benchmarks/scripts/tf_cnn_benchmarks/models/model.py:245: The name tf.truncated_normal is deprecated. Please use tf.random.truncated_normal instead.
WARNING:tensorflow:From /data/benchmarks/scripts/tf_cnn_benchmarks/models/model.py:252: The name tf.random_uniform is deprecated. Please use tf.random.uniform instead.
W1216 08:39:37.392255 139914130491200 module_wrapper.py:139] From /data/benchmarks/scripts/tf_cnn_benchmarks/models/model.py:252: The name tf.random_uniform is deprecated. Please use tf.random.uniform instead.
WARNING:tensorflow:From /data/benchmarks/scripts/tf_cnn_benchmarks/convnet_builder.py:129: conv2d (from tensorflow.python.layers.convolutional) is deprecated and will be removed in a future version.
Instructions for updating:
Use `tf.keras.layers.Conv2D` instead.
W1216 08:39:37.396633 139914130491200 deprecation.py:323] From /data/benchmarks/scripts/tf_cnn_benchmarks/convnet_builder.py:129: conv2d (from tensorflow.python.layers.convolutional) is deprecated and will be removed in a future version.
Instructions for updating:
Use `tf.keras.layers.Conv2D` instead.
WARNING:tensorflow:From /usr/local/lib/python3.6/dist-packages/tensorflow_core/python/layers/convolutional.py:424: Layer.apply (from tensorflow.python.keras.engine.base_layer) is deprecated and will be removed in a future version.
Instructions for updating:
Please use `layer.__call__` method instead.
W1216 08:39:37.397571 139914130491200 deprecation.py:323] From /usr/local/lib/python3.6/dist-packages/tensorflow_core/python/layers/convolutional.py:424: Layer.apply (from tensorflow.python.keras.engine.base_layer) is deprecated and will be removed in a future version.
Instructions for updating:
Please use `layer.__call__` method instead.
WARNING:tensorflow:From /data/benchmarks/scripts/tf_cnn_benchmarks/convnet_builder.py:261: max_pooling2d (from tensorflow.python.layers.pooling) is deprecated and will be removed in a future version.
Instructions for updating:
Use keras.layers.MaxPooling2D instead.
W1216 08:39:37.424758 139914130491200 deprecation.py:323] From /data/benchmarks/scripts/tf_cnn_benchmarks/convnet_builder.py:261: max_pooling2d (from tensorflow.python.layers.pooling) is deprecated and will be removed in a future version.
Instructions for updating:
Use keras.layers.MaxPooling2D instead.
WARNING:tensorflow:From /data/benchmarks/scripts/tf_cnn_benchmarks/convnet_builder.py:120: The name tf.get_variable is deprecated. Please use tf.compat.v1.get_variable instead.
W1216 08:39:38.709852 139914130491200 module_wrapper.py:139] From /data/benchmarks/scripts/tf_cnn_benchmarks/convnet_builder.py:120: The name tf.get_variable is deprecated. Please use tf.compat.v1.get_variable instead.
WARNING:tensorflow:From /data/benchmarks/scripts/tf_cnn_benchmarks/convnet_builder.py:334: The name tf.nn.xw_plus_b is deprecated. Please use tf.compat.v1.nn.xw_plus_b instead.
W1216 08:39:38.716611 139914130491200 module_wrapper.py:139] From /data/benchmarks/scripts/tf_cnn_benchmarks/convnet_builder.py:334: The name tf.nn.xw_plus_b is deprecated. Please use tf.compat.v1.nn.xw_plus_b instead.
WARNING:tensorflow:From /data/benchmarks/scripts/tf_cnn_benchmarks/models/model.py:319: The name tf.losses.sparse_softmax_cross_entropy is deprecated. Please use tf.compat.v1.losses.sparse_softmax_cross_entropy instead.
W1216 08:39:38.717865 139914130491200 module_wrapper.py:139] From /data/benchmarks/scripts/tf_cnn_benchmarks/models/model.py:319: The name tf.losses.sparse_softmax_cross_entropy is deprecated. Please use tf.compat.v1.losses.sparse_softmax_cross_entropy instead.
WARNING:tensorflow:From /usr/local/lib/python3.6/dist-packages/tensorflow_core/python/ops/losses/losses_impl.py:121: where (from tensorflow.python.ops.array_ops) is deprecated and will be removed in a future version.
Instructions for updating:
Use tf.where in 2.0, which has the same broadcast rule as np.where
W1216 08:39:38.724012 139914130491200 deprecation.py:323] From /usr/local/lib/python3.6/dist-packages/tensorflow_core/python/ops/losses/losses_impl.py:121: where (from tensorflow.python.ops.array_ops) is deprecated and will be removed in a future version.
Instructions for updating:
Use tf.where in 2.0, which has the same broadcast rule as np.where
WARNING:tensorflow:From /data/benchmarks/scripts/tf_cnn_benchmarks/variable_mgr.py:147: The name tf.trainable_variables is deprecated. Please use tf.compat.v1.trainable_variables instead.
W1216 08:39:38.730463 139914130491200 module_wrapper.py:139] From /data/benchmarks/scripts/tf_cnn_benchmarks/variable_mgr.py:147: The name tf.trainable_variables is deprecated. Please use tf.compat.v1.trainable_variables instead.
WARNING:tensorflow:From /data/benchmarks/scripts/tf_cnn_benchmarks/benchmark_cnn.py:2856: The name tf.get_collection is deprecated. Please use tf.compat.v1.get_collection instead.
W1216 08:39:39.126976 139914130491200 module_wrapper.py:139] From /data/benchmarks/scripts/tf_cnn_benchmarks/benchmark_cnn.py:2856: The name tf.get_collection is deprecated. Please use tf.compat.v1.get_collection instead.
WARNING:tensorflow:From /data/benchmarks/scripts/tf_cnn_benchmarks/benchmark_cnn.py:2856: The name tf.GraphKeys is deprecated. Please use tf.compat.v1.GraphKeys instead.
W1216 08:39:39.127145 139914130491200 module_wrapper.py:139] From /data/benchmarks/scripts/tf_cnn_benchmarks/benchmark_cnn.py:2856: The name tf.GraphKeys is deprecated. Please use tf.compat.v1.GraphKeys instead.
WARNING:tensorflow:From /data/benchmarks/scripts/tf_cnn_benchmarks/models/resnet_model.py:333: The name tf.train.piecewise_constant is deprecated. Please use tf.compat.v1.train.piecewise_constant instead.
W1216 08:39:39.138721 139914130491200 module_wrapper.py:139] From /data/benchmarks/scripts/tf_cnn_benchmarks/models/resnet_model.py:333: The name tf.train.piecewise_constant is deprecated. Please use tf.compat.v1.train.piecewise_constant instead.
WARNING:tensorflow:From /data/benchmarks/scripts/tf_cnn_benchmarks/benchmark_cnn.py:1237: The name tf.train.GradientDescentOptimizer is deprecated. Please use tf.compat.v1.train.GradientDescentOptimizer instead.
W1216 08:39:39.185851 139914130491200 module_wrapper.py:139] From /data/benchmarks/scripts/tf_cnn_benchmarks/benchmark_cnn.py:1237: The name tf.train.GradientDescentOptimizer is deprecated. Please use tf.compat.v1.train.GradientDescentOptimizer instead.
WARNING:tensorflow:From /data/benchmarks/scripts/tf_cnn_benchmarks/benchmark_cnn.py:2118: The name tf.train.get_global_step is deprecated. Please use tf.compat.v1.train.get_global_step instead.
W1216 08:39:39.276628 139914130491200 module_wrapper.py:139] From /data/benchmarks/scripts/tf_cnn_benchmarks/benchmark_cnn.py:2118: The name tf.train.get_global_step is deprecated. Please use tf.compat.v1.train.get_global_step instead.
WARNING:tensorflow:From /data/benchmarks/scripts/tf_cnn_benchmarks/benchmark_cnn.py:2136: The name tf.local_variables_initializer is deprecated. Please use tf.compat.v1.local_variables_initializer instead.
W1216 08:39:39.277722 139914130491200 module_wrapper.py:139] From /data/benchmarks/scripts/tf_cnn_benchmarks/benchmark_cnn.py:2136: The name tf.local_variables_initializer is deprecated. Please use tf.compat.v1.local_variables_initializer instead.
WARNING:tensorflow:From /data/benchmarks/scripts/tf_cnn_benchmarks/benchmark_cnn.py:2137: The name tf.tables_initializer is deprecated. Please use tf.compat.v1.tables_initializer instead.
W1216 08:39:39.278185 139914130491200 module_wrapper.py:139] From /data/benchmarks/scripts/tf_cnn_benchmarks/benchmark_cnn.py:2137: The name tf.tables_initializer is deprecated. Please use tf.compat.v1.tables_initializer instead.
WARNING:tensorflow:From /data/benchmarks/scripts/tf_cnn_benchmarks/benchmark_cnn.py:2154: The name tf.summary.merge_all is deprecated. Please use tf.compat.v1.summary.merge_all instead.
W1216 08:39:39.279364 139914130491200 module_wrapper.py:139] From /data/benchmarks/scripts/tf_cnn_benchmarks/benchmark_cnn.py:2154: The name tf.summary.merge_all is deprecated. Please use tf.compat.v1.summary.merge_all instead.
Initializing graph
WARNING:tensorflow:From /data/benchmarks/scripts/tf_cnn_benchmarks/benchmark_cnn.py:2211: The name tf.train.Saver is deprecated. Please use tf.compat.v1.train.Saver instead.
W1216 08:39:39.279520 139914130491200 module_wrapper.py:139] From /data/benchmarks/scripts/tf_cnn_benchmarks/benchmark_cnn.py:2211: The name tf.train.Saver is deprecated. Please use tf.compat.v1.train.Saver instead.
WARNING:tensorflow:From /data/benchmarks/scripts/tf_cnn_benchmarks/variable_mgr.py:124: The name tf.global_variables is deprecated. Please use tf.compat.v1.global_variables instead.
W1216 08:39:39.279612 139914130491200 module_wrapper.py:139] From /data/benchmarks/scripts/tf_cnn_benchmarks/variable_mgr.py:124: The name tf.global_variables is deprecated. Please use tf.compat.v1.global_variables instead.
WARNING:tensorflow:From /data/benchmarks/scripts/tf_cnn_benchmarks/benchmark_cnn.py:2240: The name tf.RunOptions is deprecated. Please use tf.compat.v1.RunOptions instead.
W1216 08:39:39.472222 139914130491200 module_wrapper.py:139] From /data/benchmarks/scripts/tf_cnn_benchmarks/benchmark_cnn.py:2240: The name tf.RunOptions is deprecated. Please use tf.compat.v1.RunOptions instead.
WARNING:tensorflow:From /data/benchmarks/scripts/tf_cnn_benchmarks/benchmark_cnn.py:2266: Supervisor.__init__ (from tensorflow.python.training.supervisor) is deprecated and will be removed in a future version.
Instructions for updating:
Please switch to tf.train.MonitoredTrainingSession
W1216 08:39:39.472406 139914130491200 deprecation.py:323] From /data/benchmarks/scripts/tf_cnn_benchmarks/benchmark_cnn.py:2266: Supervisor.__init__ (from tensorflow.python.training.supervisor) is deprecated and will be removed in a future version.
Instructions for updating:
Please switch to tf.train.MonitoredTrainingSession
2019-12-16 08:39:39.766808: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:983] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2019-12-16 08:39:39.767298: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1618] Found device 0 with properties:
name: Tesla T4 major: 7 minor: 5 memoryClockRate(GHz): 1.59
pciBusID: 0000:01:00.0
2019-12-16 08:39:39.767335: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.2
2019-12-16 08:39:39.767361: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10
2019-12-16 08:39:39.767371: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10
2019-12-16 08:39:39.767380: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10
2019-12-16 08:39:39.767390: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10
2019-12-16 08:39:39.767400: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10
2019-12-16 08:39:39.767409: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7
2019-12-16 08:39:39.767457: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:983] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2019-12-16 08:39:39.767876: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:983] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2019-12-16 08:39:39.768243: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1746] Adding visible gpu devices: 0
2019-12-16 08:39:39.768261: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1159] Device interconnect StreamExecutor with strength 1 edge matrix:
2019-12-16 08:39:39.768266: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1165] 0
2019-12-16 08:39:39.768270: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1178] 0: N
2019-12-16 08:39:39.768324: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:983] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2019-12-16 08:39:39.768725: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:983] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2019-12-16 08:39:39.769103: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1304] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 14003 MB memory) -> physical GPU (device: 0, name: Tesla T4, pci bus id: 0000:01:00.0, compute capability: 7.5)
INFO:tensorflow:Running local_init_op.
I1216 08:39:40.219716 139914130491200 session_manager.py:500] Running local_init_op.
INFO:tensorflow:Done running local_init_op.
I1216 08:39:40.284223 139914130491200 session_manager.py:502] Done running local_init_op.
Running warm up
Done warm up
Step Img/sec total_loss
1 images/sec: 7.0 +/- 0.0 (jitter = 0.0) 8.108
10 images/sec: 7.1 +/- 0.0 (jitter = 0.0) 8.122
20 images/sec: 7.1 +/- 0.0 (jitter = 0.0) 7.983
30 images/sec: 7.1 +/- 0.0 (jitter = 0.0) 7.780
40 images/sec: 7.1 +/- 0.0 (jitter = 0.0) 7.848
50 images/sec: 7.1 +/- 0.0 (jitter = 0.0) 7.779
60 images/sec: 7.1 +/- 0.0 (jitter = 0.0) 7.825
70 images/sec: 7.1 +/- 0.0 (jitter = 0.0) 7.839
80 images/sec: 7.1 +/- 0.0 (jitter = 0.0) 7.817
90 images/sec: 7.1 +/- 0.0 (jitter = 0.0) 7.647
100 images/sec: 7.1 +/- 0.0 (jitter = 0.0) 7.915
----------------------------------------------------------------
total images/sec: 7.07
----------------------------------------------------------------
real 8m28.115s
user 0m0.138s
sys 0m0.053s
Run a Tensorflow benchmark with the NVIDIA T4 GPU:
[egallen@lab0 data]$ time sudo podman run --volume /data:/data -it nvcr.io/nvidia/tensorflow:19.11-tf1-py3 python3 /data/benchmarks/scripts/tf_cnn_benchmarks/tf_cnn_benchmarks.py --num_gpus=1 --data_format=NHWC --batch_size=32 --model=resnet50 --variable_update=parameter_server
================
== TensorFlow ==
================
NVIDIA Release 19.11-tf1 (build 8788896)
TensorFlow Version 1.15.0
Container image Copyright (c) 2019, NVIDIA CORPORATION. All rights reserved.
Copyright 2017-2019 The TensorFlow Authors. All rights reserved.
Various files include modifications (c) NVIDIA CORPORATION. All rights reserved.
NVIDIA modifications are covered by the license terms that apply to the underlying project or file.
NOTE: MOFED driver for multi-node communication was not detected.
Multi-node communication performance may be reduced.
2019-12-16 08:48:38.144025: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.2
WARNING:tensorflow:
The TensorFlow contrib module will not be included in TensorFlow 2.0.
For more information, please see:
* https://github.com/tensorflow/community/blob/master/rfcs/20180907-contrib-sunset.md
* https://github.com/tensorflow/addons
* https://github.com/tensorflow/io (for I/O related ops)
If you depend on functionality not listed there, please file an issue.
WARNING:tensorflow:From /data/benchmarks/scripts/tf_cnn_benchmarks/models/mobilenet.py:388: The name tf.nn.avg_pool is deprecated. Please use tf.nn.avg_pool2d instead.
WARNING:tensorflow:From /data/benchmarks/scripts/tf_cnn_benchmarks/models/experimental/deepspeech.py:131: The name tf.nn.rnn_cell.RNNCell is deprecated. Please use tf.compat.v1.nn.rnn_cell.RNNCell instead.
WARNING:tensorflow:From /data/benchmarks/scripts/tf_cnn_benchmarks/benchmark_cnn.py:737: The name tf.ConfigProto is deprecated. Please use tf.compat.v1.ConfigProto instead.
W1216 08:48:39.634068 140512265873216 module_wrapper.py:139] From /data/benchmarks/scripts/tf_cnn_benchmarks/benchmark_cnn.py:737: The name tf.ConfigProto is deprecated. Please use tf.compat.v1.ConfigProto instead.
WARNING:tensorflow:From /data/benchmarks/scripts/tf_cnn_benchmarks/benchmark_cnn.py:3531: The name tf.Session is deprecated. Please use tf.compat.v1.Session instead.
W1216 08:48:39.634273 140512265873216 module_wrapper.py:139] From /data/benchmarks/scripts/tf_cnn_benchmarks/benchmark_cnn.py:3531: The name tf.Session is deprecated. Please use tf.compat.v1.Session instead.
2019-12-16 08:48:39.650397: I tensorflow/core/platform/profile_utils/cpu_utils.cc:94] CPU Frequency: 4200000000 Hz
2019-12-16 08:48:39.650516: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x668bd40 initialized for platform Host (this does not guarantee that XLA will be used). Devices:
2019-12-16 08:48:39.650528: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): Host, Default Version
2019-12-16 08:48:39.652025: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcuda.so.1
2019-12-16 08:48:40.161619: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:983] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2019-12-16 08:48:40.162131: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x6621540 initialized for platform CUDA (this does not guarantee that XLA will be used). Devices:
2019-12-16 08:48:40.162144: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): Tesla T4, Compute Capability 7.5
2019-12-16 08:48:40.162267: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:983] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2019-12-16 08:48:40.162643: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1618] Found device 0 with properties:
name: Tesla T4 major: 7 minor: 5 memoryClockRate(GHz): 1.59
pciBusID: 0000:01:00.0
2019-12-16 08:48:40.162676: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.2
2019-12-16 08:48:40.163811: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10
2019-12-16 08:48:40.164897: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10
2019-12-16 08:48:40.165091: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10
2019-12-16 08:48:40.166297: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10
2019-12-16 08:48:40.166939: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10
2019-12-16 08:48:40.169549: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7
2019-12-16 08:48:40.169658: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:983] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2019-12-16 08:48:40.170087: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:983] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2019-12-16 08:48:40.170456: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1746] Adding visible gpu devices: 0
2019-12-16 08:48:40.170493: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.2
2019-12-16 08:48:40.406276: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1159] Device interconnect StreamExecutor with strength 1 edge matrix:
2019-12-16 08:48:40.406318: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1165] 0
2019-12-16 08:48:40.406324: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1178] 0: N
2019-12-16 08:48:40.406519: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:983] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2019-12-16 08:48:40.406954: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:983] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2019-12-16 08:48:40.407409: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1304] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 14003 MB memory) -> physical GPU (device: 0, name: Tesla T4, pci bus id: 0000:01:00.0, compute capability: 7.5)
TensorFlow: 1.15
Model: resnet50
Dataset: imagenet (synthetic)
Mode: training
SingleSess: False
Batch size: 32 global
32 per device
Num batches: 100
Num epochs: 0.00
Devices: ['/gpu:0']
NUMA bind: False
Data format: NHWC
Optimizer: sgd
Variables: parameter_server
==========
WARNING:tensorflow:From /data/benchmarks/scripts/tf_cnn_benchmarks/benchmark_cnn.py:2790: The name tf.set_random_seed is deprecated. Please use tf.compat.v1.set_random_seed instead.
W1216 08:48:40.409432 140512265873216 module_wrapper.py:139] From /data/benchmarks/scripts/tf_cnn_benchmarks/benchmark_cnn.py:2790: The name tf.set_random_seed is deprecated. Please use tf.compat.v1.set_random_seed instead.
Generating training model
WARNING:tensorflow:From /data/benchmarks/scripts/tf_cnn_benchmarks/benchmark_cnn.py:2810: The name tf.train.get_or_create_global_step is deprecated. Please use tf.compat.v1.train.get_or_create_global_step instead.
W1216 08:48:40.409716 140512265873216 module_wrapper.py:139] From /data/benchmarks/scripts/tf_cnn_benchmarks/benchmark_cnn.py:2810: The name tf.train.get_or_create_global_step is deprecated. Please use tf.compat.v1.train.get_or_create_global_step instead.
WARNING:tensorflow:From /data/benchmarks/scripts/tf_cnn_benchmarks/variable_mgr.py:220: The name tf.variable_scope is deprecated. Please use tf.compat.v1.variable_scope instead.
W1216 08:48:40.413261 140512265873216 module_wrapper.py:139] From /data/benchmarks/scripts/tf_cnn_benchmarks/variable_mgr.py:220: The name tf.variable_scope is deprecated. Please use tf.compat.v1.variable_scope instead.
WARNING:tensorflow:From /data/benchmarks/scripts/tf_cnn_benchmarks/models/model.py:245: The name tf.truncated_normal is deprecated. Please use tf.random.truncated_normal instead.
W1216 08:48:40.413505 140512265873216 module_wrapper.py:139] From /data/benchmarks/scripts/tf_cnn_benchmarks/models/model.py:245: The name tf.truncated_normal is deprecated. Please use tf.random.truncated_normal instead.
WARNING:tensorflow:From /data/benchmarks/scripts/tf_cnn_benchmarks/models/model.py:252: The name tf.random_uniform is deprecated. Please use tf.random.uniform instead.
W1216 08:48:40.417449 140512265873216 module_wrapper.py:139] From /data/benchmarks/scripts/tf_cnn_benchmarks/models/model.py:252: The name tf.random_uniform is deprecated. Please use tf.random.uniform instead.
WARNING:tensorflow:From /data/benchmarks/scripts/tf_cnn_benchmarks/convnet_builder.py:129: conv2d (from tensorflow.python.layers.convolutional) is deprecated and will be removed in a future version.
Instructions for updating:
Use `tf.keras.layers.Conv2D` instead.
W1216 08:48:40.421849 140512265873216 deprecation.py:323] From /data/benchmarks/scripts/tf_cnn_benchmarks/convnet_builder.py:129: conv2d (from tensorflow.python.layers.convolutional) is deprecated and will be removed in a future version.
Instructions for updating:
Use `tf.keras.layers.Conv2D` instead.
WARNING:tensorflow:From /usr/local/lib/python3.6/dist-packages/tensorflow_core/python/layers/convolutional.py:424: Layer.apply (from tensorflow.python.keras.engine.base_layer) is deprecated and will be removed in a future version.
Instructions for updating:
Please use `layer.__call__` method instead.
W1216 08:48:40.422837 140512265873216 deprecation.py:323] From /usr/local/lib/python3.6/dist-packages/tensorflow_core/python/layers/convolutional.py:424: Layer.apply (from tensorflow.python.keras.engine.base_layer) is deprecated and will be removed in a future version.
Instructions for updating:
Please use `layer.__call__` method instead.
WARNING:tensorflow:From /data/benchmarks/scripts/tf_cnn_benchmarks/convnet_builder.py:261: max_pooling2d (from tensorflow.python.layers.pooling) is deprecated and will be removed in a future version.
Instructions for updating:
Use keras.layers.MaxPooling2D instead.
W1216 08:48:40.449749 140512265873216 deprecation.py:323] From /data/benchmarks/scripts/tf_cnn_benchmarks/convnet_builder.py:261: max_pooling2d (from tensorflow.python.layers.pooling) is deprecated and will be removed in a future version.
Instructions for updating:
Use keras.layers.MaxPooling2D instead.
WARNING:tensorflow:From /data/benchmarks/scripts/tf_cnn_benchmarks/convnet_builder.py:120: The name tf.get_variable is deprecated. Please use tf.compat.v1.get_variable instead.
W1216 08:48:41.724167 140512265873216 module_wrapper.py:139] From /data/benchmarks/scripts/tf_cnn_benchmarks/convnet_builder.py:120: The name tf.get_variable is deprecated. Please use tf.compat.v1.get_variable instead.
WARNING:tensorflow:From /data/benchmarks/scripts/tf_cnn_benchmarks/convnet_builder.py:334: The name tf.nn.xw_plus_b is deprecated. Please use tf.compat.v1.nn.xw_plus_b instead.
W1216 08:48:41.730736 140512265873216 module_wrapper.py:139] From /data/benchmarks/scripts/tf_cnn_benchmarks/convnet_builder.py:334: The name tf.nn.xw_plus_b is deprecated. Please use tf.compat.v1.nn.xw_plus_b instead.
WARNING:tensorflow:From /data/benchmarks/scripts/tf_cnn_benchmarks/models/model.py:319: The name tf.losses.sparse_softmax_cross_entropy is deprecated. Please use tf.compat.v1.losses.sparse_softmax_cross_entropy instead.
W1216 08:48:41.731995 140512265873216 module_wrapper.py:139] From /data/benchmarks/scripts/tf_cnn_benchmarks/models/model.py:319: The name tf.losses.sparse_softmax_cross_entropy is deprecated. Please use tf.compat.v1.losses.sparse_softmax_cross_entropy instead.
WARNING:tensorflow:From /usr/local/lib/python3.6/dist-packages/tensorflow_core/python/ops/losses/losses_impl.py:121: where (from tensorflow.python.ops.array_ops) is deprecated and will be removed in a future version.
Instructions for updating:
Use tf.where in 2.0, which has the same broadcast rule as np.where
W1216 08:48:41.738033 140512265873216 deprecation.py:323] From /usr/local/lib/python3.6/dist-packages/tensorflow_core/python/ops/losses/losses_impl.py:121: where (from tensorflow.python.ops.array_ops) is deprecated and will be removed in a future version.
Instructions for updating:
Use tf.where in 2.0, which has the same broadcast rule as np.where
WARNING:tensorflow:From /data/benchmarks/scripts/tf_cnn_benchmarks/variable_mgr.py:147: The name tf.trainable_variables is deprecated. Please use tf.compat.v1.trainable_variables instead.
W1216 08:48:41.744416 140512265873216 module_wrapper.py:139] From /data/benchmarks/scripts/tf_cnn_benchmarks/variable_mgr.py:147: The name tf.trainable_variables is deprecated. Please use tf.compat.v1.trainable_variables instead.
WARNING:tensorflow:From /data/benchmarks/scripts/tf_cnn_benchmarks/benchmark_cnn.py:2856: The name tf.get_collection is deprecated. Please use tf.compat.v1.get_collection instead.
W1216 08:48:42.137453 140512265873216 module_wrapper.py:139] From /data/benchmarks/scripts/tf_cnn_benchmarks/benchmark_cnn.py:2856: The name tf.get_collection is deprecated. Please use tf.compat.v1.get_collection instead.
WARNING:tensorflow:From /data/benchmarks/scripts/tf_cnn_benchmarks/benchmark_cnn.py:2856: The name tf.GraphKeys is deprecated. Please use tf.compat.v1.GraphKeys instead.
W1216 08:48:42.137614 140512265873216 module_wrapper.py:139] From /data/benchmarks/scripts/tf_cnn_benchmarks/benchmark_cnn.py:2856: The name tf.GraphKeys is deprecated. Please use tf.compat.v1.GraphKeys instead.
WARNING:tensorflow:From /data/benchmarks/scripts/tf_cnn_benchmarks/models/resnet_model.py:333: The name tf.train.piecewise_constant is deprecated. Please use tf.compat.v1.train.piecewise_constant instead.
W1216 08:48:42.149061 140512265873216 module_wrapper.py:139] From /data/benchmarks/scripts/tf_cnn_benchmarks/models/resnet_model.py:333: The name tf.train.piecewise_constant is deprecated. Please use tf.compat.v1.train.piecewise_constant instead.
WARNING:tensorflow:From /data/benchmarks/scripts/tf_cnn_benchmarks/benchmark_cnn.py:1237: The name tf.train.GradientDescentOptimizer is deprecated. Please use tf.compat.v1.train.GradientDescentOptimizer instead.
W1216 08:48:42.195959 140512265873216 module_wrapper.py:139] From /data/benchmarks/scripts/tf_cnn_benchmarks/benchmark_cnn.py:1237: The name tf.train.GradientDescentOptimizer is deprecated. Please use tf.compat.v1.train.GradientDescentOptimizer instead.
WARNING:tensorflow:From /data/benchmarks/scripts/tf_cnn_benchmarks/benchmark_cnn.py:2118: The name tf.train.get_global_step is deprecated. Please use tf.compat.v1.train.get_global_step instead.
W1216 08:48:42.286501 140512265873216 module_wrapper.py:139] From /data/benchmarks/scripts/tf_cnn_benchmarks/benchmark_cnn.py:2118: The name tf.train.get_global_step is deprecated. Please use tf.compat.v1.train.get_global_step instead.
WARNING:tensorflow:From /data/benchmarks/scripts/tf_cnn_benchmarks/benchmark_cnn.py:2136: The name tf.local_variables_initializer is deprecated. Please use tf.compat.v1.local_variables_initializer instead.
W1216 08:48:42.287627 140512265873216 module_wrapper.py:139] From /data/benchmarks/scripts/tf_cnn_benchmarks/benchmark_cnn.py:2136: The name tf.local_variables_initializer is deprecated. Please use tf.compat.v1.local_variables_initializer instead.
WARNING:tensorflow:From /data/benchmarks/scripts/tf_cnn_benchmarks/benchmark_cnn.py:2137: The name tf.tables_initializer is deprecated. Please use tf.compat.v1.tables_initializer instead.
W1216 08:48:42.288069 140512265873216 module_wrapper.py:139] From /data/benchmarks/scripts/tf_cnn_benchmarks/benchmark_cnn.py:2137: The name tf.tables_initializer is deprecated. Please use tf.compat.v1.tables_initializer instead.
WARNING:tensorflow:From /data/benchmarks/scripts/tf_cnn_benchmarks/benchmark_cnn.py:2154: The name tf.summary.merge_all is deprecated. Please use tf.compat.v1.summary.merge_all instead.
W1216 08:48:42.289203 140512265873216 module_wrapper.py:139] From /data/benchmarks/scripts/tf_cnn_benchmarks/benchmark_cnn.py:2154: The name tf.summary.merge_all is deprecated. Please use tf.compat.v1.summary.merge_all instead.
Initializing graph
WARNING:tensorflow:From /data/benchmarks/scripts/tf_cnn_benchmarks/benchmark_cnn.py:2211: The name tf.train.Saver is deprecated. Please use tf.compat.v1.train.Saver instead.
W1216 08:48:42.289375 140512265873216 module_wrapper.py:139] From /data/benchmarks/scripts/tf_cnn_benchmarks/benchmark_cnn.py:2211: The name tf.train.Saver is deprecated. Please use tf.compat.v1.train.Saver instead.
WARNING:tensorflow:From /data/benchmarks/scripts/tf_cnn_benchmarks/variable_mgr.py:124: The name tf.global_variables is deprecated. Please use tf.compat.v1.global_variables instead.
W1216 08:48:42.289470 140512265873216 module_wrapper.py:139] From /data/benchmarks/scripts/tf_cnn_benchmarks/variable_mgr.py:124: The name tf.global_variables is deprecated. Please use tf.compat.v1.global_variables instead.
WARNING:tensorflow:From /data/benchmarks/scripts/tf_cnn_benchmarks/benchmark_cnn.py:2240: The name tf.RunOptions is deprecated. Please use tf.compat.v1.RunOptions instead.
W1216 08:48:42.481318 140512265873216 module_wrapper.py:139] From /data/benchmarks/scripts/tf_cnn_benchmarks/benchmark_cnn.py:2240: The name tf.RunOptions is deprecated. Please use tf.compat.v1.RunOptions instead.
WARNING:tensorflow:From /data/benchmarks/scripts/tf_cnn_benchmarks/benchmark_cnn.py:2266: Supervisor.__init__ (from tensorflow.python.training.supervisor) is deprecated and will be removed in a future version.
Instructions for updating:
Please switch to tf.train.MonitoredTrainingSession
W1216 08:48:42.481497 140512265873216 deprecation.py:323] From /data/benchmarks/scripts/tf_cnn_benchmarks/benchmark_cnn.py:2266: Supervisor.__init__ (from tensorflow.python.training.supervisor) is deprecated and will be removed in a future version.
Instructions for updating:
Please switch to tf.train.MonitoredTrainingSession
2019-12-16 08:48:42.773993: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:983] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2019-12-16 08:48:42.774456: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1618] Found device 0 with properties:
name: Tesla T4 major: 7 minor: 5 memoryClockRate(GHz): 1.59
pciBusID: 0000:01:00.0
2019-12-16 08:48:42.774492: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.2
2019-12-16 08:48:42.774519: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10
2019-12-16 08:48:42.774531: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10
2019-12-16 08:48:42.774542: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10
2019-12-16 08:48:42.774554: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10
2019-12-16 08:48:42.774566: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10
2019-12-16 08:48:42.774581: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7
2019-12-16 08:48:42.774626: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:983] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2019-12-16 08:48:42.775016: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:983] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2019-12-16 08:48:42.775376: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1746] Adding visible gpu devices: 0
2019-12-16 08:48:42.775396: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1159] Device interconnect StreamExecutor with strength 1 edge matrix:
2019-12-16 08:48:42.775402: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1165] 0
2019-12-16 08:48:42.775406: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1178] 0: N
2019-12-16 08:48:42.775462: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:983] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2019-12-16 08:48:42.775846: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:983] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2019-12-16 08:48:42.776215: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1304] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 14003 MB memory) -> physical GPU (device: 0, name: Tesla T4, pci bus id: 0000:01:00.0, compute capability: 7.5)
INFO:tensorflow:Running local_init_op.
I1216 08:48:43.191928 140512265873216 session_manager.py:500] Running local_init_op.
INFO:tensorflow:Done running local_init_op.
I1216 08:48:43.237993 140512265873216 session_manager.py:502] Done running local_init_op.
Running warm up
2019-12-16 08:48:44.315112: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10
2019-12-16 08:48:44.468980: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7
Done warm up
Step Img/sec total_loss
1 images/sec: 125.5 +/- 0.0 (jitter = 0.0) 8.108
10 images/sec: 123.5 +/- 0.3 (jitter = 0.9) 8.122
20 images/sec: 123.4 +/- 0.2 (jitter = 1.0) 7.983
30 images/sec: 123.2 +/- 0.2 (jitter = 0.8) 7.780
40 images/sec: 123.2 +/- 0.1 (jitter = 0.6) 7.849
50 images/sec: 123.0 +/- 0.1 (jitter = 0.7) 7.779
60 images/sec: 122.9 +/- 0.1 (jitter = 0.7) 7.825
70 images/sec: 122.9 +/- 0.1 (jitter = 0.6) 7.839
80 images/sec: 122.8 +/- 0.1 (jitter = 0.6) 7.818
90 images/sec: 122.7 +/- 0.1 (jitter = 0.7) 7.646
100 images/sec: 122.7 +/- 0.1 (jitter = 0.8) 7.915
----------------------------------------------------------------
total images/sec: 122.65
----------------------------------------------------------------
real 0m44.495s
user 0m0.115s
sys 0m0.046s
Here are the overall benchmarks results between CPU and GPU for:
- model: resnet50
- dataset: imagenet (synthetic)
- mode: training
| Device type | Total run time (minutes) | Total run time (seconds) | Images/sec |
|---|---|---|---|
| CPU | 8m28.115s | 44.4 | 7.07 |
| GPU | 0m44.495s | 508.1 | 122.65 |
| Ratio | 11.4 | 17.34 |
GPU resnet50 training is about 17.34 times faster than CPU training.