nvidia-docker
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NVIDIA
Nvidia driver not detected on WSL2
1. Issue or feature description
I'm trying to use the Nvidia docker on WSL 2. I installed the driver on the host, and followed this guide to install the nividia-docker2.
When I tried docker run --gpus all -it --shm-size=1g --ulimit memlock=-1 --ulimit stack=67108864 nvcr.io/nvidia/tensorflow:20.03-tf2-py3
The output is not as expected:
================
== TensorFlow ==
================
NVIDIA Release 20.03-tf2 (build 11026100)
TensorFlow Version 2.1.0
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.
WARNING: The NVIDIA Driver was not detected. GPU functionality will not be available.
Use 'nvidia-docker run' to start this container; see
https://github.com/NVIDIA/nvidia-docker/wiki/nvidia-docker .
NOTE: MOFED driver for multi-node communication was not detected.
Multi-node communication performance may be reduced.
When I try nvidia-docker run --gpus all -it --shm-size=1g --ulimit memlock=-1 --ulimit stack=67108864 nvcr.io/nvidia/tensorflow:20.03-tf2-py3, the output is
docker: Error response from daemon: Unknown runtime specified nvidia.
See 'docker run --help
I tried modprobe nvidia, the output is modprobe: FATAL: Module nvidia not found in directory /lib/modules/4.19.128-microsoft-standard.
3. Information to attach (optional if deemed irrelevant)
- [ ] Some nvidia-container information:
nvidia-container-cli -k -d /dev/tty info
$ nvidia-container-cli -k -d /dev/tty info
-- WARNING, the following logs are for debugging purposes only --
I0203 18:12:33.732533 1637 nvc.c:376] initializing library context (version=1.8.0~rc.2, build=d48f9b0d505fca0aff7c88cee790f9c56aa1b851)
I0203 18:12:33.732591 1637 nvc.c:350] using root /
I0203 18:12:33.732597 1637 nvc.c:351] using ldcache /etc/ld.so.cache
I0203 18:12:33.732600 1637 nvc.c:352] using unprivileged user 1000:1000
I0203 18:12:33.732620 1637 nvc.c:393] attempting to load dxcore to see if we are running under Windows Subsystem for Linux (WSL)
I0203 18:12:33.749801 1637 dxcore.c:227] Creating a new WDDM Adapter for hAdapter:40000000 luid:356cc6
I0203 18:12:33.756366 1637 dxcore.c:210] Core Nvidia component libcuda.so.1.1 not found in /usr/lib/wsl/drivers/iigd_dch.inf_amd64_4be767c332df1d04
I0203 18:12:33.756975 1637 dxcore.c:210] Core Nvidia component libcuda_loader.so not found in /usr/lib/wsl/drivers/iigd_dch.inf_amd64_4be767c332df1d04
I0203 18:12:33.757599 1637 dxcore.c:210] Core Nvidia component libnvidia-ptxjitcompiler.so.1 not found in /usr/lib/wsl/drivers/iigd_dch.inf_amd64_4be767c332df1d04
I0203 18:12:33.758180 1637 dxcore.c:210] Core Nvidia component libnvidia-ml.so.1 not found in /usr/lib/wsl/drivers/iigd_dch.inf_amd64_4be767c332df1d04
I0203 18:12:33.758826 1637 dxcore.c:210] Core Nvidia component libnvidia-ml_loader.so not found in /usr/lib/wsl/drivers/iigd_dch.inf_amd64_4be767c332df1d04
I0203 18:12:33.759386 1637 dxcore.c:210] Core Nvidia component nvidia-smi not found in /usr/lib/wsl/drivers/iigd_dch.inf_amd64_4be767c332df1d04
I0203 18:12:33.759410 1637 dxcore.c:215] No Nvidia component found in /usr/lib/wsl/drivers/iigd_dch.inf_amd64_4be767c332df1d04
E0203 18:12:33.759431 1637 dxcore.c:261] Failed to query the core Nvidia libraries for the adapter. Skipping it.
I0203 18:12:33.759451 1637 dxcore.c:227] Creating a new WDDM Adapter for hAdapter:40000040 luid:356dcf
I0203 18:12:33.765143 1637 dxcore.c:268] Adding new adapter via dxcore hAdapter:40000040 luid:356dcf wddm version:3000
I0203 18:12:33.765181 1637 dxcore.c:326] dxcore layer initialized successfully
W0203 18:12:33.765546 1637 nvc.c:401] skipping kernel modules load on WSL
I0203 18:12:33.765686 1638 rpc.c:71] starting driver rpc service
I0203 18:12:33.812286 1639 rpc.c:71] starting nvcgo rpc service
I0203 18:12:33.817953 1637 nvc_info.c:759] requesting driver information with ''
I0203 18:12:33.904704 1637 nvc_info.c:198] selecting /usr/lib/wsl/lib/libnvidia-opticalflow.so.1
I0203 18:12:33.905591 1637 nvc_info.c:198] selecting /usr/lib/wsl/lib/libnvidia-ml.so.1
I0203 18:12:33.906351 1637 nvc_info.c:198] selecting /usr/lib/wsl/lib/libnvidia-encode.so.1
I0203 18:12:33.907139 1637 nvc_info.c:198] selecting /usr/lib/wsl/lib/libnvcuvid.so.1
I0203 18:12:33.907224 1637 nvc_info.c:198] selecting /usr/lib/wsl/lib/libdxcore.so
I0203 18:12:33.907257 1637 nvc_info.c:198] selecting /usr/lib/wsl/lib/libcuda.so.1
W0203 18:12:33.907319 1637 nvc_info.c:398] missing library libnvidia-cfg.so
W0203 18:12:33.907338 1637 nvc_info.c:398] missing library libnvidia-nscq.so
W0203 18:12:33.907341 1637 nvc_info.c:398] missing library libnvidia-opencl.so
W0203 18:12:33.907343 1637 nvc_info.c:398] missing library libnvidia-ptxjitcompiler.so
W0203 18:12:33.907345 1637 nvc_info.c:398] missing library libnvidia-fatbinaryloader.so
W0203 18:12:33.907346 1637 nvc_info.c:398] missing library libnvidia-allocator.so
W0203 18:12:33.907348 1637 nvc_info.c:398] missing library libnvidia-compiler.so
W0203 18:12:33.907349 1637 nvc_info.c:398] missing library libnvidia-pkcs11.so
W0203 18:12:33.907351 1637 nvc_info.c:398] missing library libnvidia-ngx.so
W0203 18:12:33.907352 1637 nvc_info.c:398] missing library libvdpau_nvidia.so
W0203 18:12:33.907354 1637 nvc_info.c:398] missing library libnvidia-eglcore.so
W0203 18:12:33.907355 1637 nvc_info.c:398] missing library libnvidia-glcore.so
W0203 18:12:33.907357 1637 nvc_info.c:398] missing library libnvidia-tls.so
W0203 18:12:33.907359 1637 nvc_info.c:398] missing library libnvidia-glsi.so
W0203 18:12:33.907360 1637 nvc_info.c:398] missing library libnvidia-fbc.so
W0203 18:12:33.907362 1637 nvc_info.c:398] missing library libnvidia-ifr.so
W0203 18:12:33.907363 1637 nvc_info.c:398] missing library libnvidia-rtcore.so
W0203 18:12:33.907365 1637 nvc_info.c:398] missing library libnvoptix.so
W0203 18:12:33.907366 1637 nvc_info.c:398] missing library libGLX_nvidia.so
W0203 18:12:33.907368 1637 nvc_info.c:398] missing library libEGL_nvidia.so
W0203 18:12:33.907369 1637 nvc_info.c:398] missing library libGLESv2_nvidia.so
W0203 18:12:33.907371 1637 nvc_info.c:398] missing library libGLESv1_CM_nvidia.so
W0203 18:12:33.907372 1637 nvc_info.c:398] missing library libnvidia-glvkspirv.so
W0203 18:12:33.907374 1637 nvc_info.c:398] missing library libnvidia-cbl.so
W0203 18:12:33.907375 1637 nvc_info.c:402] missing compat32 library libnvidia-ml.so
W0203 18:12:33.907390 1637 nvc_info.c:402] missing compat32 library libnvidia-cfg.so
W0203 18:12:33.907394 1637 nvc_info.c:402] missing compat32 library libnvidia-nscq.so
W0203 18:12:33.907396 1637 nvc_info.c:402] missing compat32 library libcuda.so
W0203 18:12:33.907399 1637 nvc_info.c:402] missing compat32 library libnvidia-opencl.so
W0203 18:12:33.907414 1637 nvc_info.c:402] missing compat32 library libnvidia-ptxjitcompiler.so
W0203 18:12:33.907431 1637 nvc_info.c:402] missing compat32 library libnvidia-fatbinaryloader.so
W0203 18:12:33.907434 1637 nvc_info.c:402] missing compat32 library libnvidia-allocator.so
W0203 18:12:33.907436 1637 nvc_info.c:402] missing compat32 library libnvidia-compiler.so
W0203 18:12:33.907437 1637 nvc_info.c:402] missing compat32 library libnvidia-pkcs11.so
W0203 18:12:33.907439 1637 nvc_info.c:402] missing compat32 library libnvidia-ngx.so
W0203 18:12:33.907441 1637 nvc_info.c:402] missing compat32 library libvdpau_nvidia.so
W0203 18:12:33.907442 1637 nvc_info.c:402] missing compat32 library libnvidia-encode.so
W0203 18:12:33.907444 1637 nvc_info.c:402] missing compat32 library libnvidia-opticalflow.so
W0203 18:12:33.907447 1637 nvc_info.c:402] missing compat32 library libnvcuvid.so
W0203 18:12:33.907461 1637 nvc_info.c:402] missing compat32 library libnvidia-eglcore.so
W0203 18:12:33.907479 1637 nvc_info.c:402] missing compat32 library libnvidia-glcore.so
W0203 18:12:33.907482 1637 nvc_info.c:402] missing compat32 library libnvidia-tls.so
W0203 18:12:33.907484 1637 nvc_info.c:402] missing compat32 library libnvidia-glsi.so
W0203 18:12:33.907486 1637 nvc_info.c:402] missing compat32 library libnvidia-fbc.so
W0203 18:12:33.907488 1637 nvc_info.c:402] missing compat32 library libnvidia-ifr.so
W0203 18:12:33.907489 1637 nvc_info.c:402] missing compat32 library libnvidia-rtcore.so
W0203 18:12:33.907491 1637 nvc_info.c:402] missing compat32 library libnvoptix.so
W0203 18:12:33.907492 1637 nvc_info.c:402] missing compat32 library libGLX_nvidia.so
W0203 18:12:33.907494 1637 nvc_info.c:402] missing compat32 library libEGL_nvidia.so
W0203 18:12:33.907495 1637 nvc_info.c:402] missing compat32 library libGLESv2_nvidia.so
W0203 18:12:33.907499 1637 nvc_info.c:402] missing compat32 library libGLESv1_CM_nvidia.so
W0203 18:12:33.907500 1637 nvc_info.c:402] missing compat32 library libnvidia-glvkspirv.so
W0203 18:12:33.907527 1637 nvc_info.c:402] missing compat32 library libnvidia-cbl.so
W0203 18:12:33.907531 1637 nvc_info.c:402] missing compat32 library libdxcore.so
I0203 18:12:33.908902 1637 nvc_info.c:278] selecting /usr/lib/wsl/drivers/nvlti.inf_amd64_f0a75371d3692c1a/nvidia-smi
W0203 18:12:34.217108 1637 nvc_info.c:424] missing binary nvidia-debugdump
W0203 18:12:34.217139 1637 nvc_info.c:424] missing binary nvidia-persistenced
W0203 18:12:34.217143 1637 nvc_info.c:424] missing binary nv-fabricmanager
W0203 18:12:34.217144 1637 nvc_info.c:424] missing binary nvidia-cuda-mps-control
W0203 18:12:34.217146 1637 nvc_info.c:424] missing binary nvidia-cuda-mps-server
I0203 18:12:34.217164 1637 nvc_info.c:439] skipping path lookup for dxcore
I0203 18:12:34.217179 1637 nvc_info.c:522] listing device /dev/dxg
W0203 18:12:34.217207 1637 nvc_info.c:348] missing ipc path /var/run/nvidia-persistenced/socket
W0203 18:12:34.217248 1637 nvc_info.c:348] missing ipc path /var/run/nvidia-fabricmanager/socket
W0203 18:12:34.217278 1637 nvc_info.c:348] missing ipc path /tmp/nvidia-mps
I0203 18:12:34.217299 1637 nvc_info.c:815] requesting device information with ''
I0203 18:12:34.227700 1637 nvc_info.c:687] listing dxcore adapter 0 (GPU-b5e386b4-3e71-5837-aca5-80c5914cf07f at 00000000:01:00.0)
NVRM version: 510.06
CUDA version: 11.6
Device Index: 0
Device Minor: 0
Model: NVIDIA GeForce GTX 1650 Ti with Max-Q Design
Brand: GeForce
GPU UUID: GPU-b5e386b4-3e71-5837-aca5-80c5914cf07f
Bus Location: 00000000:01:00.0
Architecture: 7.5
I0203 18:12:34.227772 1637 nvc.c:430] shutting down library context
I0203 18:12:34.227859 1639 rpc.c:95] terminating nvcgo rpc service
I0203 18:12:34.228242 1637 rpc.c:135] nvcgo rpc service terminated successfully
I0203 18:12:34.229403 1638 rpc.c:95] terminating driver rpc service
I0203 18:12:34.230364 1637 rpc.c:135] driver rpc service terminated successfully
- [ ] Kernel version from
uname -a
$ uname -a
Linux LAPTOP-E1MFF41S 4.19.128-microsoft-standard #1 SMP Tue Jun 23 12:58:10 UTC 2020 x86_64 x86_64 x86_64 GNU/Linux
- [ ] Any relevant kernel output lines from
dmesg - [ ] Driver information from
nvidia-smi -a
$ nvidia-smi -a
==============NVSMI LOG==============
Timestamp : Thu Feb 3 13:18:48 2022
Driver Version : 510.06
CUDA Version : 11.6
Attached GPUs : 1
GPU 00000000:01:00.0
Product Name : NVIDIA GeForce GTX 1650 Ti with Max-Q Design
Product Brand : GeForce
Product Architecture : Turing
Display Mode : Enabled
Display Active : Enabled
Persistence Mode : Enabled
MIG Mode
Current : N/A
Pending : N/A
Accounting Mode : Disabled
Accounting Mode Buffer Size : 4000
Driver Model
Current : WDDM
Pending : WDDM
Serial Number : N/A
GPU UUID : GPU-b5e386b4-3e71-5837-aca5-80c5914cf07f
Minor Number : N/A
VBIOS Version : 90.17.41.00.46
MultiGPU Board : No
Board ID : 0x100
GPU Part Number : N/A
Module ID : 0
Inforom Version
Image Version : G001.0000.02.04
OEM Object : 1.1
ECC Object : N/A
Power Management Object : N/A
GPU Operation Mode
Current : N/A
Pending : N/A
GSP Firmware Version : N/A
GPU Virtualization Mode
Virtualization Mode : None
Host VGPU Mode : N/A
IBMNPU
Relaxed Ordering Mode : N/A
PCI
Bus : 0x01
Device : 0x00
Domain : 0x0000
Device Id : 0x1F9510DE
Bus Id : 00000000:01:00.0
Sub System Id : 0x22C017AA
GPU Link Info
PCIe Generation
Max : 3
Current : 3
Link Width
Max : 16x
Current : 16x
Bridge Chip
Type : N/A
Firmware : N/A
Replays Since Reset : 0
Replay Number Rollovers : 0
Tx Throughput : 218000 KB/s
Rx Throughput : 1000 KB/s
Fan Speed : N/A
Performance State : P8
Clocks Throttle Reasons
Idle : Active
Applications Clocks Setting : Not Active
SW Power Cap : Not Active
HW Slowdown : Not Active
HW Thermal Slowdown : Not Active
HW Power Brake Slowdown : Not Active
Sync Boost : Not Active
SW Thermal Slowdown : Not Active
Display Clock Setting : Not Active
FB Memory Usage
Total : 4096 MiB
Used : 1337 MiB
Free : 2759 MiB
BAR1 Memory Usage
Total : 256 MiB
Used : 2 MiB
Free : 254 MiB
Compute Mode : Default
Utilization
Gpu : N/A
Memory : N/A
Encoder : 0 %
Decoder : 0 %
Encoder Stats
Active Sessions : 0
Average FPS : 0
Average Latency : 0
FBC Stats
Active Sessions : 0
Average FPS : 0
Average Latency : 0
Ecc Mode
Current : N/A
Pending : N/A
ECC Errors
Volatile
SRAM Correctable : N/A
SRAM Uncorrectable : N/A
DRAM Correctable : N/A
DRAM Uncorrectable : N/A
Aggregate
SRAM Correctable : N/A
SRAM Uncorrectable : N/A
DRAM Correctable : N/A
DRAM Uncorrectable : N/A
Retired Pages
Single Bit ECC : N/A
Double Bit ECC : N/A
Pending Page Blacklist : N/A
Remapped Rows : N/A
Temperature
GPU Current Temp : 40 C
GPU Shutdown Temp : 102 C
GPU Slowdown Temp : 97 C
GPU Max Operating Temp : 75 C
GPU Target Temperature : N/A
Memory Current Temp : N/A
Memory Max Operating Temp : N/A
Power Readings
Power Management : N/A
Power Draw : 3.99 W
Power Limit : N/A
Default Power Limit : N/A
Enforced Power Limit : N/A
Min Power Limit : N/A
Max Power Limit : N/A
Clocks
Graphics : 77 MHz
SM : 77 MHz
Memory : 197 MHz
Video : 540 MHz
Applications Clocks
Graphics : N/A
Memory : N/A
Default Applications Clocks
Graphics : N/A
Memory : N/A
Max Clocks
Graphics : 2100 MHz
SM : 2100 MHz
Memory : 5001 MHz
Video : 1950 MHz
Max Customer Boost Clocks
Graphics : N/A
Clock Policy
Auto Boost : N/A
Auto Boost Default : N/A
Voltage
Graphics : N/A
Processes : None
- [ ] Docker version from
docker version
Client:
Version: 20.10.7
API version: 1.41
Go version: go1.13.8
Git commit: 20.10.7-0ubuntu5~20.04.2
Built: Mon Nov 1 00:34:17 2021
OS/Arch: linux/amd64
Context: default
Experimental: true
Server: Docker Engine - Community
Engine:
Version: 20.10.12
API version: 1.41 (minimum version 1.12)
Go version: go1.16.12
Git commit: 459d0df
Built: Mon Dec 13 11:43:56 2021
OS/Arch: linux/amd64
Experimental: false
containerd:
Version: 1.4.12
GitCommit: 7b11cfaabd73bb80907dd23182b9347b4245eb5d
runc:
Version: 1.0.2
GitCommit: v1.0.2-0-g52b36a2
docker-init:
Version: 0.19.0
GitCommit: de40ad0
- [ ] NVIDIA packages version from
dpkg -l '*nvidia*'orrpm -qa '*nvidia*'
$ dpkg -l '*nvidia*'` _or_ `rpm -qa '*nvidia*'
_or_: command not found
dpkg-query: no packages found matching *nvidia*rpm
dpkg-query: no packages found matching -qa
Desired=Unknown/Install/Remove/Purge/Hold
| Status=Not/Inst/Conf-files/Unpacked/halF-conf/Half-inst/trig-aWait/Trig-pend
|/ Err?=(none)/Reinst-required (Status,Err: uppercase=bad)
||/ Name Version Architecture Description
+++-================================-============-============-=====================================================
un libgldispatch0-nvidia <none> <none> (no description available)
ii libnvidia-container-tools 1.8.0~rc.2-1 amd64 NVIDIA container runtime library (command-line tools)
ii libnvidia-container1:amd64 1.8.0~rc.2-1 amd64 NVIDIA container runtime library
un nvidia-common <none> <none> (no description available)
un nvidia-container-runtime <none> <none> (no description available)
un nvidia-container-runtime-hook <none> <none> (no description available)
ii nvidia-container-toolkit 1.8.0~rc.2-1 amd64 NVIDIA container runtime hook
un nvidia-docker <none> <none> (no description available)
ii nvidia-docker2 2.8.0-1 all nvidia-docker CLI wrapper
un nvidia-legacy-304xx-vdpau-driver <none> <none> (no description available)
un nvidia-legacy-340xx-vdpau-driver <none> <none> (no description available)
un nvidia-libopencl1-dev <none> <none> (no description available)
un nvidia-prime <none> <none> (no description available)
un nvidia-vdpau-driver <none> <none> (no description available)
- [ ] NVIDIA container library version from
nvidia-container-cli -V
$ nvidia-container-cli -V
cli-version: 1.8.0~rc.2
lib-version: 1.8.0~rc.2
build date: 2022-01-28T10:54+00:00
build revision: d48f9b0d505fca0aff7c88cee790f9c56aa1b851
build compiler: x86_64-linux-gnu-gcc-7 7.5.0
build platform: x86_64
build flags: -D_GNU_SOURCE -D_FORTIFY_SOURCE=2 -DNDEBUG -std=gnu11 -O2 -g -fdata-sections -ffunction-sections -fplan9-extensions -fstack-protector -fno-strict-aliasing -fvisibility=hidden -Wall -Wextra -Wcast-align -Wpointer-arith -Wmissing-prototypes -Wnonnull -Wwrite-strings -Wlogical-op -Wformat=2 -Wmissing-format-attribute -Winit-self -Wshadow -Wstrict-prototypes -Wunreachable-code -Wconversion -Wsign-conversion -Wno-unknown-warning-option -Wno-format-extra-args -Wno-gnu-alignof-expression -Wl,-zrelro -Wl,-znow -Wl,-zdefs -Wl,--gc-sections
- [ ] NVIDIA container library logs (see troubleshooting)
- [ ] Docker command, image and tag used
It's a strange bug, because GPU is available despite the error message, it's fixed in later images (don't mind nvidia-smi and driver version, it's the same with 510.06):
➜ docker run --gpus all --rm --shm-size=1g --ulimit memlock=-1 --ulimit stack=67108864 nvcr.io/nvidia/tensorflow:22.01-tf2-py3 nvidia-smi
================
== TensorFlow ==
================
NVIDIA Release 22.01-tf2 (build 31081301)
TensorFlow Version 2.7.0
Container image Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
Copyright 2017-2022 The TensorFlow Authors. All rights reserved.
Various files include modifications (c) NVIDIA CORPORATION & AFFILIATES. All rights reserved.
This container image and its contents are governed by the NVIDIA Deep Learning Container License.
By pulling and using the container, you accept the terms and conditions of this license:
https://developer.nvidia.com/ngc/nvidia-deep-learning-container-license
NOTE: MOFED driver for multi-node communication was not detected.
Multi-node communication performance may be reduced.
Fri Feb 4 11:22:39 2022
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 510.39.01 Driver Version: 511.23 CUDA Version: 11.6 |
|-------------------------------+----------------------+----------------------+
| GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |
| | | MIG M. |
|===============================+======================+======================|
| 0 NVIDIA GeForce ... On | 00000000:01:00.0 Off | N/A |
| N/A 56C P8 4W / N/A | 312MiB / 6144MiB | 15% Default |
| | | N/A |
+-------------------------------+----------------------+----------------------+
+-----------------------------------------------------------------------------+
| Processes: |
| GPU GI CI PID Type Process name GPU Memory |
| ID ID Usage |
|=============================================================================|
| No running processes found |
+-----------------------------------------------------------------------------+
compared to 20.03:
➜ docker run --gpus all --rm --shm-size=1g --ulimit memlock=-1 --ulimit stack=67108864 nvcr.io/nvidia/tensorflow:20.03-tf2-py3 nvidia-smi
================
== TensorFlow ==
================
NVIDIA Release 20.03-tf2 (build 11026100)
TensorFlow Version 2.1.0
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.
WARNING: The NVIDIA Driver was not detected. GPU functionality will not be available.
Use 'nvidia-docker run' to start this container; see
https://github.com/NVIDIA/nvidia-docker/wiki/nvidia-docker .
NOTE: MOFED driver for multi-node communication was not detected.
Multi-node communication performance may be reduced.
Fri Feb 4 11:23:46 2022
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 510.39.01 Driver Version: 511.23 CUDA Version: 11.6 |
|-------------------------------+----------------------+----------------------+
| GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |
| | | MIG M. |
|===============================+======================+======================|
| 0 NVIDIA GeForce ... On | 00000000:01:00.0 Off | N/A |
| N/A 53C P8 3W / N/A | 316MiB / 6144MiB | 4% Default |
| | | N/A |
+-------------------------------+----------------------+----------------------+
+-----------------------------------------------------------------------------+
| Processes: |
| GPU GI CI PID Type Process name GPU Memory |
| ID ID Usage |
|=============================================================================|
| No running processes found |
+-----------------------------------------------------------------------------+
Btw, try updating your wsl kernel, 4.19 is pretty old
I have the same issue, exactly the same setup, except for the newest kernel version. Tried modprobe nvidia and got:
modprobe: FATAL: Module nvidia not found in directory /lib/modules/5.10.60.1-microsoft-standard-WSL2
The GPU is detected and theoretically runs, in the container, but it only reserves the GPU memory. Utilization of the GPU stays at 0% which means that my cpu can perform faster calculations. Anyone found a solution yet?
I've solved my issue by using the newest Nvidia docker container. For some reason the gpu is fully utilized now