Привет!
Хост система Ubuntu 18.04. На хосте CUDA софт работает без проблем:
./deviceQuery Starting...
CUDA Device Query (Runtime API) version (CUDART static linking)
Detected 1 CUDA Capable device(s)
Device 0: «GeForce GTX 1050 Ti»
CUDA Driver Version / Runtime Version 9.1 / 9.1
CUDA Capability Major/Minor version number: 6.1
Total amount of global memory: 4039 MBytes (4234936320 bytes)
( 6) Multiprocessors, (128) CUDA Cores/MP: 768 CUDA Cores
GPU Max Clock rate: 1392 MHz (1.39 GHz)
Memory Clock rate: 3504 Mhz
Memory Bus Width: 128-bit
L2 Cache Size: 1048576 bytes
Maximum Texture Dimension Size (x,y,z) 1D=(131072), 2D=(131072, 65536), 3D=(16384, 16384, 16384)
Maximum Layered 1D Texture Size, (num) layers 1D=(32768), 2048 layers
Maximum Layered 2D Texture Size, (num) layers 2D=(32768, 32768), 2048 layers
Total amount of constant memory: 65536 bytes
Total amount of shared memory per block: 49152 bytes
Total number of registers available per block: 65536
Warp size: 32
Maximum number of threads per multiprocessor: 2048
Maximum number of threads per block: 1024
Max dimension size of a thread block (x,y,z): (1024, 1024, 64)
Max dimension size of a grid size (x,y,z): (2147483647, 65535, 65535)
Maximum memory pitch: 2147483647 bytes
Texture alignment: 512 bytes
Concurrent copy and kernel execution: Yes with 2 copy engine(s)
Run time limit on kernels: Yes
Integrated GPU sharing Host Memory: No
Support host page-locked memory mapping: Yes
Alignment requirement for Surfaces: Yes
Device has ECC support: Disabled
Device supports Unified Addressing (UVA): Yes
Device supports Compute Preemption: Yes
Supports Cooperative Kernel Launch: Yes
Supports MultiDevice Co-op Kernel Launch: Yes
Device PCI Domain ID / Bus ID / location ID: 0 / 130 / 0
Compute Mode:
< Default (multiple host threads can use ::cudaSetDevice() with device simultaneously) >
deviceQuery, CUDA Driver = CUDART, CUDA Driver Version = 9.1, CUDA Runtime Version = 9.1, NumDevs = 1
Result = PASS
В контейнере происходит ошибка:
./deviceQuery Starting...
CUDA Device Query (Runtime API) version (CUDART static linking)
cudaGetDeviceCount returned 30
-> unknown error
Result = FAIL
Но при этом nvidia-smi внутри контейнера работает нормально:
Sat Aug 4 22:49:53 2018
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 390.48 Driver Version: 390.48 |
|-------------------------------+----------------------+----------------------+
| GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |
|===============================+======================+======================|
| 0 GeForce GTX 105... Off | 00000000:82:00.0 On | N/A |
| 29% 35C P8 N/A / 75W | 291MiB / 4038MiB | 0% Default |
+-------------------------------+----------------------+----------------------+
+-----------------------------------------------------------------------------+
| Processes: GPU Memory |
| GPU PID Type Process name Usage |
|=============================================================================|
+-----------------------------------------------------------------------------+
Для проброса в конфиге контейнера присутствуют таки строки:
# GPU Passthrough config
lxc.cgroup.devices.allow = c 195:* rwm
lxc.cgroup.devices.allow = c 243:* rwm
lxc.mount.entry = /dev/nvidia0 dev/nvidia0 none bind,optional,create=file
lxc.mount.entry = /dev/nvidiactl dev/nvidiactl none bind,optional,create=file
lxc.mount.entry = /dev/nvidia-uvm dev/nvidia-uvm none bind,optional,create=file
lxc.mount.entry = /dev/nvidia-modeset dev/nvidia-modeset none bind,optional,create=file
В контейнере стоят пакеты:
libcudart9.1 nvidia-cuda-dev nvidia-cuda-doc nvidia-cuda-gdb nvidia-cuda-toolkit
Файлы устройства присутствуют в /dev:
crw-rw-rw- 1 root root 195, 254 Jul 27 21:19 /dev/nvidia-modeset
crw-rw-rw- 1 root root 238, 0 Jul 27 21:18 /dev/nvidia-uvm
crw-rw-rw- 1 root root 195, 0 Jul 27 21:18 /dev/nvidia0
crw-rw-rw- 1 root root 195, 255 Jul 27 21:18 /dev/nvidiactl
Контейнер привилегированный.
Что я упустил в настройке?
