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This repository has been archived by the owner on Jan 22, 2024. It is now read-only.
I tried ./nvidia-docker/nvidia-docker run deviceQuery and it works fine:
./deviceQuery Starting...
CUDA Device Query (Runtime API) version (CUDART static linking)
Detected 1 CUDA Capable device(s)
Device 0: "GeForce GTX 970"
CUDA Driver Version / Runtime Version 7.5 / 7.5
CUDA Capability Major/Minor version number: 5.2
Total amount of global memory: 4082 MBytes (4279894016 bytes)
(13) Multiprocessors, (128) CUDA Cores/MP: 1664 CUDA Cores
GPU Max Clock rate: 1367 MHz (1.37 GHz)
Memory Clock rate: 3505 Mhz
Memory Bus Width: 256-bit
L2 Cache Size: 1835008 bytes
Maximum Texture Dimension Size (x,y,z) 1D=(65536), 2D=(65536, 65536), 3D=(4096, 4096, 4096)
Maximum Layered 1D Texture Size, (num) layers 1D=(16384), 2048 layers
Maximum Layered 2D Texture Size, (num) layers 2D=(16384, 16384), 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 PCI Domain ID / Bus ID / location ID: 0 / 3 / 0
Compute Mode:
< Default (multiple host threads can use ::cudaSetDevice() with device simultaneously) >
deviceQuery, CUDA Driver = CUDART, CUDA Driver Version = 7.5, CUDA Runtime Version = 7.5, NumDevs = 1, Device0 = GeForce GTX 970
Result = PASS
but when I tried to use sudo ./nvidia-docker/nvidia-docker -H 0.0.0.0:2375 -d to create a docker daemon and use docker API to create container and run, it failed and gave this error:
./deviceQuery Starting...
CUDA Device Query (Runtime API) version (CUDART static linking)
cudaGetDeviceCount returned 35
-> CUDA driver version is insufficient for CUDA runtime version
Result = FAIL
The text was updated successfully, but these errors were encountered:
I tried
./nvidia-docker/nvidia-docker run deviceQuery
and it works fine:but when I tried to use
sudo ./nvidia-docker/nvidia-docker -H 0.0.0.0:2375 -d
to create a docker daemon and use docker API to create container and run, it failed and gave this error:The text was updated successfully, but these errors were encountered: