Open Chancebair opened 5 years ago
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@KellenSunderland would you have any ideas on this issue?
I think this is due to GluonCV model zoo trying to download cifar which is not available, taking a deeper look...
Links seem to be alright
Might be an issue with the CUDA driver, need to check for the version on the hosts in the AMI's
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Strange, did this just start happening with a cuda driver update? Did we change instance type or anything else at the same time?
The documentation shows that the error code happens when the driver is running an older version than the runtime, but we've been running this runtime for quite some time in CI, and presumably if we changed the driver it would have been to a newer version, so I'm not sure how we could have that regressions.
For reference docs are at: https://docs.nvidia.com/cuda/cuda-runtime-api/group__CUDART__TYPES.html#group__CUDART__TYPES_1g3f51e3575c2178246db0a94a430e0038
This indicates that the installed NVIDIA CUDA driver is older than the CUDA runtime library. This is not a supported configuration. Users should install an updated NVIDIA display driver to allow the application to run.
I wonder if there was an update to the bases image that now requires a newer driver on the host? If so we can probably pin to an older base image. What driver version is running on the host?
Also see this for the most of the time in http://jenkins.mxnet-ci.amazon-ml.com/blue/organizations/jenkins/mxnet-validation%2Funix-gpu/detail/PR-14622/15/pipeline/274
Error message shows it's a cuda driver initialization problem.
Created this PR https://github.com/apache/incubator-mxnet/pull/14642 to unblock PRs while we fix this issue
Driver on the host:
~$ nvidia-smi
Mon Apr 8 13:43:24 2019
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 410.73 Driver Version: 410.73 CUDA Version: 10.0 |
|-------------------------------+----------------------+----------------------+
| 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 V100-SXM2... Off | 00000000:00:1E.0 Off | 0 |
| N/A 46C P0 43W / 300W | 0MiB / 16130MiB | 0% Default |
+-------------------------------+----------------------+----------------------+
+-----------------------------------------------------------------------------+
| Processes: GPU Memory |
| GPU PID Type Process name Usage |
|=============================================================================|
| No running processes found |
+-----------------------------------------------------------------------------+
And on the docker container (nvidia/cuda:10.0-cudnn7-devel):
# nvidia-smi
Mon Apr 8 14:20:56 2019
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 410.73 Driver Version: 410.73 CUDA Version: 10.0 |
|-------------------------------+----------------------+----------------------+
| 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 V100-SXM2... Off | 00000000:00:1E.0 Off | 0 |
| N/A 47C P0 43W / 300W | 0MiB / 16130MiB | 0% Default |
+-------------------------------+----------------------+----------------------+
+-----------------------------------------------------------------------------+
| Processes: GPU Memory |
| GPU PID Type Process name Usage |
|=============================================================================|
| No running processes found |
+-----------------------------------------------------------------------------+
On the docker container the CUDNN version appears to be 7.5.0:
# cat /usr/include/cudnn.h | grep CUDNN_MAJOR -A 2
#define CUDNN_MAJOR 7
#define CUDNN_MINOR 5
#define CUDNN_PATCHLEVEL 0
Good info, as a heads up I'm using NVIDIA-SMI 418.40.04 Driver Version: 418.40.04 CUDA Version: 10.1 in a service and so far haven't seen any issues with this version.
Updating our host AMI with that driver version and giving it a test
That appears to have fixed it, will be deploying to prod shortly: http://jenkins.mxnet-ci-dev.amazon-ml.com/blue/organizations/jenkins/mxnet-validation%2Fchancebair-unix-gpu/detail/chanbair-disable-tensorrtgpu/4/pipeline/276
http://jenkins.mxnet-ci.amazon-ml.com/blue/organizations/jenkins/mxnet-validation%2Funix-gpu/detail/master/496/pipeline http://jenkins.mxnet-ci.amazon-ml.com/blue/organizations/jenkins/mxnet-validation%2Funix-gpu/detail/master/497/pipeline http://jenkins.mxnet-ci.amazon-ml.com/blue/organizations/jenkins/mxnet-validation%2Funix-gpu/detail/master/498/pipeline
The following stages are failing:
Python3: TensorRT GPU