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https://issues.apache.org/jira/browse/MESOS-7730?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16099717#comment-16099717
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Till Toenshoff commented on MESOS-7730:
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[~klueska] which patch is fixing this?
> CUDA not working anymore on 1.3.0
> ---------------------------------
>
> Key: MESOS-7730
> URL: https://issues.apache.org/jira/browse/MESOS-7730
> Project: Mesos
> Issue Type: Bug
> Components: containerization
> Affects Versions: 1.3.0
> Reporter: Adam Cecile
> Assignee: Kevin Klues
> Fix For: 1.3.1
>
>
> Hello,
> My docker container using CUDA do not detect it anymore.
> Here the tensorflow output with 1.2.1:
> {noformat}
> I0628 12:39:45.505900 16309 exec.cpp:162] Version: 1.2.1
> I0628 12:39:45.508358 16301 exec.cpp:237] Executor registered on agent
> 84c99d0b-8551-4f30-a9bc-6c1edbf7c18c-S1
> I tensorflow/stream_executor/dso_loader.cc:135] successfully opened CUDA
> library libcublas.so.8.0 locally
> I tensorflow/stream_executor/dso_loader.cc:135] successfully opened CUDA
> library libcudnn.so.5 locally
> I tensorflow/stream_executor/dso_loader.cc:135] successfully opened CUDA
> library libcufft.so.8.0 locally
> I tensorflow/stream_executor/dso_loader.cc:135] successfully opened CUDA
> library libcuda.so.1 locally
> I tensorflow/stream_executor/dso_loader.cc:135] successfully opened CUDA
> library libcurand.so.8.0 locally
> W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library
> wasn't compiled to use SSE3 instructions, but these are available on your
> machine and could speed up CPU computations.
> W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library
> wasn't compiled to use SSE4.1 instructions, but these are available on your
> machine and could speed up CPU computations.
> W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library
> wasn't compiled to use SSE4.2 instructions, but these are available on your
> machine and could speed up CPU computations.
> W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library
> wasn't compiled to use AVX instructions, but these are available on your
> machine and could speed up CPU computations.
> W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library
> wasn't compiled to use AVX2 instructions, but these are available on your
> machine and could speed up CPU computations.
> W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library
> wasn't compiled to use FMA instructions, but these are available on your
> machine and could speed up CPU computations.
> I tensorflow/core/common_runtime/gpu/gpu_device.cc:885] Found device 0 with
> properties:
> name: GeForce GTX 1080
> major: 6 minor: 1 memoryClockRate (GHz) 1.7335
> pciBusID 0000:82:00.0
> Total memory: 7.92GiB
> Free memory: 7.81GiB
> I tensorflow/core/common_runtime/gpu/gpu_device.cc:906] DMA: 0
> I tensorflow/core/common_runtime/gpu/gpu_device.cc:916] 0: Y
> I tensorflow/core/common_runtime/gpu/gpu_device.cc:975] Creating TensorFlow
> device (/gpu:0) -> (device: 0, name: GeForce GTX 1080, pci bus id:
> 0000:82:00.0)
> {noformat}
> And with 1.3.0
> {noformat}
> I0628 12:40:30.833947 16854 exec.cpp:162] Version: 1.3.0
> I0628 12:40:30.836612 16845 exec.cpp:237] Executor registered on agent
> 84c99d0b-8551-4f30-a9bc-6c1edbf7c18c-S1
> I tensorflow/stream_executor/dso_loader.cc:135] successfully opened CUDA
> library libcublas.so.8.0 locally
> I tensorflow/stream_executor/dso_loader.cc:135] successfully opened CUDA
> library libcudnn.so.5 locally
> I tensorflow/stream_executor/dso_loader.cc:135] successfully opened CUDA
> library libcufft.so.8.0 locally
> I tensorflow/stream_executor/dso_loader.cc:126] Couldn't open CUDA library
> libcuda.so.1. LD_LIBRARY_PATH:
> I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:165] hostname:
> zelda.service.earthlab.lu
> I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:189] libcuda reported
> version is: Not found: was unable to find libcuda.so DSO loaded into this
> program
> I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:363] driver version
> file contents: """NVRM version: NVIDIA UNIX x86_64 Kernel Module 375.66 Mon
> May 1 15:29:16 PDT 2017
> GCC version: gcc version 4.9.2 (Debian 4.9.2-10)
> """
> I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:193] kernel reported
> version is: 375.66.0
> I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:1065] LD_LIBRARY_PATH:
> I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:1066] failed to find
> libcuda.so on this system: Failed precondition: could not dlopen DSO:
> libcuda.so.1; dlerror: libcuda.so.1: cannot open shared object file: No such
> file or directory
> I tensorflow/stream_executor/dso_loader.cc:135] successfully opened CUDA
> library libcurand.so.8.0 locally
> W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library
> wasn't compiled to use SSE3 instructions, but these are available on your
> machine and could speed up CPU computations.
> W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library
> wasn't compiled to use SSE4.1 instructions, but these are available on your
> machine and could speed up CPU computations.
> W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library
> wasn't compiled to use SSE4.2 instructions, but these are available on your
> machine and could speed up CPU computations.
> W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library
> wasn't compiled to use AVX instructions, but these are available on your
> machine and could speed up CPU computations.
> W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library
> wasn't compiled to use AVX2 instructions, but these are available on your
> machine and could speed up CPU computations.
> W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library
> wasn't compiled to use FMA instructions, but these are available on your
> machine and could speed up CPU computations.
> E tensorflow/stream_executor/cuda/cuda_driver.cc:509] failed call to cuInit:
> CUDA_ERROR_NO_DEVICE
> I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:158] retrieving CUDA
> diagnostic information for host: zelda.service.earthlab.lu
> I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:165] hostname:
> zelda.service.earthlab.lu
> I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:189] libcuda reported
> version is: Not found: was unable to find libcuda.so DSO loaded into this
> program
> I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:363] driver version
> file contents: """NVRM version: NVIDIA UNIX x86_64 Kernel Module 375.66 Mon
> May 1 15:29:16 PDT 2017
> GCC version: gcc version 4.9.2 (Debian 4.9.2-10)
> """
> I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:193] kernel reported
> version is: 375.66.0
> {noformat}
> All i did is upgrading/downgrading mesos package and restarted the container.
> I did the test several time and it's 100% reproductible.
> Regards, Adam.
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