I have the following configuration:
- SUSE Linux Enterprise Server 12 SP3 (x86_64)
- CUDA Toolkit: CUDA 9.2 (9.2.148 Update 1)
- CUDA Driver Version: 396.37
According to NVIDIA just right (https://docs.nvidia.com/cuda/cuda-toolkit-release-notes/index.html#major-components).
I set up a new environment with Anaconda and installed tensorflow-gpu in it:
conda create -n keras python=3.6.8 anaconda conda install -c anaconda tensorflow-gpu
But if I then want to check the installation via python console:
import tensorflow as tf sess = tf.Session(config=tf.ConfigProto(log_device_placement=True))
I get the following error:
2019-04-17 15:23:45.753926: I tensorflow/core/platform/cpu_feature_guard.cc:141] Your CPU supports instructions that this TensorFlow binary was not compiled to use: SSE4.1 SSE4.2 AVX AVX2 FMA
2019-04-17 15:23:45.793109: I tensorflow/core/platform/profile_utils/cpu_utils.cc:94] CPU Frequency: 2600180000 Hz
2019-04-17 15:23:45.798218: I tensorflow/compiler/xla/service/service.cc:150] XLA service 0x561f42601240 executing computations on platform Host. Devices:
2019-04-17 15:23:45.798258: I tensorflow/compiler/xla/service/service.cc:158] StreamExecutor device (0): ,
2019-04-17 15:23:45.981727: I tensorflow/compiler/xla/service/service.cc:150] XLA service 0x561f426ad9b0 executing computations on platform CUDA. Devices:
2019-04-17 15:23:45.981777: I tensorflow/compiler/xla/service/service.cc:158] StreamExecutor device (0): Tesla K40c, Compute Capability 3.5
2019-04-17 15:23:45.982175: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1433] Found device 0 with properties:
name: Tesla K40c major: 3 minor: 5 memoryClockRate(GHz): 0.745 pciBusID: 0000:06:00.0 totalMemory: 11.17GiB freeMemory: 11.09GiB
2019-04-17 15:23:45.982206: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1512] Adding visible gpu devices: 0
Traceback (most recent call last): File "", line 1, in File "/home/fuchs/.conda/envs/keras/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 1551, in init super(Session, self).init(target, graph, config=config) File "/home/fuchs/.conda/envs/keras/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 676, in init self._session = tf_session.TF_NewSessionRef(self._graph._c_graph, opts) tensorflow.python.framework.errors_impl.InternalError: cudaGetDevice() failed. Status: CUDA driver version is insufficient for CUDA runtime version
I've been looking for solutions from others with this problem, but for most of them it was because the CUDA Toolkit and Driver version didn't match. Which is not the case with me.
I'd really appreciate the help.