04:21:34.666369: I tensorflow/core/common_runtime/gpu/gpu_:1716] Found device 0 with properties: 04:21:34.665738: I tensorflow/stream_executor/cuda/cuda_gpu_:982] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero 04:21:34.499432: I tensorflow/stream_executor/platform/default/dso_:48] Successfully opened dynamic library libcuda.so.1 In : print("Num GPUs Available: ", len(tf.config.list_physical_devices('GPU'))) 04:21:31.110443: I tensorflow/stream_executor/platform/default/dso_:48] Successfully opened dynamic library libcudart.so.10.1 The following test is good: import tensorflow as tf My conda env list shows: cudatoolkit 10.1.243 h6bb024c_0 I installed cudatoolkit=10.1, but the cuda driver still not good.
Cuda driver compatibility how to#
If I can't keep cuda 10.0, how to directly upgrade cuda to 10.1 with or without conda? It's best if I can upgrade in Conda.
Cuda driver compatibility install#
If I want to keep the old version cuda 10.0, can I update cuda to 10.1 through Conda? This won't work: conda install cuda=10.1 I know how to install cudakit in conda: conda install cudatoolkit=10.1īut this seems not enough: Status: CUDA driver version is insufficient for CUDA runtime version I want to install Tensorflow 2.3/2.4, so I need to upgrade cuda to 10.1 at least in Conda. | Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M.
| GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr.
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