how to install cuda on ubuntu 16.04 ec2 aws

22:31:57.248055: W tensorflow/core/platform/cpu_feature_:45] The TensorFlow library wasn't compiled to use AVX instructions, but these are available on your machine and could speed up CPU computations. 22:31:57.248044: W tensorflow/core/platform/cpu_feature_: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. 22:31:57.248006: W tensorflow/core/platform/cpu_feature_: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. | N/A 44C P8 31W / 149W | 0MiB / 11439MiB | 0% Default |Īfter getting the basic setup done, you may notice the following warnings whenever you run TensorFlow code: Running nvidia-smi should now be blazing fast: (this only took 0.047 seconds time nvidia-smi Set all GPU clock speeds to their maximum frequency sudo nvidia-smi -ac 2505,875 You can follow the steps below to re-configure the GPU settings:Ĭonfigure the GPU settings to be persistent sudo nvidia-smi -pm 1ĭisable the autoboost feature for all GPUs on the instance sudo nvidia-smi -auto-boost-default=0 After checking with AWS support, it turns out this is due to the default configurations being suboptimal. It takes almost 3 seconds to time nvidia-smi You may notice very quickly that nvidia-smi seems to run much slower than expected. | Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. | GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. Now you should be able to execute the nvidia-smi utility that displays information about the GPU nvidia-smi

How to install cuda on ubuntu 16.04 ec2 aws