![]() ![]() It is possible the system was flashed not taking advantage of all of the eMMC…if that is the case then you might not need an external disk (or excess unused disk could be mounted at “/usr/local”). To see the current system disk space run “df -H -t ext4”. You could mount a hard drive or SD card there (make sure they are formatted as type ext4…you may get unexpected results if they are the windows VFAT type). I can’t answer the CUDA-specific stuff, but most everything related to this is installed in “/usr/local”. Second, I want to use gpu to run my code on TX2, so I followed some instructions from some other topics, download the cuda_9.1.85_387.26_n (linux->X86_64->ubuntu->16.04->runfile(local)) from Īfter Run sudo sh cuda_9.1.85_387.26_n, it shows that the disk space is not enough… How should I do for this? Would it be possible that I insert an additional SD card to solve this problem? Or still need to do something else to make the CUDA can be installed in additional SD card?Īll I want to do is to run tensorflow code by GPU, are the above steps necessary? Or something else I need to do? Thanks! Then you must still copy to the Jetson and manually install.įor SDK Manager 4.First, I have already checked some previous topics from others, I got the idea that I can check the usage of GPU on my TX2 by using the command: sudo ~/tegrastats, and GR3D means GPU, but still have no idea on xx% what does these number really mean? ![]() The manifest contains a base web server URL, and then notation exists describing each download URL for specific files…you can use wget to download files that way as well. Depending on release the packages can then be found on the host PC for manual copy to the Jetson and manual install.įurthermore, there is also a manifest downloaded. ![]() The basic theme is that both can be told to not delete temporary files, and you tell it you are going to add packages (deselect every other operation), and then upon actual install don’t install packages. Is this JetPack4.2? Or something earlier? The answer can change depending on which one. Unofficially there are essentially two options (both require extra work, but one requires far more work than the other). No other method is supported (and the supported method is much easier), and only JetPack can be used to download CUDA for a Jetson…at least normally. I will try all this again carefully with the next L4T version. Next time I will keep a better record of the log files. The problem is, that I started Jetpack in the same directory again/several times. ![]()
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