I set up two Jetson Orin Nano Developer Kits back to back over the last couple of months, and I kept hitting the same wall on both. Not the flashing, and not the firmware black screen that many of us fight first. I mean the stretch right after the board finally boots, where the device is technically running but is not actually ready to do real work. I ended up fixing the same three or four things by hand on the second board that I had already fixed on the first, so I wrote a small tool to do the checking for me.
It is called jetson-postboot. It runs with nothing but system Python 3. You clone it and run it, no pip install and no dependencies. By default it is read-only and just prints a report of what it finds.
The specific things it looks at, all of which I ran into personally:
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Storage after an SD to NVMe migration. When you clone a 64 GB card onto a 500 GB SSD, the filesystem keeps the old geometry and you are left with a 60 GB root sitting on a 500 GB disk. The tool detects the unallocated trailing space and prints the exact growpart and resize2fs commands for your specific layout. It does not run the partition operation for you, on purpose, because getting that wrong is one of the faster ways to brick a board. It advises, and you decide.
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Swap and zram. The default JetPack configuration gives you roughly 3.7 GB of zram on the 8 GB board with swappiness at 60. Because zram lives inside RAM, and because GPU unified-memory allocations cannot be swapped, that compressed store eats directly into what a model can use. The tool can apply the tuning I settled on by hand, which is low swappiness plus an NVMe swapfile in place of zram, and every change it makes records an undo path.
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CUDA stack and model fit. It reports your L4T, CUDA, cuDNN, and Python versions in one place, points out that nvidia-smi showing N/A is expected on Jetson and not a fault, and for a requested Ollama model it estimates whether that model will actually fit in memory before you pull it.
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To be clear about scope, here is what it does not do: no flashing, no firmware or QSPI work, and no automatic edits to extlinux.conf or the boot order. Those are either pre-boot territory or too risky to automate, so they stay out. The boot section is report-only.
I built it because none of these issues are rare. The same questions recur on this forum year after year and across every Jetson generation, from the partition that will not expand to torch.cuda.is_available() returning False after hours of effort. If the tool saves someone else the afternoon it cost me, it did its job.
Repo: GitHub - Muhit1204/jetson-postboot · GitHub
It is early, and I would genuinely welcome feedback, especially on edge cases in the storage detection across different disk layouts. If you run it on your board, please tell me what it got wrong.
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To address the issues you’ve encountered with the Jetson Orin Nano Developer Kits, particularly those related to the post-boot setup and configuration, the jetson-postboot tool you’ve developed seems to offer a practical solution. This tool, designed to run with system Python 3, checks for several common issues that users might face after the initial boot, including storage configuration after migrating from an SD card to an NVMe SSD, swap and zram settings, and CUDA stack and model compatibility.
Given the context, here are some steps and considerations for using and potentially improving the jetson-postboot tool:
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Storage Configuration: The tool detects unallocated space on the disk after an SD to NVMe migration and provides the exact commands for growing the partition and resizing the filesystem. It’s crucial to review these commands carefully before executing them to avoid potential data loss or bricking the board.
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Swap and ZRAM: The default JetPack configuration may not be optimal for all use cases, especially regarding swap and zram settings. The tool can adjust these settings based on your preferences, such as reducing swappiness and replacing zram with an NVMe swap file. It keeps a record of changes made, allowing for easy reversion if needed.
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CUDA Stack and Model Compatibility: The tool reports on the versions of L4T, CUDA, cuDNN, and Python, which is helpful for ensuring compatibility with the models you intend to run. It also estimates whether a requested model will fit in memory, which can save time and frustration.
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Feedback and Improvement: Since the tool is in its early stages, feedback from the community, especially regarding edge cases and different disk layouts, would be invaluable. Running the tool on various setups and reporting back any inaccuracies or suggestions for improvement can help refine its functionality and usefulness.
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Scope and Limitations: It’s important to note what the tool does not do, such as flashing, firmware or QSPI work, and automatic edits to extlinux.conf or boot order changes. These limitations are in place to avoid risky operations that could potentially brick the board or cause significant issues.
In summary, the jetson-postboot tool appears to be a useful resource for streamlining the post-boot configuration of Jetson Orin Nano Developer Kits, addressing common pain points such as storage, swap, and CUDA compatibility. By using this tool and contributing feedback, users can potentially save a significant amount of time and effort in setting up their boards for development and deployment.
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Hi,
Many thanks for the sharing. It would be great if you can specify which Jetpack 6 version you are using, such as Jetpack 6.2.2 r36.5. This would be clearer than Jetpack 6.x.