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Proofread with Argo/GPT4o #562
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2. Checked all links; they appear to be correct and functional. 3. No formatting issues were identified. 4. The page reads great, no changes required.
…cludes content from another file (`./docs/polaris/containers/containers.md:commoncontainerdoc`). Without the content of the included file, it's not possible to review the full document for errors or improvements. However, the visible portion of the markdown does not contain any grammatical errors or formatting issues. 2. Ensure that the included file path is correct and accessible, as this will affect whether the content is properly displayed when the markdown is rendered. 3. If the included file contains additional content, it should be reviewed separately for any issues.
… system" for consistency with product naming conventions. 2. Added a comma after "peak performance of 1.18 PF" for clarity. 3. Removed the space before colons in the NUMA lists for consistency with standard punctuation practices.
…columns correctly. 2. Corrected a typo in the section "Running Multiple MPI Applications on Multiple Nodes" where "innvocations" was changed to "invocations". 3. Ensured consistent formatting for code blocks and inline code for better readability. 4. Verified and corrected the link to the `hello_affinity` program to point to the correct directory for Crux examples.
2. Added bash syntax highlighting to code blocks for improved readability. 3. Added colons after list items to maintain consistency in punctuation.
… clarity. 2. Fixed grammar: Removed the hyphen in "commonly-used" to correctly use "commonly used" as an adjective phrase. 3. Improved formatting: Ensured consistent spacing and punctuation for clarity and readability.
You can see the code here. |
This was referenced Dec 8, 2024
See issue #563 for more general discussions. |
This was referenced Dec 8, 2024
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Continuing with using Argo/GPT4o to improve our documentation. See discussion in #504. Eventually, we can do this with a GitHub action for better automation. The problem with GitHub action is the requirement for an OpenAI key. We can also try free LLMs, but performance might not be as good. Alternative is to have a GitLab mirror and run the action on our machines with Argo.