docs: document more for multiprocessing #4190
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Fix deepmodeling#4182. Signed-off-by: Jinzhe Zeng <[email protected]>
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Actionable comments posted: 0
🧹 Outside diff range and nitpick comments (6)
doc/troubleshooting/howtoset_num_nodes.md (4)
13-17: Great addition of TensorFlow-specific instructions!The new content clearly explains how to enable MPI support for TensorFlow, which is crucial for users implementing parallel processing. The link to Horovod installation instructions is particularly helpful.
Consider adding a brief example command or code snippet demonstrating how to use Horovod with DeePMD-kit for TensorFlow users. This could further enhance the practical value of this section.
18-22: Good addition of PyTorch-specific information, but could be enhanced.The inclusion of PyTorch-specific multiprocessing information using torchrun is valuable. However, this section could benefit from more detailed instructions or examples, similar to the TensorFlow section.
Consider expanding this section to include:
- A brief example of how to use torchrun with DeePMD-kit.
- Any specific configuration options or best practices for PyTorch multiprocessing in the context of DeePMD-kit.
This would provide more actionable information for PyTorch users and maintain consistency with the level of detail in the TensorFlow section.
40-40: Excellent addition of GPU usage limitation!This crucial note directly addresses the GPU memory issue mentioned in the linked issue #4182. It provides clear guidance on resource allocation, which is essential for users to avoid memory exhaustion errors.
To further enhance this section, consider adding a brief explanation of why this limitation exists and how it relates to the GPU memory issues some users might encounter. This could help users better understand the underlying reasons for this constraint and how to work within it effectively.
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1-40: Excellent overall improvements to parallelism documentation!The document now provides a comprehensive guide to parallelism in DeePMD-kit, covering MPI/multiprocessing, inter-operator parallelism, and intra-operator parallelism. The additions and changes align well with the PR objective of improving documentation for multiprocessing and addressing the GPU memory issue.
To further enhance the document's usefulness:
- Consider adding a troubleshooting section that directly addresses common issues, such as the GPU memory problem mentioned in issue GPU memory issue while executing lmp #4182. This could include symptoms, potential causes, and solutions.
- It might be beneficial to include a decision tree or flowchart to help users determine which parallelism approach is best for their specific use case and hardware configuration.
These additions would make the document even more valuable as a comprehensive resource for users dealing with parallelism and resource allocation in DeePMD-kit.
doc/third-party/lammps-command.md (2)
7-10: Excellent addition addressing GPU usage limitations.This note directly addresses the GPU memory issue mentioned in the linked issue #4182. It provides crucial information for users to understand the limitations of GPU usage with MPI ranks.
Consider adding a brief explanation of why this limitation exists (e.g., "due to the current implementation of DeePMD-kit") to provide more context for users.
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13-25: Consider enhancing the "units" section for clarity.While the current changes effectively address the GPU memory issue, there's an opportunity to further clarify the relationship between units and GPU memory usage. This could help users better understand how their choice of units might impact memory allocation.
Consider adding a note in the "units" section that explains how different unit choices might affect memory usage, especially in the context of GPU calculations. For example:
"Note: The choice of units can indirectly affect GPU memory usage. Certain unit systems may lead to larger or smaller numeric values, potentially impacting the memory required for calculations. When working with limited GPU memory, consider how your choice of units might influence overall memory consumption."
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📒 Files selected for processing (2)
- doc/third-party/lammps-command.md (1 hunks)
- doc/troubleshooting/howtoset_num_nodes.md (2 hunks)
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🔇 Additional comments (3)
doc/troubleshooting/howtoset_num_nodes.md (1)
7-13: Excellent update to the MPI section!The changes in this section effectively address the PR objective of improving documentation for multiprocessing. The updated header and introduction clearly indicate that both MPI and multiprocessing are options for parallelism. The new tab set structure promises a more organized presentation of framework-specific information.
doc/third-party/lammps-command.md (2)
11-11: Improved readability with added spacing.The addition of an empty line after the new note enhances the document's readability by clearly separating sections.
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1-391: Overall, excellent documentation update addressing GPU usage.This update effectively addresses the GPU memory issue mentioned in the linked issue #4182 by adding crucial information about MPI rank and GPU usage limitations. The changes are well-integrated into the existing documentation and maintain consistency in style and formatting.
The added note and reference to the troubleshooting guide provide valuable information for users encountering GPU memory issues. The suggested minor enhancements, if implemented, would further improve the document's clarity and usefulness.
Great job on this documentation update!
Codecov ReportAll modified and coverable lines are covered by tests ✅
Additional details and impacted files@@ Coverage Diff @@
## devel #4190 +/- ##
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+ Coverage 83.45% 83.46% +0.01%
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Files 537 537
Lines 52148 52224 +76
Branches 3047 3047
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+ Hits 43518 43590 +72
- Misses 7683 7689 +6
+ Partials 947 945 -2 ☔ View full report in Codecov by Sentry. |
Fix #4182.
Summary by CodeRabbit
lammps-command.mdto clarify GPU usage and unit handling in LAMMPS.howtoset_num_nodes.mdwith new sections on MPI and multiprocessing for TensorFlow and PyTorch, improving clarity and usability.