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docs: fix the header of the scaling test table (#4507)
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Fix #4494.

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## Summary by CodeRabbit

- **Documentation**
- Updated the parallel training documentation for TensorFlow and PyTorch
to enhance clarity.
- Expanded explanations on parallel training processes and data loading
utilities.
- Introduced a flowchart to illustrate data flow and modified the
scaling tests table format for better understanding.

<!-- end of auto-generated comment: release notes by coderabbit.ai -->

Signed-off-by: Jinzhe Zeng <[email protected]>
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njzjz authored Dec 26, 2024
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15 changes: 8 additions & 7 deletions doc/train/parallel-training.md
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Expand Up @@ -27,13 +27,14 @@ In some cases, it won't work well when scaling the learning rate by worker count
### Scaling test

Testing `examples/water/se_e2_a` on an 8-GPU host, linear acceleration can be observed with the increasing number of cards.

| Num of GPU cards | Seconds every 100 samples | Samples per second | Speed up |
| ---------------- | ------------------------- | ------------------ | -------- |
| 1 | 1.4515 | 68.89 | 1.00 |
| 2 | 1.5962 | 62.65\*2 | 1.82 |
| 4 | 1.7635 | 56.71\*4 | 3.29 |
| 8 | 1.7267 | 57.91\*8 | 6.72 |
In this example, the number of samples per batch on a single GPU card ({ref}`batch_size <training/training_data/batch_size>`) is set to `1`.

| Num of GPU cards | Samples per batch | Seconds every 100 batches | Samples per second | Speed up |
| ---------------- | ----------------- | ------------------------- | ------------------ | -------- |
| 1 | 1 | 1.4515 | 68.89 | 1.00 |
| 2 | 2 | 1.5962 | 62.65\*2 | 1.82 |
| 4 | 4 | 1.7635 | 56.71\*4 | 3.29 |
| 8 | 8 | 1.7267 | 57.91\*8 | 6.72 |

### How to use

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