svtr_tiny 性能优化 和 修改多卡启动方式为msrun #810
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alien-0119
reviewed
Feb 28, 2025
| export MS_ENABLE_NUMA=True | ||
| msrun --bind_core=True --worker_num=2 --local_worker_num=2 python tools/train.py --config configs/det/dbnet/db_r50_icdar15.yaml | ||
| ``` | ||
| **Note:** For more information about msrun configuration, please refer to [here](https://www.mindspore.cn/tutorials/experts/en/r2.3.1/parallel/msrun_launcher.html). |
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这里是不是链接mindspore 2.5.0的文档好一些
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文档上环境信息就是2.3.1，这边是考虑保持一致
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好的 了解 后续v0.5.0分支适配的pr会把这里修改掉
Ash-Lee233
approved these changes
Feb 28, 2025
| export MS_ENABLE_NUMA=True | ||
| msrun --bind_core=True --worker_num=2 --local_worker_num=2 python tools/train.py --config configs/det/dbnet/db_r50_icdar15.yaml | ||
| ``` | ||
| **Note:** For more information about msrun configuration, please refer to [here](https://www.mindspore.cn/tutorials/experts/en/r2.3.1/parallel/msrun_launcher.html). |
CaitinZhao
reviewed
Mar 3, 2025
configs/det/east/README_CN.md
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| msrun --worker_num=8 --local_worker_num=8 python tools/train.py --config configs/det/east/east_r50_icdar15.yaml | ||
| # 经验证，绑核在大部分情况下有性能加速，请配置参数并运行 | ||
| export MS_ENABLE_NUMA=True |
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为什么numa和msrun的bind_core要同时加？
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我这边尝试一起加性能会有提升，只加bind_core性能不明显
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最开始尝试的只设置MS_ENABLE_NUMA=True，没有加bind_core参数，性能基本没什么变化，后面参考
这个写法两个一起尝试，性能有所提升
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云上或者在容器跑numa绑核会有问题，这个应该只有裸机跑可以有效
Ash-Lee233
approved these changes
Mar 4, 2025
CaitinZhao
approved these changes
Mar 4, 2025
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Before submitting this PR, please make sure:
Motivation
1、GradSampler2D算子优化
2、多卡启动由mpirun修改为msrun
Test Plan
(How should this PR be tested? Do you require special setup to run the test or repro the fixed bug?)
Related Issues and PRs
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