Paddle Difference in GPU memory usage between master/slave nodes

b1payxdu 于 2022-11-13 发布在其他

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Hi,

First of all, thank you for all your work.

I got a small question regarding training multi-gpu. I see that the GPU memory usage on the master node is much less then on the slave nodes. Is this normal behaviour? It seems like there is almost 1GB more free memory on the master node, compared tot he slave nodes.
My training sometimes gets killed with a docker exit code 137. There are no fleetrun logs output, that tells that any error in the code happend. The program just gets killed. Do you have any idea what this might mean?

kind regards

Paddle

来源：https://github.com/PaddlePaddle/Paddle/issues/44421

3条答案

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wz3gfoph1#

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赞(0）回复(0）举报 2022-11-13

q43xntqr2#

Thanks for reporting this case.

Is your data length variable? If your data length is not variable, you can try paddle.device.cuda.empty_cache() to releases all unoccupied cached memory currently and check visible in nvidia-smi.
You can set GLOG_v=3 in your executive script to find the error.

赞(0）回复(0）举报 2022-11-13

z9smfwbn3#

Hi, thank you for your response. I experimented around a little bit and activated GLOG_v=3. The last output I get from the GLOG logging is: