alibaba / alibaba/x-deeplearning
单机模式下,一机多卡GPU显存占用问题
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Description
在xdl.python.backend.tf.tf_bachend.py中定义了
def tf_wrapper(is_training=True, init_grad=None, gpu_memory_fraction=0.5, device_type='cpu'):
小白有两个问题:
1、我单机上有4块GPU,用local模式运行可不可以自动全部占满显存?
2、目前我提交的任务只能占一块卡的0.5,改gpu_memory_fraction参数到0.8也没有变化(两个任务把第一块用完),为啥其他三块卡没用完呢?

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Research direction
Start by reading xdl.python.backend.tf.tf_bachend.py and the tf_wrapper function, then reproduce local-mode execution with four GPUs while varying gpu_memory_fraction. Determine whether the observed single-GPU allocation is expected or faulty; document the supported behavior or define a scoped fix once the GPU placement and memory configuration are understood.
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Assessment
- Tech stack
- python, tensorflow
- Domain
- machine-learning
- Issue type
- Bug
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100