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https://issues.apache.org/jira/browse/SPARK-32429?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Thomas Graves updated SPARK-32429:
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Description:
It would be nice if standalone mode could allow users to set
CUDA_VISIBLE_DEVICES before launching an executor. This has multiple benefits.
* kind of an isolation in that the executor can only see the GPUs set there.
* If your GPU application doesn't support explicitly setting the GPU device
id, setting this will make any GPU look like the default (id 0) and things
generally just work without any explicit setting
* New features are being added on newer GPUs that require explicit setting of
CUDA_VISIBLE_DEVICES like MIG
([https://www.nvidia.com/en-us/technologies/multi-instance-gpu/])
The code changes to just set this are very small, once we set them we would
also possibly need to change the gpu addresses as it changes them to start from
device id 0 again.
The easiest implementation would just specifically support this and have it
behind a config and set when the config is on and GPU resources are allocated.
Note we probably want to have this same thing set when we launch a python
process as well so that it gets same env.
was:
It would be nice if standalone mode could allow users to set
CUDA_VISIBLE_DEVICES before launching an executor. This has multiple benefits.
* kind of an isolation in that the executor can only see the GPUs set there.
* If your GPU application doesn't support explicitly setting the GPU device
id, setting this will make any GPU look like the default (id 0) and things
generally just work without any explicit setting
* New features are being added on newer GPUs that require explicit setting of
CUDA_VISIBLE_DEVICES like MIG
([https://www.nvidia.com/en-us/technologies/multi-instance-gpu/])
The code changes to just set this are very small, once we set them we would
also possibly need to change the gpu addresses as it changes them to start from
device id 0 again.
The easiest implementation would just specifically support this and have it
behind a config and set when the config is on and GPU resources are allocated.
> Standalone Mode allow setting CUDA_VISIBLE_DEVICES on executor launch
> ---------------------------------------------------------------------
>
> Key: SPARK-32429
> URL: https://issues.apache.org/jira/browse/SPARK-32429
> Project: Spark
> Issue Type: Improvement
> Components: Deploy
> Affects Versions: 3.0.0
> Reporter: Thomas Graves
> Priority: Major
>
> It would be nice if standalone mode could allow users to set
> CUDA_VISIBLE_DEVICES before launching an executor. This has multiple
> benefits.
> * kind of an isolation in that the executor can only see the GPUs set there.
> * If your GPU application doesn't support explicitly setting the GPU device
> id, setting this will make any GPU look like the default (id 0) and things
> generally just work without any explicit setting
> * New features are being added on newer GPUs that require explicit setting
> of CUDA_VISIBLE_DEVICES like MIG
> ([https://www.nvidia.com/en-us/technologies/multi-instance-gpu/])
> The code changes to just set this are very small, once we set them we would
> also possibly need to change the gpu addresses as it changes them to start
> from device id 0 again.
> The easiest implementation would just specifically support this and have it
> behind a config and set when the config is on and GPU resources are
> allocated.
> Note we probably want to have this same thing set when we launch a python
> process as well so that it gets same env.
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