prototype sharding by device group #1882
Closed
Conversation
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
facebook-github-bot
added
the
CLA Signed
|
This pull request was exported from Phabricator. Differential Revision: D56147625 |
gnahzg
added a commit
to gnahzg/torchrec
that referenced
this pull request
May 7, 2024
…c sharding type in SQEC (pytorch#1882) Summary: This is a prototype that support tables with same sharding type but place on different device group. e.g some table-wise sharded table placed on CPU, some table-wise sharded table on CUDA. The main change is instead of group sharding infos by sharding_type, we group them by (sharding_type, device_group) Differential Revision: D56147625
gnahzg
added a commit
to gnahzg/torchrec
that referenced
this pull request
May 8, 2024
…c sharding type in SQEC (pytorch#1882) Summary: This is a prototype that support tables with same sharding type but place on different device group. e.g some table-wise sharded table placed on CPU, some table-wise sharded table on CUDA. The main change is instead of group sharding infos by sharding_type, we group them by (sharding_type, device_group) Differential Revision: D56147625
gnahzg
added a commit
to gnahzg/torchrec
that referenced
this pull request
May 10, 2024
…c sharding type in SQEC (pytorch#1882) Summary: This is a prototype that support tables with same sharding type but place on different device group. e.g some table-wise sharded table placed on CPU, some table-wise sharded table on CUDA. The main change is instead of group sharding infos by sharding_type, we group them by (sharding_type, device_group) Differential Revision: D56147625
gnahzg
added a commit
to gnahzg/torchrec
that referenced
this pull request
May 14, 2024
…c sharding type in SQEC (pytorch#1882) Summary: This is a prototype that support tables with same sharding type but place on different device group. e.g some table-wise sharded table placed on CPU, some table-wise sharded table on CUDA. The main change is instead of group sharding infos by sharding_type, we group them by (sharding_type, device_group) Reviewed By: IvanKobzarev Differential Revision: D56147625
gnahzg
pushed a commit
to gnahzg/torchrec
that referenced
this pull request
May 14, 2024
…c sharding type in SQEC (pytorch#1882) Summary: Pull Request resolved: pytorch#1882 This is a prototype that support tables with same sharding type but place on different device group. e.g some table-wise sharded table placed on CPU, some table-wise sharded table on CUDA. The main change is instead of group sharding infos by sharding_type, we group them by (sharding_type, device_group) Differential Revision: D56147625
gnahzg
added a commit
to gnahzg/torchrec
that referenced
this pull request
May 14, 2024
…c sharding type in SQEC (pytorch#1882) Summary: This is a prototype that support tables with same sharding type but place on different device group. e.g some table-wise sharded table placed on CPU, some table-wise sharded table on CUDA. The main change is instead of group sharding infos by sharding_type, we group them by (sharding_type, device_group) Reviewed By: IvanKobzarev Differential Revision: D56147625
|
This pull request was exported from Phabricator. Differential Revision: D56147625 |
gnahzg
added a commit
to gnahzg/torchrec
that referenced
this pull request
May 14, 2024
…c sharding type in SQEC (pytorch#1882) Summary: This is a prototype that support tables with same sharding type but place on different device group. e.g some table-wise sharded table placed on CPU, some table-wise sharded table on CUDA. The main change is instead of group sharding infos by sharding_type, we group them by (sharding_type, device_group) Reviewed By: IvanKobzarev Differential Revision: D56147625
…c sharding type in SQEC (pytorch#1882) Summary: This is a prototype that support tables with same sharding type but place on different device group. e.g some table-wise sharded table placed on CPU, some table-wise sharded table on CUDA. The main change is instead of group sharding infos by sharding_type, we group them by (sharding_type, device_group) Reviewed By: IvanKobzarev Differential Revision: D56147625
|
This pull request was exported from Phabricator. Differential Revision: D56147625 |
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
Summary:
This is a prototype that support tables with same sharding type but place on different device group. e.g some table-wise sharded table placed on CPU, some table-wise sharded table on CUDA.
The main change is instead of group sharding infos by sharding_type, we group them by (sharding_type, device_group)
Differential Revision: D56147625