[Gradient Compression] Warm-start of PowerSGD#49451
Closed
wayi1 wants to merge 8 commits intogh/SciPioneer/38/basefrom
Closed
[Gradient Compression] Warm-start of PowerSGD#49451wayi1 wants to merge 8 commits intogh/SciPioneer/38/basefrom
wayi1 wants to merge 8 commits intogh/SciPioneer/38/basefrom
Conversation
Reuse the low-rank tensors P(s) and Q(s) from the previous iteration if possible. This can give a better compression performance in terms of both accuracy and speed. Also add a unit test for batched PowerSGD to test_c10d.py. Original PR issue: Investigate Applying PowerSGD to Communication Hook for Gradient Compression #47202 Differential Revision: [D25583086](https://our.internmc.facebook.com/intern/diff/D25583086/) [ghstack-poisoned]
wayi1
pushed a commit
that referenced
this pull request
Dec 16, 2020
Reuse the low-rank tensors P(s) and Q(s) from the previous iteration if possible. This can give a better compression performance in terms of both accuracy and speed. Also add a unit test for batched PowerSGD to test_c10d.py. Original PR issue: Investigate Applying PowerSGD to Communication Hook for Gradient Compression #47202 Differential Revision: [D25583086](https://our.internmc.facebook.com/intern/diff/D25583086/) ghstack-source-id: 118695432 Pull Request resolved: #49451
Contributor
💊 CI failures summary and remediationsAs of commit 390dd4e (more details on the Dr. CI page): 💚 💚 Looks good so far! There are no failures yet. 💚 💚 This comment was automatically generated by Dr. CI (expand for details).Follow this link to opt-out of these comments for your Pull Requests.Please report bugs/suggestions to the (internal) Dr. CI Users group. This comment has been revised 59 times. |
Reuse the low-rank tensors P(s) and Q(s) from the previous iteration if possible. This can give a better compression performance in terms of both accuracy and speed. Also add a unit test for batched PowerSGD to test_c10d.py. Original PR issue: Investigate Applying PowerSGD to Communication Hook for Gradient Compression #47202 Differential Revision: [D25583086](https://our.internmc.facebook.com/intern/diff/D25583086/) [ghstack-poisoned]
wayi1
pushed a commit
that referenced
this pull request
Dec 16, 2020
Pull Request resolved: #49451 Reuse the low-rank tensors P(s) and Q(s) from the previous iteration if possible. This can give a better compression performance in terms of both accuracy and speed. Also add a unit test for batched PowerSGD to test_c10d.py. Original PR issue: Investigate Applying PowerSGD to Communication Hook for Gradient Compression #47202 ghstack-source-id: 118736193 Differential Revision: [D25583086](https://our.internmc.facebook.com/intern/diff/D25583086/)
Reuse the low-rank tensors P(s) and Q(s) from the previous iteration if possible. This can give a better compression performance in terms of both accuracy and speed. Also add a unit test for batched PowerSGD to test_c10d.py. Original PR issue: Investigate Applying PowerSGD to Communication Hook for Gradient Compression #47202 Differential Revision: [D25583086](https://our.internmc.facebook.com/intern/diff/D25583086/) [ghstack-poisoned]
wayi1
pushed a commit
that referenced
this pull request
Dec 16, 2020
Pull Request resolved: #49451 Reuse the low-rank tensors P(s) and Q(s) from the previous iteration if possible. This can give a better compression performance in terms of both accuracy and speed. Also add a unit test for batched PowerSGD to test_c10d.py. Original PR issue: Investigate Applying PowerSGD to Communication Hook for Gradient Compression #47202 ghstack-source-id: 118751780 Differential Revision: [D25583086](https://our.internmc.facebook.com/intern/diff/D25583086/)
Reuse the low-rank tensors P(s) and Q(s) from the previous iteration if possible. This can give a better compression performance in terms of both accuracy and speed. Also add a unit test for batched PowerSGD to test_c10d.py. Original PR issue: Investigate Applying PowerSGD to Communication Hook for Gradient Compression #47202 Differential Revision: [D25583086](https://our.internmc.facebook.com/intern/diff/D25583086/) [ghstack-poisoned]
wayi1
pushed a commit
that referenced
this pull request
Dec 16, 2020
Pull Request resolved: #49451 Reuse the low-rank tensors P(s) and Q(s) from the previous iteration if possible. This can give a better compression performance in terms of both accuracy and speed. Also add a unit test for batched PowerSGD to test_c10d.py. Original PR issue: Investigate Applying PowerSGD to Communication Hook for Gradient Compression #47202 ghstack-source-id: 118758002 Differential Revision: [D25583086](https://our.internmc.facebook.com/intern/diff/D25583086/)
rohan-varma
reviewed
Dec 18, 2020
Reuse the low-rank tensors P(s) and Q(s) from the previous iteration if possible. This can give a better compression performance in terms of both accuracy and speed. Also add a unit test for batched PowerSGD to test_c10d.py. Original PR issue: Investigate Applying PowerSGD to Communication Hook for Gradient Compression #47202 Differential Revision: [D25583086](https://our.internmc.facebook.com/intern/diff/D25583086/) [ghstack-poisoned]
wayi1
pushed a commit
that referenced
this pull request
Dec 18, 2020
Pull Request resolved: #49451 Reuse the low-rank tensors P(s) and Q(s) from the previous iteration if possible. This can give a better compression performance in terms of both accuracy and speed. Also add a unit test for batched PowerSGD to test_c10d.py. Original PR issue: Investigate Applying PowerSGD to Communication Hook for Gradient Compression #47202 ghstack-source-id: 118948215 Differential Revision: [D25583086](https://our.internmc.facebook.com/intern/diff/D25583086/)
Reuse the low-rank tensors P(s) and Q(s) from the previous iteration if possible. This can give a better compression performance in terms of both accuracy and speed. Also add a unit test for batched PowerSGD to test_c10d.py. Original PR issue: Investigate Applying PowerSGD to Communication Hook for Gradient Compression #47202 Differential Revision: [D25583086](https://our.internmc.facebook.com/intern/diff/D25583086/) [ghstack-poisoned]
Reuse the low-rank tensors P(s) and Q(s) from the previous iteration if possible. This can give a better compression performance in terms of both accuracy and speed. Also add a unit test for batched PowerSGD to test_c10d.py. Original PR issue: Investigate Applying PowerSGD to Communication Hook for Gradient Compression #47202 Differential Revision: [D25583086](https://our.internmc.facebook.com/intern/diff/D25583086/) [ghstack-poisoned]
wayi1
pushed a commit
that referenced
this pull request
Dec 21, 2020
Pull Request resolved: #49451 Reuse the low-rank tensors P(s) and Q(s) from the previous iteration if possible. This can give a better compression performance in terms of both accuracy and speed. Also add a unit test for batched PowerSGD to test_c10d.py. Original PR issue: Investigate Applying PowerSGD to Communication Hook for Gradient Compression #47202 ghstack-source-id: 118984540 Differential Revision: [D25583086](https://our.internmc.facebook.com/intern/diff/D25583086/)
rohan-varma
approved these changes
Dec 21, 2020
Contributor
rohan-varma
left a comment
There was a problem hiding this comment.
LGTM. I suppose that we'll follow up with information regarding data around the accuracy/speed tradeoffs for all of these configurations? Would be great to get some data around how the different flags trade off.
Contributor
Author
Have collected some experimental results for only one experiment so far, but still need experiment on a more training cases to draw a conclusion. |
Reuse the low-rank tensors P(s) and Q(s) from the previous iteration if possible. This can give a better compression performance in terms of both accuracy and speed. Also add a unit test for batched PowerSGD to test_c10d.py. Original PR issue: Investigate Applying PowerSGD to Communication Hook for Gradient Compression #47202 Differential Revision: [D25583086](https://our.internmc.facebook.com/intern/diff/D25583086/) [ghstack-poisoned]
This was referenced Dec 21, 2020
Contributor
|
This pull request has been merged in c348fae. |
hwangdeyu
pushed a commit
to hwangdeyu/pytorch
that referenced
this pull request
Jan 6, 2021
Summary: Pull Request resolved: pytorch#49451 Reuse the low-rank tensors P(s) and Q(s) from the previous iteration if possible. This can give a better compression performance in terms of both accuracy and speed. Also add a unit test for batched PowerSGD to test_c10d.py. Original PR issue: Investigate Applying PowerSGD to Communication Hook for Gradient Compression pytorch#47202 ghstack-source-id: 119014132 Test Plan: buck test mode/dev-nosan caffe2/test/distributed:c10d -- test_powerSGD_ddp_comm_hook_nccl buck test mode/dev-nosan caffe2/test/distributed:distributed_nccl_fork -- test_DistributedDataParallel_powerSGD_ddp_comm_hook Reviewed By: rohan-varma Differential Revision: D25583086 fbshipit-source-id: a757df3c4cfcc0ead4647f7de2f43198f1e063ee
laurentdupin
pushed a commit
to laurentdupin/pytorch
that referenced
this pull request
Apr 24, 2026
Summary: Pull Request resolved: pytorch#49451 Reuse the low-rank tensors P(s) and Q(s) from the previous iteration if possible. This can give a better compression performance in terms of both accuracy and speed. Also add a unit test for batched PowerSGD to test_c10d.py. Original PR issue: Investigate Applying PowerSGD to Communication Hook for Gradient Compression pytorch#47202 ghstack-source-id: 119014132 Test Plan: buck test mode/dev-nosan caffe2/test/distributed:c10d -- test_powerSGD_ddp_comm_hook_nccl buck test mode/dev-nosan caffe2/test/distributed:distributed_nccl_fork -- test_DistributedDataParallel_powerSGD_ddp_comm_hook Reviewed By: rohan-varma Differential Revision: D25583086 fbshipit-source-id: a757df3c4cfcc0ead4647f7de2f43198f1e063ee
This file contains hidden or 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
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
3 participants
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.
Stack from ghstack:
Reuse the low-rank tensors P(s) and Q(s) from the previous iteration if possible.
This can give a better compression performance in terms of both accuracy and speed.
Also add a unit test for batched PowerSGD to test_c10d.py.
Original PR issue: Investigate Applying PowerSGD to Communication Hook for Gradient Compression #47202
Differential Revision: D25583086