[Gradient Compression] Warm-start of PowerSGD #49451
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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
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mingzhe09088,
mrshenli,
pritamdamania87,
rohan-varma and
zhaojuanmao
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wayi1
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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: 1186954 Pull Request resolved: #49451
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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
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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
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
|
This pull request has been merged in c348fae. |
hwangdeyu
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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
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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