Improve complex lerp performance #84844
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
The complex lerp kernel uses `std::abs(z) < 0.5` which involves computing a sqrt. Instead compare the square against 0.25 has much lower latency and so performs much better overall. In a simple timeit benchmark I see more than 10x speedup on CPU for a 4096 element complex lerp, from 84 us to 6.7 us. [ghstack-poisoned]
🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/84844
Note: Links to docs will display an error until the docs builds have been completed. ✅ No FailuresAs of commit 92b3719: This comment was automatically generated by Dr. CI and updates every 15 minutes. |
This was referenced Sep 11, 2022
peterbell10
added a commit
to peterbell10/pytorch
that referenced
this pull request
Sep 11, 2022
The complex lerp kernel uses `std::abs(z) < 0.5` which involves computing a sqrt. Instead compare the square against 0.25 has much lower latency and so performs much better overall. In a simple timeit benchmark I see more than 10x speedup on CPU for a 4096 element complex lerp, from 84 us to 6.7 us. ghstack-source-id: d402414a6a71a8e522a25f2819f83248e19b0b05 Pull Request resolved: pytorch#84844
The complex lerp kernel uses `std::abs(z) < 0.5` which involves computing a sqrt. Instead compare the square against 0.25 has much lower latency and so performs much better overall. In a simple timeit benchmark I see more than 10x speedup on CPU for a 4096 element complex lerp, from 84 us to 6.7 us. [ghstack-poisoned]
The complex lerp kernel uses `std::abs(z) < 0.5` which involves computing a sqrt. Instead compare the square against 0.25 has much lower latency and so performs much better overall. In a simple timeit benchmark I see more than 10x speedup on CPU for a 4096 element complex lerp, from 84 us to 6.7 us. [ghstack-poisoned]
The complex lerp kernel uses `std::abs(z) < 0.5` which involves computing a sqrt. Instead compare the square against 0.25 has much lower latency and so performs much better overall. In a simple timeit benchmark I see more than 10x speedup on CPU for a 4096 element complex lerp, from 84 us to 6.7 us. [ghstack-poisoned]
peterbell10
added a commit
to peterbell10/pytorch
that referenced
this pull request
Sep 22, 2022
The complex lerp kernel uses `std::abs(z) < 0.5` which involves computing a sqrt. Instead compare the square against 0.25 has much lower latency and so performs much better overall. In a simple timeit benchmark I see more than 10x speedup on CPU for a 4096 element complex lerp, from 84 us to 6.7 us. ghstack-source-id: 3fd059b6e41f541a6a48b26d2c87e67c01fe236d Pull Request resolved: pytorch#84844
peterbell10
added a commit
to peterbell10/pytorch
that referenced
this pull request
Sep 22, 2022
The complex lerp kernel uses `std::abs(z) < 0.5` which involves computing a sqrt. Instead compare the square against 0.25 has much lower latency and so performs much better overall. In a simple timeit benchmark I see more than 10x speedup on CPU for a 4096 element complex lerp, from 84 us to 6.7 us. ghstack-source-id: 3fd059b6e41f541a6a48b26d2c87e67c01fe236d Pull Request resolved: pytorch#84844
peterbell10
added a commit
to peterbell10/pytorch
that referenced
this pull request
Sep 22, 2022
The complex lerp kernel uses `std::abs(z) < 0.5` which involves computing a sqrt. Instead compare the square against 0.25 has much lower latency and so performs much better overall. In a simple timeit benchmark I see more than 10x speedup on CPU for a 4096 element complex lerp, from 84 us to 6.7 us. ghstack-source-id: 3fd059b6e41f541a6a48b26d2c87e67c01fe236d Pull Request resolved: pytorch#84844
peterbell10
added a commit
to peterbell10/pytorch
that referenced
this pull request
Sep 22, 2022
The complex lerp kernel uses `std::abs(z) < 0.5` which involves computing a sqrt. Instead compare the square against 0.25 has much lower latency and so performs much better overall. In a simple timeit benchmark I see more than 10x speedup on CPU for a 4096 element complex lerp, from 84 us to 6.7 us. ghstack-source-id: 3fd059b6e41f541a6a48b26d2c87e67c01fe236d Pull Request resolved: pytorch#84844
peterbell10
added a commit
to peterbell10/pytorch
that referenced
this pull request
Sep 22, 2022
The complex lerp kernel uses `std::abs(z) < 0.5` which involves computing a sqrt. Instead compare the square against 0.25 has much lower latency and so performs much better overall. In a simple timeit benchmark I see more than 10x speedup on CPU for a 4096 element complex lerp, from 84 us to 6.7 us. ghstack-source-id: 3fd059b6e41f541a6a48b26d2c87e67c01fe236d Pull Request resolved: pytorch#84844
peterbell10
added a commit
to peterbell10/pytorch
that referenced
this pull request
Sep 22, 2022
The complex lerp kernel uses `std::abs(z) < 0.5` which involves computing a sqrt. Instead compare the square against 0.25 has much lower latency and so performs much better overall. In a simple timeit benchmark I see more than 10x speedup on CPU for a 4096 element complex lerp, from 84 us to 6.7 us. ghstack-source-id: 3fd059b6e41f541a6a48b26d2c87e67c01fe236d Pull Request resolved: pytorch#84844
peterbell10
added a commit
to peterbell10/pytorch
that referenced
this pull request
Sep 23, 2022
The complex lerp kernel uses `std::abs(z) < 0.5` which involves computing a sqrt. Instead compare the square against 0.25 has much lower latency and so performs much better overall. In a simple timeit benchmark I see more than 10x speedup on CPU for a 4096 element complex lerp, from 84 us to 6.7 us. ghstack-source-id: 3fd059b6e41f541a6a48b26d2c87e67c01fe236d Pull Request resolved: pytorch#84844
peterbell10
added a commit
to peterbell10/pytorch
that referenced
this pull request
Sep 23, 2022
The complex lerp kernel uses `std::abs(z) < 0.5` which involves computing a sqrt. Instead compare the square against 0.25 has much lower latency and so performs much better overall. In a simple timeit benchmark I see more than 10x speedup on CPU for a 4096 element complex lerp, from 84 us to 6.7 us. ghstack-source-id: 3fd059b6e41f541a6a48b26d2c87e67c01fe236d Pull Request resolved: pytorch#84844
peterbell10
added a commit
to peterbell10/pytorch
that referenced
this pull request
Sep 23, 2022
The complex lerp kernel uses `std::abs(z) < 0.5` which involves computing a sqrt. Instead compare the square against 0.25 has much lower latency and so performs much better overall. In a simple timeit benchmark I see more than 10x speedup on CPU for a 4096 element complex lerp, from 84 us to 6.7 us. ghstack-source-id: 3fd059b6e41f541a6a48b26d2c87e67c01fe236d Pull Request resolved: pytorch#84844
peterbell10
added a commit
to peterbell10/pytorch
that referenced
this pull request
Sep 23, 2022
The complex lerp kernel uses `std::abs(z) < 0.5` which involves computing a sqrt. Instead compare the square against 0.25 has much lower latency and so performs much better overall. In a simple timeit benchmark I see more than 10x speedup on CPU for a 4096 element complex lerp, from 84 us to 6.7 us. ghstack-source-id: 3fd059b6e41f541a6a48b26d2c87e67c01fe236d Pull Request resolved: pytorch#84844
|
/easycla As part of the transition to the PyTorch Foundation, this project now requires contributions be covered under the new CLA. See #85559 for additional details. This comment will trigger a new check of this PR. If you are already covered, you will simply see a new "EasyCLA" check that passes. If you are not covered, a bot will leave a new comment with a link to sign. |
The complex lerp kernel uses `std::abs(z) < 0.5` which involves computing a sqrt. Instead compare the square against 0.25 has much lower latency and so performs much better overall. In a simple timeit benchmark I see more than 10x speedup on CPU for a 4096 element complex lerp, from 84 us to 6.7 us. [ghstack-poisoned]
The complex lerp kernel uses `std::abs(z) < 0.5` which involves computing a sqrt. Instead compare the square against 0.25 has much lower latency and so performs much better overall. In a simple timeit benchmark I see more than 10x speedup on CPU for a 4096 element complex lerp, from 84 us to 6.7 us. [ghstack-poisoned]
|
@ngimel ping |
|
@pytorchbot rebase |
ngimel
approved these changes
Oct 13, 2022
|
@pytorchbot successfully started a rebase job. Check the current status here |
The complex lerp kernel uses `std::abs(z) < 0.5` which involves computing a sqrt. Instead compare the square against 0.25 has much lower latency and so performs much better overall. In a simple timeit benchmark I see more than 10x speedup on CPU for a 4096 element complex lerp, from 84 us to 6.7 us. [ghstack-poisoned]
|
Successfully rebased |
pytorchmergebot
pushed a commit
that referenced
this pull request
Oct 13, 2022
The complex lerp kernel uses `std::abs(z) < 0.5` which involves computing a sqrt. Instead compare the square against 0.25 has much lower latency and so performs much better overall. In a simple timeit benchmark I see more than 10x speedup on CPU for a 4096 element complex lerp, from 84 us to 6.7 us. ghstack-source-id: 3baffe91f2c44d0e29df0d39459a2e4ac457c7cc Pull Request resolved: #84844
|
@pytorchbot merge -g |
Merge startedYour change will be merged once all checks on your PR pass since you used the green (-g) flag (ETA: 0-4 Hours). Learn more about merging in the wiki. Questions? Feedback? Please reach out to the PyTorch DevX Team |
|
Hey @peterbell10. |
peterbell10
added
release notes: complex
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.
Stack from ghstack (oldest at bottom):
The complex lerp kernel uses
std::abs(z) < 0.5which involvescomputing a sqrt. Instead compare the square against 0.25 has much
lower latency and so performs much better overall.
In a simple timeit benchmark I see more than 10x speedup on CPU for a 4096
element complex lerp, from 84 us to 6.7 us.