Add warpSize to Device properties #128449
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
🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/128449
Note: Links to docs will display an error until the docs builds have been completed. ✅ You can merge normally! (4 Unrelated Failures)As of commit 1e68689 with merge base c12a4f2 ( FLAKY - The following jobs failed but were likely due to flakiness present on trunk:
This comment was automatically generated by Dr. CI and updates every 15 minutes. |
eqy
approved these changes
Jun 11, 2024
pruthvistony
added
ciflow/trunk
jataylo
approved these changes
Jun 14, 2024
|
@pytorchbot rebase |
|
@pytorchbot started a rebase job onto refs/remotes/origin/viable/strict. Check the current status here |
|
Successfully rebased |
pytorchmergebot
force-pushed
the
warp_size-dev-prop
branch
from
36071ef
to
5b77544
Compare
jithunnair-amd
approved these changes
Jun 27, 2024
malfet
approved these changes
Jun 27, 2024
|
@pytorchbot merge |
Merge failedReason: This PR needs a If not, please add the To add a label, you can comment to pytorchbot, for example For more information, see Details for Dev Infra teamRaised by workflow job |
|
@pytorchbot merge |
Merge startedYour change will be merged once all checks pass (ETA 0-4 Hours). Learn more about merging in the wiki. Questions? Feedback? Please reach out to the PyTorch DevX Team |
|
The merge job was canceled or timed out. This most often happen if two merge requests were issued for the same PR, or if merge job was waiting for more than 6 hours for tests to finish. In later case, please do not hesitate to reissue the merge command |
|
@pytorchbot merge |
Merge startedYour change will be merged once all checks pass (ETA 0-4 Hours). Learn more about merging in the wiki. Questions? Feedback? Please reach out to the PyTorch DevX Team |
pytorchmergebot
pushed a commit
to khushi-411/pytorch
that referenced
this pull request
Jul 2, 2024
Adding warp_size to CudaDeviceProperties. >>> import torch >>> prop = torch.cuda.get_device_properties(torch.cuda.current_device()) >>> prop.warp_size 64 >>> @jeffdaily @pruthvistony @jithunnair-amd @ROCmSupport Co-authored-by: Jithun Nair <[email protected]> Pull Request resolved: pytorch#128449 Approved by: https://github.com/eqy, https://github.com/jataylo, https://github.com/jithunnair-amd, https://github.com/malfet
pytorchmergebot
pushed a commit
that referenced
this pull request
Jul 19, 2024
…9663) As of ROCm 6.1 [hipDeviceProp_t::regsPerMultiprocessor](https://rocm.docs.amd.com/projects/HIP/en/latest/doxygen/html/structhip_device_prop__t.html#a7390d5b180d63978c81aa971060270b4) is now available allowing us to enable this attribute on ROCm. ``` >>> torch.cuda.get_device_properties(0) _CudaDeviceProperties(name='AMD Instinct MI250X/MI250', major=9, minor=0, gcnArchName='gfx90a:sramecc+:xnack-', total_memory=65520MB, multi_processor_count=104) >>> torch.cuda.get_device_properties(0).regs_per_multiprocessor 65536 ``` With https://github.com/triton-lang/triton/pull/3962we can extract n_regs and n_spells from a triton binary with AMD backend allowing us to enable inductor's dynamic_rblock_scaling on ROCm initially implemented in #115094 Leaving this in draft until following PRs have landed: - #129361 to bump the triton commit pin - #128449 to allow us to grab warp_size from device properties instead of hard coding 64 on ROCm. Pull Request resolved: #129663 Approved by: https://github.com/jansel, https://github.com/shunting314
DiweiSun
pushed a commit
to DiweiSun/pytorch
that referenced
this pull request
Jul 22, 2024
…orch#129663) As of ROCm 6.1 [hipDeviceProp_t::regsPerMultiprocessor](https://rocm.docs.amd.com/projects/HIP/en/latest/doxygen/html/structhip_device_prop__t.html#a7390d5b180d63978c81aa971060270b4) is now available allowing us to enable this attribute on ROCm. ``` >>> torch.cuda.get_device_properties(0) _CudaDeviceProperties(name='AMD Instinct MI250X/MI250', major=9, minor=0, gcnArchName='gfx90a:sramecc+:xnack-', total_memory=65520MB, multi_processor_count=104) >>> torch.cuda.get_device_properties(0).regs_per_multiprocessor 65536 ``` With https://github.com/triton-lang/triton/pull/3962we can extract n_regs and n_spells from a triton binary with AMD backend allowing us to enable inductor's dynamic_rblock_scaling on ROCm initially implemented in pytorch#115094 Leaving this in draft until following PRs have landed: - pytorch#129361 to bump the triton commit pin - pytorch#128449 to allow us to grab warp_size from device properties instead of hard coding 64 on ROCm. Pull Request resolved: pytorch#129663 Approved by: https://github.com/jansel, https://github.com/shunting314
xuhancn
pushed a commit
to xuhancn/pytorch
that referenced
this pull request
Jul 25, 2024
…orch#129663) As of ROCm 6.1 [hipDeviceProp_t::regsPerMultiprocessor](https://rocm.docs.amd.com/projects/HIP/en/latest/doxygen/html/structhip_device_prop__t.html#a7390d5b180d63978c81aa971060270b4) is now available allowing us to enable this attribute on ROCm. ``` >>> torch.cuda.get_device_properties(0) _CudaDeviceProperties(name='AMD Instinct MI250X/MI250', major=9, minor=0, gcnArchName='gfx90a:sramecc+:xnack-', total_memory=65520MB, multi_processor_count=104) >>> torch.cuda.get_device_properties(0).regs_per_multiprocessor 65536 ``` With https://github.com/triton-lang/triton/pull/3962we can extract n_regs and n_spells from a triton binary with AMD backend allowing us to enable inductor's dynamic_rblock_scaling on ROCm initially implemented in pytorch#115094 Leaving this in draft until following PRs have landed: - pytorch#129361 to bump the triton commit pin - pytorch#128449 to allow us to grab warp_size from device properties instead of hard coding 64 on ROCm. Pull Request resolved: pytorch#129663 Approved by: https://github.com/jansel, https://github.com/shunting314
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.
Adding warp_size to CudaDeviceProperties.
@jeffdaily @pruthvistony @jithunnair-amd @ROCmSupport
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @peterbell10 @ipiszy @yf225 @chenyang78 @kadeng @muchulee8 @ColinPeppler @amjames @desertfire @chauhang