Skip to content

perf: reduce repeated Triton autotuning for L2Norm - #1

Open
Kamleecoder wants to merge 1 commit into
Ascend:core_r0.16.0from
Kamleecoder:fix/l2norm-autotune
Open

perf: reduce repeated Triton autotuning for L2Norm#1
Kamleecoder wants to merge 1 commit into
Ascend:core_r0.16.0from
Kamleecoder:fix/l2norm-autotune

Conversation

@Kamleecoder

Copy link
Copy Markdown

修复 L2Norm Triton kernel 在动态 token 数场景下因输入 T/NB 变化反复触发 autotune,导致训练 iteration 耗时异常增长的问题。

动态 shape / 动态 token 数训练时,L2Norm Triton kernel
会随着 T/NB 变化重复执行 autotune。

每次 autotune 需要遍历大量 BT × num_warps 配置,
单次可能耗时 20s+,多次累积导致一个训练 step 超过 10 分钟。

@ascend-robot

Copy link
Copy Markdown

Hello,

This repo is only a mirror with no active development or maintenance.
All bug reports, questions and code contributions should be submitted via the original repository link below.
Thanks for your interest!

Original Repository Link: https://gitcode.com/Ascend/MindSpeed

@ascend-robot

Copy link
Copy Markdown

CLA Signature Guide

@Kamleecoder , thanks for your pull request.

The following commit(s) are not associated with a signed Contributor License Agreement (CLA).

Commit Reason
484b4e7c 修复 L2Norm Triton kernel 在�... the email used in the commit is not linked to a signed CLA!
please verify that it matches the email you used when signing the CLA.

To sign CLA, click here.

To check if your email is configured correctly, refer to the FAQs.

Once you've signed the CLA or updating your email, please comment /check-cla to revalidate CLA status.

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment

Projects

None yet

Development

Successfully merging this pull request may close these issues.

2 participants