Update hipDNN roadmap for end of Q1 2026#5569
Merged
dpeabody-amd merged 1 commit intodevelopfrom Mar 18, 2026
Merged
Conversation
Reflect actual completion status based on code review of hipDNN and dnn-providers. Q1 items completed ahead of schedule (Fusilli batchnorm, SDPA frontend, LayerNorm/RMSNorm frontend, Python POC, benchmarking tooling) are added with done status. PyTorch integration moved to early Q2 with upstream PR reference. Q2 updated with in-progress markers and current SDPA/normalization/GEMM status. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
BrianHarrisonAMD
approved these changes
Mar 18, 2026
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
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Outdated suggestions cannot be applied.This suggestion has been applied or marked resolved.Suggestions cannot be applied from pending reviews.Suggestions cannot be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.
Updated Q1 2026 status markers to reflect actual completion based on code review of hipDNN and dnn-providers\n- Added Q1 items completed ahead of schedule: Fusilli batchnorm, SDPA frontend API, LayerNorm/RMSNorm frontend, Python bindings POC, benchmarking tooling\n- Moved PyTorch integration to early Q2 with upstream PR reference\n- Updated Q2 with in-progress markers for SDPA, normalization, GEMM, and other active items\n- Moved client auto-tuning API from Q3 to Q2