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ROCm Sparse Marlin Kernels #1206
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ROCm build infrastructure
[ROCm] Enable Tiled layout extension and minor changes to setup
🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/ao/1206
Note: Links to docs will display an error until the docs builds have been completed. ❌ 11 New FailuresAs of commit 00bc94d with merge base ce4822b (): NEW FAILURES - The following jobs have failed:
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@@ -46,9 +46,11 @@ def read_version(file_path="version.txt"): | |||
CUDAExtension, |
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I think you might enjoy stack based PR development https://github.com/modularml/stack-pr
@@ -19,6 +19,28 @@ | |||
#include "base.h" | |||
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namespace torchao { | |||
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@xw285cornell looking for some quick advice, do you recommend we support AMD by adding conditional compilation flags to our existing cuda kernels or be OK with some more copy paste?
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Chatted offline and indeed ifdefs are the way to go
Do you have performance numbers by any chance relative to fp16? wanna make sure the performance improvements are competitive with CUDA |
still WIP, but would you share the benchmark you guys are using? will try that on mi300x when the PR is ready. |
Ok holler at me again whenever you need a review. Really excited to see this land |
For benchmarking it is a little ad hoc the best place for this today would be to verify on: https://github.com/pytorch/ao/blob/main/torchao/_models/llama/generate.py |
[WIP] Built on top pf #1201. This pull request introduces support for ROCm (Radeon Open Compute) for sparse marling kernel in addition to CUDA, enabling the code to run on AMD GPUs.
The main changes involve conditional compilation to handle differences between CUDA and ROCm, as well as adding ROCm-specific intrinsics for MI300x.
co-author : @lcskrishna
Key changes include:
ROCm Support in
setup.py
:Conditional Compilation in CUDA Source Files:
ROCm-specific Implementations:
Next: