Difference between revisions of "Porting/ncnn"
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JeremyRand (talk | contribs) (Finished: Update Vulkan dependency docs) |
JeremyRand (talk | contribs) (Move to subcategory) |
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* [https://github.com/Tencent/ncnn/pull/5174 Update POWER Clang version docs] | * [https://github.com/Tencent/ncnn/pull/5174 Update POWER Clang version docs] | ||
* [https://github.com/Tencent/ncnn/pull/5178 Update Vulkan dependency docs] | * [https://github.com/Tencent/ncnn/pull/5178 Update Vulkan dependency docs] | ||
| + | * [https://github.com/Tencent/ncnn/pull/5228 Document libomp-dev dependency] | ||
| + | * [https://github.com/Tencent/ncnn/pull/5229 python: document CMAKE_TOOLCHAIN_FILE env var] | ||
= In progress = | = In progress = | ||
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* CI missing for POWER9/Clang | * CI missing for POWER9/Clang | ||
* Replace SSE with native VSX | * Replace SSE with native VSX | ||
| + | |||
| + | = VSX Targets = | ||
| + | |||
| + | When running Real-ESRGAN in ncnn on POWER9, most CPU time (over 81%) is spent inside [https://github.com/Tencent/ncnn/blob/575098640c254be2208095254f3e5de412751447/src/layer/x86/convolution_3x3_winograd.h#L613 <code>gemm_transB_packed_tile</code> in <code>convolution_3x3_winograd.h</code>], which uses SSE2. This may be a good target for rewriting in native VSX. | ||
= See Also = | = See Also = | ||
| Line 21: | Line 27: | ||
* [[Porting/PyTorch|PyTorch]] | * [[Porting/PyTorch|PyTorch]] | ||
| − | [[Category:Ports]] | + | [[Category:Ports/AI]] |
Latest revision as of 15:40, 18 May 2025
Contents
Finished
- Translate x86_64 SSE to ppc64le VSX intrinsics
- VSX toolchains: check for SSE2 support
- Add POWER8 VSX toolchains
- load_param_mem pybind
- test_squeezenet failed under Lubuntu 16.04 PowerPC 32-bit
- support big endian platform, add powerpc ci
- Update POWER Clang version docs
- Update Vulkan dependency docs
- Document libomp-dev dependency
- python: document CMAKE_TOOLCHAIN_FILE env var
In progress
- CI missing for POWER9/Clang
- Replace SSE with native VSX
VSX Targets
When running Real-ESRGAN in ncnn on POWER9, most CPU time (over 81%) is spent inside gemm_transB_packed_tile in convolution_3x3_winograd.h, which uses SSE2. This may be a good target for rewriting in native VSX.
