massive mips and loongarch optimization#6662
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Codecov Report❌ Patch coverage is Additional details and impacted files@@ Coverage Diff @@
## master #6662 +/- ##
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+ Coverage 95.83% 95.93% +0.09%
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Files 933 966 +33
Lines 312469 402676 +90207
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+ Hits 299448 386297 +86849
- Misses 13021 16379 +3358 ☔ View full report in Codecov by Sentry. 🚀 New features to boost your workflow:
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Add jj+=12 loop unrolling to pack_B_tile, transpose_pack_B_tile, transpose_unpack_output_tile, and gemm_transB_packed_tile for all ii sections (8, 4, 2, 1). MIPS MSA has 32 SIMD registers so jj+=12 fits well (24 registers for ii+=8, 12 for ii+=4). Update get_optimal_tile_mnk to align TILE_N to multiples of 12 for better utilization of the new kernel. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
…ngArch Integrate bf16 storage support into multiple operators: MIPS: batchnorm, clip, dropout, selu, erf LoongArch: batchnorm, clip, dropout Each operator now declares forward_inplace_bf16s in its header, sets support_bf16_storage=true in the constructor, dispatches bf16 inputs from forward_inplace, and implements the bf16s path using the existing bf16s helper headers. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
- Add support_bf16_storage = true in constructors for both architectures - Add crop_pack4_bf16s_msa() for MIPS MSA using int64_t copies (8 bytes) - Add crop_pack4_bf16s_lsx() for LoongArch LSX using int64_t copies - Add crop_pack8_lasx() for LoongArch LASX float pack8 (256-bit) - Add crop_pack8_bf16s_lsx() for LoongArch LASX bf16 pack8 (128-bit) - Dispatch to bf16 variants when elemsize matches bf16 packing - Remove debug fprintf statements from MIPS deconvolution_packed_bf16s.h Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
Add interp_bilinear_pack8.h and interp_bicubic_pack8.h implementing 256-bit SIMD (8 floats) resize operations using LASX intrinsics. Update interp_loongarch.cpp to: - Include lasxintrin.h and the new pack8 headers under __loongarch_asx - Add elempack == 8 paths for dims 1, 2, and 3 (nearest, bilinear, bicubic) Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
… approach - Replace hand-written kernel packing and convolution loops with convolution1d_transform_kernel_packed() and convolution1d_packed() from convolution1d_packed.h - Rename weight_data_packed to weight_data_tm to match x86 pattern - Add LASX (256-bit) support with pack8 out_elempack - Add NCNN_BF16 support using cast-based approach (bf16->fp32->conv->bf16) - Add bf16 weight/bias cast in dynamic weight forward path - Include cpu.h, lasxintrin.h headers for new functionality Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
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3a6000 loongnix-20
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