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Add Loongson Advanced SIMD Extension support: -DCPU_BASELINE=LASX
* Add Loongson Advanced SIMD Extension support: -DCPU_BASELINE=LASX * Add resize.lasx.cpp for Loongson SIMD acceleration * Add imgwarp.lasx.cpp for Loongson SIMD acceleration * Add LASX acceleration support for dnn/conv * Add CV_PAUSE(v) for Loongarch * Set LASX by default on Loongarch64 * LoongArch: tune test threshold for Core/HAL.mat_decomp/15 Co-authored-by: shengwenxue <shengwenxue@loongson.cn>
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wxsheng
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/*M///////////////////////////////////////////////////////////////////////////////////////
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//
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// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
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// By downloading, copying, installing or using the software you agree to this license.
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// If you do not agree to this license, do not download, install,
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// copy or use the software.
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//
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//
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// License Agreement
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// For Open Source Computer Vision Library
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//
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// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
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// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
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// Copyright (C) 2014-2015, Itseez Inc., all rights reserved.
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// Third party copyrights are property of their respective owners.
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// this list of conditions and the following disclaimer.
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// * Redistribution's in binary form must reproduce the above copyright notice,
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// * The name of the copyright holders may not be used to endorse or promote products
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// This software is provided by the copyright holders and contributors "as is" and
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// any express or implied warranties, including, but not limited to, the implied
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//M*/
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/* ////////////////////////////////////////////////////////////////////
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//
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// Geometrical transforms on images and matrices: rotation, zoom etc.
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//
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// */
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#include "precomp.hpp"
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#include "resize.hpp"
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#include "opencv2/core/hal/intrin.hpp"
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namespace cv
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{
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namespace opt_LASX
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{
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class resizeNNInvokerLASX4 CV_FINAL :
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public ParallelLoopBody
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{
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public:
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resizeNNInvokerLASX4(const Mat& _src, Mat &_dst, int *_x_ofs, double _ify) :
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ParallelLoopBody(), src(_src), dst(_dst), x_ofs(_x_ofs),
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ify(_ify)
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{
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}
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virtual void operator() (const Range& range) const CV_OVERRIDE
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{
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Size ssize = src.size(), dsize = dst.size();
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int y, x;
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int width = dsize.width;
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int avxWidth = width - (width & 0x7);
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if(((int64)(dst.data + dst.step) & 0x1f) == 0)
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{
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for(y = range.start; y < range.end; y++)
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{
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uchar* D = dst.data + dst.step*y;
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uchar* Dstart = D;
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int sy = std::min(cvFloor(y*ify), ssize.height-1);
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const uchar* S = src.data + sy*src.step;
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#ifdef CV_ICC
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#pragma unroll(4)
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#endif
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for(x = 0; x < avxWidth; x += 8)
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{
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const __m256i CV_DECL_ALIGNED(64) *addr = (__m256i*)(x_ofs + x);
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__m256i CV_DECL_ALIGNED(64) pixels = v256_lut_quads((schar *)S, (int *)addr).val;
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__lasx_xvst(pixels, (int*)D, 0);
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D += 32;
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}
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for(; x < width; x++)
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{
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*(int*)(Dstart + x*4) = *(int*)(S + x_ofs[x]);
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}
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}
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}
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else
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{
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for(y = range.start; y < range.end; y++)
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{
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uchar* D = dst.data + dst.step*y;
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uchar* Dstart = D;
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int sy = std::min(cvFloor(y*ify), ssize.height-1);
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const uchar* S = src.data + sy*src.step;
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#ifdef CV_ICC
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#pragma unroll(4)
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#endif
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for(x = 0; x < avxWidth; x += 8)
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{
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const __m256i CV_DECL_ALIGNED(64) *addr = (__m256i*)(x_ofs + x);
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__m256i CV_DECL_ALIGNED(64) pixels = v256_lut_quads((schar *)S, (int *)addr).val;
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__lasx_xvst(pixels, (int*)D, 0);
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D += 32;
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}
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for(; x < width; x++)
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{
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*(int*)(Dstart + x*4) = *(int*)(S + x_ofs[x]);
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}
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}
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}
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}
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private:
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const Mat& src;
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Mat& dst;
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int* x_ofs;
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double ify;
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resizeNNInvokerLASX4(const resizeNNInvokerLASX4&);
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resizeNNInvokerLASX4& operator=(const resizeNNInvokerLASX4&);
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};
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class resizeNNInvokerLASX2 CV_FINAL :
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public ParallelLoopBody
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{
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public:
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resizeNNInvokerLASX2(const Mat& _src, Mat &_dst, int *_x_ofs, double _ify) :
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ParallelLoopBody(), src(_src), dst(_dst), x_ofs(_x_ofs),
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ify(_ify)
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{
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}
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virtual void operator() (const Range& range) const CV_OVERRIDE
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{
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Size ssize = src.size(), dsize = dst.size();
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int y, x;
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int width = dsize.width;
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int avxWidth = width - (width & 0xf);
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const __m256i CV_DECL_ALIGNED(64) shuffle_mask = _v256_set_b(15,14,11,10,13,12,9,8,7,6,3,2,5,4,1,0,
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15,14,11,10,13,12,9,8,7,6,3,2,5,4,1,0);
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const __m256i CV_DECL_ALIGNED(64) permute_mask = _v256_set_w(7, 5, 3, 1, 6, 4, 2, 0);
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if(((int64)(dst.data + dst.step) & 0x1f) == 0)
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{
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for(y = range.start; y < range.end; y++)
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{
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uchar* D = dst.data + dst.step*y;
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uchar* Dstart = D;
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int sy = std::min(cvFloor(y*ify), ssize.height-1);
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const uchar* S = src.data + sy*src.step;
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const uchar* S2 = S - 2;
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#ifdef CV_ICC
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#pragma unroll(4)
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#endif
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for(x = 0; x < avxWidth; x += 16)
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{
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const __m256i CV_DECL_ALIGNED(64) *addr = (__m256i*)(x_ofs + x);
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__m256i CV_DECL_ALIGNED(64) pixels1 = v256_lut_quads((schar *)S, (int *)addr).val;
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const __m256i CV_DECL_ALIGNED(64) *addr2 = (__m256i*)(x_ofs + x + 8);
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__m256i CV_DECL_ALIGNED(64) pixels2 = v256_lut_quads((schar *)S2, (int *)addr2).val;
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const __m256i h_mask = __lasx_xvreplgr2vr_w(0xFFFF0000);
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__m256i CV_DECL_ALIGNED(64) unpacked = __lasx_xvbitsel_v(pixels1, pixels2, h_mask);
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__m256i CV_DECL_ALIGNED(64) bytes_shuffled = __lasx_xvshuf_b(unpacked, unpacked, shuffle_mask);
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__m256i CV_DECL_ALIGNED(64) ints_permuted = __lasx_xvperm_w(bytes_shuffled, permute_mask);
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__lasx_xvst(ints_permuted, (int*)D, 0);
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D += 32;
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}
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for(; x < width; x++)
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{
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*(ushort*)(Dstart + x*2) = *(ushort*)(S + x_ofs[x]);
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}
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}
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}
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else
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{
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for(y = range.start; y < range.end; y++)
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{
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uchar* D = dst.data + dst.step*y;
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uchar* Dstart = D;
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int sy = std::min(cvFloor(y*ify), ssize.height-1);
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const uchar* S = src.data + sy*src.step;
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const uchar* S2 = S - 2;
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#ifdef CV_ICC
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#pragma unroll(4)
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#endif
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for(x = 0; x < avxWidth; x += 16)
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{
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const __m256i CV_DECL_ALIGNED(64) *addr = (__m256i*)(x_ofs + x);
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__m256i CV_DECL_ALIGNED(64) pixels1 = v256_lut_quads((schar *)S, (int *)addr).val;
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const __m256i CV_DECL_ALIGNED(64) *addr2 = (__m256i*)(x_ofs + x + 8);
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__m256i CV_DECL_ALIGNED(64) pixels2 = v256_lut_quads((schar *)S2, (int *)addr2).val;
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const __m256i h_mask = __lasx_xvreplgr2vr_w(0xFFFF0000);
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__m256i CV_DECL_ALIGNED(64) unpacked = __lasx_xvbitsel_v(pixels1, pixels2, h_mask);
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__m256i CV_DECL_ALIGNED(64) bytes_shuffled = __lasx_xvshuf_b(unpacked, unpacked, shuffle_mask);
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__m256i CV_DECL_ALIGNED(64) ints_permuted = __lasx_xvperm_w(bytes_shuffled, permute_mask);
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__lasx_xvst(ints_permuted, (int*)D, 0);
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D += 32;
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}
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for(; x < width; x++)
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{
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*(ushort*)(Dstart + x*2) = *(ushort*)(S + x_ofs[x]);
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}
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}
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}
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}
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private:
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const Mat& src;
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Mat& dst;
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int* x_ofs;
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double ify;
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resizeNNInvokerLASX2(const resizeNNInvokerLASX2&);
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resizeNNInvokerLASX2& operator=(const resizeNNInvokerLASX2&);
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};
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void resizeNN2_LASX(const Range& range, const Mat& src, Mat &dst, int *x_ofs, double ify)
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{
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resizeNNInvokerLASX2 invoker(src, dst, x_ofs, ify);
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parallel_for_(range, invoker, dst.total() / (double)(1 << 16));
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}
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void resizeNN4_LASX(const Range& range, const Mat& src, Mat &dst, int *x_ofs, double ify)
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{
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resizeNNInvokerLASX4 invoker(src, dst, x_ofs, ify);
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parallel_for_(range, invoker, dst.total() / (double)(1 << 16));
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}
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}
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}
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/* End of file. */
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