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core: dispatch merge.cpp

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This commit is contained in:
Alexander Alekhin 2019-02-22 11:17:18 +00:00
parent 93a36b0df1
commit fd49ee5f39
3 changed files with 35 additions and 421 deletions
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1
modules/core/CMakeLists.txt
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@ -8,6 +8,7 @@ ocv_add_dispatched_file(convert_scale SSE2 AVX2)
ocv_add_dispatched_file(count_non_zero SSE2 AVX2)
ocv_add_dispatched_file(matmul SSE2 AVX2)
ocv_add_dispatched_file(mean SSE2 AVX2)
ocv_add_dispatched_file(merge SSE2 AVX2)
ocv_add_dispatched_file(split SSE2 AVX2)
ocv_add_dispatched_file(sum SSE2 AVX2)

208
modules/core/src/merge.dispatch.cpp
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@ -6,208 +6,44 @@
#include "precomp.hpp"
#include "opencl_kernels_core.hpp"
#include "merge.simd.hpp"
#include "merge.simd_declarations.hpp" // defines CV_CPU_DISPATCH_MODES_ALL=AVX2,...,BASELINE based on CMakeLists.txt content
namespace cv { namespace hal {
#if CV_SIMD
/*
The trick with STORE_UNALIGNED/STORE_ALIGNED_NOCACHE is the following:
on IA there are instructions movntps and such to which
v_store_interleave(...., STORE_ALIGNED_NOCACHE) is mapped.
Those instructions write directly into memory w/o touching cache
that results in dramatic speed improvements, especially on
large arrays (FullHD, 4K etc.).
Those intrinsics require the destination address to be aligned
by 16/32 bits (with SSE2 and AVX2, respectively).
So we potentially split the processing into 3 stages:
1) the optional prefix part [0:i0), where we use simple unaligned stores.
2) the optional main part [i0:len - VECSZ], where we use "nocache" mode.
But in some cases we have to use unaligned stores in this part.
3) the optional suffix part (the tail) (len - VECSZ:len) where we switch back to "unaligned" mode
to process the remaining len - VECSZ elements.
In principle there can be very poorly aligned data where there is no main part.
For that we set i0=0 and use unaligned stores for the whole array.
*/
template<typename T, typename VecT> static void
vecmerge_( const T** src, T* dst, int len, int cn )
{
const int VECSZ = VecT::nlanes;
int i, i0 = 0;
const T* src0 = src[0];
const T* src1 = src[1];
const int dstElemSize = cn * sizeof(T);
int r = (int)((size_t)(void*)dst % (VECSZ*sizeof(T)));
hal::StoreMode mode = hal::STORE_ALIGNED_NOCACHE;
if( r != 0 )
{
mode = hal::STORE_UNALIGNED;
if (r % dstElemSize == 0 && len > VECSZ*2)
i0 = VECSZ - (r / dstElemSize);
}
if( cn == 2 )
{
for( i = 0; i < len; i += VECSZ )
{
if( i > len - VECSZ )
{
i = len - VECSZ;
mode = hal::STORE_UNALIGNED;
}
VecT a = vx_load(src0 + i), b = vx_load(src1 + i);
v_store_interleave(dst + i*cn, a, b, mode);
if( i < i0 )
{
i = i0 - VECSZ;
mode = hal::STORE_ALIGNED_NOCACHE;
}
}
}
else if( cn == 3 )
{
const T* src2 = src[2];
for( i = 0; i < len; i += VECSZ )
{
if( i > len - VECSZ )
{
i = len - VECSZ;
mode = hal::STORE_UNALIGNED;
}
VecT a = vx_load(src0 + i), b = vx_load(src1 + i), c = vx_load(src2 + i);
v_store_interleave(dst + i*cn, a, b, c, mode);
if( i < i0 )
{
i = i0 - VECSZ;
mode = hal::STORE_ALIGNED_NOCACHE;
}
}
}
else
{
CV_Assert( cn == 4 );
const T* src2 = src[2];
const T* src3 = src[3];
for( i = 0; i < len; i += VECSZ )
{
if( i > len - VECSZ )
{
i = len - VECSZ;
mode = hal::STORE_UNALIGNED;
}
VecT a = vx_load(src0 + i), b = vx_load(src1 + i);
VecT c = vx_load(src2 + i), d = vx_load(src3 + i);
v_store_interleave(dst + i*cn, a, b, c, d, mode);
if( i < i0 )
{
i = i0 - VECSZ;
mode = hal::STORE_ALIGNED_NOCACHE;
}
}
}
vx_cleanup();
}
#endif
template<typename T> static void
merge_( const T** src, T* dst, int len, int cn )
{
int k = cn % 4 ? cn % 4 : 4;
int i, j;
if( k == 1 )
{
const T* src0 = src[0];
for( i = j = 0; i < len; i++, j += cn )
dst[j] = src0[i];
}
else if( k == 2 )
{
const T *src0 = src[0], *src1 = src[1];
i = j = 0;
for( ; i < len; i++, j += cn )
{
dst[j] = src0[i];
dst[j+1] = src1[i];
}
}
else if( k == 3 )
{
const T *src0 = src[0], *src1 = src[1], *src2 = src[2];
i = j = 0;
for( ; i < len; i++, j += cn )
{
dst[j] = src0[i];
dst[j+1] = src1[i];
dst[j+2] = src2[i];
}
}
else
{
const T *src0 = src[0], *src1 = src[1], *src2 = src[2], *src3 = src[3];
i = j = 0;
for( ; i < len; i++, j += cn )
{
dst[j] = src0[i]; dst[j+1] = src1[i];
dst[j+2] = src2[i]; dst[j+3] = src3[i];
}
}
for( ; k < cn; k += 4 )
{
const T *src0 = src[k], *src1 = src[k+1], *src2 = src[k+2], *src3 = src[k+3];
for( i = 0, j = k; i < len; i++, j += cn )
{
dst[j] = src0[i]; dst[j+1] = src1[i];
dst[j+2] = src2[i]; dst[j+3] = src3[i];
}
}
}
void merge8u(const uchar** src, uchar* dst, int len, int cn )
{
CV_INSTRUMENT_REGION();
CALL_HAL(merge8u, cv_hal_merge8u, src, dst, len, cn)
#if CV_SIMD
if( len >= v_uint8::nlanes && 2 <= cn && cn <= 4 )
vecmerge_<uchar, v_uint8>(src, dst, len, cn);
else
#endif
merge_(src, dst, len, cn);
CV_CPU_DISPATCH(merge8u, (src, dst, len, cn),
CV_CPU_DISPATCH_MODES_ALL);
}
void merge16u(const ushort** src, ushort* dst, int len, int cn )
{
CV_INSTRUMENT_REGION();
CALL_HAL(merge16u, cv_hal_merge16u, src, dst, len, cn)
#if CV_SIMD
if( len >= v_uint16::nlanes && 2 <= cn && cn <= 4 )
vecmerge_<ushort, v_uint16>(src, dst, len, cn);
else
#endif
merge_(src, dst, len, cn);
CV_CPU_DISPATCH(merge16u, (src, dst, len, cn),
CV_CPU_DISPATCH_MODES_ALL);
}
void merge32s(const int** src, int* dst, int len, int cn )
{
CV_INSTRUMENT_REGION();
CALL_HAL(merge32s, cv_hal_merge32s, src, dst, len, cn)
#if CV_SIMD
if( len >= v_int32::nlanes && 2 <= cn && cn <= 4 )
vecmerge_<int, v_int32>(src, dst, len, cn);
else
#endif
merge_(src, dst, len, cn);
CV_CPU_DISPATCH(merge32s, (src, dst, len, cn),
CV_CPU_DISPATCH_MODES_ALL);
}
void merge64s(const int64** src, int64* dst, int len, int cn )
{
CV_INSTRUMENT_REGION();
CALL_HAL(merge64s, cv_hal_merge64s, src, dst, len, cn)
#if CV_SIMD
if( len >= v_int64::nlanes && 2 <= cn && cn <= 4 )
vecmerge_<int64, v_int64>(src, dst, len, cn);
else
#endif
merge_(src, dst, len, cn);
CV_CPU_DISPATCH(merge64s, (src, dst, len, cn),
CV_CPU_DISPATCH_MODES_ALL);
}
}} // cv::hal::
} // namespace cv::hal::
typedef void (*MergeFunc)(const uchar** src, uchar* dst, int len, int cn);
@ -225,7 +61,6 @@ static MergeFunc getMergeFunc(int depth)
#ifdef HAVE_IPP
namespace cv {
static bool ipp_merge(const Mat* mv, Mat& dst, int channels)
{
#ifdef HAVE_IPP_IW_LL
@ -274,10 +109,9 @@ static bool ipp_merge(const Mat* mv, Mat& dst, int channels)
return false;
#endif
}
}
#endif
void cv::merge(const Mat* mv, size_t n, OutputArray _dst)
void merge(const Mat* mv, size_t n, OutputArray _dst)
{
CV_INSTRUMENT_REGION();
@ -361,8 +195,6 @@ void cv::merge(const Mat* mv, size_t n, OutputArray _dst)
#ifdef HAVE_OPENCL
namespace cv {
static bool ocl_merge( InputArrayOfArrays _mv, OutputArray _dst )
{
std::vector<UMat> src, ksrc;
@ -421,11 +253,9 @@ static bool ocl_merge( InputArrayOfArrays _mv, OutputArray _dst )
return k.run(2, globalsize, NULL, false);
}
}
#endif
void cv::merge(InputArrayOfArrays _mv, OutputArray _dst)
void merge(InputArrayOfArrays _mv, OutputArray _dst)
{
CV_INSTRUMENT_REGION();
@ -436,3 +266,5 @@ void cv::merge(InputArrayOfArrays _mv, OutputArray _dst)
_mv.getMatVector(mv);
merge(!mv.empty() ? &mv[0] : 0, mv.size(), _dst);
}
} // namespace

247
modules/core/src/merge.simd.hpp
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@ -4,9 +4,16 @@
#include "precomp.hpp"
#include "opencl_kernels_core.hpp"
namespace cv { namespace hal {
CV_CPU_OPTIMIZATION_NAMESPACE_BEGIN
void merge8u(const uchar** src, uchar* dst, int len, int cn);
void merge16u(const ushort** src, ushort* dst, int len, int cn);
void merge32s(const int** src, int* dst, int len, int cn);
void merge64s(const int64** src, int64* dst, int len, int cn);
#ifndef CV_CPU_OPTIMIZATION_DECLARATIONS_ONLY
#if CV_SIMD
/*
@ -165,7 +172,7 @@ merge_( const T** src, T* dst, int len, int cn )
void merge8u(const uchar** src, uchar* dst, int len, int cn )
{
CALL_HAL(merge8u, cv_hal_merge8u, src, dst, len, cn)
CV_INSTRUMENT_REGION();
#if CV_SIMD
if( len >= v_uint8::nlanes && 2 <= cn && cn <= 4 )
vecmerge_<uchar, v_uint8>(src, dst, len, cn);
@ -176,7 +183,7 @@ void merge8u(const uchar** src, uchar* dst, int len, int cn )
void merge16u(const ushort** src, ushort* dst, int len, int cn )
{
CALL_HAL(merge16u, cv_hal_merge16u, src, dst, len, cn)
CV_INSTRUMENT_REGION();
#if CV_SIMD
if( len >= v_uint16::nlanes && 2 <= cn && cn <= 4 )
vecmerge_<ushort, v_uint16>(src, dst, len, cn);
@ -187,7 +194,7 @@ void merge16u(const ushort** src, ushort* dst, int len, int cn )
void merge32s(const int** src, int* dst, int len, int cn )
{
CALL_HAL(merge32s, cv_hal_merge32s, src, dst, len, cn)
CV_INSTRUMENT_REGION();
#if CV_SIMD
if( len >= v_int32::nlanes && 2 <= cn && cn <= 4 )
vecmerge_<int, v_int32>(src, dst, len, cn);
@ -198,7 +205,7 @@ void merge32s(const int** src, int* dst, int len, int cn )
void merge64s(const int64** src, int64* dst, int len, int cn )
{
CALL_HAL(merge64s, cv_hal_merge64s, src, dst, len, cn)
CV_INSTRUMENT_REGION();
#if CV_SIMD
if( len >= v_int64::nlanes && 2 <= cn && cn <= 4 )
vecmerge_<int64, v_int64>(src, dst, len, cn);
@ -207,232 +214,6 @@ void merge64s(const int64** src, int64* dst, int len, int cn )
merge_(src, dst, len, cn);
}
}} // cv::hal::
typedef void (*MergeFunc)(const uchar** src, uchar* dst, int len, int cn);
static MergeFunc getMergeFunc(int depth)
{
static MergeFunc mergeTab[] =
{
(MergeFunc)GET_OPTIMIZED(cv::hal::merge8u), (MergeFunc)GET_OPTIMIZED(cv::hal::merge8u), (MergeFunc)GET_OPTIMIZED(cv::hal::merge16u), (MergeFunc)GET_OPTIMIZED(cv::hal::merge16u),
(MergeFunc)GET_OPTIMIZED(cv::hal::merge32s), (MergeFunc)GET_OPTIMIZED(cv::hal::merge32s), (MergeFunc)GET_OPTIMIZED(cv::hal::merge64s), 0
};
return mergeTab[depth];
}
#ifdef HAVE_IPP
namespace cv {
static bool ipp_merge(const Mat* mv, Mat& dst, int channels)
{
#ifdef HAVE_IPP_IW_LL
CV_INSTRUMENT_REGION_IPP();
if(channels != 3 && channels != 4)
return false;
if(mv[0].dims <= 2)
{
IppiSize size = ippiSize(mv[0].size());
const void *srcPtrs[4] = {NULL};
size_t srcStep = mv[0].step;
for(int i = 0; i < channels; i++)
{
srcPtrs[i] = mv[i].ptr();
if(srcStep != mv[i].step)
return false;
}
return CV_INSTRUMENT_FUN_IPP(llwiCopyMerge, srcPtrs, (int)srcStep, dst.ptr(), (int)dst.step, size, (int)mv[0].elemSize1(), channels, 0) >= 0;
}
else
{
const Mat *arrays[5] = {NULL};
uchar *ptrs[5] = {NULL};
arrays[0] = &dst;
for(int i = 1; i < channels; i++)
{
arrays[i] = &mv[i-1];
}
NAryMatIterator it(arrays, ptrs);
IppiSize size = { (int)it.size, 1 };
for( size_t i = 0; i < it.nplanes; i++, ++it )
{
if(CV_INSTRUMENT_FUN_IPP(llwiCopyMerge, (const void**)&ptrs[1], 0, ptrs[0], 0, size, (int)mv[0].elemSize1(), channels, 0) < 0)
return false;
}
return true;
}
#else
CV_UNUSED(dst); CV_UNUSED(mv); CV_UNUSED(channels);
return false;
#endif
}
}
#endif
void cv::merge(const Mat* mv, size_t n, OutputArray _dst)
{
CV_INSTRUMENT_REGION();
CV_Assert( mv && n > 0 );
int depth = mv[0].depth();
bool allch1 = true;
int k, cn = 0;
size_t i;
for( i = 0; i < n; i++ )
{
CV_Assert(mv[i].size == mv[0].size && mv[i].depth() == depth);
allch1 = allch1 && mv[i].channels() == 1;
cn += mv[i].channels();
}
CV_Assert( 0 < cn && cn <= CV_CN_MAX );
_dst.create(mv[0].dims, mv[0].size, CV_MAKETYPE(depth, cn));
Mat dst = _dst.getMat();
if( n == 1 )
{
mv[0].copyTo(dst);
return;
}
CV_IPP_RUN(allch1, ipp_merge(mv, dst, (int)n));
if( !allch1 )
{
AutoBuffer<int> pairs(cn*2);
int j, ni=0;
for( i = 0, j = 0; i < n; i++, j += ni )
{
ni = mv[i].channels();
for( k = 0; k < ni; k++ )
{
pairs[(j+k)*2] = j + k;
pairs[(j+k)*2+1] = j + k;
}
}
mixChannels( mv, n, &dst, 1, &pairs[0], cn );
return;
}
MergeFunc func = getMergeFunc(depth);
CV_Assert( func != 0 );
size_t esz = dst.elemSize(), esz1 = dst.elemSize1();
size_t blocksize0 = (int)((BLOCK_SIZE + esz-1)/esz);
AutoBuffer<uchar> _buf((cn+1)*(sizeof(Mat*) + sizeof(uchar*)) + 16);
const Mat** arrays = (const Mat**)_buf.data();
uchar** ptrs = (uchar**)alignPtr(arrays + cn + 1, 16);
arrays[0] = &dst;
for( k = 0; k < cn; k++ )
arrays[k+1] = &mv[k];
NAryMatIterator it(arrays, ptrs, cn+1);
size_t total = (int)it.size;
size_t blocksize = std::min((size_t)CV_SPLIT_MERGE_MAX_BLOCK_SIZE(cn), cn <= 4 ? total : std::min(total, blocksize0));
for( i = 0; i < it.nplanes; i++, ++it )
{
for( size_t j = 0; j < total; j += blocksize )
{
size_t bsz = std::min(total - j, blocksize);
func( (const uchar**)&ptrs[1], ptrs[0], (int)bsz, cn );
if( j + blocksize < total )
{
ptrs[0] += bsz*esz;
for( int t = 0; t < cn; t++ )
ptrs[t+1] += bsz*esz1;
}
}
}
}
#ifdef HAVE_OPENCL
namespace cv {
static bool ocl_merge( InputArrayOfArrays _mv, OutputArray _dst )
{
std::vector<UMat> src, ksrc;
_mv.getUMatVector(src);
CV_Assert(!src.empty());
int type = src[0].type(), depth = CV_MAT_DEPTH(type),
rowsPerWI = ocl::Device::getDefault().isIntel() ? 4 : 1;
Size size = src[0].size();
for (size_t i = 0, srcsize = src.size(); i < srcsize; ++i)
{
int itype = src[i].type(), icn = CV_MAT_CN(itype), idepth = CV_MAT_DEPTH(itype),
esz1 = CV_ELEM_SIZE1(idepth);
if (src[i].dims > 2)
return false;
CV_Assert(size == src[i].size() && depth == idepth);
for (int cn = 0; cn < icn; ++cn)
{
UMat tsrc = src[i];
tsrc.offset += cn * esz1;
ksrc.push_back(tsrc);
}
}
int dcn = (int)ksrc.size();
String srcargs, processelem, cndecl, indexdecl;
for (int i = 0; i < dcn; ++i)
{
srcargs += format("DECLARE_SRC_PARAM(%d)", i);
processelem += format("PROCESS_ELEM(%d)", i);
indexdecl += format("DECLARE_INDEX(%d)", i);
cndecl += format(" -D scn%d=%d", i, ksrc[i].channels());
}
ocl::Kernel k("merge", ocl::core::split_merge_oclsrc,
format("-D OP_MERGE -D cn=%d -D T=%s -D DECLARE_SRC_PARAMS_N=%s"
" -D DECLARE_INDEX_N=%s -D PROCESS_ELEMS_N=%s%s",
dcn, ocl::memopTypeToStr(depth), srcargs.c_str(),
indexdecl.c_str(), processelem.c_str(), cndecl.c_str()));
if (k.empty())
return false;
_dst.create(size, CV_MAKE_TYPE(depth, dcn));
UMat dst = _dst.getUMat();
int argidx = 0;
for (int i = 0; i < dcn; ++i)
argidx = k.set(argidx, ocl::KernelArg::ReadOnlyNoSize(ksrc[i]));
argidx = k.set(argidx, ocl::KernelArg::WriteOnly(dst));
k.set(argidx, rowsPerWI);
size_t globalsize[2] = { (size_t)dst.cols, ((size_t)dst.rows + rowsPerWI - 1) / rowsPerWI };
return k.run(2, globalsize, NULL, false);
}
}
#endif
void cv::merge(InputArrayOfArrays _mv, OutputArray _dst)
{
CV_INSTRUMENT_REGION();
CV_OCL_RUN(_mv.isUMatVector() && _dst.isUMat(),
ocl_merge(_mv, _dst))
std::vector<Mat> mv;
_mv.getMatVector(mv);
merge(!mv.empty() ? &mv[0] : 0, mv.size(), _dst);
}
CV_CPU_OPTIMIZATION_NAMESPACE_END
}} // namespace