improved cv::ocl::predictOptimalVectorWidth

This commit is contained in:
Ilya Lavrenov 2014-07-09 19:57:27 +04:00
parent a350b76738
commit 2c6b7a52e9
2 changed files with 38 additions and 22 deletions

View File

@ -598,9 +598,24 @@ CV_EXPORTS const char* typeToStr(int t);
CV_EXPORTS const char* memopTypeToStr(int t);
CV_EXPORTS String kernelToStr(InputArray _kernel, int ddepth = -1, const char * name = NULL);
CV_EXPORTS void getPlatfomsInfo(std::vector<PlatformInfo>& platform_info);
enum OclVectorStrategy
{
// all matrices have its own vector width
OCL_VECTOR_OWN = 0,
// all matrices have maximal vector width among all matrices
// (useful for cases when matrices have different data types)
OCL_VECTOR_MAX = 1,
// default strategy
OCL_VECTOR_DEFAULT = OCL_VECTOR_OWN
};
CV_EXPORTS int predictOptimalVectorWidth(InputArray src1, InputArray src2 = noArray(), InputArray src3 = noArray(),
InputArray src4 = noArray(), InputArray src5 = noArray(), InputArray src6 = noArray(),
InputArray src7 = noArray(), InputArray src8 = noArray(), InputArray src9 = noArray());
InputArray src7 = noArray(), InputArray src8 = noArray(), InputArray src9 = noArray(),
OclVectorStrategy strat = OCL_VECTOR_DEFAULT);
CV_EXPORTS void buildOptionsAddMatrixDescription(String& buildOptions, const String& name, InputArray _m);

View File

@ -4451,42 +4451,45 @@ String kernelToStr(InputArray _kernel, int ddepth, const char * name)
if (!src.empty()) \
{ \
CV_Assert(src.isMat() || src.isUMat()); \
int ctype = src.type(), ccn = CV_MAT_CN(ctype); \
Size csize = src.size(); \
cols.push_back(ccn * csize.width); \
if (ctype != type) \
int ctype = src.type(), ccn = CV_MAT_CN(ctype), cdepth = CV_MAT_DEPTH(ctype), \
ckercn = vectorWidths[cdepth], cwidth = ccn * csize.width; \
if (cwidth < ckercn || ckercn <= 0) \
return 1; \
cols.push_back(cwidth); \
if (strat == OCL_VECTOR_OWN && ctype != ref_type) \
return 1; \
offsets.push_back(src.offset()); \
steps.push_back(src.step()); \
dividers.push_back(ckercn * CV_ELEM_SIZE1(ctype)); \
} \
} \
while ((void)0, 0)
int predictOptimalVectorWidth(InputArray src1, InputArray src2, InputArray src3,
InputArray src4, InputArray src5, InputArray src6,
InputArray src7, InputArray src8, InputArray src9)
InputArray src7, InputArray src8, InputArray src9,
OclVectorStrategy strat)
{
int type = src1.type(), depth = CV_MAT_DEPTH(type), cn = CV_MAT_CN(type), esz1 = CV_ELEM_SIZE1(depth);
Size ssize = src1.size();
const ocl::Device & d = ocl::Device::getDefault();
int ref_type = src1.type();
int vectorWidths[] = { d.preferredVectorWidthChar(), d.preferredVectorWidthChar(),
d.preferredVectorWidthShort(), d.preferredVectorWidthShort(),
d.preferredVectorWidthInt(), d.preferredVectorWidthFloat(),
d.preferredVectorWidthDouble(), -1 }, kercn = vectorWidths[depth];
d.preferredVectorWidthDouble(), -1 };
// if the device says don't use vectors
if (vectorWidths[0] == 1)
{
// it's heuristic
int vectorWidthsOthers[] = { 16, 16, 8, 8, 1, 1, 1, -1 };
kercn = vectorWidthsOthers[depth];
vectorWidths[0] = vectorWidths[1] = 4;
vectorWidths[2] = vectorWidths[3] = 2;
vectorWidths[4] = vectorWidths[5] = vectorWidths[6] = 4;
}
if (ssize.width * cn < kercn || kercn <= 0)
return 1;
std::vector<size_t> offsets, steps, cols;
std::vector<int> dividers;
PROCESS_SRC(src1);
PROCESS_SRC(src2);
PROCESS_SRC(src3);
@ -4498,23 +4501,21 @@ int predictOptimalVectorWidth(InputArray src1, InputArray src2, InputArray src3,
PROCESS_SRC(src9);
size_t size = offsets.size();
int wsz = kercn * esz1;
std::vector<int> dividers(size, wsz);
for (size_t i = 0; i < size; ++i)
while (offsets[i] % dividers[i] != 0 || steps[i] % dividers[i] != 0 || cols[i] % dividers[i] != 0)
dividers[i] >>= 1;
// default strategy
for (size_t i = 0; i < size; ++i)
if (dividers[i] != wsz)
{
kercn = 1;
break;
}
int kercn = *std::min_element(dividers.begin(), dividers.end());
// another strategy
// width = *std::min_element(dividers.begin(), dividers.end());
// for (size_t i = 0; i < size; ++i)
// if (dividers[i] != wsz)
// {
// kercn = 1;
// break;
// }
return kercn;
}