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Further optimize bfmatcher by passing macros.
This commit is contained in:
peng xiao
parent
113b7584e0
commit
6eefd276cf
@ -16,6 +16,7 @@
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//
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// @Authors
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// Nathan, liujun@multicorewareinc.com
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// Peng Xiao, pengxiao@outlook.com
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//
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// Redistribution and use in source and binary forms, with or without modification,
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// are permitted provided that the following conditions are met:
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@ -61,6 +62,8 @@ namespace cv
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}
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}
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static const int OPT_SIZE = 100;
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template < int BLOCK_SIZE, int MAX_DESC_LEN/*, typename Mask*/ >
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void matchUnrolledCached(const oclMat &query, const oclMat &train, const oclMat &/*mask*/,
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const oclMat &trainIdx, const oclMat &distance, int distType)
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@ -74,9 +77,9 @@ void matchUnrolledCached(const oclMat &query, const oclMat &train, const oclMat
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int m_size = MAX_DESC_LEN;
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vector< pair<size_t, const void *> > args;
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static const int OPT_SIZE = 40;
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char opt [OPT_SIZE] = "";
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sprintf(opt, "-D block_size=%d -D max_desc_len=%d", block_size, m_size);
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sprintf(opt, "-D distType=%d -D block_size=%d -D max_desc_len=%d", distType, block_size, m_size);
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if(globalSize[0] != 0)
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{
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args.push_back( make_pair( sizeof(cl_mem), (void *)&query.data ));
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@ -90,7 +93,6 @@ void matchUnrolledCached(const oclMat &query, const oclMat &train, const oclMat
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args.push_back( make_pair( sizeof(cl_int), (void *)&train.rows ));
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args.push_back( make_pair( sizeof(cl_int), (void *)&train.cols ));
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args.push_back( make_pair( sizeof(cl_int), (void *)&query.step ));
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args.push_back( make_pair( sizeof(cl_int), (void *)&distType ));
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std::string kernelName = "BruteForceMatch_UnrollMatch";
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@ -116,9 +118,9 @@ void match(const oclMat &query, const oclMat &train, const oclMat &/*mask*/,
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int block_size = BLOCK_SIZE;
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vector< pair<size_t, const void *> > args;
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static const int OPT_SIZE = 40;
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char opt [OPT_SIZE] = "";
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sprintf(opt, "-D block_size=%d", block_size);
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sprintf(opt, "-D distType=%d -D block_size=%d", distType, block_size);
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if(globalSize[0] != 0)
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{
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args.push_back( make_pair( sizeof(cl_mem), (void *)&query.data ));
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@ -132,7 +134,6 @@ void match(const oclMat &query, const oclMat &train, const oclMat &/*mask*/,
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args.push_back( make_pair( sizeof(cl_int), (void *)&train.rows ));
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args.push_back( make_pair( sizeof(cl_int), (void *)&train.cols ));
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args.push_back( make_pair( sizeof(cl_int), (void *)&query.step ));
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args.push_back( make_pair( sizeof(cl_int), (void *)&distType ));
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std::string kernelName = "BruteForceMatch_Match";
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@ -160,9 +161,9 @@ void matchUnrolledCached(const oclMat &query, const oclMat &train, float maxDist
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int m_size = MAX_DESC_LEN;
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vector< pair<size_t, const void *> > args;
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static const int OPT_SIZE = 40;
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char opt [OPT_SIZE] = "";
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sprintf(opt, "-D block_size=%d -D max_desc_len=%d", block_size, m_size);
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sprintf(opt, "-D distType=%d -D block_size=%d -D max_desc_len=%d", distType, block_size, m_size);
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if(globalSize[0] != 0)
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{
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args.push_back( make_pair( sizeof(cl_mem), (void *)&query.data ));
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@ -180,7 +181,6 @@ void matchUnrolledCached(const oclMat &query, const oclMat &train, float maxDist
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args.push_back( make_pair( sizeof(cl_int), (void *)&trainIdx.cols ));
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args.push_back( make_pair( sizeof(cl_int), (void *)&query.step ));
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args.push_back( make_pair( sizeof(cl_int), (void *)&trainIdx.step ));
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args.push_back( make_pair( sizeof(cl_int), (void *)&distType ));
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std::string kernelName = "BruteForceMatch_RadiusUnrollMatch";
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@ -201,9 +201,9 @@ void radius_match(const oclMat &query, const oclMat &train, float maxDistance, c
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int block_size = BLOCK_SIZE;
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vector< pair<size_t, const void *> > args;
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static const int OPT_SIZE = 40;
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char opt [OPT_SIZE] = "";
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sprintf(opt, "-D block_size=%d", block_size);
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sprintf(opt, "-D distType=%d -D block_size=%d", distType, block_size);
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if(globalSize[0] != 0)
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{
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args.push_back( make_pair( sizeof(cl_mem), (void *)&query.data ));
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@ -221,7 +221,6 @@ void radius_match(const oclMat &query, const oclMat &train, float maxDistance, c
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args.push_back( make_pair( sizeof(cl_int), (void *)&trainIdx.cols ));
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args.push_back( make_pair( sizeof(cl_int), (void *)&query.step ));
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args.push_back( make_pair( sizeof(cl_int), (void *)&trainIdx.step ));
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args.push_back( make_pair( sizeof(cl_int), (void *)&distType ));
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std::string kernelName = "BruteForceMatch_RadiusMatch";
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@ -300,9 +299,9 @@ void knn_matchUnrolledCached(const oclMat &query, const oclMat &train, const ocl
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int m_size = MAX_DESC_LEN;
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vector< pair<size_t, const void *> > args;
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static const int OPT_SIZE = 40;
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char opt [OPT_SIZE] = "";
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sprintf(opt, "-D block_size=%d -D max_desc_len=%d", block_size, m_size);
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sprintf(opt, "-D distType=%d -D block_size=%d -D max_desc_len=%d", distType, block_size, m_size);
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if(globalSize[0] != 0)
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{
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args.push_back( make_pair( sizeof(cl_mem), (void *)&query.data ));
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@ -316,7 +315,6 @@ void knn_matchUnrolledCached(const oclMat &query, const oclMat &train, const ocl
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args.push_back( make_pair( sizeof(cl_int), (void *)&train.rows ));
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args.push_back( make_pair( sizeof(cl_int), (void *)&train.cols ));
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args.push_back( make_pair( sizeof(cl_int), (void *)&query.step ));
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args.push_back( make_pair( sizeof(cl_int), (void *)&distType ));
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std::string kernelName = "BruteForceMatch_knnUnrollMatch";
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@ -335,9 +333,9 @@ void knn_match(const oclMat &query, const oclMat &train, const oclMat &/*mask*/,
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int block_size = BLOCK_SIZE;
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vector< pair<size_t, const void *> > args;
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static const int OPT_SIZE = 40;
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char opt [OPT_SIZE] = "";
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sprintf(opt, "-D block_size=%d", block_size);
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sprintf(opt, "-D distType=%d -D block_size=%d", distType, block_size);
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if(globalSize[0] != 0)
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{
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args.push_back( make_pair( sizeof(cl_mem), (void *)&query.data ));
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@ -351,7 +349,6 @@ void knn_match(const oclMat &query, const oclMat &train, const oclMat &/*mask*/,
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args.push_back( make_pair( sizeof(cl_int), (void *)&train.rows ));
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args.push_back( make_pair( sizeof(cl_int), (void *)&train.cols ));
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args.push_back( make_pair( sizeof(cl_int), (void *)&query.step ));
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args.push_back( make_pair( sizeof(cl_int), (void *)&distType ));
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std::string kernelName = "BruteForceMatch_knnMatch";
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@ -370,6 +367,8 @@ void calcDistanceUnrolled(const oclMat &query, const oclMat &train, const oclMat
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int m_size = MAX_DESC_LEN;
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vector< pair<size_t, const void *> > args;
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char opt [OPT_SIZE] = "";
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sprintf(opt, "-D distType=%d", distType);
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if(globalSize[0] != 0)
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{
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args.push_back( make_pair( sizeof(cl_mem), (void *)&query.data ));
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@ -384,11 +383,10 @@ void calcDistanceUnrolled(const oclMat &query, const oclMat &train, const oclMat
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args.push_back( make_pair( sizeof(cl_int), (void *)&train.rows ));
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args.push_back( make_pair( sizeof(cl_int), (void *)&train.cols ));
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args.push_back( make_pair( sizeof(cl_int), (void *)&query.step ));
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args.push_back( make_pair( sizeof(cl_int), (void *)&distType ));
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std::string kernelName = "BruteForceMatch_calcDistanceUnrolled";
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openCLExecuteKernel(ctx, &brute_force_match, kernelName, globalSize, localSize, args, -1, query.depth());
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openCLExecuteKernel(ctx, &brute_force_match, kernelName, globalSize, localSize, args, -1, query.depth(), opt);
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}
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}
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@ -402,6 +400,8 @@ void calcDistance(const oclMat &query, const oclMat &train, const oclMat &/*mask
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int block_size = BLOCK_SIZE;
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vector< pair<size_t, const void *> > args;
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char opt [OPT_SIZE] = "";
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sprintf(opt, "-D distType=%d", distType);
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if(globalSize[0] != 0)
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{
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args.push_back( make_pair( sizeof(cl_mem), (void *)&query.data ));
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@ -415,11 +415,10 @@ void calcDistance(const oclMat &query, const oclMat &train, const oclMat &/*mask
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args.push_back( make_pair( sizeof(cl_int), (void *)&train.rows ));
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args.push_back( make_pair( sizeof(cl_int), (void *)&train.cols ));
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args.push_back( make_pair( sizeof(cl_int), (void *)&query.step ));
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args.push_back( make_pair( sizeof(cl_int), (void *)&distType ));
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std::string kernelName = "BruteForceMatch_calcDistance";
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openCLExecuteKernel(ctx, &brute_force_match, kernelName, globalSize, localSize, args, -1, query.depth());
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openCLExecuteKernel(ctx, &brute_force_match, kernelName, globalSize, localSize, args, -1, query.depth(), opt);
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}
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}
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@ -676,12 +675,14 @@ void cv::ocl::BruteForceMatcher_OCL_base::matchCollection(const oclMat &query, c
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}
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CV_Assert(query.channels() == 1 && query.depth() < CV_64F);
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const int nQuery = query.rows;
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ensureSizeIsEnough(1, nQuery, CV_32S, trainIdx);
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ensureSizeIsEnough(1, nQuery, CV_32S, imgIdx);
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ensureSizeIsEnough(1, nQuery, CV_32F, distance);
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matchDispatcher(query, (const oclMat *)trainCollection.ptr(), trainCollection.cols, masks, trainIdx, imgIdx, distance, distType);
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exit:
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return;
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@ -771,6 +772,7 @@ void cv::ocl::BruteForceMatcher_OCL_base::knnMatchSingle(const oclMat &query, co
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const int nQuery = query.rows;
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const int nTrain = train.rows;
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if (k == 2)
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{
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ensureSizeIsEnough(1, nQuery, CV_32SC2, trainIdx);
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@ -1045,6 +1047,7 @@ void cv::ocl::BruteForceMatcher_OCL_base::radiusMatchSingle(const oclMat &query,
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const int nQuery = query.rows;
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const int nTrain = train.rows;
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CV_Assert(query.channels() == 1 && query.depth() < CV_64F);
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CV_Assert(train.type() == query.type() && train.cols == query.cols);
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CV_Assert(trainIdx.empty() || (trainIdx.rows == query.rows && trainIdx.size() == distance.size()));
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@ -66,37 +66,30 @@ int bit1Count(float x)
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return (float)c;
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}
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#ifndef distType
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#define distType 0
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#endif
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#if (distType == 0)
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#define DIST(x, y) fabs((x) - (y))
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#elif (distType == 1)
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#define DIST(x, y) (((x) - (y)) * ((x) - (y)))
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#elif (distType == 2)
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#define DIST(x, y) bit1Count((uint)(x) ^ (uint)(y))
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#endif
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float reduce_block(__local float *s_query,
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__local float *s_train,
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int lidx,
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int lidy,
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int distType
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int lidy
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)
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{
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/* there are threee types in the reducer. the first is L1Dist, which to sum the abs(v1, v2), the second is L2Dist, which to
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sum the (v1 - v2) * (v1 - v2), the third is humming, which to popc(v1 ^ v2), popc is to count the bits are set to 1*/
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float result = 0;
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switch(distType)
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#pragma unroll
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for (int j = 0 ; j < block_size ; j++)
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{
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case 0:
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for (int j = 0 ; j < block_size ; j++)
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{
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result += fabs(s_query[lidy * block_size + j] - s_train[j * block_size + lidx]);
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}
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break;
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case 1:
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for (int j = 0 ; j < block_size ; j++)
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{
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float qr = s_query[lidy * block_size + j] - s_train[j * block_size + lidx];
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result += qr * qr;
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}
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break;
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case 2:
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for (int j = 0 ; j < block_size ; j++)
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{
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result += bit1Count((uint)s_query[lidy * block_size + j] ^ (uint)s_train[(uint)j * block_size + lidx]);
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}
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break;
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result += DIST(s_query[lidy * block_size + j], s_train[j * block_size + lidx]);
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}
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return result;
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}
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@ -105,35 +98,14 @@ float reduce_multi_block(__local float *s_query,
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__local float *s_train,
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int block_index,
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int lidx,
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int lidy,
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int distType
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int lidy
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)
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{
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/* there are threee types in the reducer. the first is L1Dist, which to sum the abs(v1, v2), the second is L2Dist, which to
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sum the (v1 - v2) * (v1 - v2), the third is humming, which to popc(v1 ^ v2), popc is to count the bits are set to 1*/
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float result = 0;
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switch(distType)
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#pragma unroll
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for (int j = 0 ; j < block_size ; j++)
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{
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case 0:
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for (int j = 0 ; j < block_size ; j++)
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{
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result += fabs(s_query[lidy * max_desc_len + block_index * block_size + j] - s_train[j * block_size + lidx]);
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}
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break;
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case 1:
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for (int j = 0 ; j < block_size ; j++)
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{
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float qr = s_query[lidy * max_desc_len + block_index * block_size + j] - s_train[j * block_size + lidx];
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result += qr * qr;
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}
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break;
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case 2:
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for (int j = 0 ; j < block_size ; j++)
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{
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//result += popcount((uint)s_query[lidy * max_desc_len + block_index * block_size + j] ^ (uint)s_train[j * block_size + lidx]);
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result += bit1Count((uint)s_query[lidy * max_desc_len + block_index * block_size + j] ^ (uint)s_train[j * block_size + lidx]);
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}
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break;
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result += DIST(s_query[lidy * max_desc_len + block_index * block_size + j], s_train[j * block_size + lidx]);
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}
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return result;
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}
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@ -152,8 +124,7 @@ __kernel void BruteForceMatch_UnrollMatch_D5(
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int query_cols,
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int train_rows,
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int train_cols,
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int step,
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int distType
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int step
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)
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{
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@ -191,7 +162,7 @@ __kernel void BruteForceMatch_UnrollMatch_D5(
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//synchronize to make sure each elem for reduceIteration in share memory is written already.
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barrier(CLK_LOCAL_MEM_FENCE);
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result += reduce_multi_block(s_query, s_train, i, lidx, lidy, distType);
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result += reduce_multi_block(s_query, s_train, i, lidx, lidy);
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barrier(CLK_LOCAL_MEM_FENCE);
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}
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@ -247,8 +218,7 @@ __kernel void BruteForceMatch_Match_D5(
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int query_cols,
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int train_rows,
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int train_cols,
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int step,
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int distType
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int step
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)
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{
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const int lidx = get_local_id(0);
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@ -283,7 +253,7 @@ __kernel void BruteForceMatch_Match_D5(
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barrier(CLK_LOCAL_MEM_FENCE);
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result += reduce_block(s_query, s_train, lidx, lidy, distType);
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result += reduce_block(s_query, s_train, lidx, lidy);
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barrier(CLK_LOCAL_MEM_FENCE);
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}
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@ -344,8 +314,7 @@ __kernel void BruteForceMatch_RadiusUnrollMatch_D5(
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int train_cols,
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int bestTrainIdx_cols,
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int step,
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int ostep,
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int distType
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int ostep
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)
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{
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const int lidx = get_local_id(0);
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@ -371,7 +340,7 @@ __kernel void BruteForceMatch_RadiusUnrollMatch_D5(
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//synchronize to make sure each elem for reduceIteration in share memory is written already.
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barrier(CLK_LOCAL_MEM_FENCE);
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result += reduce_block(s_query, s_train, lidx, lidy, distType);
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result += reduce_block(s_query, s_train, lidx, lidy);
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barrier(CLK_LOCAL_MEM_FENCE);
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}
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@ -405,8 +374,7 @@ __kernel void BruteForceMatch_RadiusMatch_D5(
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int train_cols,
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int bestTrainIdx_cols,
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int step,
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int ostep,
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int distType
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int ostep
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)
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{
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const int lidx = get_local_id(0);
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@ -432,7 +400,7 @@ __kernel void BruteForceMatch_RadiusMatch_D5(
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//synchronize to make sure each elem for reduceIteration in share memory is written already.
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barrier(CLK_LOCAL_MEM_FENCE);
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result += reduce_block(s_query, s_train, lidx, lidy, distType);
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result += reduce_block(s_query, s_train, lidx, lidy);
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barrier(CLK_LOCAL_MEM_FENCE);
|
||||
}
|
||||
@ -462,8 +430,7 @@ __kernel void BruteForceMatch_knnUnrollMatch_D5(
|
||||
int query_cols,
|
||||
int train_rows,
|
||||
int train_cols,
|
||||
int step,
|
||||
int distType
|
||||
int step
|
||||
)
|
||||
{
|
||||
const int lidx = get_local_id(0);
|
||||
@ -501,7 +468,7 @@ __kernel void BruteForceMatch_knnUnrollMatch_D5(
|
||||
//synchronize to make sure each elem for reduceIteration in share memory is written already.
|
||||
barrier(CLK_LOCAL_MEM_FENCE);
|
||||
|
||||
result += reduce_multi_block(s_query, s_train, i, lidx, lidy, distType);
|
||||
result += reduce_multi_block(s_query, s_train, i, lidx, lidy);
|
||||
|
||||
barrier(CLK_LOCAL_MEM_FENCE);
|
||||
}
|
||||
@ -609,8 +576,7 @@ __kernel void BruteForceMatch_knnMatch_D5(
|
||||
int query_cols,
|
||||
int train_rows,
|
||||
int train_cols,
|
||||
int step,
|
||||
int distType
|
||||
int step
|
||||
)
|
||||
{
|
||||
const int lidx = get_local_id(0);
|
||||
@ -645,7 +611,7 @@ __kernel void BruteForceMatch_knnMatch_D5(
|
||||
|
||||
barrier(CLK_LOCAL_MEM_FENCE);
|
||||
|
||||
result += reduce_block(s_query, s_train, lidx, lidy, distType);
|
||||
result += reduce_block(s_query, s_train, lidx, lidy);
|
||||
|
||||
barrier(CLK_LOCAL_MEM_FENCE);
|
||||
}
|
||||
@ -752,8 +718,7 @@ kernel void BruteForceMatch_calcDistanceUnrolled_D5(
|
||||
int query_cols,
|
||||
int train_rows,
|
||||
int train_cols,
|
||||
int step,
|
||||
int distType)
|
||||
int step)
|
||||
{
|
||||
/* Todo */
|
||||
}
|
||||
@ -768,8 +733,7 @@ kernel void BruteForceMatch_calcDistance_D5(
|
||||
int query_cols,
|
||||
int train_rows,
|
||||
int train_cols,
|
||||
int step,
|
||||
int distType)
|
||||
int step)
|
||||
{
|
||||
/* Todo */
|
||||
}
|
||||
|
||||
Loading…
Reference in New Issue
Block a user