generic-library/opencv
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Remove unnecesary operations and calculations in loop body.

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Signed-off-by: Yan Wang <yan.wang@linux.intel.com>
This commit is contained in:
Yan Wang 2014-12-04 14:35:54 +08:00
parent be5c910358
commit 1c9f956b88
1 changed files with 27 additions and 15 deletions
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42
modules/features2d/src/opencl/brute_force_match.cl
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@ -210,6 +210,8 @@ __kernel void BruteForceMatch_Match(
} }
#else #else
__local value_type *s_train = (__local value_type *)sharebuffer + BLOCK_SIZE_ODD * BLOCK_SIZE; __local value_type *s_train = (__local value_type *)sharebuffer + BLOCK_SIZE_ODD * BLOCK_SIZE;
const int s_query_i = mad24(BLOCK_SIZE_ODD, lidy, lidx);
const int s_train_i = mad24(BLOCK_SIZE_ODD, lidx, lidy);
#endif #endif
float myBestDistance = MAX_FLOAT; float myBestDistance = MAX_FLOAT;
@ -242,13 +244,15 @@ __kernel void BruteForceMatch_Match(
{ {
const int loadx = mad24(i, BLOCK_SIZE, lidx); const int loadx = mad24(i, BLOCK_SIZE, lidx);
//load query and train into local memory //load query and train into local memory
s_query[mad24(BLOCK_SIZE_ODD, lidy, lidx)] = 0;
s_train[mad24(BLOCK_SIZE_ODD, lidx, lidy)] = 0;
if (loadx < query_cols) if (loadx < query_cols)
{ {
s_query[mad24(BLOCK_SIZE_ODD, lidy, lidx)] = query_vec[loadx]; s_query[s_query_i] = query_vec[loadx];
s_train[mad24(BLOCK_SIZE_ODD, lidx, lidy)] = train_vec[loadx]; s_train[s_train_i] = train_vec[loadx];
}
else
{
s_query[s_query_i] = 0;
s_train[s_train_i] = 0;
} }
barrier(CLK_LOCAL_MEM_FENCE); barrier(CLK_LOCAL_MEM_FENCE);
@ -337,18 +341,22 @@ __kernel void BruteForceMatch_RadiusMatch(
__local value_type *s_train = (__local value_type *)sharebuffer + BLOCK_SIZE_ODD * BLOCK_SIZE; __local value_type *s_train = (__local value_type *)sharebuffer + BLOCK_SIZE_ODD * BLOCK_SIZE;
result_type result = 0; result_type result = 0;
const int s_query_i = mad24(BLOCK_SIZE_ODD, lidy, lidx);
const int s_train_i = mad24(BLOCK_SIZE_ODD, lidx, lidy);
for (int i = 0 ; i < (query_cols + BLOCK_SIZE - 1) / BLOCK_SIZE ; ++i) for (int i = 0 ; i < (query_cols + BLOCK_SIZE - 1) / BLOCK_SIZE ; ++i)
{ {
//load a BLOCK_SIZE * BLOCK_SIZE block into local train. //load a BLOCK_SIZE * BLOCK_SIZE block into local train.
const int loadx = mad24(BLOCK_SIZE, i, lidx); const int loadx = mad24(BLOCK_SIZE, i, lidx);
s_query[mad24(BLOCK_SIZE_ODD, lidy, lidx)] = 0;
s_train[mad24(BLOCK_SIZE_ODD, lidx, lidy)] = 0;
if (loadx < query_cols) if (loadx < query_cols)
{ {
s_query[mad24(BLOCK_SIZE_ODD, lidy, lidx)] = query_vec[loadx]; s_query[s_query_i] = query_vec[loadx];
s_train[mad24(BLOCK_SIZE_ODD, lidx, lidy)] = train_vec[loadx]; s_train[s_train_i] = train_vec[loadx];
}
else
{
s_query[s_query_i] = 0;
s_train[s_train_i] = 0;
} }
//synchronize to make sure each elem for reduceIteration in share memory is written already. //synchronize to make sure each elem for reduceIteration in share memory is written already.
@ -405,6 +413,8 @@ __kernel void BruteForceMatch_knnMatch(
} }
#else #else
__local value_type *s_train = (__local value_type *)sharebuffer + BLOCK_SIZE_ODD * BLOCK_SIZE; __local value_type *s_train = (__local value_type *)sharebuffer + BLOCK_SIZE_ODD * BLOCK_SIZE;
const int s_query_i = mad24(BLOCK_SIZE_ODD, lidy, lidx);
const int s_train_i = mad24(BLOCK_SIZE_ODD, lidx, lidy);
#endif #endif
float myBestDistance1 = MAX_FLOAT; float myBestDistance1 = MAX_FLOAT;
@ -438,13 +448,15 @@ __kernel void BruteForceMatch_knnMatch(
{ {
const int loadx = mad24(BLOCK_SIZE, i, lidx); const int loadx = mad24(BLOCK_SIZE, i, lidx);
//load query and train into local memory //load query and train into local memory
s_query[mad24(BLOCK_SIZE_ODD, lidy, lidx)] = 0;
s_train[mad24(BLOCK_SIZE_ODD, lidx, lidy)] = 0;
if (loadx < query_cols) if (loadx < query_cols)
{ {
s_query[mad24(BLOCK_SIZE_ODD, lidy, lidx)] = query_vec[loadx]; s_query[s_query_i] = query_vec[loadx];
s_train[mad24(BLOCK_SIZE_ODD, lidx, lidy)] = train_vec[loadx]; s_train[s_train_i] = train_vec[loadx];
}
else
{
s_query[s_query_i] = 0;
s_train[s_train_i] = 0;
} }
barrier(CLK_LOCAL_MEM_FENCE); barrier(CLK_LOCAL_MEM_FENCE);