fix BruteForceMatcher resource distribution

added launch bounds attributes for all CUDA kernels
pull/3924/head
Vladislav Vinogradov 10 years ago
parent 17608f7ade
commit d22516872c
  1. 9
      modules/gpu/src/cuda/bf_knnmatch.cu
  2. 6
      modules/gpu/src/cuda/bf_match.cu
  3. 2
      modules/gpu/src/cuda/bf_radius_match.cu

@ -374,6 +374,7 @@ namespace cv { namespace gpu { namespace device
}
template <int BLOCK_SIZE, int MAX_DESC_LEN, typename Dist, typename T, typename Mask>
__launch_bounds__(BLOCK_SIZE * BLOCK_SIZE)
__global__ void matchUnrolledCached(const PtrStepSz<T> query, const PtrStepSz<T> train, const Mask mask, int2* bestTrainIdx, float2* bestDistance)
{
extern __shared__ int smem[];
@ -424,6 +425,7 @@ namespace cv { namespace gpu { namespace device
}
template <int BLOCK_SIZE, int MAX_DESC_LEN, typename Dist, typename T, typename Mask>
__launch_bounds__(BLOCK_SIZE * BLOCK_SIZE)
__global__ void matchUnrolledCached(const PtrStepSz<T> query, const PtrStepSz<T>* trains, int n, const Mask mask, int2* bestTrainIdx, int2* bestImgIdx, float2* bestDistance)
{
extern __shared__ int smem[];
@ -553,6 +555,7 @@ namespace cv { namespace gpu { namespace device
}
template <int BLOCK_SIZE, int MAX_DESC_LEN, typename Dist, typename T, typename Mask>
__launch_bounds__(BLOCK_SIZE * BLOCK_SIZE)
__global__ void matchUnrolled(const PtrStepSz<T> query, const PtrStepSz<T> train, const Mask mask, int2* bestTrainIdx, float2* bestDistance)
{
extern __shared__ int smem[];
@ -601,6 +604,7 @@ namespace cv { namespace gpu { namespace device
}
template <int BLOCK_SIZE, int MAX_DESC_LEN, typename Dist, typename T, typename Mask>
__launch_bounds__(BLOCK_SIZE * BLOCK_SIZE)
__global__ void matchUnrolled(const PtrStepSz<T> query, const PtrStepSz<T>* trains, int n, const Mask mask, int2* bestTrainIdx, int2* bestImgIdx, float2* bestDistance)
{
extern __shared__ int smem[];
@ -727,6 +731,7 @@ namespace cv { namespace gpu { namespace device
}
template <int BLOCK_SIZE, typename Dist, typename T, typename Mask>
__launch_bounds__(BLOCK_SIZE * BLOCK_SIZE)
__global__ void match(const PtrStepSz<T> query, const PtrStepSz<T> train, const Mask mask, int2* bestTrainIdx, float2* bestDistance)
{
extern __shared__ int smem[];
@ -775,6 +780,7 @@ namespace cv { namespace gpu { namespace device
}
template <int BLOCK_SIZE, typename Dist, typename T, typename Mask>
__launch_bounds__(BLOCK_SIZE * BLOCK_SIZE)
__global__ void match(const PtrStepSz<T> query, const PtrStepSz<T>* trains, int n, const Mask mask, int2* bestTrainIdx, int2* bestImgIdx, float2* bestDistance)
{
extern __shared__ int smem[];
@ -902,6 +908,7 @@ namespace cv { namespace gpu { namespace device
// Calc distance kernel
template <int BLOCK_SIZE, int MAX_DESC_LEN, typename Dist, typename T, typename Mask>
__launch_bounds__(BLOCK_SIZE * BLOCK_SIZE)
__global__ void calcDistanceUnrolled(const PtrStepSz<T> query, const PtrStepSz<T> train, const Mask mask, PtrStepf allDist)
{
extern __shared__ int smem[];
@ -966,6 +973,7 @@ namespace cv { namespace gpu { namespace device
}
template <int BLOCK_SIZE, typename Dist, typename T, typename Mask>
__launch_bounds__(BLOCK_SIZE * BLOCK_SIZE)
__global__ void calcDistance(const PtrStepSz<T> query, const PtrStepSz<T> train, const Mask mask, PtrStepf allDist)
{
extern __shared__ int smem[];
@ -1066,6 +1074,7 @@ namespace cv { namespace gpu { namespace device
// find knn match kernel
template <int BLOCK_SIZE>
__launch_bounds__(BLOCK_SIZE)
__global__ void findBestMatch(PtrStepSzf allDist, int i, PtrStepi trainIdx, PtrStepf distance)
{
const int SMEM_SIZE = BLOCK_SIZE > 64 ? BLOCK_SIZE : 64;

@ -136,6 +136,7 @@ namespace cv { namespace gpu { namespace device
}
template <int BLOCK_SIZE, int MAX_DESC_LEN, typename Dist, typename T, typename Mask>
__launch_bounds__(BLOCK_SIZE * BLOCK_SIZE)
__global__ void matchUnrolledCached(const PtrStepSz<T> query, const PtrStepSz<T> train, const Mask mask, int* bestTrainIdx, float* bestDistance)
{
extern __shared__ int smem[];
@ -184,6 +185,7 @@ namespace cv { namespace gpu { namespace device
}
template <int BLOCK_SIZE, int MAX_DESC_LEN, typename Dist, typename T, typename Mask>
__launch_bounds__(BLOCK_SIZE * BLOCK_SIZE)
__global__ void matchUnrolledCached(const PtrStepSz<T> query, const PtrStepSz<T>* trains, int n, const Mask mask,
int* bestTrainIdx, int* bestImgIdx, float* bestDistance)
{
@ -296,6 +298,7 @@ namespace cv { namespace gpu { namespace device
}
template <int BLOCK_SIZE, int MAX_DESC_LEN, typename Dist, typename T, typename Mask>
__launch_bounds__(BLOCK_SIZE * BLOCK_SIZE)
__global__ void matchUnrolled(const PtrStepSz<T> query, const PtrStepSz<T> train, const Mask mask, int* bestTrainIdx, float* bestDistance)
{
extern __shared__ int smem[];
@ -342,6 +345,7 @@ namespace cv { namespace gpu { namespace device
}
template <int BLOCK_SIZE, int MAX_DESC_LEN, typename Dist, typename T, typename Mask>
__launch_bounds__(BLOCK_SIZE * BLOCK_SIZE)
__global__ void matchUnrolled(const PtrStepSz<T> query, const PtrStepSz<T>* trains, int n, const Mask mask,
int* bestTrainIdx, int* bestImgIdx, float* bestDistance)
{
@ -451,6 +455,7 @@ namespace cv { namespace gpu { namespace device
}
template <int BLOCK_SIZE, typename Dist, typename T, typename Mask>
__launch_bounds__(BLOCK_SIZE * BLOCK_SIZE)
__global__ void match(const PtrStepSz<T> query, const PtrStepSz<T> train, const Mask mask, int* bestTrainIdx, float* bestDistance)
{
extern __shared__ int smem[];
@ -497,6 +502,7 @@ namespace cv { namespace gpu { namespace device
}
template <int BLOCK_SIZE, typename Dist, typename T, typename Mask>
__launch_bounds__(BLOCK_SIZE * BLOCK_SIZE)
__global__ void match(const PtrStepSz<T> query, const PtrStepSz<T>* trains, int n, const Mask mask,
int* bestTrainIdx, int* bestImgIdx, float* bestDistance)
{

@ -56,6 +56,7 @@ namespace cv { namespace gpu { namespace device
// Match Unrolled
template <int BLOCK_SIZE, int MAX_DESC_LEN, bool SAVE_IMG_IDX, typename Dist, typename T, typename Mask>
__launch_bounds__(BLOCK_SIZE * BLOCK_SIZE)
__global__ void matchUnrolled(const PtrStepSz<T> query, int imgIdx, const PtrStepSz<T> train, float maxDistance, const Mask mask,
PtrStepi bestTrainIdx, PtrStepi bestImgIdx, PtrStepf bestDistance, unsigned int* nMatches, int maxCount)
{
@ -164,6 +165,7 @@ namespace cv { namespace gpu { namespace device
// Match
template <int BLOCK_SIZE, bool SAVE_IMG_IDX, typename Dist, typename T, typename Mask>
__launch_bounds__(BLOCK_SIZE * BLOCK_SIZE)
__global__ void match(const PtrStepSz<T> query, int imgIdx, const PtrStepSz<T> train, float maxDistance, const Mask mask,
PtrStepi bestTrainIdx, PtrStepi bestImgIdx, PtrStepf bestDistance, unsigned int* nMatches, int maxCount)
{

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