implemented optimized version of gpu::bf_radius_match

pull/13383/head
Vladislav Vinogradov 13 years ago
parent 961dc4e348
commit b119833ad1
  1. 18
      modules/gpu/src/brute_force_matcher.cpp
  2. 2
      modules/gpu/src/cuda/bf_knnmatch.cu
  3. 2
      modules/gpu/src/cuda/bf_match.cu
  4. 196
      modules/gpu/src/cuda/bf_radius_match.cu

@ -76,7 +76,7 @@ void cv::gpu::BruteForceMatcher_GPU_base::radiusMatch(const GpuMat&, std::vector
#else /* !defined (HAVE_CUDA) */
namespace cv { namespace gpu { namespace bfmatcher
namespace cv { namespace gpu { namespace bf_match
{
template <typename T> void matchSingleL1_gpu(const DevMem2D& query, const DevMem2D& train, const DevMem2D& mask,
const DevMem2D& trainIdx, const DevMem2D& distance,
@ -97,7 +97,10 @@ namespace cv { namespace gpu { namespace bfmatcher
template <typename T> void matchCollectionHamming_gpu(const DevMem2D& query, const DevMem2D& trainCollection, const DevMem2D_<PtrStep>& maskCollection,
const DevMem2D& trainIdx, const DevMem2D& imgIdx, const DevMem2D& distance,
int cc, cudaStream_t stream);
}}}
namespace cv { namespace gpu { namespace bf_knnmatch
{
template <typename T> void knnMatchL1_gpu(const DevMem2D& query, const DevMem2D& train, int k, const DevMem2D& mask,
const DevMem2D& trainIdx, const DevMem2D& distance, const DevMem2D& allDist,
int cc, cudaStream_t stream);
@ -107,7 +110,10 @@ namespace cv { namespace gpu { namespace bfmatcher
template <typename T> void knnMatchHamming_gpu(const DevMem2D& query, const DevMem2D& train, int k, const DevMem2D& mask,
const DevMem2D& trainIdx, const DevMem2D& distance, const DevMem2D& allDist,
int cc, cudaStream_t stream);
}}}
namespace cv { namespace gpu { namespace bf_radius_match
{
template <typename T> void radiusMatchL1_gpu(const DevMem2D& query, const DevMem2D& train, float maxDistance, const DevMem2D& mask,
const DevMem2D& trainIdx, const DevMem2D& nMatches, const DevMem2D& distance,
cudaStream_t stream);
@ -170,7 +176,7 @@ void cv::gpu::BruteForceMatcher_GPU_base::matchSingle(const GpuMat& queryDescs,
if (queryDescs.empty() || trainDescs.empty())
return;
using namespace cv::gpu::bfmatcher;
using namespace cv::gpu::bf_match;
typedef void (*match_caller_t)(const DevMem2D& query, const DevMem2D& train, const DevMem2D& mask,
const DevMem2D& trainIdx, const DevMem2D& distance,
@ -309,7 +315,7 @@ void cv::gpu::BruteForceMatcher_GPU_base::matchCollection(const GpuMat& queryDes
if (queryDescs.empty() || trainCollection.empty())
return;
using namespace cv::gpu::bfmatcher;
using namespace cv::gpu::bf_match;
typedef void (*match_caller_t)(const DevMem2D& query, const DevMem2D& trainCollection, const DevMem2D_<PtrStep>& maskCollection,
const DevMem2D& trainIdx, const DevMem2D& imgIdx, const DevMem2D& distance,
@ -418,7 +424,7 @@ void cv::gpu::BruteForceMatcher_GPU_base::knnMatch(const GpuMat& queryDescs, con
if (queryDescs.empty() || trainDescs.empty())
return;
using namespace cv::gpu::bfmatcher;
using namespace cv::gpu::bf_knnmatch;
typedef void (*match_caller_t)(const DevMem2D& query, const DevMem2D& train, int k, const DevMem2D& mask,
const DevMem2D& trainIdx, const DevMem2D& distance, const DevMem2D& allDist,
@ -596,7 +602,7 @@ void cv::gpu::BruteForceMatcher_GPU_base::radiusMatch(const GpuMat& queryDescs,
if (queryDescs.empty() || trainDescs.empty())
return;
using namespace cv::gpu::bfmatcher;
using namespace cv::gpu::bf_radius_match;
typedef void (*radiusMatch_caller_t)(const DevMem2D& query, const DevMem2D& train, float maxDistance, const DevMem2D& mask,
const DevMem2D& trainIdx, const DevMem2D& nMatches, const DevMem2D& distance,
@ -618,7 +624,7 @@ void cv::gpu::BruteForceMatcher_GPU_base::radiusMatch(const GpuMat& queryDescs,
}
};
CV_Assert(TargetArchs::builtWith(GLOBAL_ATOMICS) && DeviceInfo().supports(GLOBAL_ATOMICS));
CV_Assert(TargetArchs::builtWith(SHARED_ATOMICS) && DeviceInfo().supports(GLOBAL_ATOMICS));
const int nQuery = queryDescs.rows;
const int nTrain = trainDescs.rows;

@ -47,7 +47,7 @@
using namespace cv::gpu;
using namespace cv::gpu::device;
namespace cv { namespace gpu { namespace bfmatcher
namespace cv { namespace gpu { namespace bf_knnmatch
{
template <typename VecDiff, typename Dist, typename T, typename Mask>
__device__ void distanceCalcLoop(const PtrStep_<T>& query, const DevMem2D_<T>& train, const Mask& m, int queryIdx,

@ -47,7 +47,7 @@
using namespace cv::gpu;
using namespace cv::gpu::device;
namespace cv { namespace gpu { namespace bfmatcher
namespace cv { namespace gpu { namespace bf_match
{
template <int BLOCK_DIM_Y, typename T>
__device__ void findBestMatch(T& myDist, int2& myIdx, T* smin, int2* sIdx)

@ -47,81 +47,191 @@
using namespace cv::gpu;
using namespace cv::gpu::device;
namespace cv { namespace gpu { namespace bfmatcher
namespace cv { namespace gpu { namespace bf_radius_match
{
template <int BLOCK_DIM_X, int BLOCK_DIM_Y, typename Dist, typename T, typename Mask>
__global__ void radiusMatch(const PtrStep_<T> query, const DevMem2D_<T> train, float maxDistance, const Mask mask,
DevMem2Di trainIdx_, unsigned int* nMatches, PtrStepf distance)
__device__ __forceinline__ void store(const int* sidx, const float* sdist, const unsigned int scount, int* trainIdx, float* distance, int& sglob_ind, const int tid)
{
#if __CUDA_ARCH__ >= 110
if (tid < scount)
{
trainIdx[sglob_ind + tid] = sidx[tid];
distance[sglob_ind + tid] = sdist[tid];
}
__shared__ typename Dist::result_type smem[BLOCK_DIM_X * BLOCK_DIM_Y];
if (tid == 0)
sglob_ind += scount;
}
typename Dist::result_type* sdiff_row = smem + BLOCK_DIM_X * threadIdx.y;
const int queryIdx = blockIdx.x;
const T* queryDescs = query.ptr(queryIdx);
template <int BLOCK_DIM_X, int BLOCK_DIM_Y, int BLOCK_STACK, typename VecDiff, typename Dist, typename T, typename Mask>
__global__ void radiusMatch(const PtrStep_<T> query, const DevMem2D_<T> train, const float maxDistance, const Mask mask,
DevMem2Di trainIdx_, PtrStepf distance, unsigned int* nMatches)
{
#if __CUDA_ARCH__ >= 120
typedef typename Dist::result_type result_type;
typedef typename Dist::value_type value_type;
__shared__ result_type smem[BLOCK_DIM_X * BLOCK_DIM_Y];
__shared__ int sidx[BLOCK_STACK];
__shared__ float sdist[BLOCK_STACK];
__shared__ unsigned int scount;
__shared__ int sglob_ind;
const int trainIdx = blockIdx.y * BLOCK_DIM_Y + threadIdx.y;
const int queryIdx = blockIdx.x;
const int tid = threadIdx.y * BLOCK_DIM_X + threadIdx.x;
if (trainIdx < train.rows)
if (tid == 0)
{
const T* trainDescs = train.ptr(trainIdx);
scount = 0;
sglob_ind = 0;
}
__syncthreads();
int* trainIdx_row = trainIdx_.ptr(queryIdx);
float* distance_row = distance.ptr(queryIdx);
const VecDiff vecDiff(query.ptr(queryIdx), train.cols, (typename Dist::value_type*)smem, tid, threadIdx.x);
typename Dist::result_type* sdiffRow = smem + BLOCK_DIM_X * threadIdx.y;
for (int trainIdx = threadIdx.y; trainIdx < train.rows; trainIdx += BLOCK_DIM_Y)
{
if (mask(queryIdx, trainIdx))
{
Dist dist;
calcVecDiffGlobal<BLOCK_DIM_X>(queryDescs, trainDescs, train.cols, dist, sdiff_row, threadIdx.x);
const T* trainRow = train.ptr(trainIdx);
vecDiff.calc(trainRow, train.cols, dist, sdiffRow, threadIdx.x);
if (threadIdx.x == 0)
const typename Dist::result_type val = dist;
if (threadIdx.x == 0 && val < maxDistance)
{
if (dist < maxDistance)
{
unsigned int i = atomicInc(nMatches + queryIdx, (unsigned int) -1);
if (i < trainIdx_.cols)
{
distance.ptr(queryIdx)[i] = dist;
trainIdx_.ptr(queryIdx)[i] = trainIdx;
}
}
unsigned int i = atomicInc(&scount, (unsigned int) -1);
sidx[i] = trainIdx;
sdist[i] = val;
}
}
__syncthreads();
if (scount > BLOCK_STACK - BLOCK_DIM_Y)
{
store(sidx, sdist, scount, trainIdx_row, distance_row, sglob_ind, tid);
if (tid == 0)
scount = 0;
}
__syncthreads();
}
store(sidx, sdist, scount, trainIdx_row, distance_row, sglob_ind, tid);
if (tid == 0)
nMatches[queryIdx] = sglob_ind;
#endif
}
///////////////////////////////////////////////////////////////////////////////
// Radius Match kernel caller
template <int BLOCK_DIM_X, int BLOCK_DIM_Y, typename Dist, typename T, typename Mask>
void radiusMatch_caller(const DevMem2D_<T>& query, const DevMem2D_<T>& train, float maxDistance, const Mask& mask,
const DevMem2Di& trainIdx, const DevMem2D_<unsigned int>& nMatches, const DevMem2Df& distance,
template <int BLOCK_DIM_X, int BLOCK_DIM_Y, int BLOCK_STACK, typename Dist, typename T, typename Mask>
void radiusMatchSimple_caller(const DevMem2D_<T>& query, const DevMem2D_<T>& train, float maxDistance, const Mask& mask,
const DevMem2Di& trainIdx, const DevMem2Df& distance, unsigned int* nMatches,
cudaStream_t stream)
{
StaticAssert<BLOCK_STACK >= BLOCK_DIM_Y>::check();
StaticAssert<BLOCK_STACK <= BLOCK_DIM_X * BLOCK_DIM_Y>::check();
const dim3 grid(query.rows, 1, 1);
const dim3 threads(BLOCK_DIM_X, BLOCK_DIM_Y, 1);
const dim3 grid(query.rows, divUp(train.rows, BLOCK_DIM_Y), 1);
radiusMatch<BLOCK_DIM_X, BLOCK_DIM_Y, Dist, T><<<grid, threads, 0, stream>>>(query, train, maxDistance, mask, trainIdx, nMatches.data, distance);
radiusMatch<BLOCK_DIM_X, BLOCK_DIM_Y, BLOCK_STACK, VecDiffGlobal<BLOCK_DIM_X, T>, Dist, T>
<<<grid, threads, 0, stream>>>(query, train, maxDistance, mask, trainIdx, distance, nMatches);
cudaSafeCall( cudaGetLastError() );
if (stream == 0)
cudaSafeCall( cudaDeviceSynchronize() );
}
template <int BLOCK_DIM_X, int BLOCK_DIM_Y, int BLOCK_STACK, int MAX_LEN, bool LEN_EQ_MAX_LEN, typename Dist, typename T, typename Mask>
void radiusMatchCached_caller(const DevMem2D_<T>& query, const DevMem2D_<T>& train, float maxDistance, const Mask& mask,
const DevMem2Di& trainIdx, const DevMem2Df& distance, unsigned int* nMatches,
cudaStream_t stream)
{
StaticAssert<BLOCK_STACK >= BLOCK_DIM_Y>::check();
StaticAssert<BLOCK_STACK <= BLOCK_DIM_X * BLOCK_DIM_Y>::check();
StaticAssert<BLOCK_DIM_X * BLOCK_DIM_Y >= MAX_LEN>::check();
StaticAssert<MAX_LEN % BLOCK_DIM_X == 0>::check();
const dim3 grid(query.rows, 1, 1);
const dim3 threads(BLOCK_DIM_X, BLOCK_DIM_Y, 1);
radiusMatch<BLOCK_DIM_X, BLOCK_DIM_Y, BLOCK_STACK, VecDiffCachedRegister<BLOCK_DIM_X, MAX_LEN, LEN_EQ_MAX_LEN, typename Dist::value_type>, Dist, T>
<<<grid, threads, 0, stream>>>(query, train, maxDistance, mask, trainIdx, distance, nMatches);
cudaSafeCall( cudaGetLastError() );
if (stream == 0)
cudaSafeCall( cudaDeviceSynchronize() );
}
///////////////////////////////////////////////////////////////////////////////
// Radius Match Dispatcher
template <typename Dist, typename T, typename Mask>
void radiusMatchDispatcher(const DevMem2D_<T>& query, const DevMem2D_<T>& train, float maxDistance, const Mask& mask,
const DevMem2D& trainIdx, const DevMem2D& nMatches, const DevMem2D& distance,
const DevMem2D& trainIdx, const DevMem2D& distance, const DevMem2D& nMatches,
cudaStream_t stream)
{
radiusMatch_caller<16, 16, Dist>(query, train, maxDistance, mask,
static_cast<DevMem2Di>(trainIdx), static_cast< const DevMem2D_<unsigned int> >(nMatches), static_cast<DevMem2Df>(distance),
stream);
}
if (query.cols < 64)
{
radiusMatchCached_caller<16, 16, 64, 64, false, Dist>(
query, train, maxDistance, mask,
static_cast<DevMem2Di>(trainIdx), static_cast<DevMem2Df>(distance), (unsigned int*)nMatches.data,
stream);
}
else if (query.cols == 64)
{
radiusMatchCached_caller<16, 16, 64, 64, true, Dist>(
query, train, maxDistance, mask,
static_cast<DevMem2Di>(trainIdx), static_cast<DevMem2Df>(distance), (unsigned int*)nMatches.data,
stream);
}
else if (query.cols < 128)
{
radiusMatchCached_caller<16, 16, 64, 128, false, Dist>(
query, train, maxDistance, mask,
static_cast<DevMem2Di>(trainIdx), static_cast<DevMem2Df>(distance), (unsigned int*)nMatches.data,
stream);
}
else if (query.cols == 128)
{
radiusMatchCached_caller<16, 16, 64, 128, true, Dist>(
query, train, maxDistance, mask,
static_cast<DevMem2Di>(trainIdx), static_cast<DevMem2Df>(distance), (unsigned int*)nMatches.data,
stream);
}
else if (query.cols < 256)
{
radiusMatchCached_caller<16, 16, 64, 256, false, Dist>(
query, train, maxDistance, mask,
static_cast<DevMem2Di>(trainIdx), static_cast<DevMem2Df>(distance), (unsigned int*)nMatches.data,
stream);
}
else if (query.cols == 256)
{
radiusMatchCached_caller<16, 16, 64, 256, true, Dist>(
query, train, maxDistance, mask,
static_cast<DevMem2Di>(trainIdx), static_cast<DevMem2Df>(distance), (unsigned int*)nMatches.data,
stream);
}
else
{
radiusMatchSimple_caller<16, 16, 64, Dist>(
query, train, maxDistance, mask,
static_cast<DevMem2Di>(trainIdx), static_cast<DevMem2Df>(distance), (unsigned int*)nMatches.data,
stream);
}
}
///////////////////////////////////////////////////////////////////////////////
// Radius Match caller
@ -133,13 +243,13 @@ namespace cv { namespace gpu { namespace bfmatcher
if (mask.data)
{
radiusMatchDispatcher< L1Dist<T> >(static_cast< DevMem2D_<T> >(query), static_cast< DevMem2D_<T> >(train), maxDistance, SingleMask(mask),
trainIdx, nMatches, distance,
trainIdx, distance, nMatches,
stream);
}
else
{
radiusMatchDispatcher< L1Dist<T> >(static_cast< DevMem2D_<T> >(query), static_cast< DevMem2D_<T> >(train), maxDistance, WithOutMask(),
trainIdx, nMatches, distance,
trainIdx, distance, nMatches,
stream);
}
}
@ -158,13 +268,13 @@ namespace cv { namespace gpu { namespace bfmatcher
if (mask.data)
{
radiusMatchDispatcher<L2Dist>(static_cast< DevMem2D_<T> >(query), static_cast< DevMem2D_<T> >(train), maxDistance, SingleMask(mask),
trainIdx, nMatches, distance,
trainIdx, distance, nMatches,
stream);
}
else
{
radiusMatchDispatcher<L2Dist>(static_cast< DevMem2D_<T> >(query), static_cast< DevMem2D_<T> >(train), maxDistance, WithOutMask(),
trainIdx, nMatches, distance,
trainIdx, distance, nMatches,
stream);
}
}
@ -183,13 +293,13 @@ namespace cv { namespace gpu { namespace bfmatcher
if (mask.data)
{
radiusMatchDispatcher<HammingDist>(static_cast< DevMem2D_<T> >(query), static_cast< DevMem2D_<T> >(train), maxDistance, SingleMask(mask),
trainIdx, nMatches, distance,
trainIdx, distance, nMatches,
stream);
}
else
{
radiusMatchDispatcher<HammingDist>(static_cast< DevMem2D_<T> >(query), static_cast< DevMem2D_<T> >(train), maxDistance, WithOutMask(),
trainIdx, nMatches, distance,
trainIdx, distance, nMatches,
stream);
}
}

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