summaryrefslogtreecommitdiff
path: root/2.3-1/thirdparty/includes/OpenCV/opencv2/gpu/device/scan.hpp
diff options
context:
space:
mode:
authorsiddhu89902017-04-24 14:08:37 +0530
committersiddhu89902017-04-24 14:08:37 +0530
commit472b2e7ebbd2d8b3ecd00b228128aa8a0bd3f920 (patch)
tree506e85e6c959148c052747d61ffd29d98fa058bf /2.3-1/thirdparty/includes/OpenCV/opencv2/gpu/device/scan.hpp
parentb9cfdca438347fe4d28f7caff3cb7b382e455d3a (diff)
downloadScilab2C-472b2e7ebbd2d8b3ecd00b228128aa8a0bd3f920.tar.gz
Scilab2C-472b2e7ebbd2d8b3ecd00b228128aa8a0bd3f920.tar.bz2
Scilab2C-472b2e7ebbd2d8b3ecd00b228128aa8a0bd3f920.zip
Fixed float.h issue. OpenCV with built libraries working for linux x64
Diffstat (limited to '2.3-1/thirdparty/includes/OpenCV/opencv2/gpu/device/scan.hpp')
-rw-r--r--2.3-1/thirdparty/includes/OpenCV/opencv2/gpu/device/scan.hpp250
1 files changed, 250 insertions, 0 deletions
diff --git a/2.3-1/thirdparty/includes/OpenCV/opencv2/gpu/device/scan.hpp b/2.3-1/thirdparty/includes/OpenCV/opencv2/gpu/device/scan.hpp
new file mode 100644
index 00000000..3d8da16f
--- /dev/null
+++ b/2.3-1/thirdparty/includes/OpenCV/opencv2/gpu/device/scan.hpp
@@ -0,0 +1,250 @@
+/*M///////////////////////////////////////////////////////////////////////////////////////
+//
+// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+//
+// By downloading, copying, installing or using the software you agree to this license.
+// If you do not agree to this license, do not download, install,
+// copy or use the software.
+//
+//
+// License Agreement
+// For Open Source Computer Vision Library
+//
+// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
+// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
+// Third party copyrights are property of their respective owners.
+//
+// Redistribution and use in source and binary forms, with or without modification,
+// are permitted provided that the following conditions are met:
+//
+// * Redistribution's of source code must retain the above copyright notice,
+// this list of conditions and the following disclaimer.
+//
+// * Redistribution's in binary form must reproduce the above copyright notice,
+// this list of conditions and the following disclaimer in the documentation
+// and/or other materials provided with the distribution.
+//
+// * The name of the copyright holders may not be used to endorse or promote products
+// derived from this software without specific prior written permission.
+//
+// This software is provided by the copyright holders and contributors "as is" and
+// any express or implied warranties, including, but not limited to, the implied
+// warranties of merchantability and fitness for a particular purpose are disclaimed.
+// In no event shall the Intel Corporation or contributors be liable for any direct,
+// indirect, incidental, special, exemplary, or consequential damages
+// (including, but not limited to, procurement of substitute goods or services;
+// loss of use, data, or profits; or business interruption) however caused
+// and on any theory of liability, whether in contract, strict liability,
+// or tort (including negligence or otherwise) arising in any way out of
+// the use of this software, even if advised of the possibility of such damage.
+//
+//M*/
+
+#ifndef __OPENCV_GPU_SCAN_HPP__
+#define __OPENCV_GPU_SCAN_HPP__
+
+#include "opencv2/gpu/device/common.hpp"
+#include "opencv2/gpu/device/utility.hpp"
+#include "opencv2/gpu/device/warp.hpp"
+#include "opencv2/gpu/device/warp_shuffle.hpp"
+
+namespace cv { namespace gpu { namespace device
+{
+ enum ScanKind { EXCLUSIVE = 0, INCLUSIVE = 1 };
+
+ template <ScanKind Kind, typename T, typename F> struct WarpScan
+ {
+ __device__ __forceinline__ WarpScan() {}
+ __device__ __forceinline__ WarpScan(const WarpScan& other) { (void)other; }
+
+ __device__ __forceinline__ T operator()( volatile T *ptr , const unsigned int idx)
+ {
+ const unsigned int lane = idx & 31;
+ F op;
+
+ if ( lane >= 1) ptr [idx ] = op(ptr [idx - 1], ptr [idx]);
+ if ( lane >= 2) ptr [idx ] = op(ptr [idx - 2], ptr [idx]);
+ if ( lane >= 4) ptr [idx ] = op(ptr [idx - 4], ptr [idx]);
+ if ( lane >= 8) ptr [idx ] = op(ptr [idx - 8], ptr [idx]);
+ if ( lane >= 16) ptr [idx ] = op(ptr [idx - 16], ptr [idx]);
+
+ if( Kind == INCLUSIVE )
+ return ptr [idx];
+ else
+ return (lane > 0) ? ptr [idx - 1] : 0;
+ }
+
+ __device__ __forceinline__ unsigned int index(const unsigned int tid)
+ {
+ return tid;
+ }
+
+ __device__ __forceinline__ void init(volatile T *ptr){}
+
+ static const int warp_offset = 0;
+
+ typedef WarpScan<INCLUSIVE, T, F> merge;
+ };
+
+ template <ScanKind Kind , typename T, typename F> struct WarpScanNoComp
+ {
+ __device__ __forceinline__ WarpScanNoComp() {}
+ __device__ __forceinline__ WarpScanNoComp(const WarpScanNoComp& other) { (void)other; }
+
+ __device__ __forceinline__ T operator()( volatile T *ptr , const unsigned int idx)
+ {
+ const unsigned int lane = threadIdx.x & 31;
+ F op;
+
+ ptr [idx ] = op(ptr [idx - 1], ptr [idx]);
+ ptr [idx ] = op(ptr [idx - 2], ptr [idx]);
+ ptr [idx ] = op(ptr [idx - 4], ptr [idx]);
+ ptr [idx ] = op(ptr [idx - 8], ptr [idx]);
+ ptr [idx ] = op(ptr [idx - 16], ptr [idx]);
+
+ if( Kind == INCLUSIVE )
+ return ptr [idx];
+ else
+ return (lane > 0) ? ptr [idx - 1] : 0;
+ }
+
+ __device__ __forceinline__ unsigned int index(const unsigned int tid)
+ {
+ return (tid >> warp_log) * warp_smem_stride + 16 + (tid & warp_mask);
+ }
+
+ __device__ __forceinline__ void init(volatile T *ptr)
+ {
+ ptr[threadIdx.x] = 0;
+ }
+
+ static const int warp_smem_stride = 32 + 16 + 1;
+ static const int warp_offset = 16;
+ static const int warp_log = 5;
+ static const int warp_mask = 31;
+
+ typedef WarpScanNoComp<INCLUSIVE, T, F> merge;
+ };
+
+ template <ScanKind Kind , typename T, typename Sc, typename F> struct BlockScan
+ {
+ __device__ __forceinline__ BlockScan() {}
+ __device__ __forceinline__ BlockScan(const BlockScan& other) { (void)other; }
+
+ __device__ __forceinline__ T operator()(volatile T *ptr)
+ {
+ const unsigned int tid = threadIdx.x;
+ const unsigned int lane = tid & warp_mask;
+ const unsigned int warp = tid >> warp_log;
+
+ Sc scan;
+ typename Sc::merge merge_scan;
+ const unsigned int idx = scan.index(tid);
+
+ T val = scan(ptr, idx);
+ __syncthreads ();
+
+ if( warp == 0)
+ scan.init(ptr);
+ __syncthreads ();
+
+ if( lane == 31 )
+ ptr [scan.warp_offset + warp ] = (Kind == INCLUSIVE) ? val : ptr [idx];
+ __syncthreads ();
+
+ if( warp == 0 )
+ merge_scan(ptr, idx);
+ __syncthreads();
+
+ if ( warp > 0)
+ val = ptr [scan.warp_offset + warp - 1] + val;
+ __syncthreads ();
+
+ ptr[idx] = val;
+ __syncthreads ();
+
+ return val ;
+ }
+
+ static const int warp_log = 5;
+ static const int warp_mask = 31;
+ };
+
+ template <typename T>
+ __device__ T warpScanInclusive(T idata, volatile T* s_Data, unsigned int tid)
+ {
+ #if __CUDA_ARCH__ >= 300
+ const unsigned int laneId = cv::gpu::device::Warp::laneId();
+
+ // scan on shuffl functions
+ #pragma unroll
+ for (int i = 1; i <= (OPENCV_GPU_WARP_SIZE / 2); i *= 2)
+ {
+ const T n = cv::gpu::device::shfl_up(idata, i);
+ if (laneId >= i)
+ idata += n;
+ }
+
+ return idata;
+ #else
+ unsigned int pos = 2 * tid - (tid & (OPENCV_GPU_WARP_SIZE - 1));
+ s_Data[pos] = 0;
+ pos += OPENCV_GPU_WARP_SIZE;
+ s_Data[pos] = idata;
+
+ s_Data[pos] += s_Data[pos - 1];
+ s_Data[pos] += s_Data[pos - 2];
+ s_Data[pos] += s_Data[pos - 4];
+ s_Data[pos] += s_Data[pos - 8];
+ s_Data[pos] += s_Data[pos - 16];
+
+ return s_Data[pos];
+ #endif
+ }
+
+ template <typename T>
+ __device__ __forceinline__ T warpScanExclusive(T idata, volatile T* s_Data, unsigned int tid)
+ {
+ return warpScanInclusive(idata, s_Data, tid) - idata;
+ }
+
+ template <int tiNumScanThreads, typename T>
+ __device__ T blockScanInclusive(T idata, volatile T* s_Data, unsigned int tid)
+ {
+ if (tiNumScanThreads > OPENCV_GPU_WARP_SIZE)
+ {
+ //Bottom-level inclusive warp scan
+ T warpResult = warpScanInclusive(idata, s_Data, tid);
+
+ //Save top elements of each warp for exclusive warp scan
+ //sync to wait for warp scans to complete (because s_Data is being overwritten)
+ __syncthreads();
+ if ((tid & (OPENCV_GPU_WARP_SIZE - 1)) == (OPENCV_GPU_WARP_SIZE - 1))
+ {
+ s_Data[tid >> OPENCV_GPU_LOG_WARP_SIZE] = warpResult;
+ }
+
+ //wait for warp scans to complete
+ __syncthreads();
+
+ if (tid < (tiNumScanThreads / OPENCV_GPU_WARP_SIZE) )
+ {
+ //grab top warp elements
+ T val = s_Data[tid];
+ //calculate exclusive scan and write back to shared memory
+ s_Data[tid] = warpScanExclusive(val, s_Data, tid);
+ }
+
+ //return updated warp scans with exclusive scan results
+ __syncthreads();
+
+ return warpResult + s_Data[tid >> OPENCV_GPU_LOG_WARP_SIZE];
+ }
+ else
+ {
+ return warpScanInclusive(idata, s_Data, tid);
+ }
+ }
+}}}
+
+#endif // __OPENCV_GPU_SCAN_HPP__