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some device layer utility functions

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pull/13383/head
Anatoly Baksheev 14 years ago
parent 19544b3d54
commit ac5298815a
4 changed files with 295 additions and 3 deletions
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  1. 83
      modules/gpu/src/cuda/dynamic_smem.hpp
  2. 208
      modules/gpu/src/cuda/limits_gpu.hpp
  3. 3
      modules/gpu/src/error.cpp
  4. 4
      modules/gpu/src/matrix_operations.cpp

83
modules/gpu/src/cuda/dynamic_smem.hpp
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@ -0,0 +1,83 @@
/*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*/
namespace cv
{
namespace gpu
{
namespace device
{
template<class T> struct DynamicSharedMem
{
__device__ operator T*()
{
extern __shared__ int __smem[];
return (T*)__smem;
}
__device__ operator const T*() const
{
extern __shared__ int __smem[];
return (T*)__smem;
}
};
// specialize for double to avoid unaligned memory access compile errors
template<> struct DynamicSharedMem<double>
{
__device__ operator double*()
{
extern __shared__ double __smem_d[];
return (double*)__smem_d;
}
__device__ operator const double*() const
{
extern __shared__ double __smem_d[];
return (double*)__smem_d;
}
};
}
}
}

208
modules/gpu/src/cuda/limits_gpu.hpp
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@ -0,0 +1,208 @@
/*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*/
namespace cv
{
namespace gpu
{
namespace device
{
template<class T> struct numeric_limits_gpu
{
typedef T type;
__device__ static type min() { return type(); };
__device__ static type max() { return type(); };
__device__ static type epsilon() { return type(); }
__device__ static type round_error() { return type(); }
__device__ static type denorm_min() { return type(); }
__device__ static type infinity() { return type(); }
__device__ static type quiet_NaN() { return type(); }
__device__ static type signaling_NaN() { return T(); }
};
template<> struct numeric_limits_gpu<bool>
{
typedef bool type;
__device__ static type min() { return false; };
__device__ static type max() { return true; };
__device__ static type epsilon();
__device__ static type round_error();
__device__ static type denorm_min();
__device__ static type infinity();
__device__ static type quiet_NaN();
__device__ static type signaling_NaN();
};
template<> struct numeric_limits_gpu<char>
{
typedef char type;
__device__ static type min() { return CHAR_MIN; };
__device__ static type max() { return CHAR_MAX; };
__device__ static type epsilon();
__device__ static type round_error();
__device__ static type denorm_min();
__device__ static type infinity();
__device__ static type quiet_NaN();
__device__ static type signaling_NaN();
};
template<> struct numeric_limits_gpu<unsigned char>
{
typedef unsigned char type;
__device__ static type min() { return 0; };
__device__ static type max() { return UCHAR_MAX; };
__device__ static type epsilon();
__device__ static type round_error();
__device__ static type denorm_min();
__device__ static type infinity();
__device__ static type quiet_NaN();
__device__ static type signaling_NaN();
};
template<> struct numeric_limits_gpu<short>
{
typedef short type;
__device__ static type min() { return SHRT_MIN; };
__device__ static type max() { return SHRT_MAX; };
__device__ static type epsilon();
__device__ static type round_error();
__device__ static type denorm_min();
__device__ static type infinity();
__device__ static type quiet_NaN();
__device__ static type signaling_NaN();
};
template<> struct numeric_limits_gpu<unsigned short>
{
typedef unsigned short type;
__device__ static type min() { return 0; };
__device__ static type max() { return USHRT_MAX; };
__device__ static type epsilon();
__device__ static type round_error();
__device__ static type denorm_min();
__device__ static type infinity();
__device__ static type quiet_NaN();
__device__ static type signaling_NaN();
};
template<> struct numeric_limits_gpu<int>
{
typedef int type;
__device__ static type min() { return INT_MIN; };
__device__ static type max() { return INT_MAX; };
__device__ static type epsilon();
__device__ static type round_error();
__device__ static type denorm_min();
__device__ static type infinity();
__device__ static type quiet_NaN();
__device__ static type signaling_NaN();
};
template<> struct numeric_limits_gpu<unsigned int>
{
typedef unsigned int type;
__device__ static type min() { return 0; };
__device__ static type max() { return UINT_MAX; };
__device__ static type epsilon();
__device__ static type round_error();
__device__ static type denorm_min();
__device__ static type infinity();
__device__ static type quiet_NaN();
__device__ static type signaling_NaN();
};
template<> struct numeric_limits_gpu<long>
{
typedef long type;
__device__ static type min() { return LONG_MIN; };
__device__ static type max() { return LONG_MAX; };
__device__ static type epsilon();
__device__ static type round_error();
__device__ static type denorm_min();
__device__ static type infinity();
__device__ static type quiet_NaN();
__device__ static type signaling_NaN();
};
template<> struct numeric_limits_gpu<unsigned long>
{
typedef unsigned long type;
__device__ static type min() { return 0; };
__device__ static type max() { return ULONG_MAX; };
__device__ static type epsilon();
__device__ static type round_error();
__device__ static type denorm_min();
__device__ static type infinity();
__device__ static type quiet_NaN();
__device__ static type signaling_NaN();
};
template<> struct numeric_limits_gpu<float>
{
typedef float type;
__device__ static type min() { return 1.175494351e-38f/*FLT_MIN*/; };
__device__ static type max() { return 3.402823466e+38f/*FLT_MAX*/; };
__device__ static type epsilon();
__device__ static type round_error();
__device__ static type denorm_min();
__device__ static type infinity();
__device__ static type quiet_NaN();
__device__ static type signaling_NaN();
};
template<> struct numeric_limits_gpu<double>
{
typedef double type;
__device__ static type min() { return 2.2250738585072014e-308/*DBL_MIN*/; };
__device__ static type max() { return 1.7976931348623158e+308/*DBL_MAX*/; };
__device__ static type epsilon();
__device__ static type round_error();
__device__ static type denorm_min();
__device__ static type infinity();
__device__ static type quiet_NaN();
__device__ static type signaling_NaN();
};
}
}
}

3
modules/gpu/src/error.cpp
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@ -135,7 +135,8 @@ namespace cv
}
void error(const char *error_string, const char *file, const int line, const char *func)
{
{
//if (uncaught_exception())
cv::error( cv::Exception(CV_GpuApiCallError, error_string, func, file, line) );
}
}

4
modules/gpu/src/matrix_operations.cpp
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@ -572,7 +572,7 @@ void cv::gpu::GpuMat::release()
//////////////////////////////// CudaMem //////////////////////////////
///////////////////////////////////////////////////////////////////////
bool cv::gpu::CudaMem::can_device_map_to_host()
bool cv::gpu::CudaMem::canMapHostMemory()
{
cudaDeviceProp prop;
cudaGetDeviceProperties(&prop, 0);
@ -581,7 +581,7 @@ bool cv::gpu::CudaMem::can_device_map_to_host()
void cv::gpu::CudaMem::create(int _rows, int _cols, int _type, int _alloc_type)
{
if (_alloc_type == ALLOC_ZEROCOPY && !can_device_map_to_host())
if (_alloc_type == ALLOC_ZEROCOPY && !canMapHostMemory())
cv::gpu::error("ZeroCopy is not supported by current device", __FILE__, __LINE__);
_type &= TYPE_MASK;

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