some device layer utility functions
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Anatoly Baksheev
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19544b3d54
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ac5298815a
83
modules/gpu/src/cuda/dynamic_smem.hpp
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83
modules/gpu/src/cuda/dynamic_smem.hpp
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@ -0,0 +1,83 @@
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/*M///////////////////////////////////////////////////////////////////////////////////////
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//
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// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
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//
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// By downloading, copying, installing or using the software you agree to this license.
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// If you do not agree to this license, do not download, install,
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// copy or use the software.
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//
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//
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// License Agreement
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// For Open Source Computer Vision Library
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//
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// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
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// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
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// Third party copyrights are property of their respective owners.
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//
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// Redistribution and use in source and binary forms, with or without modification,
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// are permitted provided that the following conditions are met:
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//
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// * Redistribution's of source code must retain the above copyright notice,
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// this list of conditions and the following disclaimer.
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//
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// * Redistribution's in binary form must reproduce the above copyright notice,
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// this list of conditions and the following disclaimer in the documentation
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// and/or other materials provided with the distribution.
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//
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// * The name of the copyright holders may not be used to endorse or promote products
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// derived from this software without specific prior written permission.
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//
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// This software is provided by the copyright holders and contributors "as is" and
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// any express or implied warranties, including, but not limited to, the implied
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// warranties of merchantability and fitness for a particular purpose are disclaimed.
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// In no event shall the Intel Corporation or contributors be liable for any direct,
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// indirect, incidental, special, exemplary, or consequential damages
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// (including, but not limited to, procurement of substitute goods or services;
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// loss of use, data, or profits; or business interruption) however caused
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// and on any theory of liability, whether in contract, strict liability,
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// or tort (including negligence or otherwise) arising in any way out of
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// the use of this software, even if advised of the possibility of such damage.
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//
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//M*/
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namespace cv
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{
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namespace gpu
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{
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namespace device
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{
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template<class T> struct DynamicSharedMem
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{
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__device__ operator T*()
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{
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extern __shared__ int __smem[];
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return (T*)__smem;
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}
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__device__ operator const T*() const
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{
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extern __shared__ int __smem[];
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return (T*)__smem;
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}
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};
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// specialize for double to avoid unaligned memory access compile errors
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template<> struct DynamicSharedMem<double>
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{
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__device__ operator double*()
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{
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extern __shared__ double __smem_d[];
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return (double*)__smem_d;
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}
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__device__ operator const double*() const
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{
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extern __shared__ double __smem_d[];
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return (double*)__smem_d;
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}
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};
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}
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}
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}
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208
modules/gpu/src/cuda/limits_gpu.hpp
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208
modules/gpu/src/cuda/limits_gpu.hpp
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@ -0,0 +1,208 @@
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/*M///////////////////////////////////////////////////////////////////////////////////////
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//
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// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
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//
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// By downloading, copying, installing or using the software you agree to this license.
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// If you do not agree to this license, do not download, install,
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// copy or use the software.
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||||
//
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||||
//
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// License Agreement
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// For Open Source Computer Vision Library
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//
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// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
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// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
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// Third party copyrights are property of their respective owners.
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//
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// Redistribution and use in source and binary forms, with or without modification,
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// are permitted provided that the following conditions are met:
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//
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// * Redistribution's of source code must retain the above copyright notice,
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// this list of conditions and the following disclaimer.
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||||
//
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// * Redistribution's in binary form must reproduce the above copyright notice,
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// this list of conditions and the following disclaimer in the documentation
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// and/or other materials provided with the distribution.
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//
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// * The name of the copyright holders may not be used to endorse or promote products
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// derived from this software without specific prior written permission.
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//
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// This software is provided by the copyright holders and contributors "as is" and
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// any express or implied warranties, including, but not limited to, the implied
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// warranties of merchantability and fitness for a particular purpose are disclaimed.
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// In no event shall the Intel Corporation or contributors be liable for any direct,
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// indirect, incidental, special, exemplary, or consequential damages
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||||
// (including, but not limited to, procurement of substitute goods or services;
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// loss of use, data, or profits; or business interruption) however caused
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// and on any theory of liability, whether in contract, strict liability,
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// or tort (including negligence or otherwise) arising in any way out of
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// the use of this software, even if advised of the possibility of such damage.
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//
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//M*/
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namespace cv
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{
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namespace gpu
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{
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namespace device
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{
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template<class T> struct numeric_limits_gpu
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{
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typedef T type;
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__device__ static type min() { return type(); };
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__device__ static type max() { return type(); };
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__device__ static type epsilon() { return type(); }
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__device__ static type round_error() { return type(); }
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__device__ static type denorm_min() { return type(); }
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__device__ static type infinity() { return type(); }
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__device__ static type quiet_NaN() { return type(); }
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__device__ static type signaling_NaN() { return T(); }
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};
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template<> struct numeric_limits_gpu<bool>
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{
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typedef bool type;
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__device__ static type min() { return false; };
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__device__ static type max() { return true; };
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__device__ static type epsilon();
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__device__ static type round_error();
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__device__ static type denorm_min();
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__device__ static type infinity();
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__device__ static type quiet_NaN();
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__device__ static type signaling_NaN();
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};
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template<> struct numeric_limits_gpu<char>
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{
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typedef char type;
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__device__ static type min() { return CHAR_MIN; };
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__device__ static type max() { return CHAR_MAX; };
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__device__ static type epsilon();
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__device__ static type round_error();
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__device__ static type denorm_min();
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__device__ static type infinity();
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__device__ static type quiet_NaN();
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__device__ static type signaling_NaN();
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};
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template<> struct numeric_limits_gpu<unsigned char>
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{
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typedef unsigned char type;
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__device__ static type min() { return 0; };
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__device__ static type max() { return UCHAR_MAX; };
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__device__ static type epsilon();
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__device__ static type round_error();
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__device__ static type denorm_min();
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__device__ static type infinity();
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__device__ static type quiet_NaN();
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__device__ static type signaling_NaN();
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};
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template<> struct numeric_limits_gpu<short>
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{
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typedef short type;
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__device__ static type min() { return SHRT_MIN; };
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__device__ static type max() { return SHRT_MAX; };
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__device__ static type epsilon();
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__device__ static type round_error();
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__device__ static type denorm_min();
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__device__ static type infinity();
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__device__ static type quiet_NaN();
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__device__ static type signaling_NaN();
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};
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template<> struct numeric_limits_gpu<unsigned short>
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{
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typedef unsigned short type;
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__device__ static type min() { return 0; };
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__device__ static type max() { return USHRT_MAX; };
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__device__ static type epsilon();
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__device__ static type round_error();
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__device__ static type denorm_min();
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__device__ static type infinity();
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__device__ static type quiet_NaN();
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__device__ static type signaling_NaN();
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};
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template<> struct numeric_limits_gpu<int>
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{
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typedef int type;
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__device__ static type min() { return INT_MIN; };
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__device__ static type max() { return INT_MAX; };
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__device__ static type epsilon();
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__device__ static type round_error();
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__device__ static type denorm_min();
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__device__ static type infinity();
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__device__ static type quiet_NaN();
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__device__ static type signaling_NaN();
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};
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template<> struct numeric_limits_gpu<unsigned int>
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{
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typedef unsigned int type;
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__device__ static type min() { return 0; };
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__device__ static type max() { return UINT_MAX; };
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__device__ static type epsilon();
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__device__ static type round_error();
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__device__ static type denorm_min();
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__device__ static type infinity();
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__device__ static type quiet_NaN();
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__device__ static type signaling_NaN();
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};
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template<> struct numeric_limits_gpu<long>
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{
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typedef long type;
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__device__ static type min() { return LONG_MIN; };
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__device__ static type max() { return LONG_MAX; };
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__device__ static type epsilon();
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__device__ static type round_error();
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__device__ static type denorm_min();
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__device__ static type infinity();
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__device__ static type quiet_NaN();
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__device__ static type signaling_NaN();
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};
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template<> struct numeric_limits_gpu<unsigned long>
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{
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typedef unsigned long type;
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__device__ static type min() { return 0; };
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__device__ static type max() { return ULONG_MAX; };
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__device__ static type epsilon();
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__device__ static type round_error();
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__device__ static type denorm_min();
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__device__ static type infinity();
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__device__ static type quiet_NaN();
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__device__ static type signaling_NaN();
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};
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template<> struct numeric_limits_gpu<float>
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{
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typedef float type;
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__device__ static type min() { return 1.175494351e-38f/*FLT_MIN*/; };
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__device__ static type max() { return 3.402823466e+38f/*FLT_MAX*/; };
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__device__ static type epsilon();
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__device__ static type round_error();
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__device__ static type denorm_min();
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__device__ static type infinity();
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__device__ static type quiet_NaN();
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__device__ static type signaling_NaN();
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};
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template<> struct numeric_limits_gpu<double>
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{
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typedef double type;
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__device__ static type min() { return 2.2250738585072014e-308/*DBL_MIN*/; };
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__device__ static type max() { return 1.7976931348623158e+308/*DBL_MAX*/; };
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__device__ static type epsilon();
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__device__ static type round_error();
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__device__ static type denorm_min();
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__device__ static type infinity();
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__device__ static type quiet_NaN();
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__device__ static type signaling_NaN();
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};
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}
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}
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}
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@ -136,6 +136,7 @@ namespace cv
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void error(const char *error_string, const char *file, const int line, const char *func)
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{
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//if (uncaught_exception())
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cv::error( cv::Exception(CV_GpuApiCallError, error_string, func, file, line) );
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}
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}
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@ -572,7 +572,7 @@ void cv::gpu::GpuMat::release()
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//////////////////////////////// CudaMem //////////////////////////////
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///////////////////////////////////////////////////////////////////////
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bool cv::gpu::CudaMem::can_device_map_to_host()
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bool cv::gpu::CudaMem::canMapHostMemory()
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{
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cudaDeviceProp prop;
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cudaGetDeviceProperties(&prop, 0);
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@ -581,7 +581,7 @@ bool cv::gpu::CudaMem::can_device_map_to_host()
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void cv::gpu::CudaMem::create(int _rows, int _cols, int _type, int _alloc_type)
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{
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if (_alloc_type == ALLOC_ZEROCOPY && !can_device_map_to_host())
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if (_alloc_type == ALLOC_ZEROCOPY && !canMapHostMemory())
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cv::gpu::error("ZeroCopy is not supported by current device", __FILE__, __LINE__);
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_type &= TYPE_MASK;
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