430 lines
15 KiB
C++
430 lines
15 KiB
C++
/*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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// Copyright (C) 2013, OpenCV Foundation, 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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#pragma once
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#ifndef OPENCV_CUDEV_BLOCK_REDUCE_DETAIL_HPP
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#define OPENCV_CUDEV_BLOCK_REDUCE_DETAIL_HPP
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#include "../../common.hpp"
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#include "../../util/tuple.hpp"
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#include "../../util/type_traits.hpp"
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#include "../../warp/warp.hpp"
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#include "../../warp/shuffle.hpp"
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namespace cv { namespace cudev {
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namespace block_reduce_detail
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{
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// GetType
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template <typename T> struct GetType;
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template <typename T> struct GetType<T*>
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{
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typedef T type;
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};
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template <typename T> struct GetType<volatile T*>
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{
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typedef T type;
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};
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template <typename T> struct GetType<T&>
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{
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typedef T type;
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};
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// For
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template <int I, int N> struct For
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{
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template <class PointerTuple, class ValTuple>
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__device__ static void loadToSmem(const PointerTuple& smem, const ValTuple& val, uint tid)
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{
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get<I>(smem)[tid] = get<I>(val);
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For<I + 1, N>::loadToSmem(smem, val, tid);
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}
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template <class PointerTuple, class ValTuple>
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__device__ static void loadFromSmem(const PointerTuple& smem, const ValTuple& val, uint tid)
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{
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get<I>(val) = get<I>(smem)[tid];
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For<I + 1, N>::loadFromSmem(smem, val, tid);
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}
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template <class PointerTuple, class ValTuple, class OpTuple>
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__device__ static void merge(const PointerTuple& smem, const ValTuple& val, uint tid, uint delta, const OpTuple& op)
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{
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typename GetType<typename tuple_element<I, PointerTuple>::type>::type reg = get<I>(smem)[tid + delta];
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get<I>(smem)[tid] = get<I>(val) = get<I>(op)(get<I>(val), reg);
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For<I + 1, N>::merge(smem, val, tid, delta, op);
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}
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#if CV_CUDEV_ARCH >= 300
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template <class ValTuple, class OpTuple>
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__device__ static void mergeShfl(const ValTuple& val, uint delta, uint width, const OpTuple& op)
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{
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typename GetType<typename tuple_element<I, ValTuple>::type>::type reg = shfl_down(get<I>(val), delta, width);
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get<I>(val) = get<I>(op)(get<I>(val), reg);
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For<I + 1, N>::mergeShfl(val, delta, width, op);
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}
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#endif
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};
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template <int N> struct For<N, N>
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{
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template <class PointerTuple, class ValTuple>
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__device__ __forceinline__ static void loadToSmem(const PointerTuple&, const ValTuple&, uint)
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{
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}
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template <class PointerTuple, class ValTuple>
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__device__ __forceinline__ static void loadFromSmem(const PointerTuple&, const ValTuple&, uint)
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{
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}
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template <class PointerTuple, class ValTuple, class OpTuple>
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__device__ __forceinline__ static void merge(const PointerTuple&, const ValTuple&, uint, uint, const OpTuple&)
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{
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}
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#if CV_CUDEV_ARCH >= 300
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template <class ValTuple, class OpTuple>
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__device__ __forceinline__ static void mergeShfl(const ValTuple&, uint, uint, const OpTuple&)
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{
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}
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#endif
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};
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// loadToSmem / loadFromSmem
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template <typename T>
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__device__ __forceinline__ void loadToSmem(volatile T* smem, T& val, uint tid)
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{
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smem[tid] = val;
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}
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template <typename T>
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__device__ __forceinline__ void loadFromSmem(volatile T* smem, T& val, uint tid)
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{
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val = smem[tid];
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}
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// merge
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template <typename T, class Op>
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__device__ __forceinline__ void merge(volatile T* smem, T& val, uint tid, uint delta, const Op& op)
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{
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T reg = smem[tid + delta];
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smem[tid] = val = op(val, reg);
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}
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#if (CUDART_VERSION < 12040)
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template <typename P0, typename P1, typename P2, typename P3, typename P4, typename P5, typename P6, typename P7, typename P8, typename P9,
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typename R0, typename R1, typename R2, typename R3, typename R4, typename R5, typename R6, typename R7, typename R8, typename R9>
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__device__ __forceinline__ void loadToSmem(const tuple<P0, P1, P2, P3, P4, P5, P6, P7, P8, P9>& smem,
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const tuple<R0, R1, R2, R3, R4, R5, R6, R7, R8, R9>& val,
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uint tid)
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{
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For<0, tuple_size<tuple<P0, P1, P2, P3, P4, P5, P6, P7, P8, P9> >::value>::loadToSmem(smem, val, tid);
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}
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template <typename P0, typename P1, typename P2, typename P3, typename P4, typename P5, typename P6, typename P7, typename P8, typename P9,
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typename R0, typename R1, typename R2, typename R3, typename R4, typename R5, typename R6, typename R7, typename R8, typename R9>
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__device__ __forceinline__ void loadFromSmem(const tuple<P0, P1, P2, P3, P4, P5, P6, P7, P8, P9>& smem,
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const tuple<R0, R1, R2, R3, R4, R5, R6, R7, R8, R9>& val,
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uint tid)
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{
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For<0, tuple_size<tuple<P0, P1, P2, P3, P4, P5, P6, P7, P8, P9> >::value>::loadFromSmem(smem, val, tid);
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}
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template <typename P0, typename P1, typename P2, typename P3, typename P4, typename P5, typename P6, typename P7, typename P8, typename P9,
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typename R0, typename R1, typename R2, typename R3, typename R4, typename R5, typename R6, typename R7, typename R8, typename R9,
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class Op0, class Op1, class Op2, class Op3, class Op4, class Op5, class Op6, class Op7, class Op8, class Op9>
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__device__ __forceinline__ void merge(const tuple<P0, P1, P2, P3, P4, P5, P6, P7, P8, P9>& smem,
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const tuple<R0, R1, R2, R3, R4, R5, R6, R7, R8, R9>& val,
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uint tid,
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uint delta,
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const tuple<Op0, Op1, Op2, Op3, Op4, Op5, Op6, Op7, Op8, Op9>& op)
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{
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For<0, tuple_size<tuple<P0, P1, P2, P3, P4, P5, P6, P7, P8, P9> >::value>::merge(smem, val, tid, delta, op);
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}
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// mergeShfl
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#if CV_CUDEV_ARCH >= 300
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template <typename T, class Op>
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__device__ __forceinline__ void mergeShfl(T& val, uint delta, uint width, const Op& op)
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{
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T reg = shfl_down(val, delta, width);
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val = op(val, reg);
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}
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template <typename R0, typename R1, typename R2, typename R3, typename R4, typename R5, typename R6, typename R7, typename R8, typename R9,
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class Op0, class Op1, class Op2, class Op3, class Op4, class Op5, class Op6, class Op7, class Op8, class Op9>
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__device__ __forceinline__ void mergeShfl(const tuple<R0, R1, R2, R3, R4, R5, R6, R7, R8, R9>& val,
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uint delta,
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uint width,
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const tuple<Op0, Op1, Op2, Op3, Op4, Op5, Op6, Op7, Op8, Op9>& op)
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{
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For<0, tuple_size<tuple<R0, R1, R2, R3, R4, R5, R6, R7, R8, R9> >::value>::mergeShfl(val, delta, width, op);
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}
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#endif
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#else
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template <typename... P, typename... R>
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__device__ __forceinline__ void loadToSmem(const tuple<P...>& smem, const tuple<R...>& val, uint tid)
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{
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For<0, tuple_size<tuple<P...> >::value>::loadToSmem(smem, val, tid);
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}
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template <typename... P, typename... R>
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__device__ __forceinline__ void loadFromSmem(const tuple<P...>& smem, const tuple<R...>& val, uint tid)
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{
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For<0, tuple_size<tuple<P...> >::value>::loadFromSmem(smem, val, tid);
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}
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template <typename... P, typename... R, class... Op>
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__device__ __forceinline__ void merge(const tuple<P...>& smem, const tuple<R...>& val, uint tid, uint delta, const tuple<Op...>& op)
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{
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For<0, tuple_size<tuple<P...> >::value>::merge(smem, val, tid, delta, op);
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}
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// mergeShfl
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template <typename T, class Op>
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__device__ __forceinline__ void mergeShfl(T& val, uint delta, uint width, const Op& op)
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{
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T reg = shfl_down(val, delta, width);
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val = op(val, reg);
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}
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template <typename... R, class... Op>
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__device__ __forceinline__ void mergeShfl(const tuple<R...>& val, uint delta, uint width, const tuple<Op...>& op)
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{
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For<0, tuple_size<tuple<R...> >::value>::mergeShfl(val, delta, width, op);
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}
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#endif
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// Generic
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template <int N> struct Generic
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{
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template <typename Pointer, typename Reference, class Op>
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__device__ static void reduce(Pointer smem, Reference val, uint tid, Op op)
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{
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loadToSmem(smem, val, tid);
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if (N >= 32)
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__syncthreads();
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if (N >= 2048)
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{
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if (tid < 1024)
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merge(smem, val, tid, 1024, op);
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__syncthreads();
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}
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if (N >= 1024)
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{
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if (tid < 512)
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merge(smem, val, tid, 512, op);
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__syncthreads();
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}
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if (N >= 512)
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{
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if (tid < 256)
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merge(smem, val, tid, 256, op);
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__syncthreads();
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}
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if (N >= 256)
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{
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if (tid < 128)
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merge(smem, val, tid, 128, op);
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__syncthreads();
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}
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if (N >= 128)
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{
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if (tid < 64)
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merge(smem, val, tid, 64, op);
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__syncthreads();
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}
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if (N >= 64)
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{
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if (tid < 32)
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merge(smem, val, tid, 32, op);
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}
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if (tid < 16)
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{
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merge(smem, val, tid, 16, op);
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merge(smem, val, tid, 8, op);
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merge(smem, val, tid, 4, op);
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merge(smem, val, tid, 2, op);
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merge(smem, val, tid, 1, op);
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}
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}
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};
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// Unroll
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template <int I, typename Pointer, typename Reference, class Op> struct Unroll
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{
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__device__ static void loop(Pointer smem, Reference val, uint tid, Op op)
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{
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merge(smem, val, tid, I, op);
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Unroll<I / 2, Pointer, Reference, Op>::loop(smem, val, tid, op);
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}
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#if CV_CUDEV_ARCH >= 300
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__device__ static void loopShfl(Reference val, Op op, uint N)
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{
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mergeShfl(val, I, N, op);
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Unroll<I / 2, Pointer, Reference, Op>::loopShfl(val, op, N);
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}
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#endif
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};
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template <typename Pointer, typename Reference, class Op> struct Unroll<0, Pointer, Reference, Op>
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{
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__device__ __forceinline__ static void loop(Pointer, Reference, uint, Op)
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{
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}
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#if CV_CUDEV_ARCH >= 300
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__device__ __forceinline__ static void loopShfl(Reference, Op, uint)
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{
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}
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#endif
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};
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// WarpOptimized
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template <int N> struct WarpOptimized
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{
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template <typename Pointer, typename Reference, class Op>
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__device__ static void reduce(Pointer smem, Reference val, uint tid, Op op)
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{
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#if CV_CUDEV_ARCH >= 300
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CV_UNUSED(smem);
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CV_UNUSED(tid);
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Unroll<N / 2, Pointer, Reference, Op>::loopShfl(val, op, N);
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#else
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loadToSmem(smem, val, tid);
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if (tid < N / 2)
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Unroll<N / 2, Pointer, Reference, Op>::loop(smem, val, tid, op);
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#endif
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}
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};
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// GenericOptimized32
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template <int N> struct GenericOptimized32
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{
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enum { M = N / 32 };
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template <typename Pointer, typename Reference, class Op>
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__device__ static void reduce(Pointer smem, Reference val, uint tid, Op op)
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{
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const uint laneId = Warp::laneId();
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#if CV_CUDEV_ARCH >= 300
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Unroll<16, Pointer, Reference, Op>::loopShfl(val, op, warpSize);
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if (laneId == 0)
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loadToSmem(smem, val, tid / 32);
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#else
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loadToSmem(smem, val, tid);
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if (laneId < 16)
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Unroll<16, Pointer, Reference, Op>::loop(smem, val, tid, op);
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__syncthreads();
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if (laneId == 0)
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loadToSmem(smem, val, tid / 32);
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#endif
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__syncthreads();
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loadFromSmem(smem, val, tid);
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if (tid < 32)
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{
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#if CV_CUDEV_ARCH >= 300
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Unroll<M / 2, Pointer, Reference, Op>::loopShfl(val, op, M);
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#else
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Unroll<M / 2, Pointer, Reference, Op>::loop(smem, val, tid, op);
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#endif
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}
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}
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};
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template <int N> struct Dispatcher
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{
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typedef typename SelectIf<
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(N <= 32) && IsPowerOf2<N>::value,
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WarpOptimized<N>,
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typename SelectIf<
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(N <= 1024) && IsPowerOf2<N>::value,
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GenericOptimized32<N>,
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Generic<N>
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>::type
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>::type reductor;
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};
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}
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}}
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#endif
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