/*******************************************************************
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* CUDALERP.h
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* CUDALERP
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*
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* Author: Kareem Omar
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* kareem.omar@uah.edu
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* https://github.com/komrad36
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*
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* Last updated Jan 7, 2016
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*******************************************************************/
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//
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// The file CUDALERP.h exposes two extremely high performance GPU
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// resize operations,
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// CUDALERP (bilinear interpolation), and
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// CUDANERP (nearest neighbor interpolation), for 8-bit unsigned
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// integer (i.e. grayscale) data.
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//
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// For 32-bit float data, see the CUDAFLERP project instead.
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//
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// CUDALERP offers superior accuracy to CUDA's built-in texture
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// interpolator at comparable performance. The accuracy if compiled
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// with -use-fast-math off is nearly equivalent to my CPU interpolator,
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// KLERP, while still being as fast as the built-in interpolation.
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//
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// Particularly for large images, CUDALERP dramatically outperforms
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// even the highly tuned CPU AVX2 versions.
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//
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// All functionality is contained in the header 'CUDALERP.h' and
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// the source file 'CUDALERP.cu' and has no external dependencies at all.
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//
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// Note that these are intended for computer vision use(hence the speed)
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// and are designed for grayscale images.
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//
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// The file 'main.cpp' is an example and speed test driver.
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//
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#pragma once
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#include "cuda_runtime.h"
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#include <cstdint>
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#ifdef __INTELLISENSE__
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#include <algorithm>
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#define asm(x)
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#include "device_launch_parameters.h"
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#define __CUDACC__
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#include "device_functions.h"
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#undef __CUDACC__
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#endif
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void CUDALERP(const cudaTextureObject_t d_img_tex, const int oldw, const int oldh, uint8_t* __restrict const d_out, const uint32_t neww, const uint32_t newh);
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void CUDANERP(const cudaTextureObject_t d_img_tex, const int oldw, const int oldh, uint8_t* __restrict const d_out, const uint32_t neww, const uint32_t newh);
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