Commit 406eb708 authored by Andrey Filippov's avatar Andrey Filippov

preparing for separate compilation in java2

parent 3c3ebfa9
/**
**
** dtt8x8.h
**
** Copyright (C) 2018 Elphel, Inc.
**
** -----------------------------------------------------------------------------**
**
** dtt8x8.cuh is free software: you can redistribute it and/or modify
** it under the terms of the GNU General Public License as published by
** the Free Software Foundation, either version 3 of the License, or
** (at your option) any later version.
**
** This program is distributed in the hope that it will be useful,
** but WITHOUT ANY WARRANTY; without even the implied warranty of
** MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
** GNU General Public License for more details.
**
** You should have received a copy of the GNU General Public License
** along with this program. If not, see <http://www.gnu.org/licenses/>.
**
** Additional permission under GNU GPL version 3 section 7
**
** If you modify this Program, or any covered work, by linking or
** combining it with NVIDIA Corporation's CUDA libraries from the
** NVIDIA CUDA Toolkit (or a modified version of those libraries),
** containing parts covered by the terms of NVIDIA CUDA Toolkit
** EULA, the licensors of this Program grant you additional
** permission to convey the resulting work.
** -----------------------------------------------------------------------------**
*/
/**
**************************************************************************
* \file dtt8x8.h
* \brief DCT-II, DST-II, DCT-IV and DST-IV for Complex Lapped Transform of 16x16 (stride 8)
* in GPU
* This file contains building blocks for the 16x16 stride 8 COmplex Lapped Transform (CLT)
* implementation. DTT-IV are used for forward and inverse 2D CLT, DTT-II - to convert correlation
* results from the frequency to pixel domain. DTT-III (inverse of DTT-II) is not implemented
* here it is used to convert convolution kernels and LPF to the frequency domain - done in
* software.
*
* This file is cpompatible with both runtime and driver API, runtime is used for development
* with Nvidia Nsight, driver API when calling these kernels from Java
*/
#ifndef JCUDA
#define DTT_SIZE_LOG2 3
#endif
#pragma once
#define DTT_SIZE (1 << DTT_SIZE_LOG2)
#define DTT_SIZE1 (DTT_SIZE + 1)
#define DTT_SIZE2 (2 * DTT_SIZE)
#define DTT_SIZE21 (DTT_SIZE2 + 1)
#define DTT_SIZE4 (4 * DTT_SIZE)
#define DTT_SIZE2M1 (DTT_SIZE2 - 1)
#define BAYER_RED 0
#define BAYER_BLUE 1
#define BAYER_GREEN 2
// assuming GR/BG as now
#define BAYER_RED_ROW 0
#define BAYER_RED_COL 1
#define DTTTEST_BLOCK_WIDTH 32
#define DTTTEST_BLOCK_HEIGHT 16
#define DTTTEST_BLK_STRIDE (DTTTEST_BLOCK_WIDTH+1)
extern __constant__ float idct_signs[4][4][4];
extern __constant__ int imclt_indx9[16];
extern __constant__ float HWINDOW2[];
inline __device__ void dttii_shared_mem_nonortho(float * x0, int inc, int dst_not_dct); // does not scale by y[0] (y[7]) by 1/sqrt[0]
inline __device__ void dttii_shared_mem(float * x0, int inc, int dst_not_dct); // used in GPU_DTT24_DRV
inline __device__ void dttiv_shared_mem(float * x0, int inc, int dst_not_dct); // used in GPU_DTT24_DRV
inline __device__ void dttiv_nodiverg (float * x, int inc, int dst_not_dct); // not used
inline __device__ void dctiv_nodiverg (float * x0, int inc); // used in TP
inline __device__ void dstiv_nodiverg (float * x0, int inc); // used in TP
inline __device__ void dct_ii8 ( float x[8], float y[8]); // x,y point to 8-element arrays each // not used
inline __device__ void dct_iv8 ( float x[8], float y[8]); // x,y point to 8-element arrays each // not used
inline __device__ void dst_iv8 ( float x[8], float y[8]); // x,y point to 8-element arrays each // not used
inline __device__ void _dctii_nrecurs8 ( float x[8], float y[8]); // x,y point to 8-element arrays each // not used
inline __device__ void _dctiv_nrecurs8 ( float x[8], float y[8]); // x,y point to 8-element arrays each // not used
// kernels (not used so far)
extern "C" __global__ void GPU_DTT24_DRV(float *dst, float *src, int src_stride, int dtt_mode);
//=========================== 2D functions ===============
extern __device__ void corrUnfoldTile(
int corr_radius,
float* qdata0, // [4][DTT_SIZE][DTT_SIZE1], // 4 quadrants of the clt data, rows extended to optimize shared ports
float* rslt); // [DTT_SIZE2M1][DTT_SIZE2M1]) // 15x15
extern __device__ void dttii_2d(
float * clt_corr); // shared memory, [4][DTT_SIZE1][DTT_SIZE]
extern __device__ void dttiv_color_2d(
float * clt_tile,
int color);
extern __device__ void imclt(
float * clt_tile, // [4][DTT_SIZE][DTT_SIZE1], // +1 to alternate column ports [4][8][9]
float * mclt_tile );
extern __device__ void imclt8threads(
int do_acc, // 1 - add to previous value, 0 - overwrite
float * clt_tile, // [4][DTT_SIZE][DTT_SIZE1], // +1 to alternate column ports [4][8][9]
float * mclt_tile, // [2* DTT_SIZE][DTT_SIZE1+ DTT_SIZE], // +1 to alternate column ports[16][17]
int debug);
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