preparing for separate compilation in java2

/**

 **

 ** 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);