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imagej-elphel
Commit dc4e1f60 authored by Andrey Filippov's avatar Andrey Filippov
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updated tested GPU image conversion with selectable kernel source

parent ed43abc2
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Showing with 796 additions and 10 deletions
src/main/java/com/elphel/imagej/cameras/EyesisCorrectionParameters.java
View file @ dc4e1f60
......@@ -85,6 +85,7 @@ public class EyesisCorrectionParameters {
public boolean equirectangular= true;
public boolean zcorrect= true;
public boolean saveSettings = true;
public String tile_processor_gpu = ""; // absolute path to tile_processor_gpu project or empty to use default GPU kernels
public String [] sourcePaths= {};
// public String [] sourceSetPaths= {}; // 2019 - directories with image sets
......@@ -909,6 +910,9 @@ public class EyesisCorrectionParameters {
gd.addTab ("File paths", "Select files and directories paths (common to main and optional auxiliary)");
gd.addMessage ("============ Common to the main and optional auxiliary camera============");
gd.addStringField ("GPU tile_processor_gpu project absolute path", this.tile_processor_gpu, 60,
"Keep empty to use default GPU kernels");
gd.addCheckbox ("Select GPU directory", false);
gd.addCheckbox ("Save current settings with results", this.saveSettings); // 1
gd.addStringField ("Source files directory", this.sourceDirectory, 60); // 2
......@@ -1022,7 +1026,7 @@ public class EyesisCorrectionParameters {
gd.showDialog();
if (gd.wasCanceled()) return false;
this.tile_processor_gpu = gd.getNextString(); if (gd.getNextBoolean()) selectGPUSourceDirectory(false, false);
this.saveSettings= gd.getNextBoolean(); // 1
......@@ -1760,6 +1764,17 @@ public class EyesisCorrectionParameters {
if (dir!=null) this.sourceDirectory=dir;
return dir;
}
public String selectGPUSourceDirectory(boolean smart, boolean newAllowed) { // normally newAllowed=false
String dir= CalibrationFileManagement.selectDirectory(
smart,
newAllowed, // save
"GPU kernel development project", // title
"Select GPU project directory", // button
null, // filter
this.tile_processor_gpu); // this.sourceDirectory);
if (dir!=null) this.tile_processor_gpu=dir;
return dir;
}
public String selectSensorDirectory(boolean smart, boolean newAllowed) {
String dir= CalibrationFileManagement.selectDirectory(
smart,
......
src/main/java/com/elphel/imagej/correction/Eyesis_Correction.java
View file @ dc4e1f60
......@@ -5784,7 +5784,7 @@ private Panel panel1,
}
if (GPU_TILE_PROCESSOR == null) {
try {
GPU_TILE_PROCESSOR = new GPUTileProcessor();
GPU_TILE_PROCESSOR = new GPUTileProcessor(CORRECTION_PARAMETERS.tile_processor_gpu);
} catch (Exception e) {
System.out.println("Failed to initialize GPU class");
// TODO Auto-generated catch block
......
src/main/java/com/elphel/imagej/gpu/GPUTileProcessor.java
View file @ dc4e1f60
......@@ -240,7 +240,7 @@ public class GPUTileProcessor {
return new PointerWithAddress(p).getAddress();
}
public GPUTileProcessor() throws IOException
public GPUTileProcessor(String cuda_project_directory) throws IOException
{
// From code by Marco Hutter - http://www.jcuda.org
// Enable exceptions and omit all subsequent error checks
......@@ -276,7 +276,15 @@ public class GPUTileProcessor {
"#define IMCLT_TILES_PER_BLOCK " + IMCLT_TILES_PER_BLOCK+"\n";
for (String src_file:GPU_KERNEL_FILES) {
File file = new File(classLoader.getResource(src_file).getFile());
File file = null;
if ((cuda_project_directory == null) || (cuda_project_directory == "")) {
file = new File(classLoader.getResource(src_file).getFile());
System.out.println("Loading resource "+file);
} else {
File src_dir = new File(cuda_project_directory, "src");
file = new File(src_dir.getPath(), src_file);
System.out.println("Loading resource "+file);
}
System.out.println(file.getAbsolutePath());
String cuFileName = file.getAbsolutePath(); // /home/eyesis/workspace-python3/nvidia_dct8x8/src/dtt8x8.cuh";// "dtt8x8.cuh";
String sourceFile = readFileAsString(cuFileName); // readResourceAsString(cuFileName);
......
src/main/java/com/elphel/imagej/gpu/JCuda_ImageJ_Example_Plugin.java
View file @ dc4e1f60
......@@ -206,8 +206,6 @@ public class JCuda_ImageJ_Example_Plugin implements PlugInFilter
*/
private static String readResourceAsString(String name)
{
int a = 0;
Class ccc = JCuda_ImageJ_Example_Plugin.class;
InputStream inputStream =
JCuda_ImageJ_Example_Plugin.class.getResourceAsStream(name);
if (inputStream == null)
......
src/main/java/com/elphel/imagej/tileprocessor/TwoQuadCLT.java
View file @ dc4e1f60
......@@ -1920,6 +1920,7 @@ public class TwoQuadCLT {
String [] rgb_titles = {"red","blue","green"};
int out_width = GPUTileProcessor.IMG_WIDTH + GPUTileProcessor.DTT_SIZE;
int out_height = GPUTileProcessor.IMG_HEIGHT + GPUTileProcessor.DTT_SIZE;
/*
for (int ncam = 0; ncam < iclt_fimg.length; ncam++) {
String title=name+"-RBG"+String.format("%02d", ncam);
......@@ -1931,7 +1932,7 @@ public class TwoQuadCLT {
title,
rgb_titles);
}
*/
ImagePlus [] imps_RGB = new ImagePlus[iclt_fimg.length];
for (int ncam = 0; ncam < iclt_fimg.length; ncam++) {
String title=name+"-"+String.format("%02d", ncam);
......@@ -2081,11 +2082,14 @@ public class TwoQuadCLT {
double_stacks_main[i][2][j]*=0.5; // Scale green 0.5 to compensate more pixels than R,B
}
}
for (int i = 0; i < double_stacks_aux.length; i++){
if (double_stacks_aux[i].length > 2) { // skip for monochrome, only if color
for (int j =0 ; j < double_stacks_aux[i][0].length; j++){
double_stacks_aux[i][2][j]*=0.5; // Scale green 0.5 to compensate more pixels than R,B
}
}
}
quadCLT_main.setTiles (imp_quad_main[0], // set global tp.tilesX, tp.tilesY
clt_parameters,
threadsMax);
......
src/main/resources/dtt8x8.cuh 0 → 100644
View file @ dc4e1f60
/**
**
** dtt8x8.cuh
**
** 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.cuh
* \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)
* imlementation. 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
* softwaer.
*
* 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 8
#endif
#pragma once
#define DTTTEST_BLOCK_WIDTH 32
#define DTTTEST_BLOCK_HEIGHT 16
#define DTTTEST_BLK_STRIDE (DTTTEST_BLOCK_WIDTH+1)
//#define CUDART_INF_F __int_as_float(0x7f800000)
/*
Python code to generate constant coefficients:
def dct_constants():
COSPI_1_8_SQRT2 = math.cos(math.pi/8)*math.sqrt(2.0)
COSPI_3_8_SQRT2 = math.cos(3*math.pi/8)*math.sqrt(2.0)
SQRT_2 = math.sqrt(2.0)
SQRT1_2 = 1/math.sqrt(2.0)
SQRT1_8 = 1/math.sqrt(8.0)
CN = [[math.cos((2*k+1)*(math.pi/(8*(2 << t)))) for k in range (2 << t)] for t in range (2)]
SN = [[math.sin((2*k+1)*(math.pi/(8*(2 << t)))) for k in range (2 << t)] for t in range (2)]
print("__constant__ float COSPI_1_8_SQRT2 = %ff;"%(COSPI_1_8_SQRT2))
print("__constant__ float COSPI_3_8_SQRT2 = %ff;"%(COSPI_3_8_SQRT2))
print("__constant__ float SQRT_2 = %ff;"% (SQRT_2))
print("__constant__ float SQRT1_2 = %ff;"% (SQRT1_2))
print("__constant__ float SQRT1_8 = %ff;"% (SQRT1_8))
print("__constant__ float COSN1[] = {%ff,%ff};"% (CN[0][0],CN[0][1]))
print("__constant__ float COSN2[] = {%ff,%ff,%ff,%ff};"% (CN[1][0],CN[1][1],CN[1][2],CN[1][3]))
print("__constant__ float SINN1[] = {%ff,%ff};"% (SN[0][0],SN[0][1]))
print("__constant__ float SINN2[] = {%ff,%ff,%ff,%ff};"% (SN[1][0],SN[1][1],SN[1][2],SN[1][3]))
*/
__constant__ float COSPI_1_8_SQRT2 = 1.306563f;
__constant__ float COSPI_3_8_SQRT2 = 0.541196f;
__constant__ float SQRT_2 = 1.414214f;
__constant__ float SQRT1_2 = 0.707107f;
__constant__ float SQRT1_8 = 0.353553f;
__constant__ float COSN1[] = {0.980785f,0.831470f};
__constant__ float COSN2[] = {0.995185f,0.956940f,0.881921f,0.773010f};
__constant__ float SINN1[] = {0.195090f,0.555570f};
__constant__ float SINN2[] = {0.098017f,0.290285f,0.471397f,0.634393f};
inline __device__ void dttii_shared_mem(float * x0, int inc, int dst_not_dct);
inline __device__ void dttiv_shared_mem(float * x0, int inc, int dst_not_dct);
inline __device__ void dttiv_nodiverg(float * x, int inc, int dst_not_dct);
inline __device__ void dctiv_nodiverg(float * x0, int inc);
inline __device__ void dstiv_nodiverg(float * x0, int inc);
inline __device__ void dct_ii8 ( float x[8], float y[8]); // x,y point to 8-element arrays each
inline __device__ void dct_iv8 ( float x[8], float y[8]); // x,y point to 8-element arrays each
inline __device__ void dst_iv8 ( float x[8], float y[8]); // x,y point to 8-element arrays each
inline __device__ void _dctii_nrecurs8 ( float x[8], float y[8]); // x,y point to 8-element arrays each
inline __device__ void _dctiv_nrecurs8 ( float x[8], float y[8]); // x,y point to 8-element arrays each
/**
**************************************************************************
* Converts 2D image (in the GPU memory) using 8x8 DTT 8x8 tiles.
* Mostly for testing and profiling individual converions
*
* \param dst [OUT] - Coefficients as 8x8 tiles
* \param src [IN] - Source image of floats
* \param src_stride [IN] - Source image stride
* \param mode [IN] - DTT mode:
* 0 - horizontal DCT-IV followed by vertical DCT-IV
* 1 - horizontal DST-IV followed by vertical DCT-IV
* 2 - horizontal DCT-IV followed by vertical DST-IV
* 3 - horizontal DST-IV followed by vertical DST-IV
* 4 - horizontal DCT-II followed by vertical DCT-II
* 5 - horizontal DST-II followed by vertical DCT-II
* 6 - horizontal DCT-II followed by vertical DST-II
* 7 - horizontal DST-II followed by vertical DST-II
*
* \return None
*/
extern "C"
__global__ void GPU_DTT24_DRV(float *dst, float *src, int src_stride, int dtt_mode)
{
int dtt_mode0 = dtt_mode & 1;
int dtt_mode1 = (dtt_mode >>1) & 1;
__shared__ float block[DTTTEST_BLOCK_HEIGHT * DTTTEST_BLK_STRIDE];
int OffsThreadInRow = threadIdx.y * DTT_SIZE + threadIdx.x;
int OffsThreadInCol = threadIdx.z * DTT_SIZE;
src += ((blockIdx.y * DTTTEST_BLOCK_HEIGHT + OffsThreadInCol) * src_stride) + blockIdx.x * DTTTEST_BLOCK_WIDTH + OffsThreadInRow;
dst += ((blockIdx.y * DTTTEST_BLOCK_HEIGHT + OffsThreadInCol) * src_stride) + blockIdx.x * DTTTEST_BLOCK_WIDTH + OffsThreadInRow;
float *bl_ptr = block + OffsThreadInCol * DTTTEST_BLK_STRIDE + OffsThreadInRow;
#pragma unroll
for (unsigned int i = 0; i < DTT_SIZE; i++)
bl_ptr[i * DTTTEST_BLK_STRIDE] = src[i * src_stride];
__syncthreads();
// horizontal pass
if (dtt_mode > 3) {
dttii_shared_mem (block + (OffsThreadInCol + threadIdx.x) * DTTTEST_BLK_STRIDE + OffsThreadInRow - threadIdx.x, 1, dtt_mode0);
} else {
dttiv_shared_mem (block + (OffsThreadInCol + threadIdx.x) * DTTTEST_BLK_STRIDE + OffsThreadInRow - threadIdx.x, 1, dtt_mode0);
}
__syncthreads();
// vertical pass
if (dtt_mode > 3) {
dttii_shared_mem (bl_ptr, DTTTEST_BLK_STRIDE, dtt_mode1);
} else {
dttiv_shared_mem (bl_ptr, DTTTEST_BLK_STRIDE, dtt_mode1);
}
__syncthreads();
for (unsigned int i = 0; i < DTT_SIZE; i++)
dst[i * src_stride] = bl_ptr[i * DTTTEST_BLK_STRIDE];
}
inline __device__ void _dctiv_nrecurs8( float x[8], float y[8]) // x,y point to 8-element arrays each
{
float u00= ( COSN2[0] * x[0] + SINN2[0] * x[7]);
float u10= (-SINN2[3] * x[3] + COSN2[3] * x[4]);
float u01= ( COSN2[1] * x[1] + SINN2[1] * x[6]);
float u11= -(-SINN2[2] * x[2] + COSN2[2] * x[5]);
float u02= ( COSN2[2] * x[2] + SINN2[2] * x[5]);
float u12= (-SINN2[1] * x[1] + COSN2[1] * x[6]);
float u03= ( COSN2[3] * x[3] + SINN2[3] * x[4]);
float u13= -(-SINN2[0] * x[0] + COSN2[0] * x[7]);
// _dctii_nrecurs4(u00, u01, u02, u03, &v00, &v01, &v02, &v03);
float ua00= u00 + u03;
float ua10= u00 - u03;
float ua01= u01 + u02;
float ua11= u01 - u02;
float v00= ua00 + ua01;
float v02= ua00 - ua01;
float v01= COSPI_1_8_SQRT2 * ua10 + COSPI_3_8_SQRT2 * ua11;
float v03= COSPI_3_8_SQRT2 * ua10 - COSPI_1_8_SQRT2 * ua11;
// _dctii_nrecurs4(u10, u11, u12, u13, &v10, &v11, &v12, &v13);
float ub00= u10 + u13;
float ub10= u10 - u13;
float ub01= u11 + u12;
float ub11= u11 - u12;
float vb00= ub00 + ub01;
float vb01= ub00 - ub01;
float vb10= COSPI_1_8_SQRT2*ub10 + COSPI_3_8_SQRT2*ub11;
float vb11= COSPI_3_8_SQRT2*ub10 - COSPI_1_8_SQRT2*ub11;
y[0] = SQRT_2 * v00; // w0[0];
y[1] = v01 - vb11; // w1[0];
// j == 1
y[2] = v01 + vb11; // w0[1];
y[3] = v02 + vb01; // w1[1];
// j == 2
y[4] = v02 - vb01; // w0[2];
y[5] = v03 - vb10; // w1[2]; - same as y[3]
// j == 3
y[6] = v03 + vb10; // w0[3];
y[7] = SQRT_2 * vb00; // w1[3];
}
inline __device__ void _dttiv(float x0, float x1,float x2, float x3,float x4, float x5,float x6, float x7,
float *y0, float *y1, float *y2, float *y3, float *y4, float *y5, float *y6, float *y7, int dst_not_dct)
{
float u00, u01, u02, u03, u10, u11, u12, u13;
if (dst_not_dct) { // DSTIV
u00= ( COSN2[0] * x7 + SINN2[0] * x0);
u10= (-SINN2[3] * x4 + COSN2[3] * x3);
u01= ( COSN2[1] * x6 + SINN2[1] * x1);
u11= -(-SINN2[2] * x5 + COSN2[2] * x2);
u02= ( COSN2[2] * x5 + SINN2[2] * x2);
u12= (-SINN2[1] * x6 + COSN2[1] * x1);
u03= ( COSN2[3] * x4 + SINN2[3] * x3);
u13= -(-SINN2[0] * x7 + COSN2[0] * x0);
} else { // DCTIV
u00= ( COSN2[0] * x0 + SINN2[0] * x7);
u10= (-SINN2[3] * x3 + COSN2[3] * x4);
u01= ( COSN2[1] * x1 + SINN2[1] * x6);
u11= -(-SINN2[2] * x2 + COSN2[2] * x5);
u02= ( COSN2[2] * x2 + SINN2[2] * x5);
u12= (-SINN2[1] * x1 + COSN2[1] * x6);
u03= ( COSN2[3] * x3 + SINN2[3] * x4);
u13= -(-SINN2[0] * x0 + COSN2[0] * x7);
}
// _dctii_nrecurs4(u00, u01, u02, u03, &v00, &v01, &v02, &v03);
float ua00= u00 + u03;
float ua10= u00 - u03;
float ua01= u01 + u02;
float ua11= u01 - u02;
float v00= ua00 + ua01;
float v02= ua00 - ua01;
float v01= COSPI_1_8_SQRT2 * ua10 + COSPI_3_8_SQRT2 * ua11;
float v03= COSPI_3_8_SQRT2 * ua10 - COSPI_1_8_SQRT2 * ua11;
// _dctii_nrecurs4(u10, u11, u12, u13, &v10, &v11, &v12, &v13);
float ub00= u10 + u13;
float ub10= u10 - u13;
float ub01= u11 + u12;
float ub11= u11 - u12;
float vb00= ub00 + ub01;
float vb01= ub00 - ub01;
float vb10= COSPI_1_8_SQRT2*ub10 + COSPI_3_8_SQRT2*ub11;
float vb11= COSPI_3_8_SQRT2*ub10 - COSPI_1_8_SQRT2*ub11;
*y0 = v00 * 0.5f; // w0[0];
// j == 1
*y2 = (v01 + vb11) * SQRT1_8; // w0[1];
// j == 2
*y4 = (v02 - vb01) * SQRT1_8; // w0[2];
// j == 3
*y6 = (v03 + vb10) * SQRT1_8; // w0[3];
if (dst_not_dct) { // DSTIV
*y1 = (vb11 - v01) * SQRT1_8; // w1[0];
*y3 = -(v02 + vb01) * SQRT1_8; // w1[1];
*y5 = (vb10 - v03) * SQRT1_8; // w1[2]; - same as y[3]
*y7 = -vb00 * 0.5f; // w1[3];
} else {
*y1 = (v01 - vb11) * SQRT1_8; // w1[0];
*y3 = (v02 + vb01) * SQRT1_8; // w1[1];
*y5 = (v03 - vb10) * SQRT1_8; // w1[2]; - same as y[3]
*y7 = vb00 * 0.5f; // w1[3];
}
}
inline __device__ void dttii_shared_mem(float * x0, int inc, int dst_not_dct)
{
float *x1 = x0 + inc;
float *x2 = x1 + inc;
float *x3 = x2 + inc;
float *x4 = x3 + inc;
float *x5 = x4 + inc;
float *x6 = x5 + inc;
float *x7 = x6 + inc;
float u00, u01, u02, u03, u10, u11, u12, u13;
if (dst_not_dct) { // DSTII
// invert odd input samples
u00= ( (*x0) - (*x7));
u10= ( (*x0) + (*x7));
u01= (-(*x1) + (*x6));
u11= (-(*x1) - (*x6));
u02= ( (*x2) - (*x5));
u12= ( (*x2) + (*x5));
u03= (-(*x3) + (*x4));
u13= (-(*x3) - (*x4));
} else { // DCTII
u00= ( (*x0) + (*x7));
u10= ( (*x0) - (*x7));
u01= ( (*x1) + (*x6));
u11= ( (*x1) - (*x6));
u02= ( (*x2) + (*x5));
u12= ( (*x2) - (*x5));
u03= ( (*x3) + (*x4));
u13= ( (*x3) - (*x4));
}
// _dctii_nrecurs4(u00,u01, u02, u03, &v00, &v01, &v02, &v03);
float w00= u00 + u03;
float w10= u00 - u03;
float w01= (u01 + u02);
float w11= (u01 - u02);
float v01= COSPI_1_8_SQRT2 * w10 + COSPI_3_8_SQRT2 * w11;
float v03= COSPI_3_8_SQRT2 * w10 - COSPI_1_8_SQRT2 * w11;
// _dctiv_nrecurs4(u10, u11, u12, u13, &v10, &v11, &v12, &v13);
float w20= ( COSN1[0] * u10 + SINN1[0] * u13);
float w30= (-SINN1[1] * u11 + COSN1[1] * u12);
float w21= ( COSN1[1] * u11 + SINN1[1] * u12);
float w31= -(-SINN1[0] * u10 + COSN1[0] * u13);
float v11 = w20 - w21 - w30 + w31;
float v12 = w20 - w21 + w30 - w31;
if (dst_not_dct) { // DSTII
// Invert output sequence
*x0 = (w30 + w31)* 0.5f; // v13 * SQRT1_8; z10 * 0.5f
*x1 = v03 * SQRT1_8;
*x2 = v12 * SQRT1_8;
*x3 = (w00 - w01) * SQRT1_8; // v02 * SQRT1_8
*x4 = v11 * SQRT1_8;
*x5 = v01 * SQRT1_8;
*x6 = (w20 + w21) * 0.5f; // v10 * SQRT1_8; z00 * 0.5f;
*x7 = (w00 + w01) * SQRT1_8; // v00 * SQRT1_8
} else {
*x0 = (w00 + w01) * SQRT1_8; // v00 * SQRT1_8
*x1 = (w20 + w21) * 0.5f; // v10 * SQRT1_8; z00 * 0.5f;
*x2 = v01 * SQRT1_8;
*x3 = v11 * SQRT1_8;
*x4 = (w00 - w01) * SQRT1_8; // v02 * SQRT1_8
*x5 = v12 * SQRT1_8;
*x6 = v03 * SQRT1_8;
*x7 = (w30 + w31)* 0.5f; // v13 * SQRT1_8; z10 * 0.5f
}
}
inline __device__ void dttiv_shared_mem(float * x0, int inc, int dst_not_dct)
{
float *x1 = x0 + inc;
float *x2 = x1 + inc;
float *x3 = x2 + inc;
float *x4 = x3 + inc;
float *x5 = x4 + inc;
float *x6 = x5 + inc;
float *x7 = x6 + inc;
float u00, u01, u02, u03, u10, u11, u12, u13;
if (dst_not_dct) { // DSTIV
u00= ( COSN2[0] * (*x7) + SINN2[0] * (*x0));
u10= (-SINN2[3] * (*x4) + COSN2[3] * (*x3));
u01= ( COSN2[1] * (*x6) + SINN2[1] * (*x1));
u11= -(-SINN2[2] * (*x5) + COSN2[2] * (*x2));
u02= ( COSN2[2] * (*x5) + SINN2[2] * (*x2));
u12= (-SINN2[1] * (*x6) + COSN2[1] * (*x1));
u03= ( COSN2[3] * (*x4) + SINN2[3] * (*x3));
u13= -(-SINN2[0] * (*x7) + COSN2[0] * (*x0));
} else { // DCTIV
u00= ( COSN2[0] * (*x0) + SINN2[0] * (*x7));
u10= (-SINN2[3] * (*x3) + COSN2[3] * (*x4));
u01= ( COSN2[1] * (*x1) + SINN2[1] * (*x6));
u11= -(-SINN2[2] * (*x2) + COSN2[2] * (*x5));
u02= ( COSN2[2] * (*x2) + SINN2[2] * (*x5));
u12= (-SINN2[1] * (*x1) + COSN2[1] * (*x6));
u03= ( COSN2[3] * (*x3) + SINN2[3] * (*x4));
u13= -(-SINN2[0] * (*x0) + COSN2[0] * (*x7));
}
// _dctii_nrecurs4(u00, u01, u02, u03, &v00, &v01, &v02, &v03);
float ua00= u00 + u03;
float ua10= u00 - u03;
float ua01= u01 + u02;
float ua11= u01 - u02;
float v00= ua00 + ua01;
float v02= ua00 - ua01;
float v01= COSPI_1_8_SQRT2 * ua10 + COSPI_3_8_SQRT2 * ua11;
float v03= COSPI_3_8_SQRT2 * ua10 - COSPI_1_8_SQRT2 * ua11;
// _dctii_nrecurs4(u10, u11, u12, u13, &v10, &v11, &v12, &v13);
float ub00= u10 + u13;
float ub10= u10 - u13;
float ub01= u11 + u12;
float ub11= u11 - u12;
float vb00= ub00 + ub01;
float vb01= ub00 - ub01;
float vb10= COSPI_1_8_SQRT2*ub10 + COSPI_3_8_SQRT2*ub11;
float vb11= COSPI_3_8_SQRT2*ub10 - COSPI_1_8_SQRT2*ub11;
*x0 = v00 * 0.5f; // w0[0];
*x2 = (v01 + vb11) * SQRT1_8; // w0[1];
*x4 = (v02 - vb01) * SQRT1_8; // w0[2];
*x6 = (v03 + vb10) * SQRT1_8; // w0[3];
if (dst_not_dct) { // DSTIV
*x1 = (vb11 - v01) * SQRT1_8; // w1[0];
*x3 = -(v02 + vb01) * SQRT1_8; // w1[1];
*x5 = (vb10 - v03) * SQRT1_8; // w1[2]; - same as y[3]
*x7 = -vb00 * 0.5f; // w1[3];
} else {
*x1 = (v01 - vb11) * SQRT1_8; // w1[0];
*x3 = (v02 + vb01) * SQRT1_8; // w1[1];
*x5 = (v03 - vb10) * SQRT1_8; // w1[2]; - same as y[3]
*x7 = vb00 * 0.5f; // w1[3];
}
}
inline __device__ void dttiv_nodiverg(float * x, int inc, int dst_not_dct)
{
float sgn = 1 - 2* dst_not_dct;
float *y0 = x;
float *y1 = y0 + inc;
float *y2 = y1 + inc;
float *y3 = y2 + inc;
float *y4 = y3 + inc;
float *y5 = y4 + inc;
float *y6 = y5 + inc;
float *y7 = y6 + inc;
float *x0 = x + dst_not_dct * 7 * inc;
// negate inc, replace
inc *= sgn;
float *x1 = x0 + inc;
float *x2 = x1 + inc;
float *x3 = x2 + inc;
float *x4 = x3 + inc;
float *x5 = x4 + inc;
float *x6 = x5 + inc;
float *x7 = x6 + inc;
float u00, u01, u02, u03, u10, u11, u12, u13;
u00= ( COSN2[0] * (*x0) + SINN2[0] * (*x7));
u10= (-SINN2[3] * (*x3) + COSN2[3] * (*x4));
u01= ( COSN2[1] * (*x1) + SINN2[1] * (*x6));
u11= -(-SINN2[2] * (*x2) + COSN2[2] * (*x5));
u02= ( COSN2[2] * (*x2) + SINN2[2] * (*x5));
u12= (-SINN2[1] * (*x1) + COSN2[1] * (*x6));
u03= ( COSN2[3] * (*x3) + SINN2[3] * (*x4));
u13= -(-SINN2[0] * (*x0) + COSN2[0] * (*x7));
// _dctii_nrecurs4(u00, u01, u02, u03, &v00, &v01, &v02, &v03);
float ua00= u00 + u03;
float ua10= u00 - u03;
float ua01= u01 + u02;
float ua11= u01 - u02;
float v00= ua00 + ua01;
float v02= ua00 - ua01;
float v01= COSPI_1_8_SQRT2 * ua10 + COSPI_3_8_SQRT2 * ua11;
float v03= COSPI_3_8_SQRT2 * ua10 - COSPI_1_8_SQRT2 * ua11;
// _dctii_nrecurs4(u10, u11, u12, u13, &v10, &v11, &v12, &v13);
float ub00= u10 + u13;
float ub10= u10 - u13;
float ub01= u11 + u12;
float ub11= u11 - u12;
float vb00= ub00 + ub01;
float vb01= ub00 - ub01;
float vb10= COSPI_1_8_SQRT2*ub10 + COSPI_3_8_SQRT2*ub11;
float vb11= COSPI_3_8_SQRT2*ub10 - COSPI_1_8_SQRT2*ub11;
*y0 = v00 * 0.5f; // w0[0];
*y2 = (v01 + vb11) * SQRT1_8; // w0[1];
*y4 = (v02 - vb01) * SQRT1_8; // w0[2];
*y6 = (v03 + vb10) * SQRT1_8; // w0[3];
*y1 = sgn * (v01 - vb11) * SQRT1_8; // w1[0];
*y3 = sgn * (v02 + vb01) * SQRT1_8; // w1[1];
*y5 = sgn * (v03 - vb10) * SQRT1_8; // w1[2]; - same as y[3]
*y7 = sgn * vb00 * 0.5f; // w1[3];
}
inline __device__ void dctiv_nodiverg(float * x0, int inc)
{
float *x1 = x0 + inc;
float *x2 = x1 + inc;
float *x3 = x2 + inc;
float *x4 = x3 + inc;
float *x5 = x4 + inc;
float *x6 = x5 + inc;
float *x7 = x6 + inc;
float u00, u01, u02, u03, u10, u11, u12, u13;
u00= ( COSN2[0] * (*x0) + SINN2[0] * (*x7));
u10= (-SINN2[3] * (*x3) + COSN2[3] * (*x4));
u01= ( COSN2[1] * (*x1) + SINN2[1] * (*x6));
u11= -(-SINN2[2] * (*x2) + COSN2[2] * (*x5));
u02= ( COSN2[2] * (*x2) + SINN2[2] * (*x5));
u12= (-SINN2[1] * (*x1) + COSN2[1] * (*x6));
u03= ( COSN2[3] * (*x3) + SINN2[3] * (*x4));
u13= -(-SINN2[0] * (*x0) + COSN2[0] * (*x7));
// _dctii_nrecurs4(u00, u01, u02, u03, &v00, &v01, &v02, &v03);
float ua00= u00 + u03;
float ua10= u00 - u03;
float ua01= u01 + u02;
float ua11= u01 - u02;
float v00= ua00 + ua01;
float v02= ua00 - ua01;
float v01= COSPI_1_8_SQRT2 * ua10 + COSPI_3_8_SQRT2 * ua11;
float v03= COSPI_3_8_SQRT2 * ua10 - COSPI_1_8_SQRT2 * ua11;
// _dctii_nrecurs4(u10, u11, u12, u13, &v10, &v11, &v12, &v13);
float ub00= u10 + u13;
float ub10= u10 - u13;
float ub01= u11 + u12;
float ub11= u11 - u12;
float vb00= ub00 + ub01;
float vb01= ub00 - ub01;
float vb10= COSPI_1_8_SQRT2*ub10 + COSPI_3_8_SQRT2*ub11;
float vb11= COSPI_3_8_SQRT2*ub10 - COSPI_1_8_SQRT2*ub11;
*x0 = v00 * 0.5f; // w0[0];
*x2 = (v01 + vb11) * SQRT1_8; // w0[1];
*x4 = (v02 - vb01) * SQRT1_8; // w0[2];
*x6 = (v03 + vb10) * SQRT1_8; // w0[3];
*x1 = (v01 - vb11) * SQRT1_8; // w1[0];
*x3 = (v02 + vb01) * SQRT1_8; // w1[1];
*x5 = (v03 - vb10) * SQRT1_8; // w1[2]; - same as y[3]
*x7 = vb00 * 0.5f; // w1[3];
}
inline __device__ void dstiv_nodiverg(float * x, int inc)
{
float *x0 = x + 7 * inc;
// negate inc, replace
inc = -inc;
float *x1 = x0 + inc;
float *x2 = x1 + inc;
float *x3 = x2 + inc;
float *x4 = x3 + inc;
float *x5 = x4 + inc;
float *x6 = x5 + inc;
float *x7 = x6 + inc;
float u00, u01, u02, u03, u10, u11, u12, u13;
u00= ( COSN2[0] * (*x0) + SINN2[0] * (*x7));
u10= (-SINN2[3] * (*x3) + COSN2[3] * (*x4));
u01= ( COSN2[1] * (*x1) + SINN2[1] * (*x6));
u11= -(-SINN2[2] * (*x2) + COSN2[2] * (*x5));
u02= ( COSN2[2] * (*x2) + SINN2[2] * (*x5));
u12= (-SINN2[1] * (*x1) + COSN2[1] * (*x6));
u03= ( COSN2[3] * (*x3) + SINN2[3] * (*x4));
u13= -(-SINN2[0] * (*x0) + COSN2[0] * (*x7));
// _dctii_nrecurs4(u00, u01, u02, u03, &v00, &v01, &v02, &v03);
float ua00= u00 + u03;
float ua10= u00 - u03;
float ua01= u01 + u02;
float ua11= u01 - u02;
float v00= ua00 + ua01;
float v02= ua00 - ua01;
float v01= COSPI_1_8_SQRT2 * ua10 + COSPI_3_8_SQRT2 * ua11;
float v03= COSPI_3_8_SQRT2 * ua10 - COSPI_1_8_SQRT2 * ua11;
// _dctii_nrecurs4(u10, u11, u12, u13, &v10, &v11, &v12, &v13);
float ub00= u10 + u13;
float ub10= u10 - u13;
float ub01= u11 + u12;
float ub11= u11 - u12;
float vb00= ub00 + ub01;
float vb01= ub00 - ub01;
float vb10= COSPI_1_8_SQRT2*ub10 + COSPI_3_8_SQRT2*ub11;
float vb11= COSPI_3_8_SQRT2*ub10 - COSPI_1_8_SQRT2*ub11;
*x7 = v00 * 0.5f; // w0[0];
*x5 = (v01 + vb11) * SQRT1_8; // w0[1];
*x3 = (v02 - vb01) * SQRT1_8; // w0[2];
*x1 = (v03 + vb10) * SQRT1_8; // w0[3];
*x6 = (vb11 - v01) * SQRT1_8; // w1[0];
*x4 = -(v02 + vb01) * SQRT1_8; // w1[1];
*x2 = (vb10 - v03) * SQRT1_8; // w1[2]; - same as y[3]
*x0 = -vb00 * 0.5f; // w1[3];
}
inline __device__ void _dctii_nrecurs8( float x[8], float y[8]) // x,y point to 8-element arrays each
{
float u00= (x[0] + x[7]);
float u10= (x[0] - x[7]);
float u01= (x[1] + x[6]);
float u11= (x[1] - x[6]);
float u02= (x[2] + x[5]);
float u12= (x[2] - x[5]);
float u03= (x[3] + x[4]);
float u13= (x[3] - x[4]);
// _dctii_nrecurs4(u00, u01, u02, u03, &v00, &v01, &v02, &v03);
float w00= u00 + u03;
float w10= u00 - u03;
float w01= (u01 + u02);
float w11= (u01 - u02);
float v00= w00 + w01;
float v02= w00 - w01;
float v01= COSPI_1_8_SQRT2 * w10 + COSPI_3_8_SQRT2 * w11;
float v03= COSPI_3_8_SQRT2 * w10 - COSPI_1_8_SQRT2 * w11;
// _dctiv_nrecurs4(u10, u11, u12, u13, &v10, &v11, &v12, &v13);
float w20= ( COSN1[0] * u10 + SINN1[0] * u13);
float w30= (-SINN1[1] * u11 + COSN1[1] * u12);
float w21= ( COSN1[1] * u11 + SINN1[1] * u12);
float w31= -(-SINN1[0] * u10 + COSN1[0] * u13);
// _dctii_nrecurs2(u00, u01, &v00, &v01);
float z00= w20 + w21;
float z01= w20 - w21;
// _dctii_nrecurs2(u10, u11, &v10, &v11);
float z10= w30 + w31;
float z11= w30 - w31;
float v10 = SQRT_2 * z00;
float v11 = z01 - z11;
float v12 = z01 + z11;
float v13 = SQRT_2 * z10;
y[0] = v00;
y[1] = v10;
y[2] = v01;
y[3] = v11;
y[4] = v02;
y[5] = v12;
y[6] = v03;
y[7] = v13;
}
inline __device__ void dct_ii8( float x[8], float y[8]) // x,y point to 8-element arrays each
{
_dctii_nrecurs8(x, y);
#pragma unroll
for (int i = 0; i < 8 ; i++) {
y[i] *= SQRT1_8;
}
}
inline __device__ void dct_iv8( float x[8], float y[8]) // x,y point to 8-element arrays each
{
_dctiv_nrecurs8(x, y);
#pragma unroll
for (int i = 0; i < 8 ; i++) {
y[i] *= SQRT1_8;
}
}
inline __device__ void dst_iv8( float x[8], float y[8]) // x,y point to 8-element arrays each
{
float xr[8];
#pragma unroll
for (int i=0; i < 8;i++){
xr[i] = x[7 - i];
}
_dctiv_nrecurs8(xr, y);
#pragma unroll
for (int i=0; i < 8;i+=2){
y[i] *= SQRT1_8;
y[i+1] *= -SQRT1_8;
}
}
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