private void myWindow_Loaded(object sender, RoutedEventArgs e)
{
infoLog.SetValue(Paragraph.LineHeightProperty, 1.0);
string devName;
if (findGraphicsGPU(out devName) == 0)
{
infoLog.AppendText(devName + " is not supported on " + System.AppDomain.CurrentDomain.FriendlyName + ".");
return;
}
if (!InitializeD3D())
{
return;
}
InitializeCUFFT();
InitializeVB();
InitializePointTexture();
stopwatch = new CudaStopWatch(CUEventFlags.BlockingSync);
frameTimer.Start();
//Make sure we start with a content size of 512x512 but can still resize the window after start up
ClearValue(SizeToContentProperty);
infoLog.ClearValue(WidthProperty);
grid.ClearValue(WidthProperty);
grid.ClearValue(HeightProperty);
}
private void Form1_Load(object sender, EventArgs e)
{
string devName;
if (findGraphicsGPU(out devName) == 0)
{
Console.WriteLine(devName + " is not supported on " + System.AppDomain.CurrentDomain.FriendlyName + ".");
return;
}
InitializeD3D();
InitializeCUFFT();
InitializeVB();
InitializePointTexture();
stopwatch = new CudaStopWatch(CUEventFlags.BlockingSync);
Show();
while (isRunning)
{
display();
// Yield the CPU
System.Threading.Thread.Sleep(1);
Application.DoEvents();
}
}
public void CUDA_AddFloatArrays()
{
//Load Kernel image from resources
Stream stream = new StreamReader(resName).BaseStream;
if (stream == null)
{
throw new ArgumentException("Kernel not found in resources.");
}
vectorAddKernel = ctx.LoadKernelPTX(stream, "VecAdd");
var threadsPerBlock = 1024;
vectorAddKernel.BlockDimensions = threadsPerBlock;
vectorAddKernel.GridDimensions = (Count + threadsPerBlock - 1) / threadsPerBlock;
CudaStopWatch w = new CudaStopWatch();
w.Start();
vectorAddKernel.Run(d_A.DevicePointer, d_B.DevicePointer, C.DevicePointer, Count);
w.Stop();
Debug.Log(w.GetElapsedTime() / 1000.0f);
Debug.Log($"{h_A[0]} + {h_B[0]} = {C[0]}");
Debug.Log($"{h_A[Count-1]} + {h_B[Count-1]} = {C[Count-1]}");
// Copy result from device memory to host memory
// h_C contains the result in host memory
// h_C = d_C;
}
static void Main(string[] args)
{
const int nx = 2048;
const int ny = 2048;
// shifts applied to x and y data
const int x_shift = 5;
const int y_shift = 7;
ShrQATest.shrQAStart(args);
if ((nx % TILE_DIM != 0) || (ny % TILE_DIM != 0))
{
Console.Write("nx and ny must be multiples of TILE_DIM\n");
ShrQATest.shrQAFinishExit(args, ShrQATest.eQAstatus.QA_WAIVED);
}
// execution configuration parameters
dim3 grid = new dim3(nx / TILE_DIM, ny / TILE_DIM, 1);
dim3 threads = new dim3(TILE_DIM, TILE_DIM, 1);
// This will pick the best possible CUDA capable device
int devID = findCudaDevice(args);
//Load Kernel image from resources
string resName;
if (IntPtr.Size == 8)
{
resName = "simplePitchLinearTexture_x64.ptx";
}
else
{
resName = "simplePitchLinearTexture.ptx";
}
string resNamespace = "simplePitchLinearTexture";
string resource = resNamespace + "." + resName;
Stream stream = Assembly.GetExecutingAssembly().GetManifestResourceStream(resource);
if (stream == null)
{
throw new ArgumentException("Kernel not found in resources.");
}
byte[] kernels = new byte[stream.Length];
int bytesToRead = (int)stream.Length;
while (bytesToRead > 0)
{
bytesToRead -= stream.Read(kernels, (int)stream.Position, bytesToRead);
}
CudaKernel PLKernel = ctx.LoadKernelPTX(kernels, "shiftPitchLinear");
CudaKernel ArrayKernel = ctx.LoadKernelPTX(kernels, "shiftArray");
CudaStopWatch stopwatch = new CudaStopWatch();
// ----------------------------------
// Host allocation and initialization
// ----------------------------------
float[] h_idata = new float[nx * ny];
float[] h_odata = new float[nx * ny];
float[] gold = new float[nx * ny];
for (int i = 0; i < nx * ny; ++i)
{
h_idata[i] = (float)i;
}
// ------------------------
// Device memory allocation
// ------------------------
// Pitch linear input data
CudaPitchedDeviceVariable <float> d_idataPL = new CudaPitchedDeviceVariable <float>(nx, ny);
// Array input data
CudaArray2D d_idataArray = new CudaArray2D(CUArrayFormat.Float, nx, ny, CudaArray2DNumChannels.One);
// Pitch linear output data
CudaPitchedDeviceVariable <float> d_odata = new CudaPitchedDeviceVariable <float>(nx, ny);
// ------------------------
// copy host data to device
// ------------------------
// Pitch linear
d_idataPL.CopyToDevice(h_idata);
// Array
d_idataArray.CopyFromHostToThis <float>(h_idata);
// ----------------------
// Bind texture to memory
// ----------------------
// Pitch linear
CudaTextureLinearPitched2D <float> texRefPL = new CudaTextureLinearPitched2D <float>(PLKernel, "texRefPL", CUAddressMode.Wrap, CUFilterMode.Point, CUTexRefSetFlags.NormalizedCoordinates, CUArrayFormat.Float, d_idataPL);
CudaTextureArray2D texRefArray = new CudaTextureArray2D(ArrayKernel, "texRefArray", CUAddressMode.Wrap, CUFilterMode.Point, CUTexRefSetFlags.NormalizedCoordinates, d_idataArray);
// ---------------------
// reference calculation
// ---------------------
for (int j = 0; j < ny; j++)
{
int jshift = (j + y_shift) % ny;
for (int i = 0; i < nx; i++)
{
int ishift = (i + x_shift) % nx;
gold[j * nx + i] = h_idata[jshift * nx + ishift];
}
}
// ----------------
// shiftPitchLinear
// ----------------
ctx.ClearMemory(d_odata.DevicePointer, 0, d_odata.TotalSizeInBytes);
PLKernel.BlockDimensions = threads;
PLKernel.GridDimensions = grid;
stopwatch.Start();
for (int i = 0; i < NUM_REPS; i++)
{
PLKernel.Run(d_odata.DevicePointer, (int)(d_odata.Pitch / sizeof(float)), nx, ny, x_shift, y_shift);
}
stopwatch.Stop();
stopwatch.StopEvent.Synchronize();
float timePL = stopwatch.GetElapsedTime();
// check results
d_odata.CopyToHost(h_odata);
bool res = cutComparef(gold, h_odata);
bool success = true;
if (res == false)
{
Console.Write("*** shiftPitchLinear failed ***\n");
success = false;
}
// ----------
// shiftArray
// ----------
ctx.ClearMemory(d_odata.DevicePointer, 0, d_odata.TotalSizeInBytes);
ArrayKernel.BlockDimensions = threads;
ArrayKernel.GridDimensions = grid;
stopwatch.Start();
for (int i = 0; i < NUM_REPS; i++)
{
ArrayKernel.Run(d_odata.DevicePointer, (int)(d_odata.Pitch / sizeof(float)), nx, ny, x_shift, y_shift);
}
stopwatch.Stop();
stopwatch.StopEvent.Synchronize();
float timeArray = stopwatch.GetElapsedTime();
// check results
d_odata.CopyToHost(h_odata);
res = cutComparef(gold, h_odata);
if (res == false)
{
Console.Write("*** shiftArray failed ***\n");
success = false;
}
float bandwidthPL = 2.0f * 1000.0f * nx * ny * sizeof(float) / (1e+9f) / (timePL / NUM_REPS);
float bandwidthArray = 2.0f * 1000.0f * nx * ny * sizeof(float) / (1e+9f) / (timeArray / NUM_REPS);
Console.Write("\nBandwidth (GB/s) for pitch linear: {0}; for array: {1}\n",
bandwidthPL, bandwidthArray);
float fetchRatePL = nx * ny / 1e+6f / (timePL / (1000.0f * NUM_REPS));
float fetchRateArray = nx * ny / 1e+6f / (timeArray / (1000.0f * NUM_REPS));
Console.Write("\nTexture fetch rate (Mpix/s) for pitch linear: {0}; for array: {1}\n\n",
fetchRatePL, fetchRateArray);
// cleanup
texRefPL.Dispose();
texRefArray.Dispose();
d_idataPL.Dispose();
d_idataArray.Dispose();
d_odata.Dispose();
stopwatch.Dispose();
ctx.Dispose();
ShrQATest.shrQAFinishExit(args, (success == true) ? ShrQATest.eQAstatus.QA_PASSED : ShrQATest.eQAstatus.QA_FAILED);
}
public void computeSegmentationFromTrimap()
{
CudaStopWatch stopwatch = new CudaStopWatch();
stopwatch.Start();
iteration = 0;
current_alpha = 0;
// Solve Grabcut on lower resolution first. Reduces total computation time.
createSmallTrimap();
d_alpha[0].AsyncCopyToDevice(d_small_trimap[small_trimap_idx], new CUstream());
for (int i = 0; i < 2; ++i)
{
grabCutGMM.GMMInitialize(gmms, d_gmm, d_scratch_mem, gmm_pitch, d_small_image, d_alpha[current_alpha], small_size.width, small_size.height);
grabCutGMM.GMMUpdate(gmms, d_gmm, d_scratch_mem, gmm_pitch, d_small_image, d_alpha[current_alpha], small_size.width, small_size.height);
grabCutGMM.EdgeCues(edge_strength, d_small_image, d_left_transposed, d_right_transposed, d_top, d_bottom, d_topleft, d_topright, d_bottomleft, d_bottomright, small_size.width, small_size.height, d_scratch_mem);
grabCutGMM.DataTerm(d_terminals, gmms, d_gmm, gmm_pitch, d_small_image, d_small_trimap[small_trimap_idx], small_size.width, small_size.height);
graphcut8Small.GraphCut(d_terminals, d_left_transposed, d_right_transposed, d_top, d_topleft, d_topright, d_bottom, d_bottomleft, d_bottomright, d_alpha[1 - current_alpha]);
current_alpha = 1 - current_alpha;
}
grabCutGMM.UpsampleAlpha(d_alpha[1 - current_alpha], d_alpha[current_alpha], size.width, size.height, small_size.width, small_size.height);
current_alpha = 1 - current_alpha;
grabCutGMM.GMMInitialize(gmms, d_gmm, d_scratch_mem, gmm_pitch, d_image, d_alpha[current_alpha], size.width, size.height);
grabCutGMM.GMMUpdate(gmms, d_gmm, d_scratch_mem, gmm_pitch, d_image, d_alpha[current_alpha], size.width, size.height);
while (true)
{
grabCutGMM.EdgeCues(edge_strength, d_image, d_left_transposed, d_right_transposed, d_top, d_bottom, d_topleft, d_topright, d_bottomleft, d_bottomright, size.width, size.height, d_scratch_mem);
grabCutGMM.DataTerm(d_terminals, gmms, d_gmm, gmm_pitch, d_image, d_trimap, size.width, size.height);
current_alpha = 1 ^ current_alpha;
graphcut8.GraphCut(d_terminals, d_left_transposed, d_right_transposed, d_top, d_topleft, d_topright, d_bottom, d_bottomleft, d_bottomright, d_alpha[current_alpha]);
if (iteration > 0)
{
bool changed = grabCutGMM.SegmentationChanged(d_scratch_mem, d_alpha[1 - current_alpha], d_alpha[current_alpha], size.width, size.height);
// Solution has converged
if (!changed)
{
break;
}
}
if (iteration > MAX_ITERATIONS)
{
// Does not converge, fallback to rect selection
System.Windows.Forms.MessageBox.Show("Warning: Color models did not converge after " + MAX_ITERATIONS + " iterations.");
break;
}
grabCutGMM.GMMInitialize(gmms, d_gmm, d_scratch_mem, gmm_pitch, d_image, d_alpha[current_alpha], size.width, size.height);
grabCutGMM.GMMUpdate(gmms, d_gmm, d_scratch_mem, gmm_pitch, d_image, d_alpha[current_alpha], size.width, size.height);
iteration++;
}
stopwatch.Stop();
stopwatch.StopEvent.Synchronize();
runtime = stopwatch.GetElapsedTime();
}
private void Btn_ProcessPEF_Click(object sender, EventArgs e)
{
if (pef == null)
{
return;
}
denoiseAndDemoisaic.LoadNetwork("epoch_" + learningRate.ToString(CultureInfo.InvariantCulture) + "_" + noiseLevelsFolders[cmb_IsoValue.SelectedIndex] + "_1999.cnn");
NPPImage_16uC1 rawTemp = new NPPImage_16uC1(pef.RawWidth, pef.RawHeight);
rawTemp.CopyToDevice(pef.RawImage);
rawTemp.Convert(imageBayer);
float whiteLevelAll = pef.WhiteLevel.Value;
float3 whitePoint = new float3(whiteLevelAll, whiteLevelAll, whiteLevelAll);
float3 blackPoint = new float3(pef.BlackPoint.Value[0], pef.BlackPoint.Value[1], pef.BlackPoint.Value[3]);
whitePoint -= blackPoint;
float scale = pef.Scaling.Value;
float3 scaling = new float3(pef.WhitePoint.Value[0] / scale, pef.WhitePoint.Value[1] / scale, pef.WhitePoint.Value[3] / scale);
inputImage32f.Set(new float[] { 0, 0, 0 });
deBayerGreenKernel.RunSafe(imageBayer, inputImage32f, blackPoint, scaling);
deBayerRedBlueKernel.RunSafe(imageBayer, inputImage32f, blackPoint, scaling);
inputImage32f.Div(new float[] { whitePoint.x *scaling.x, whitePoint.y *scaling.y, whitePoint.z *scaling.z });
highlightRecoveryKernel.RunSafe(inputImage32f, new float3(scaling.x, scaling.y, scaling.z), 1);
inputImage32f.Sub(new float[] { 0.5f, 0.5f, 0.5f }, noiseImage32f);
Console.WriteLine("Start denoising...");
CudaStopWatch csw = new CudaStopWatch();
csw.Start();
denoiseAndDemoisaic.RunImage(noiseImage32f, resultImage32f);
csw.Stop();
Console.WriteLine("Needed time: " + csw.GetElapsedTime() + " [msec]");
csw.Dispose();
resultImage32f.Add(new float[] { 0.5f, 0.5f, 0.5f });
ColorManagment cm = new ColorManagment();
float3 wp = 1.0f / scaling;
double3 wb = new double3(wp.x, wp.y, wp.z);
double2 neutralXY = cm.NeutralToXY(wb);
cm.SetWhiteXY(neutralXY);
ColorMatrix camToXYZ2 = cm.CameraToPCS;
ColorMatrix d50Tod65 = new ColorMatrix(new double[] { 0.9555766, -0.0230393, 0.0631636, -0.0282895, 1.0099416, 0.0210077, 0.0122982, -0.0204830, 1.3299098 });
ColorMatrix d65TosRGB = new ColorMatrix(new double[] { 3.2406, -1.5372, -0.4986, -0.9689, 1.8758, 0.0415, 0.0557, -0.2040, 1.0570 });
ColorMatrix final = d65TosRGB * d50Tod65 * camToXYZ2;
float[] matData = new float[9];
for (int i = 0; i < 3; i++)
{
for (int j = 0; j < 3; j++)
{
matData[j + i * 3] = (float)final[i, j];
}
}
camToXYZKernel.RunSafe(inputImage32f, matData);
camToXYZKernel.RunSafe(resultImage32f, matData);
//This is a LUT that maps well to most of the JPEGs out of camera, but not always... found somewhere on internet, if I remember well from darktable?
float[] x = new float[] { 0,
0.004754f,
0.009529f,
0.023713f,
0.031866f,
0.046734f,
0.059989f,
0.088415f,
0.13661f,
0.17448f,
0.205192f,
0.228896f,
0.286411f,
0.355314f,
0.440014f,
0.567096f,
0.620597f,
0.760355f,
0.875139f,
1 };
float[] y = new float[] { 0,
0.002208f,
0.004214f,
0.013508f,
0.020352f,
0.034063f,
0.052413f,
0.09603f,
0.190629f,
0.256484f,
0.30743f,
0.348447f,
0.42868f,
0.513527f,
0.607651f,
0.732791f,
0.775968f,
0.881828f,
0.960682f,
1 };
CudaDeviceVariable <float> d_x = x;
CudaDeviceVariable <float> d_y = y;
inputImage32f.LUTCubic(new CudaDeviceVariable <float>[] { d_y, d_y, d_y }, new CudaDeviceVariable <float>[] { d_x, d_x, d_x });
resultImage32f.LUTCubic(new CudaDeviceVariable <float>[] { d_y, d_y, d_y }, new CudaDeviceVariable <float>[] { d_x, d_x, d_x });
convertRGBTosRGBKernel.RunSafe(inputImage32f);
convertRGBTosRGBKernel.RunSafe(resultImage32f);
inputImage32f.Convert(noisyImage8u, NppRoundMode.Near);
resultImage32f.Convert(resultImage8u, NppRoundMode.Near);
noisyImage8u.SetRoi(0, 0, bmpNoisy.Width - 4, bmpNoisy.Height - 4);
noisyImage8u.CopyToHostRoi(bmpNoisy, new NppiRect(2, 2, bmpNoisy.Width - 4, bmpNoisy.Height - 4));
resultImage8u.SetRoi(0, 0, bmpResult.Width - 16, bmpResult.Height - 16);
resultImage8u.CopyToHostRoi(bmpResult, new NppiRect(8, 8, bmpResult.Width - 16, bmpResult.Height - 16));
pictureBox2.Image = bmpNoisy;
pictureBox3.Image = bmpResult;
rawTemp.Dispose();
d_y.Dispose();
d_x.Dispose();
}
private void btn_Process_Click(object sender, EventArgs e)
{
if (bmpInput == null)
{
return;
}
denoiseAndDemoisaic.LoadNetwork("epoch_" + learningRate.ToString(CultureInfo.InvariantCulture) + "_" + noiseLevelsFolders[cmb_IsoValue.SelectedIndex] + "_1999.cnn");
if (bmpInput.PixelFormat == PixelFormat.Format32bppArgb)
{
inputImage8uC4.CopyToDeviceRoi(bmpInput, new NppiRect(0, 0, bmpInput.Width, bmpInput.Height));
//Convert C4 to C3 and BGR to RGB
inputImage8uC4.Copy(inputImage8uC1, 0);
inputImage8uC1.Copy(inputImage8uC3, 2);
inputImage8uC4.Copy(inputImage8uC1, 1);
inputImage8uC1.Copy(inputImage8uC3, 1);
inputImage8uC4.Copy(inputImage8uC1, 2);
inputImage8uC1.Copy(inputImage8uC3, 0);
}
else
{
inputImage8uC3.CopyToDeviceRoi(bmpInput, new NppiRect(0, 0, bmpInput.Width, bmpInput.Height));
inputImage8uC3.ColorTwist(twist);
}
inputImage8uC3.Convert(inputImage32f);
inputImage32f.Div(new float[] { 255, 255, 255 });
NppiRect oldRoi = new NppiRect(0, 0, inputImage32f.WidthRoi, inputImage32f.HeightRoi);
IEnumerable <Tiler.RoiInputOutput> rois = Tiler.GetROIs(oldRoi, TileSize, 0);
foreach (var roi in rois)
{
inputImage32f.SetRoi(roi.inputROI);
tile.ResetRoi();
inputImage32f.Copy(tile);
tile.SetRoi(roi.outputROI);
imageBayer.SetRoi(roi.positionInFinalImage);
createBayerKernel.RunSafe(CuRandStates, tile, imageBayer, noiseLevels[cmb_IsoValue.SelectedIndex], 0);
}
imageBayer.SetRoi(oldRoi);
inputImage32f.SetRoi(oldRoi);
deBayerGreenKernel.RunSafe(imageBayer, inputImage32f, new float3(), new float3(1, 1, 1));
deBayerRedBlueKernel.RunSafe(imageBayer, inputImage32f, new float3(), new float3(1, 1, 1));
inputImage32f.Mul(new float[] { 255, 255, 255 }, noiseImage32f);
noiseImage32f.Convert(noisyImage8u, NppRoundMode.Near);
noisyImage8u.ColorTwist(twist);
noisyImage8u.CopyToHostRoi(bmpNoisy, new NppiRect(0, 0, bmpNoisy.Width, bmpNoisy.Height));
inputImage32f.Sub(new float[] { 0.5f, 0.5f, 0.5f });
CudaStopWatch csw = new CudaStopWatch();
csw.Start();
denoiseAndDemoisaic.RunImage(inputImage32f, resultImage32f);
csw.Stop();
Console.WriteLine("Needed time: " + csw.GetElapsedTime() + " [msec]");
csw.Dispose();
resultImage32f.Add(new float[] { 0.5f, 0.5f, 0.5f });
resultImage32f.Mul(new float[] { 255, 255, 255 });
resultImage32f.Convert(resultImage8u, NppRoundMode.Near);
resultImage8u.ColorTwist(twist);
resultImage8u.SetRoi(0, 0, bmpResult.Width - 16, bmpResult.Height - 16);
resultImage8u.CopyToHostRoi(bmpResult, new NppiRect(8, 8, bmpResult.Width - 16, bmpResult.Height - 16));
pictureBox2.Image = bmpNoisy;
pictureBox3.Image = bmpResult;
}
private void initGLAndCuda()
{
//Create render target control
m_renderControl = new OpenTK.GLControl(GraphicsMode.Default, 1, 0, GraphicsContextFlags.Default);
m_renderControl.Dock = DockStyle.Fill;
m_renderControl.BackColor = Color.White;
m_renderControl.BorderStyle = BorderStyle.FixedSingle;
m_renderControl.KeyDown += new KeyEventHandler(m_renderControl_KeyDown);
m_renderControl.MouseMove += new MouseEventHandler(m_renderControl_MouseMove);
m_renderControl.MouseDown += new MouseEventHandler(m_renderControl_MouseDown);
m_renderControl.SizeChanged += new EventHandler(m_renderControl_SizeChanged);
panel1.Controls.Add(m_renderControl);
Console.WriteLine(" OpenGL device is Available");
int deviceID = CudaContext.GetMaxGflopsDeviceId();
ctx = CudaContext.CreateOpenGLContext(deviceID, CUCtxFlags.BlockingSync);
string console = string.Format("CUDA device [{0}] has {1} Multi-Processors", ctx.GetDeviceName(), ctx.GetDeviceInfo().MultiProcessorCount);
Console.WriteLine(console);
CUmodule module = ctx.LoadModulePTX("kernel.ptx");
addForces_k = new CudaKernel("addForces_k", module, ctx);
advectVelocity_k = new CudaKernel("advectVelocity_k", module, ctx);
diffuseProject_k = new CudaKernel("diffuseProject_k", module, ctx);
updateVelocity_k = new CudaKernel("updateVelocity_k", module, ctx);
advectParticles_k = new CudaKernel("advectParticles_OGL", module, ctx);
hvfield = new cData[DS];
dvfield = new CudaPitchedDeviceVariable <cData>(DIM, DIM);
tPitch = dvfield.Pitch;
dvfield.CopyToDevice(hvfield);
vxfield = new CudaDeviceVariable <cData>(DS);
vyfield = new CudaDeviceVariable <cData>(DS);
// Create particle array
particles = new cData[DS];
initParticles(particles, DIM, DIM);
// TODO: update kernels to use the new unpadded memory layout for perf
// rather than the old FFTW-compatible layout
planr2c = new CudaFFTPlan2D(DIM, DIM, cufftType.R2C, Compatibility.FFTWPadding);
planc2r = new CudaFFTPlan2D(DIM, DIM, cufftType.C2R, Compatibility.FFTWPadding);
GL.GenBuffers(1, out vbo);
GL.BindBuffer(BufferTarget.ArrayBuffer, vbo);
GL.BufferData <cData>(BufferTarget.ArrayBuffer, new IntPtr(cData.SizeOf * DS), particles, BufferUsageHint.DynamicDraw);
int bsize;
GL.GetBufferParameter(BufferTarget.ArrayBuffer, BufferParameterName.BufferSize, out bsize);
if (bsize != DS * cData.SizeOf)
{
throw new Exception("Sizes don't match.");
}
GL.BindBuffer(BufferTarget.ArrayBuffer, 0);
cuda_vbo_resource = new CudaGraphicsInteropResourceCollection();
cuda_vbo_resource.Add(new CudaOpenGLBufferInteropResource(vbo, CUGraphicsRegisterFlags.None));
texref = new CudaTextureArray2D(advectVelocity_k, "texref", CUAddressMode.Wrap, CUFilterMode.Linear, 0, CUArrayFormat.Float, DIM, DIM, CudaArray2DNumChannels.Two);
stopwatch = new CudaStopWatch(CUEventFlags.Default);
reshape();
isInit = true;
display();
}
public void MinimizeCUBLAS(int tileCountX, int tileCountY)
{
int shiftCount;// = shifts.Count;
shiftCount = GetShiftCount();
concatenateShifts.RunSafe(shifts_d, shiftPitches, AllShifts_d, shiftCount, tileCountX, tileCountY);
shiftsMeasured.CopyToDevice(AllShifts_d);
CudaStopWatch sw = new CudaStopWatch();
sw.Start();
int imageCount = frameCount;
int tileCount = tileCountX * tileCountY;
int n1 = imageCount - 1;
int m = shiftCount;
status.Memset(0);
shiftMatrices.Memset(0);
float[] shiftMatrix = CreateShiftMatrix();
shiftMatrices.CopyToDevice(shiftMatrix, 0, 0, shiftMatrix.Length * sizeof(float));
copyShiftMatrixKernel.RunSafe(shiftMatrices, tileCount, imageCount, shiftCount);
shiftSafeMatrices.CopyToDevice(shiftMatrices);
for (int i = 0; i < 10; i++)
{
blas.GemmBatched(Operation.Transpose, Operation.NonTranspose, n1, n1, m, one, shiftMatrixArray, m, shiftMatrixArray, m, zero, matrixSquareArray, n1, tileCount);
//float[] mSqr = matricesSquared;
if (n1 <= 32)
{
//MatinvBatchedS can only invert up to 32x32 matrices
blas.MatinvBatchedS(n1, matrixSquareArray, n1, matrixInvertedArray, n1, infoInverse, tileCount);
}
else
{
blas.GetrfBatchedS(n1, matrixSquareArray, n1, pivotArray, infoInverse, tileCount);
blas.GetriBatchedS(n1, matrixSquareArray, n1, pivotArray, matrixInvertedArray, n1, infoInverse, tileCount);
}
//int[] info = infoInverse;
//mSqr = matricesInverted;
blas.GemmBatched(Operation.NonTranspose, Operation.Transpose, n1, m, n1, one, matrixInvertedArray, n1, shiftMatrixArray, m, zero, solvedMatrixArray, n1, tileCount);
blas.GemmBatched(Operation.NonTranspose, Operation.Transpose, n1, 2, m, one, solvedMatrixArray, n1, shiftMeasuredArray, 2, zero, shiftOneToOneArray, n1, tileCount);
blas.GemmBatched(Operation.NonTranspose, Operation.NonTranspose, m, 2, n1, one, shiftMatrixArray, m, shiftOneToOneArray, n1, zero, shiftOptimArray, m, tileCount);
checkForOutliers.RunSafe(shiftsMeasured, shiftsOptim, shiftMatrices, status, infoInverse, tileCount, imageCount, shiftCount);
status.Sum(statusSum, buffer, 0);
int[] stats = status;
for (int j = 0; j < tileCount; j++)
{
if (stats[j] >= 0)
{
Console.Write(j + ": " + stats[j] + "; ");
}
}
Console.WriteLine();
int stat = statusSum;
if (stat == -tileCount)
{
break;
}
//float2[] AllShifts_h = shiftsMeasured;
}
blas.GemmBatched(Operation.NonTranspose, Operation.NonTranspose, m, 2, n1, one, shiftMatrixSafeArray, m, shiftOneToOneArray, n1, zero, shiftMeasuredArray, m, tileCount);
AllShifts_d.Memset(0);
transposeShifts.RunSafe(AllShifts_d, shiftsMeasured, shiftsOneToOne, shiftsOneToOne_d, tileCount, imageCount, shiftCount);
//shiftsMeasured.CopyToDevice(AllShifts_d);
//float2[] AllShiftsFinal_h = shiftsMeasured;
sw.Stop();
Console.WriteLine("Time for optimisation: " + sw.GetElapsedTime() + " msec.");
separateShifts.RunSafe(AllShifts_d, shifts_d, shiftPitches, shiftCount, tileCountX, tileCountY);
}
