/// <summary>
/// Gets the values for an explicit input
/// </summary>
/// <param name="input">The explicit input</param>
/// <param name="output">The output values</param>
public void GetValues(Single3[] input, ref float[] output)
{
if (context == null || kernelExplicit == null)
{
throw new Exception("Compile first!");
}
int inputLength = input.Length;
// IO length changed
if (lastLength != inputLength)
{
lastLength = inputLength;
outputBuffer = new Cloo.ComputeBuffer <float>(context, ComputeMemoryFlags.WriteOnly | ComputeMemoryFlags.AllocateHostPointer, inputLength);
kernelExplicit.SetMemoryArgument(2, outputBuffer);
}
// Setup IO Buffers
ComputeBuffer <Single3> bufIn = new Cloo.ComputeBuffer <Single3>(context, ComputeMemoryFlags.ReadOnly | ComputeMemoryFlags.CopyHostPointer, input);
// Arrange params
kernelExplicit.SetMemoryArgument(0, bufIn);
// Exec and read
queue.Execute(kernelExplicit, null, new long[] { input.Length }, null, null);
GCHandle outHandle = GCHandle.Alloc(output, GCHandleType.Pinned);
queue.Read <float>(outputBuffer, true, 0, inputLength, outHandle.AddrOfPinnedObject(), null); // Read saves about 500 - 1000 ticks. Sweet for small queues
outHandle.Free();
queue.Finish();
}
/// <summary>
/// Copy a buffer to a float array.
/// </summary>
///
/// <param name="sourceBuffer">The source buffer.</param>
/// <param name="target">The target array.</param>
public void Buffer2Array(ComputeBuffer <float> sourceBuffer, float[] target)
{
GCHandle arrCHandle = GCHandle.Alloc(target, GCHandleType.Pinned);
commands.Read(sourceBuffer, true, 0, target.Length, arrCHandle.AddrOfPinnedObject(), null);
arrCHandle.Free();
}
// Wartosci min, max po OpenCL.
public void GetMinMaxValuesCL(Mat frame, out int[] maxValues, out int[] minValues, int windowValue)
{
maxValues = null;
minValues = null;
try
{
MinMaxCL.UpdateArguments(frame, clooCtx, ctxMinMaxKernel, windowValue);
// execute kernel
queue.Execute(ctxMinMaxKernel, null, new long[] { frame.Cols }, null, null);
// max Values.
maxValues = new int[frame.Cols];
GCHandle maxHandle = GCHandle.Alloc(maxValues, GCHandleType.Pinned);
queue.Read(MinMaxCL.maxBufferCB, true, 0, maxValues.Length, maxHandle.AddrOfPinnedObject(), null);
// min Values.
minValues = new int[frame.Cols];
GCHandle minHandle = GCHandle.Alloc(minValues, GCHandleType.Pinned);
queue.Read(MinMaxCL.minBufferCB, true, 0, minValues.Length, minHandle.AddrOfPinnedObject(), null);
// end opencl compute.
queue.Finish();
} catch (Exception ex)
{
MessageBox.Show(ex.Message);
}
}
static void Main(string[] args)
{
int[] r1 = new int[]
{ 8, 2, 3, 4 };
int[] r2 = new int[]
{ 4, 3, 2, 5 };
int[] r3 = new int[4];
int rowSize = r1.Length;
// pick first platform
ComputePlatform platform = ComputePlatform.Platforms[0];
// create context with all gpu devices
ComputeContext context = new ComputeContext(ComputeDeviceTypes.Gpu,
new ComputeContextPropertyList(platform), null, IntPtr.Zero);
// create a command queue with first gpu found
ComputeCommandQueue queue = new ComputeCommandQueue(context,
context.Devices[0], ComputeCommandQueueFlags.None);
// load opencl source and
// create program with opencl source
ComputeProgram program = new ComputeProgram(context, CalculateKernel);
// compile opencl source
program.Build(null, null, null, IntPtr.Zero);
// load chosen kernel from program
ComputeKernel kernel = program.CreateKernel("Calc");
// allocate a memory buffer with the message (the int array)
ComputeBuffer <int> row1Buffer = new ComputeBuffer <int>(context,
ComputeMemoryFlags.ReadOnly | ComputeMemoryFlags.UseHostPointer, r1);
// allocate a memory buffer with the message (the int array)
ComputeBuffer <int> row2Buffer = new ComputeBuffer <int>(context,
ComputeMemoryFlags.ReadOnly | ComputeMemoryFlags.UseHostPointer, r2);
// allocate a memory buffer with the message (the int array)
ComputeBuffer <int> resultBuffer = new ComputeBuffer <int>(context,
ComputeMemoryFlags.ReadOnly | ComputeMemoryFlags.UseHostPointer, new int[4]);
kernel.SetMemoryArgument(0, row1Buffer); // set the integer array
kernel.SetMemoryArgument(1, row2Buffer); // set the integer array
kernel.SetValueArgument(2, rowSize); // set the array size
kernel.SetMemoryArgument(3, resultBuffer); // set the integer array
// execute kernel
queue.ExecuteTask(kernel, null);
// wait for completion
queue.Finish();
GCHandle arrCHandle = GCHandle.Alloc(r3, GCHandleType.Pinned);
queue.Read <int>(resultBuffer, true, 0, r3.Length, arrCHandle.AddrOfPinnedObject(), null);
Console.WriteLine("display result from gpu buffer:");
for (int i = 0; i < r3.Length; i++)
{
Console.WriteLine(r3[i]);
}
arrCHandle.Free();
row1Buffer.Dispose();
row2Buffer.Dispose();
kernel.Dispose();
program.Dispose();
queue.Dispose();
context.Dispose();
Console.WriteLine("Finished");
Console.ReadKey();
}
public static Tuple <List <List <int> >, TimeSpan> MultiplyParallel(List <List <int> > matrixOne, List <List <int> > matrixTwo)
{
if (!isRegularMatrix(matrixOne) || !isRegularMatrix(matrixTwo))
{
throw new ArgumentException("Non regular matrix detected. Rows size mismatch detected.");
}
if (matrixOne[0].Count != matrixTwo.Count)
{
throw new ArgumentException("Matrixes is not compatible. Columns count of first matrix is not equal to rows count of second matrix.");
}
List <List <int> > result = new List <List <int> >();
ComputePlatform platform = GetGPU();
if (platform is null)
{
throw new PlatformNotSupportedException("Platform doesn't have a dedicated GPU. Run is impossible.");
}
ComputeContext context = new ComputeContext(ComputeDeviceTypes.Gpu, new ComputeContextPropertyList(platform), null, IntPtr.Zero);
ComputeCommandQueue queue = new ComputeCommandQueue(context, context.Devices[0], ComputeCommandQueueFlags.None);
ComputeProgram program = new ComputeProgram(context, CalculateKernel);
program.Build(null, null, null, IntPtr.Zero);
ComputeKernel kernel = program.CreateKernel("Multiply");
List <ComputeBuffer <int> > rowsMatrixOne = matrixOne.TransformMatrixToComputerBuffersOfRows(context);
List <ComputeBuffer <int> > columnsMatrixTwo = matrixTwo.TransformMatrixToComputerBuffersOfColumns(context);
List <ComputeBuffer <int> > resultRowsMatrix = TwoDToOneDResult(matrixOne.Count, matrixTwo[0].Count, context);
Stopwatch stopwatch = new Stopwatch();
stopwatch.Start();
for (int i = 0; i < resultRowsMatrix.Count; ++i)
{
for (int j = 0; j < resultRowsMatrix[i].Count; ++j)
{
kernel.SetMemoryArgument(0, rowsMatrixOne[i]);
kernel.SetMemoryArgument(1, columnsMatrixTwo[j]);
kernel.SetMemoryArgument(2, resultRowsMatrix[i]);
kernel.SetValueArgument(3, matrixTwo.Count);
kernel.SetValueArgument(4, j);
queue.ExecuteTask(kernel, null);
}
}
queue.Finish();
stopwatch.Stop();
for (int i = 0; i < resultRowsMatrix.Count; ++i)
{
int[] res = new int[resultRowsMatrix[i].Count];
GCHandle gCHandle = GCHandle.Alloc(res, GCHandleType.Pinned);
queue.Read <int>(resultRowsMatrix[i], true, 0, res.Length, gCHandle.AddrOfPinnedObject(), null);
result.Add(new List <int>(res));
}
return(new Tuple <List <List <int> >, TimeSpan>(result, stopwatch.Elapsed));
}
private TFP[] RunKernalTest(float num, ComputeBuffer <TFP> result, ComputeKernel kernel)
{
kernel.SetMemoryArgument(0, result);
kernel.SetValueArgument(1, num);
// BUG: ATI Stream v2.2 crash if event list not null.
commands.Execute(kernel, null, new long[] { 1, 1 }, null, events);
//commands.Execute(kernel, null, new long[] { count }, null, null);
TFP[] myresult = new TFP[1];
GCHandle arrCHandle = GCHandle.Alloc(myresult, GCHandleType.Pinned);
commands.Read(result, true, 0, 1, arrCHandle.AddrOfPinnedObject(), events);
arrCHandle.Free();
return(myresult);
}
public float[] MultiplyMatrices(float[] matrix1, float[] matrix2,
int matrix1Height, int matrix1WidthMatrix2Height, int matrix2Width)
{
if (!_initialized)
{
Initialize();
_initialized = true;
}
ComputeBuffer <float> matrix1Buffer = new ComputeBuffer <float>(_context,
ComputeMemoryFlags.ReadOnly | ComputeMemoryFlags.CopyHostPointer,
matrix1);
_kernel.SetMemoryArgument(0, matrix1Buffer);
ComputeBuffer <float> matrix2Buffer = new ComputeBuffer <float>(_context,
ComputeMemoryFlags.ReadOnly | ComputeMemoryFlags.CopyHostPointer,
matrix2);
_kernel.SetMemoryArgument(1, matrix2Buffer);
float[] ret = new float[matrix1Height * matrix2Width];
ComputeBuffer <float> retBuffer = new ComputeBuffer <float>(_context,
ComputeMemoryFlags.ReadWrite | ComputeMemoryFlags.CopyHostPointer,
ret);
_kernel.SetMemoryArgument(2, retBuffer);
_kernel.SetValueArgument <int>(3, matrix1WidthMatrix2Height);
_kernel.SetValueArgument <int>(4, matrix2Width);
_commandQueue.Execute(_kernel,
new long[] { 0 },
new long[] { matrix2Width, matrix1Height },
null, null);
unsafe
{
fixed(float *retPtr = ret)
{
_commandQueue.Read(retBuffer,
false, 0,
ret.Length,
new IntPtr(retPtr),
null);
_commandQueue.Finish();
}
}
matrix1Buffer.Dispose();
matrix2Buffer.Dispose();
retBuffer.Dispose();
return(ret);
}
private BitmapSource ReadImageDataFromGPUMemory()
{
unsafe
{
fixed(float *imgPtr = NextImageVector)
{
CQ.Read(NextImage, true, new SysIntX3(0, 0, 0), new SysIntX3(Width, Height, 1), Width * 4 * sizeof(float), 0, (IntPtr)imgPtr, null);
}
}
return(BitmapSource.Create(Width, Height, 96, 96, PixelFormats.Rgba128Float, null, NextImageVector, (PixelFormats.Rgba128Float.BitsPerPixel / 8) * Width));
}
public void DoubleSumTest()
{
var builder = new OpenCL200Factory();
string text = File.ReadAllText("Examples/SumTest.cl");
int count = 2000;
var a = new double[count];
var b = new double[count];
var ab = new double[count];
for (int i = 0; i < count; i++)
{
a[i] = i / 10.0;
b[i] = -i / 9.0;
}
var Properties = new List <ComputeContextProperty>
{
new ComputeContextProperty(ComputeContextPropertyName.Platform, Device.Platform.Handle.Value)
};
using (var Context = builder.CreateContext(ComputeDeviceTypes.All, Properties, null, IntPtr.Zero))
{
using (var Program = builder.BuildComputeProgram(Context, text))
{
var Devs = new List <IComputeDevice>()
{
Device
};
Program.Build(Devs, "", null, IntPtr.Zero);
var kernel = builder.CreateKernel(Program, "doubleVectorSum");
using (ComputeBuffer <double>
varA = new ComputeBuffer <double>(Context, ComputeMemoryFlags.ReadWrite | ComputeMemoryFlags.UseHostPointer, a),
varB = new ComputeBuffer <double>(Context, ComputeMemoryFlags.ReadOnly | ComputeMemoryFlags.UseHostPointer, b))
{
kernel.SetMemoryArgument(0, varA);
kernel.SetMemoryArgument(1, varB);
using (var Queue = new ComputeCommandQueue(Context, Device, ComputeCommandQueueFlags.None))
{
Queue.Execute(kernel, null, new long[] { count }, null, null);
ab = Queue.Read(varA, true, 0, count, null);
}
}
}
}
for (int i = 0; i < count; i++)
{
Assert.AreEqual(-i / 90.0, ab[i], 1E-13);
}
}
public void OpenClMul()
{
//ѡȡ�豸
var platform = ComputePlatform.Platforms.FirstOrDefault();
var device = platform.Devices.FirstOrDefault();
var properties = new ComputeContextPropertyList(platform);
var context = new ComputeContext(new[] { device }, properties, null, IntPtr.Zero);
ComputeCommandQueue commands = new ComputeCommandQueue(context, context.Devices[0],
ComputeCommandQueueFlags.None);
var code = File.ReadAllText(@"demos\cls\matrix_mul.cl");
var program = new ComputeProgram(context, code);
try
{
program.Build(new [] { device }, null, null, IntPtr.Zero);
}
catch (Exception ex)
{
throw;
}
var kernel = program.CreateKernel("MatrixMul");
int rank = Rank;
var result = new ComputeBuffer <int>(context, ComputeMemoryFlags.WriteOnly, rank * rank);
var matrix = CreateMatrix(context, rank);
kernel.SetMemoryArgument(0, result);
kernel.SetMemoryArgument(1, matrix);
kernel.SetValueArgument(2, rank);
Console.WriteLine($"Platform: {platform.Name}\n Device: {device.Name}\n Size: {rank}x{rank}");
Stopwatch sw = Stopwatch.StartNew();
commands.Execute(kernel, null, new long[] { rank, rank }, null, null);
int[] resultArray = new int[rank * rank];
var arrHandle = GCHandle.Alloc(resultArray, GCHandleType.Pinned);
commands.Read(result, true, 0, rank * rank, arrHandle.AddrOfPinnedObject(), null);
var elapsed = sw.Elapsed;
Console.WriteLine($"using: {elapsed.TotalMilliseconds} ms\n");
arrHandle.Free();
kernel.Dispose();
}
private TFP[] RunKernal(int unit, int w, int h, int cx, int cy, float originx, float originy, int bufferSize, ComputeBuffer <TFP> points, ComputeKernel kernel)
{
kernel.SetMemoryArgument(0, points);
kernel.SetValueArgument(1, unit);
kernel.SetValueArgument(2, w);
kernel.SetValueArgument(3, cx);
kernel.SetValueArgument(4, cy);
kernel.SetValueArgument(5, originx);
kernel.SetValueArgument(6, originy);
// BUG: ATI Stream v2.2 crash if event list not null.
commands.Execute(kernel, null, new long[] { w, h }, null, events);
//commands.Execute(kernel, null, new long[] { count }, null, null);
TFP[] pointsArray = new TFP[bufferSize];
GCHandle arrCHandle = GCHandle.Alloc(pointsArray, GCHandleType.Pinned);
commands.Read(points, true, 0, bufferSize, arrCHandle.AddrOfPinnedObject(), events);
arrCHandle.Free();
return(pointsArray);
}
public static void Run(TextWriter log, ComputeContext context)
{
StartTest(log, "Vector addition test");
try
{
int count = 10;
float[] arrA = new float[count];
float[] arrB = new float[count];
float[] arrC = new float[count];
Random rand = new Random();
for (int i = 0; i < count; i++)
{
arrA[i] = (float)(rand.NextDouble() * 100);
arrB[i] = (float)(rand.NextDouble() * 100);
}
ComputeBuffer<float> a = new ComputeBuffer<float>(context, ComputeMemoryFlags.ReadOnly | ComputeMemoryFlags.CopyHostPointer, arrA);
ComputeBuffer<float> b = new ComputeBuffer<float>(context, ComputeMemoryFlags.ReadOnly | ComputeMemoryFlags.CopyHostPointer, arrB);
ComputeBuffer<float> c = new ComputeBuffer<float>(context, ComputeMemoryFlags.WriteOnly, arrC.Length);
ComputeProgram program = new ComputeProgram(context, kernelSource);
program.Build(null, null, null, IntPtr.Zero);
ComputeKernel kernel = program.CreateKernel("VectorAdd");
kernel.SetMemoryArgument(0, a);
kernel.SetMemoryArgument(1, b);
kernel.SetMemoryArgument(2, c);
ComputeCommandQueue commands = new ComputeCommandQueue(context, context.Devices[0], ComputeCommandQueueFlags.None);
ICollection<ComputeEventBase> events = new Collection<ComputeEventBase>();
// BUG: ATI Stream v2.2 crash if event list not null.
commands.Execute(kernel, null, new long[] { count }, null, events);
//commands.Execute(kernel, null, new long[] { count }, null, null);
arrC = new float[count];
GCHandle arrCHandle = GCHandle.Alloc(arrC, GCHandleType.Pinned);
commands.Read(c, true, 0, count, arrCHandle.AddrOfPinnedObject(), events);
arrCHandle.Free();
for (int i = 0; i < count; i++)
log.WriteLine("{0} + {1} = {2}", arrA[i], arrB[i], arrC[i]);
}
catch (Exception e)
{
log.WriteLine(e.ToString());
}
EndTest(log, "Vector addition test");
}
static float ComputeAverageGPUTime(
ushort[] depthPixels,
int width,
float inverseRotatedFx,
float rotatedCx,
float inverseRotatedFy,
float rotatedCy,
Matrix bedTransformationM,
Matrix bedTransformationb,
Matrix floorTransformationM,
Matrix floorTransformationb,
int numberOfIterations)
{
// pick the device platform
ComputePlatform intelGPU = ComputePlatform.Platforms.Where(n => n.Name.Contains("Intel")).First();
ComputeContext context = new ComputeContext(
ComputeDeviceTypes.Gpu, // use the gpu
new ComputeContextPropertyList(intelGPU), // use the intel openCL platform
null,
IntPtr.Zero);
// the command queue is the, well, queue of commands sent to the "device" (GPU)
ComputeCommandQueue commandQueue = new ComputeCommandQueue(
context, // the compute context
context.Devices[0], // first device matching the context specifications
ComputeCommandQueueFlags.None); // no special flags
string kernelSource = null;
using (StreamReader sr = new StreamReader("kernel.cl"))
{
kernelSource = sr.ReadToEnd();
}
// create the "program"
ComputeProgram program = new ComputeProgram(context, new string[] { kernelSource });
// compile.
program.Build(null, null, null, IntPtr.Zero);
ComputeKernel kernel = program.CreateKernel("ComputePoints");
Point3D[] outProjectivePoints = new Point3D[depthPixels.Length];
Point3D[] outRealPoints = new Point3D[depthPixels.Length];
Point3D[] outBedPoints = new Point3D[depthPixels.Length];
Point3D[] outFloorPoints = new Point3D[depthPixels.Length];
float[] affines = new float[24];
// do bed affines first because that's what assembly code expects
int z = 0;
for (int b = 0; b < 3; b++)
{
for (int c = 0; c < 3; c++)
{
affines[z++] = bedTransformationM[b, c];
}
affines[z++] = bedTransformationb[b, 0];
}
// do floor affines next because that's what assembly code expects
for (int b = 0; b < 3; b++)
{
for (int c = 0; c < 3; c++)
{
affines[z++] = floorTransformationM[b, c];
}
affines[z++] = floorTransformationb[b, 0];
}
ComputeBuffer <float> affinesBuffer = new ComputeBuffer <float>(context,
ComputeMemoryFlags.ReadOnly | ComputeMemoryFlags.UseHostPointer,
affines);
kernel.SetMemoryArgument(1, affinesBuffer);
ComputeBuffer <Point3D> projectivePointsBuffer = new ComputeBuffer <Point3D>(context,
ComputeMemoryFlags.WriteOnly | ComputeMemoryFlags.UseHostPointer,
outProjectivePoints);
kernel.SetMemoryArgument(2, projectivePointsBuffer);
ComputeBuffer <Point3D> realPointsBuffer = new ComputeBuffer <Point3D>(context,
ComputeMemoryFlags.WriteOnly | ComputeMemoryFlags.UseHostPointer,
outBedPoints);
kernel.SetMemoryArgument(3, realPointsBuffer);
ComputeBuffer <Point3D> bedPointsBuffer = new ComputeBuffer <Point3D>(context,
ComputeMemoryFlags.WriteOnly | ComputeMemoryFlags.UseHostPointer,
outFloorPoints);
kernel.SetMemoryArgument(4, projectivePointsBuffer);
ComputeBuffer <Point3D> floorPointsBuffer = new ComputeBuffer <Point3D>(context,
ComputeMemoryFlags.WriteOnly | ComputeMemoryFlags.UseHostPointer,
outRealPoints);
kernel.SetMemoryArgument(5, realPointsBuffer);
kernel.SetValueArgument <int>(6, width);
kernel.SetValueArgument <float>(7, inverseRotatedFx);
kernel.SetValueArgument <float>(8, rotatedCx);
kernel.SetValueArgument <float>(9, inverseRotatedFy);
kernel.SetValueArgument <float>(10, rotatedCy);
Stopwatch sw = new Stopwatch();
sw.Start();
for (int c = 0; c < numberOfIterations; c++)
{
ComputeBuffer <ushort> depthPointsBuffer = new ComputeBuffer <ushort>(context,
ComputeMemoryFlags.ReadOnly | ComputeMemoryFlags.UseHostPointer,
depthPixels);
kernel.SetMemoryArgument(0, depthPointsBuffer);
commandQueue.Execute(kernel, new long[] { 0 }, new long[] { depthPixels.Length }, null, null);
unsafe
{
fixed(Point3D *projectivePointsPtr = outProjectivePoints)
{
fixed(Point3D *realPointsPtr = outRealPoints)
{
fixed(Point3D *bedPointsPtr = outBedPoints)
{
fixed(Point3D *floorPointsPtr = outFloorPoints)
{
commandQueue.Read(projectivePointsBuffer, false, 0, outProjectivePoints.Length, new IntPtr(projectivePointsPtr), null);
commandQueue.Read(realPointsBuffer, false, 0, outProjectivePoints.Length, new IntPtr(realPointsPtr), null);
commandQueue.Read(bedPointsBuffer, false, 0, outProjectivePoints.Length, new IntPtr(bedPointsPtr), null);
commandQueue.Read(floorPointsBuffer, false, 0, outProjectivePoints.Length, new IntPtr(floorPointsPtr), null);
commandQueue.Finish();
}
}
}
}
}
}
sw.Stop();
return(sw.ElapsedMilliseconds / (numberOfIterations * 1.0f));
}
// 26 ms 4096x4096@512 iter with 1024 cores
static long Method05(float ymin, float xmin, float width, int[] message)
{
// pick first platform
ComputePlatform platform = ComputePlatform.Platforms[0];
// create context with all gpu devices
ComputeContext context = new ComputeContext(ComputeDeviceTypes.Gpu,
new ComputeContextPropertyList(platform), null, IntPtr.Zero);
// create a command queue with first gpu found
ComputeCommandQueue queue = new ComputeCommandQueue(context,
context.Devices[0], ComputeCommandQueueFlags.None);
// load opencl source
StreamReader streamReader = new StreamReader("Mandel3.cl");
string clSource = streamReader.ReadToEnd();
streamReader.Close();
// create program with opencl source
ComputeProgram program = new ComputeProgram(context, clSource);
// compile opencl source
program.Build(null, null, null, IntPtr.Zero);
// load chosen kernel from program
ComputeKernel kernel = program.CreateKernel("mandel");
int messageSize = message.Length;
// allocate a memory buffer with the message
ComputeBuffer <int> messageBuffer = new ComputeBuffer <int>(context,
ComputeMemoryFlags.WriteOnly | ComputeMemoryFlags.UseHostPointer, message);
kernel.SetMemoryArgument(0, messageBuffer);
kernel.SetValueArgument(1, N);
kernel.SetValueArgument(2, ymin);
kernel.SetValueArgument(3, xmin);
kernel.SetValueArgument(4, width);
kernel.SetValueArgument(5, MaxIter);
var watch = System.Diagnostics.Stopwatch.StartNew();
// Execute kernel
//queue.ExecuteTask(kernel, null);
//queue.Execute(kernel, new long[] { 0, 0, 0, 0 }, new long[] { 8, 8 }, new long[] { 8, 8 }, null);
for (var i = 0; i < N / 32; ++i)
{
for (var j = 0; j < N / 32; ++j)
{
queue.Execute(kernel, new long[] { i *32, j *32 }, new long[] { 32, 32 }, null, null);
}
}
// Read data back
unsafe
{
fixed(int *retPtr = message)
{
queue.Read(messageBuffer,
false, 0,
messageSize,
new IntPtr(retPtr),
null);
queue.Finish();
}
}
watch.Stop();
return(watch.ElapsedMilliseconds);
}
static void GenerateMandelBrot()
{
var nWidth = width / N;
if (useDoublePrecision)
{
kernel.SetValueArgument(4, ymin);
kernel.SetValueArgument(5, xmin);
kernel.SetValueArgument(6, nWidth);
}
else
{
kernel.SetValueArgument(4, (float)ymin);
kernel.SetValueArgument(5, (float)xmin);
kernel.SetValueArgument(6, (float)nWidth);
}
kernel.SetValueArgument(7, maxIter);
kernel.SetValueArgument(8, coclorCycle);
coclorCycle += colorCycleFrameIncrement;
Stopwatch watch = new Stopwatch();
watch.Start();
// Execute kernel
queue.Execute(kernel, new long[] { 0, 0 }, new long[] { N, N }, null, null);
// Read data back
unsafe
{
fixed(int *retPtr = message)
{
queue.Read(messageBuffer,
false, 0,
messageSize,
new IntPtr(retPtr),
null);
queue.Finish();
}
}
watch.Stop();
debugLabel.Content = $"{watch.ElapsedMilliseconds} ms";
// Write to bitmap
try
{
// Reserve the back buffer for updates.
writeableBitmap.Lock();
unsafe
{
IntPtr buffer = writeableBitmap.BackBuffer;
System.Runtime.InteropServices.Marshal.Copy(message, 0, buffer, (int)(writeableBitmap.Height * writeableBitmap.Width));
}
// Specify the area of the bitmap that changed.
writeableBitmap.AddDirtyRect(new Int32Rect(0, 0, (int)writeableBitmap.Width, (int)writeableBitmap.Height));
}
finally
{
// Release the back buffer and make it available for display.
writeableBitmap.Unlock();
}
}
public void ReadResult()
{
clCommands.Read(cbuf_Result, true, 0, width * height * 4, gc_resultBuffer.AddrOfPinnedObject(), null);
clCommands.Finish();
}
/// <summary>
/// Creates the Julia image using the GPU.
/// </summary>
/// <param name="width">The width.</param>
/// <param name="height">The height.</param>
/// <returns>An image containing the Julia set.</returns>
private Image CreateGPU(int width, int height)
{
Bitmap image;
// Initialize the position of the set.
float realLeft = -1.5f;
float realRight = 1.5f;
float imaginaryBottom = -1.2f;
float imaginaryTop = imaginaryBottom + (realRight - realLeft) * height / width;
/* Compute factors for translating from the imaginary plane to the
* Cartesian plane. */
float realFactor = (realRight - realLeft) / (width - 1);
float imaginaryFactor = (imaginaryTop - imaginaryBottom) / (height - 1);
// Set the number of iterations to check for values in the set.
uint maxIterations = MAX_ITERATIONS;
// Create a buffer to for kernel output.
ComputeBuffer <char> kernelOutput = new ComputeBuffer <char>(
context, ComputeMemoryFlags.WriteOnly, width * height * 4);
// Set arguments for the kernel.
kernel.SetValueArgument <float>(0, realFactor);
kernel.SetValueArgument <float>(1, imaginaryFactor);
kernel.SetValueArgument <float>(2, realLeft);
kernel.SetValueArgument <float>(3, imaginaryBottom);
kernel.SetValueArgument <float>(4, imaginaryTop);
kernel.SetValueArgument <uint>(5, maxIterations);
kernel.SetValueArgument <int>(6, width);
kernel.SetMemoryArgument(7, kernelOutput);
// TODO: Scale work group and work item sizes to fit the resolution.
commands.Execute(kernel, null, new long[] { width, height },
null, events);
// Create a pinned buffer for kernel output.
byte[] kernelResult = new byte[width * height * 4];
GCHandle kernelResultHandle = GCHandle.Alloc(kernelResult,
GCHandleType.Pinned);
// Copy the kernel result into the pinned buffer.
commands.Read(kernelOutput, false, 0, width * height * 4,
kernelResultHandle.AddrOfPinnedObject(), events);
commands.Finish();
// Free the pinned handle.
kernelResultHandle.Free();
unsafe
{
fixed(byte *pKernelResult = kernelResult)
{
IntPtr intPtr = new IntPtr((void *)pKernelResult);
image = new Bitmap(width, height, width * 4,
PixelFormat.Format32bppArgb, intPtr);
}
}
return(image);
}
private unsafe void notify(CLProgramHandle programHandle, IntPtr userDataPtr)
{
uint[] dst = new uint[16];
fixed (uint* dstPtr = dst)
{
using (var queue = new ComputeCommandQueue(ccontext, device, ComputeCommandQueueFlags.None))
{
var buf = new ComputeBuffer<uint>(ccontext, ComputeMemoryFlags.WriteOnly, 16);
var kernel = program.CreateKernel("test");
kernel.SetValueArgument(0, 1443351125U);
kernel.SetMemoryArgument(1, buf);
var eventList = new ComputeEventList();
queue.Execute(kernel, null, new long[] { 16L, 256L, 1048576L }, null, null);
queue.Finish();
queue.Read<uint>(buf, true, 0, 16, (IntPtr)dstPtr, null);
queue.Finish();
queue.Finish();
}
}
}
protected override void RunInternal()
{
int count = 10;
float[] arrA = new float[count];
float[] arrB = new float[count];
float[] arrC = new float[count];
Random rand = new Random();
for (int i = 0; i < count; i++)
{
arrA[i] = (float)(rand.NextDouble() * 100);
arrB[i] = (float)(rand.NextDouble() * 100);
}
ComputeBuffer<float> a = new ComputeBuffer<float>(context, ComputeMemoryFlags.ReadOnly | ComputeMemoryFlags.CopyHostPointer, arrA);
ComputeBuffer<float> b = new ComputeBuffer<float>(context, ComputeMemoryFlags.ReadOnly | ComputeMemoryFlags.CopyHostPointer, arrB);
ComputeBuffer<float> c = new ComputeBuffer<float>(context, ComputeMemoryFlags.WriteOnly, arrC.Length);
ComputeProgram program = new ComputeProgram(context, new string[] { kernelSource });
program.Build(null, null, null, IntPtr.Zero);
ComputeKernel kernel = program.CreateKernel("VectorAdd");
kernel.SetMemoryArgument(0, a);
kernel.SetMemoryArgument(1, b);
kernel.SetMemoryArgument(2, c);
ComputeCommandQueue commands = new ComputeCommandQueue(context, context.Devices[0], ComputeCommandQueueFlags.None);
ComputeEventList events = new ComputeEventList();
commands.Execute(kernel, null, new long[] { count }, null, events);
arrC = new float[count];
GCHandle arrCHandle = GCHandle.Alloc(arrC, GCHandleType.Pinned);
commands.Read(c, false, 0, count, arrCHandle.AddrOfPinnedObject(), events);
commands.Finish();
arrCHandle.Free();
for (int i = 0; i < count; i++)
Console.WriteLine("{0} + {1} = {2}", arrA[i], arrB[i], arrC[i]);
}
private unsafe void ReadFromDeviceTo(void* p, ComputeCommandQueue CQ, bool BlockingRead, ICollection<ComputeEventBase> events)
{
if (CreatedFromGLBuffer && (!AcquiredInOpenCL)) throw new Exception("Attempting to use a variable created from OpenGL buffer without acquiring. Should use CLGLInteropFunctions to properly acquire and release these variables");
CQ.Read((ComputeImage)VarPointer, BlockingRead, new SysIntX3(0, 0, 0), new SysIntX3(width, height, 1), 0, 0, new IntPtr(p), events);
}
private unsafe void ReadFromDeviceTo(void* p, ComputeCommandQueue CQ, bool BlockingRead, ICollection<ComputeEventBase> events)
{
CQ.Read((ComputeImage)VarPointer, BlockingRead, new SysIntX3(0, 0, 0), new SysIntX3(width, height, 1), 0, 0, new IntPtr(p), events);
}
public void Compute_cl(string imageFile, string dst)
{
//选取设备
var platform = ComputePlatform.Platforms.FirstOrDefault();
var device = platform.Devices.FirstOrDefault();
//设置相关上下文
var properties = new ComputeContextPropertyList(platform);
var context = new ComputeContext(new[] { device }, properties, null, IntPtr.Zero);
//命令队列，用于控制执行的代码
ComputeCommandQueue commands = new ComputeCommandQueue(context, context.Devices[0],
ComputeCommandQueueFlags.None);
//读取opencl代码
var code = File.ReadAllText(@"gaussianblur.cl");
//编译
var program = new ComputeProgram(context, code);
try
{
program.Build(new[] { device }, null, null, IntPtr.Zero);
}
catch (Exception ex)
{
throw;
}
var images = CreateImageFromBitmap(imageFile, context,
ComputeMemoryFlags.ReadWrite | ComputeMemoryFlags.CopyHostPointer);
//创建核心代码，就是cl代码中以kernel标识，函数签名为MatrixMul的函数
var kernel = program.CreateKernel("gaussian_blur");
//矩阵规模
//储存计算结果的数组
//创建的核心代码函数以这种方式来传参
var resultBuffer = new ComputeBuffer <char>(context, ComputeMemoryFlags.WriteOnly, dstBytes.Length);
kernel.SetMemoryArgument(0, images);
kernel.SetMemoryArgument(1, resultBuffer);
kernel.SetMemoryArgument(2, new ComputeBuffer <float>(context, ComputeMemoryFlags.ReadOnly | ComputeMemoryFlags.CopyHostPointer, _matrix));
kernel.SetValueArgument(3, Radius);
kernel.SetValueArgument(4, (int)images.Width);
Console.WriteLine($"\n运行平台: {platform.Name}\n运行设备： {device.Name}");
Stopwatch sw = Stopwatch.StartNew();
var climg = images;
Console.WriteLine($"处理图片尺寸：{climg.Width}*{climg.Height}");
//执行代码
commands.Execute(kernel, null, new long[] { climg.Width, climg.Height }, null, null);
//read data
char[] resultArray = new char[dstBytes.Length];
var arrHandle = GCHandle.Alloc(resultArray, GCHandleType.Pinned);
commands.Read(resultBuffer, true, 0, dstBytes.Length, arrHandle.AddrOfPinnedObject(), null);
//commands.ReadFromImage(images.Item2, processeddata.Scan0, true, null);
var resultHandle = GCHandle.Alloc(resultArray, GCHandleType.Pinned);
var bmp = new Bitmap(climg.Width, climg.Height, climg.Width * 4, PixelFormat.Format32bppArgb, resultHandle.AddrOfPinnedObject());
var elapsed = sw.Elapsed;
Console.WriteLine($"OpenCL处理耗时: {elapsed.TotalMilliseconds} ms\n");
kernel.Dispose();
bmp.Save(dst);
arrHandle.Free();
}
/// <summary>Reads variable from device.</summary>
/// <param name="Values">Values to store data coming from device</param>
/// <param name="CQ">Command queue to use</param>
/// <param name="BlockingRead">TRUE to return only after completed reading.</param>
/// <param name="events">OpenCL Event associated with this operation</param>
public void ReadFromDeviceTo(byte[] Values, ComputeCommandQueue CQ, bool BlockingRead, ICollection<ComputeEventBase> events)
{
if (Values.Length != OriginalVarLength) throw new Exception("Values length should be the same as allocated length");
if (CreatedFromGLBuffer && (!AcquiredInOpenCL)) throw new Exception("Attempting to use a variable created from OpenGL buffer without acquiring. Should use CLGLInteropFunctions to properly acquire and release these variables");
unsafe
{
fixed (void* ponteiro = Values)
{
CQ.Read<byte>((ComputeBuffer<byte>)VarPointer, BlockingRead, 0, Values.Length, (IntPtr)ponteiro, events);
}
}
}
