// 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);
}
}
public float[] MultiplyMatricesZeroCopy(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.WriteOnly | ComputeMemoryFlags.UseHostPointer,
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);
IntPtr retPtr = _commandQueue.Map(
retBuffer,
true,
ComputeMemoryMappingFlags.Read,
0,
ret.Length, null);
_commandQueue.Unmap(retBuffer, ref retPtr, null);
//_commandQueue.Finish();
matrix1Buffer.Dispose();
matrix2Buffer.Dispose();
retBuffer.Dispose();
return(ret);
}
public void RunKernel(ComputeKernel kernel, int count)
{
int argOffset = _intComputeBuffers.Count + _floatComputeBuffers.Count;
foreach (string key in _intArguments.Keys)
{
kernel.SetValueArgument(argOffset, _intArguments[key]);
argOffset++;
}
foreach (string key in _floatArguments.Keys)
{
kernel.SetValueArgument(argOffset, _floatArguments[key]);
argOffset++;
}
foreach (string key in _doubleArguments.Keys)
{
kernel.SetValueArgument(argOffset, _doubleArguments[key]);
argOffset++;
}
_commands.Execute(kernel, count);
_commands.Finish();
}
private double[] MatrixMultiply(Matrix <double> L, Matrix <double> R)
{
var L_array = L.To1D();
var R_array = R.To1D();
var O_array = new double[L.M * R.N];
ComputeBuffer <double> a = new ComputeBuffer <double>(context, ComputeMemoryFlags.ReadOnly | ComputeMemoryFlags.CopyHostPointer, L_array);
ComputeBuffer <double> b = new ComputeBuffer <double>(context, ComputeMemoryFlags.ReadOnly | ComputeMemoryFlags.CopyHostPointer, R_array);
ComputeBuffer <double> c = new ComputeBuffer <double>(context, ComputeMemoryFlags.WriteOnly, O_array.Length);
kernel.SetMemoryArgument(0, a);
kernel.SetMemoryArgument(1, b);
kernel.SetMemoryArgument(2, c);
kernel.SetValueArgument(3, L.N);
kernel.SetValueArgument(4, L.M);
kernel.SetValueArgument(5, R.N);
kernel.SetValueArgument(6, R.M);
commands.Execute(kernel, null, new long[] { R.N, L.M }, null, null);
commands.ReadFromBuffer(c, ref O_array, true, null);
commands.Finish();
// cleanup buffers
a.Dispose();
b.Dispose();
c.Dispose();
return(O_array);
}
public BitmapSource Diffuse()
{
CurrImage = NextImage;
SetMemoryArguments();
if (WithLocalMem)
{
CQ.Execute(DiffuseKernel, null, new long[] { Width, Height }, new long[] { 28, 8 }, null);
}
else
{
CQ.Execute(DiffuseKernel, null, new long[] { Width, Height }, null, null);
}
return(ReadImageDataFromGPUMemory());
}
public override void Proccess()
{
// execute kernel
queue.Execute(kernel, null, new long[] { DataGenerator.InputCount }, null, null);
queue.Finish();
/*
* short[] results2 = new short[this.results.Length];
* GCHandle arrCHandle = GCHandle.Alloc(results2, GCHandleType.Pinned);
* queue.Read(result_dev, true, 0, DataFeeder.GetInputCount(), arrCHandle.AddrOfPinnedObject(), events);
*/
//bool[] results2 = new bool[DataFeeder.GetInputCount()];
queue.ReadFromBuffer(result_dev, ref resultsBytes, true, null);
queue.ReadFromBuffer(resultCalc_dev, ref calculatables, true, null);
//queue.ReadFromBuffer()
/*
* bool[] arrC = new bool[5];
* GCHandle arrCHandle = GCHandle.Alloc(arrC, GCHandleType.Pinned);
* queue.Read<bool>(result_dev, true, 0, 5, arrCHandle.AddrOfPinnedObject(), null);
*/
// wait for completion
//queue.Finish();
//kernel.Dispose();
//queue.Dispose();
//context.Dispose();
}
public unsafe static void MatrixMulti_OpenCL(double[,] result, double[,] a, double[,] b)
{
InitCloo();
var ncols = result.GetUpperBound(0) + 1;
var nrows = result.GetUpperBound(1) + 1;
fixed(double *rp = result, ap = a, bp = b)
{
ComputeBuffer <double> aBuffer = new ComputeBuffer <double>(context, ComputeMemoryFlags.ReadOnly | ComputeMemoryFlags.CopyHostPointer, a.Length, (IntPtr)ap);
ComputeBuffer <double> bBuffer = new ComputeBuffer <double>(context, ComputeMemoryFlags.ReadOnly | ComputeMemoryFlags.CopyHostPointer, b.Length, (IntPtr)bp);
ComputeBuffer <double> rBuffer = new ComputeBuffer <double>(context, ComputeMemoryFlags.WriteOnly, result.Length);
kernel.SetMemoryArgument(0, aBuffer);
kernel.SetMemoryArgument(1, bBuffer);
kernel.SetValueArgument(2, ncols);
kernel.SetMemoryArgument(3, rBuffer);
ComputeEventList events = new ComputeEventList();
ComputeCommandQueue commands = new ComputeCommandQueue(context, context.Devices[0], ComputeCommandQueueFlags.None);
commands.Execute(kernel, null, new long[] { result.Length }, null, events);
commands.ReadFromBuffer(rBuffer, ref result, false, new SysIntX2(), new SysIntX2(), new SysIntX2(ncols, nrows), events);
commands.Finish();
}
}
public uint FindProofOfWork(byte[] header, byte[] bits, uint nonceStart, uint iterations, out long elapsedMilliseconds)
{
this.stopwatch.Restart();
using var headerBuffer = new ComputeBuffer <byte>(this.computeContext, ComputeMemoryFlags.ReadOnly | ComputeMemoryFlags.CopyHostPointer, header);
using var bitsBuffer = new ComputeBuffer <byte>(this.computeContext, ComputeMemoryFlags.ReadOnly | ComputeMemoryFlags.CopyHostPointer, bits);
using var powBuffer = new ComputeBuffer <uint>(this.computeContext, ComputeMemoryFlags.WriteOnly, 1);
this.computeKernel.SetMemoryArgument(0, headerBuffer);
this.computeKernel.SetMemoryArgument(1, bitsBuffer);
this.computeKernel.SetValueArgument(2, nonceStart);
this.computeKernel.SetMemoryArgument(3, powBuffer);
using var commands = new ComputeCommandQueue(this.computeContext, this.computeDevice, ComputeCommandQueueFlags.None);
commands.Execute(this.computeKernel, null, new long[] { iterations }, null, null);
var nonceOut = new uint[1];
commands.ReadFromBuffer(powBuffer, ref nonceOut, true, null);
commands.Finish();
elapsedMilliseconds = this.stopwatch.ElapsedMilliseconds;
return(nonceOut[0]);
}
public string vectorSum()
{
string vecSum = @"
__kernel void vectorSum(__global float *v1, __global float *v2, __global float *v3) {
int i = get_global_id(0);
v3[i] = v1[i] + v2[i];
}
";
int size = 100000;
float[] v1_ = new float[size];
float[] v2_ = new float[size];
float[] v3_ = new float[size];
for (var i = 0; i < size; i++)
{
v1_[i] = (float)i;
v2_[i] = (float).5f;
}
var platform_ = ComputePlatform.Platforms[0];
ComputeContextPropertyList properties = new ComputeContextPropertyList(platform_);
ComputeContext ctx = new ComputeContext(ComputeDeviceTypes.Gpu, properties, null, IntPtr.Zero);
ComputeCommandQueue commands = new ComputeCommandQueue(ctx, ctx.Devices[0], ComputeCommandQueueFlags.None);
ComputeProgram program = new ComputeProgram(ctx, vecSum);
try
{
program.Build(null, null, null, IntPtr.Zero);
Console.WriteLine("program build completed");
}
catch
{
string log = program.GetBuildLog(ctx.Devices[0]);
}
ComputeBuffer <float> v1, v2, v3;
v1 = new ComputeBuffer <float>(ctx, ComputeMemoryFlags.ReadOnly | ComputeMemoryFlags.CopyHostPointer, v1_);
v2 = new ComputeBuffer <float>(ctx, ComputeMemoryFlags.ReadOnly | ComputeMemoryFlags.CopyHostPointer, v2_);
v3 = new ComputeBuffer <float>(ctx, ComputeMemoryFlags.WriteOnly | ComputeMemoryFlags.CopyHostPointer, v3_);
long[] worker = { size };
commands.WriteToBuffer(v1_, v1, false, null);
commands.WriteToBuffer(v2_, v2, false, null);
ComputeKernel sumKernal = program.CreateKernel("vectorSum");
Console.WriteLine("kernal created");
sumKernal.SetMemoryArgument(0, v1);
sumKernal.SetMemoryArgument(1, v2);
sumKernal.SetMemoryArgument(2, v3);
commands.Execute(sumKernal, null, worker, null, null);
Console.WriteLine("Executed");
commands.ReadFromBuffer <float>(v3, ref v3_, false, null);
StringBuilder sb = new StringBuilder();
for (int i = 0; i < size; i++)
{
sb.AppendFormat("{0} + {1} = {2}<br>", v1_[i].ToString(), v2_[i].ToString(), v3_[i].ToString());
}
var sum_expression_result = sb.ToString();
return(sum_expression_result);
}
public Bitmap ProcessImage(Bitmap inImage)
{
ComputeImage2D oclInImage = null;
ComputeImage2D oclOutImage = null;
BitmapData inImageData = inImage.LockBits(new Rectangle(0, 0, inImage.Width, inImage.Height),
ImageLockMode.ReadOnly, PixelFormat.Format32bppArgb);
Bitmap outImage = new Bitmap(inImage.Width, inImage.Height, PixelFormat.Format32bppArgb);
BitmapData outImageData = outImage.LockBits(new Rectangle(0, 0, outImage.Width, outImage.Height),
ImageLockMode.WriteOnly, PixelFormat.Format32bppArgb);
try
{
oclInImage = new ComputeImage2D(oclContext, ComputeMemoryFlags.ReadOnly |
ComputeMemoryFlags.CopyHostPointer, new ComputeImageFormat(ComputeImageChannelOrder.Bgra,
ComputeImageChannelType.UNormInt8), inImage.Width, inImage.Height, 0, inImageData.Scan0);
oclOutImage = new ComputeImage2D(oclContext, ComputeMemoryFlags.WriteOnly |
ComputeMemoryFlags.CopyHostPointer, new ComputeImageFormat(ComputeImageChannelOrder.Bgra,
ComputeImageChannelType.UNormInt8), outImage.Width, outImage.Height, 0, outImageData.Scan0);
oclKernel.SetMemoryArgument(0, oclInImage);
oclKernel.SetMemoryArgument(1, oclOutImage);
oclCommandQueue.Execute(oclKernel, new long[] { 0, 0 }, new long[] { oclInImage.Width,
oclInImage.Height }, null, null);
oclCommandQueue.Finish();
oclCommandQueue.ReadFromImage(oclOutImage, outImageData.Scan0, true, null);
}
catch (Exception)
{
throw;
}
finally
{
inImage.UnlockBits(inImageData);
outImage.UnlockBits(outImageData);
if (oclInImage != null)
{
oclInImage.Dispose();
oclInImage = null;
}
if (oclOutImage != null)
{
oclOutImage.Dispose();
oclOutImage = null;
}
}
return(outImage);
}
public async Task Can_use_struct()
{
var platform = ComputePlatform.Platforms.First();
var device = platform.Devices.First();
var context = new ComputeContext(new[] { device }, new ComputeContextPropertyList(platform), null, IntPtr.Zero);
using var program = new ComputeProgram(context, Struct_kernel);
try
{
program.Build(new[] { device }, "-cl-std=CL1.2", null, IntPtr.Zero);
}
catch (Exception ex)
{
OnProgramBuilt(program, device);
return;
}
using var queue = new ComputeCommandQueue(context, device, ComputeCommandQueueFlags.None);
using var kernel = program.CreateKernel("fill");
var target = new Target[10];
var gcHandle = GCHandle.Alloc(target, GCHandleType.Pinned);
var ptr = gcHandle.AddrOfPinnedObject();
var buffer = new ComputeBuffer <Target>(
context,
ComputeMemoryFlags.ReadWrite | ComputeMemoryFlags.UseHostPointer,
10,
ptr);
kernel.SetMemoryArgument(0, buffer);
var events = new List <ComputeEventBase>();
queue.Execute(kernel, null, new long[] { 10 }, null, events);
//await events.WaitForEvents();
unsafe
{
target[0].a.Should().Be(0);
target[0].b.Should().BeApproximately(0.5f, 0.01f);
target[0].c.Should().Be(1);
target[0].d[0].Should().Be(1);
target[0].d[1].Should().Be(2);
target[1].a.Should().Be(2);
target[1].b.Should().BeApproximately(1.5f, 0.01f);
target[1].c.Should().Be(2);
target[1].d[0].Should().Be(1);
target[1].d[1].Should().Be(2);
target[9].a.Should().Be(18);
target[9].b.Should().BeApproximately(9.5f, 0.01f);
target[9].c.Should().Be(10);
target[9].d[0].Should().Be(1);
target[9].d[1].Should().Be(2);
}
}
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 async Task Can_multiply_using_pinned_host_pointer()
{
// This doesn't seem to work on NVidia platforms
var platform = ComputePlatform.Platforms.First();
var device = platform.Devices.First();
var context = new ComputeContext(new[] { device }, new ComputeContextPropertyList(platform), null,
IntPtr.Zero);
using var program = new ComputeProgram(context, Sum_kernel);
program.Build(new[] { device }, "-cl-std=CL1.2", (handle, ptr) => OnProgramBuilt(program, device),
IntPtr.Zero);
using var queue = new ComputeCommandQueue(context, device, ComputeCommandQueueFlags.None);
using var kernel = program.CreateKernel("sum");
var source = new byte[] { 1, 2, 3, 4, 5 };
var sourceHandle = GCHandle.Alloc(source, GCHandleType.Pinned);
var sourcePtr = sourceHandle.AddrOfPinnedObject();
using var sourceBuffer = new ComputeBuffer <byte>(
context,
ComputeMemoryFlags.ReadWrite | ComputeMemoryFlags.UseHostPointer,
source.LongLength,
sourcePtr);
var target = new byte[5];
var targetHandle = GCHandle.Alloc(target, GCHandleType.Pinned);
var targetPtr = targetHandle.AddrOfPinnedObject();
using var targetBuffer = new ComputeBuffer <byte>(
context,
ComputeMemoryFlags.ReadWrite | ComputeMemoryFlags.UseHostPointer,
target.LongLength,
targetPtr);
try
{
kernel.SetMemoryArgument(0, sourceBuffer);
kernel.SetMemoryArgument(1, targetBuffer);
var events = new List <ComputeEventBase>();
queue.Execute(kernel, null, new long[] { source.Length }, null, events);
//await events.WaitForEvents();
for (var i = 0; i < target.Length; i++)
{
Console.WriteLine($"{source[i]} * 2 = {target[i]}");
}
}
finally
{
sourceHandle.Free();
targetHandle.Free();
}
}
/// <summary>
/// Subsequent calls to Invoke work faster without arguments
/// </summary>
public void Invoke(string Method, long Offset, long Worksize)
{
if (LastKernel == null)
{
throw new InvalidOperationException("You need to call Invoke with arguments before. All Arguments are saved");
}
ComputeEventList eventList = new ComputeEventList();
InvokeStarted?.Invoke(this, EventArgs.Empty);
queue.Execute(LastKernel, new long[] { Offset }, new long[] { Worksize }, null, eventList);
eventList[0].Completed += (sender, e) => EasyCL_Completed(sender, null);
eventList[0].Aborted += (sender, e) => EasyCL_Aborted(sender, Method);
queue.Finish();
}
public void Can_copy()
{
var platform = ComputePlatform.Platforms.First();
var device = platform.Devices.First();
var context = new ComputeContext(new[] { device }, new ComputeContextPropertyList(platform), null, IntPtr.Zero);
using var program = new ComputeProgram(context, Copy_kernel);
try
{
program.Build(new[] { device }, "-cl-std=CL1.2", null, IntPtr.Zero);
}
catch (Exception ex)
{
OnProgramBuilt(program, device);
return;
}
using var queue = new ComputeCommandQueue(context, device, ComputeCommandQueueFlags.None);
using var kernel = program.CreateKernel("copy");
var sourcePath = Path.GetFullPath(Path.Combine(Environment.CurrentDirectory, "sample00.png"));
using var sourceImage = (Bitmap)Image.FromFile(sourcePath);
var w = sourceImage.Width;
var h = sourceImage.Height;
var source = sourceImage.ToBytes();
source.SaveFormatted("source.txt", w, h, channels: 4);
using var sourceBuffer = context.CreateImage2D(source, w, h);
var target = new byte[h * w * 4];
using var targetBuffer = context.CreateBuffer(target);
kernel.SetMemoryArgument(0, sourceBuffer);
kernel.SetMemoryArgument(1, targetBuffer);
queue.Execute(kernel, null, new long[] { w, h }, null, null);
queue.Finish();
target.SaveFormatted("target.txt", w, h, channels: 4);
var result = target.ToBitmap(w, h, 4);
var resultPath = Path.GetFullPath(Path.Combine(Environment.CurrentDirectory, "copy.png"));
result.Save(resultPath);
Run("source.txt");
Run("target.txt");
Run(resultPath);
}
static void Main(string[] args)
{
int w = 11, h = 11, sx = 5, sy = 5, iters = 2;
var properties = new ComputeContextPropertyList(ComputePlatform.Platforms[0]);
var context = new ComputeContext(ComputeDeviceTypes.All, properties, null, IntPtr.Zero);
var quene = new ComputeCommandQueue(context, ComputePlatform.Platforms[0].Devices[0], ComputeCommandQueueFlags.None);
//Компиляция программы
var prog = new ComputeProgram(context, Source);
try
{
prog.Build(context.Devices, "", null, IntPtr.Zero);
}
catch
{
Console.WriteLine(prog.GetBuildLog(context.Devices[0]));
}
//Создание ядра
var kernel = prog.CreateKernel("Test");
var mat = new float[w * h];
for (int i = 0; i < w * h; i++)
{
mat[i] = (i == w * sy + sx) ? 1f : 0f;
}
var mat1 = new ComputeBuffer <float>(context, ComputeMemoryFlags.ReadWrite | ComputeMemoryFlags.UseHostPointer, mat);
var mat2 = new ComputeBuffer <float>(context, ComputeMemoryFlags.ReadWrite, w * h);
kernel.SetMemoryArgument(0, mat1);
kernel.SetMemoryArgument(1, mat2);
kernel.SetValueArgument(2, iters);
kernel.SetValueArgument(3, w);
kernel.SetValueArgument(4, h);
quene.Execute(kernel, null, new long[] { (long)h, (long)w }, null, null);
quene.ReadFromBuffer(mat1, ref mat, true, null);
for (int i = 0; i < h; i++)
{
for (int j = 0; j < w; j++)
{
Console.Write($"{mat[i*w+j]:.00} ");
}
Console.WriteLine();
}
Console.ReadKey();
}
private void InitializeCellGrid()
{
ComputeProgram prog = new ComputeProgram(Ctx, InitilizeGridKernelString);
prog.Build(Ctx.Devices, "", null, IntPtr.Zero);
InitilizeGridKernel = prog.CreateKernel("InitializeGrid");
InitilizeGridKernel.SetMemoryArgument(0, CurrImage);
InitilizeGridKernel.SetMemoryArgument(1, NextImage);
CQ = new ComputeCommandQueue(Ctx, Ctx.Devices[0], ComputeCommandQueueFlags.None);
CQ.Execute(InitilizeGridKernel, null, new long[] { Width, Height }, null, null);
}
public static void Enqueue(
this ComputeCommandQueue queue,
ComputeKernel kernel,
long[] globalWorkOffset = null,
long[] globalWorkSize = null,
long[] localWorkSize = null,
ICollection <ComputeEventBase> events = null)
{
events ??= new List <ComputeEventBase>();
queue.Execute(kernel, globalWorkOffset, globalWorkSize, localWorkSize, events);
}
protected T[] InternalExecuteOpencl <T>(
String source,
String function,
int bufferSize,
ParallelTaskParams loaderParams,
params Object[] kernelParams)
where T : struct
{
TriggerCheckpoint(ParallelExecutionCheckpointType.CheckpointStart);
ComputeCommandQueue queue = QueueWithDevice(loaderParams.OpenCLDevice);
TriggerCheckpoint(ParallelExecutionCheckpointType.CheckpointPlatformInit);
String updatedSource = "#define OpenCL\r\n" + source;
ComputeProgram program = new ComputeProgram(queue.Context, updatedSource);
program.Build(new ComputeDevice[] { queue.Device }, null, null, IntPtr.Zero);
TriggerCheckpoint(ParallelExecutionCheckpointType.CheckpointKernelBuild);
T[] resultBuffer = new T[bufferSize];
ComputeBuffer <T> resultBufferVar = new ComputeBuffer <T>(queue.Context, ComputeMemoryFlags.WriteOnly, bufferSize);
List <ComputeMemory> vars = new List <ComputeMemory>();
vars.Add(resultBufferVar);
vars.AddRange(WrapDeviceVariables(kernelParams, queue.Context));
ComputeKernel kernel = program.CreateKernel(function);
for (int i = 0; i < vars.Count; i++)
{
kernel.SetMemoryArgument(i, vars[i]);
}
TriggerCheckpoint(ParallelExecutionCheckpointType.CheckpointDeviceWrite);
long[] workersGlobal = new long[2] {
loaderParams.GlobalWorkers.Width, loaderParams.GlobalWorkers.Height
};
queue.Execute(kernel, null, workersGlobal, null, null);
TriggerCheckpoint(ParallelExecutionCheckpointType.CheckpointKernelExecute);
queue.ReadFromBuffer <T>(resultBufferVar, ref resultBuffer, false, null);
TriggerCheckpoint(ParallelExecutionCheckpointType.CheckpointDeviceRead);
queue.Finish();
TriggerCheckpoint(ParallelExecutionCheckpointType.CheckpointPlatformDeinit);
return(resultBuffer);
}
public PrOpenClCalculation()
{
m_Platform = ComputePlatform.Platforms.First();
m_Device = m_Platform.Devices.First();
m_ComputeContext = new ComputeContext(new [] { m_Device }, new ComputeContextPropertyList(m_Platform), null, IntPtr.Zero);
m_CommandQueue = new ComputeCommandQueue(m_ComputeContext, m_Device, ComputeCommandQueueFlags.None);
m_Program = new ComputeProgram(m_ComputeContext, ProgramSource);
m_Program.Build(new [] { m_Device }, "", null, IntPtr.Zero);
m_Kernel = m_Program.CreateKernel("Test");
long count = 100;
var result = new int[count];
var a = new int[count];
for (int i = 0; i < count; i++)
{
a[i] = i;
}
var resultDev = new ComputeBuffer <int>(m_ComputeContext,
ComputeMemoryFlags.ReadWrite | ComputeMemoryFlags.UseHostPointer,
result);
var aDev = new ComputeBuffer <int>(m_ComputeContext,
ComputeMemoryFlags.ReadWrite | ComputeMemoryFlags.UseHostPointer,
a);
var bDev = new ComputeBuffer <int>(m_ComputeContext,
ComputeMemoryFlags.ReadWrite | ComputeMemoryFlags.UseHostPointer,
a);
//Задаем их для нашего ядра
m_Kernel.SetMemoryArgument(0, resultDev);
m_Kernel.SetMemoryArgument(1, aDev);
m_Kernel.SetMemoryArgument(2, bDev);
//Вызываем ядро количество потоков равно count
m_CommandQueue.Execute(m_Kernel, null, new[] { count }, null, null);
//Читаем результат из переменной
m_CommandQueue.ReadFromBuffer(resultDev, ref result, true, null);
//Выводим результат
foreach (var i in result)
{
Console.WriteLine(i);
}
}
public static async Task ExecuteAsync(
this ComputeCommandQueue queue,
ComputeKernel kernel,
long[] globalWorkOffset = null,
long[] globalWorkSize = null,
long[] localWorkSize = null,
ICollection <ComputeEventBase> events = null)
{
events ??= new List <ComputeEventBase>();
queue.Execute(kernel, globalWorkOffset, globalWorkSize, localWorkSize, events);
await events.WaitForEvents();
}
public async Task Can_multiply_with_device_allocated_memory()
{
var platform = ComputePlatform.Platforms.First();
var device = platform.Devices.First();
var context = new ComputeContext(new[] { device }, new ComputeContextPropertyList(platform), null, IntPtr.Zero);
using var program = new ComputeProgram(context, Sum_kernel);
program.Build(new[] { device }, "-cl-std=CL1.2", (handle, ptr) => OnProgramBuilt(program, device), IntPtr.Zero);
using var queue = new ComputeCommandQueue(context, device, ComputeCommandQueueFlags.None);
using var kernel = program.CreateKernel("sum");
var source = new byte[] { 1, 2, 3, 4, 5 };
using var sourceBuffer = new ComputeBuffer <byte>(
context,
ComputeMemoryFlags.ReadWrite | ComputeMemoryFlags.CopyHostPointer,
source);
using var targetBuffer = new ComputeBuffer <byte>(
context,
ComputeMemoryFlags.ReadWrite | ComputeMemoryFlags.AllocateHostPointer,
5);
kernel.SetMemoryArgument(0, sourceBuffer);
kernel.SetMemoryArgument(1, targetBuffer);
var events = new List <ComputeEventBase>();
queue.Execute(kernel, null, new long[] { source.Length }, null, events);
var targetPtr = queue.Map(targetBuffer, true, ComputeMemoryMappingFlags.Read, 0, source.Length, events);
//await events.WaitForEvents();
unsafe
{
var result = (byte *)targetPtr.ToPointer();
for (var i = 0; i < source.Length; i++)
{
Console.WriteLine($"{source[i]} * 2 = {result[i]}");
}
}
queue.Unmap(targetBuffer, ref targetPtr, events);
//await events.WaitForEvents();
}
/// <summary>
/// Executes the specified kernel function name.
/// </summary>
/// <typeparam name="TSource">The type of the source.</typeparam>
/// <param name="functionName">Name of the function.</param>
/// <param name="args"></param>
/// <exception cref="ExecutionException">
/// </exception>
public override void Execute(string functionName, params object[] args)
{
ValidateArgs(functionName, args);
ComputeKernel kernel = _compiledKernels.FirstOrDefault(x => (x.FunctionName == functionName));
ComputeCommandQueue commands = new ComputeCommandQueue(_context, _defaultDevice, ComputeCommandQueueFlags.None);
if (kernel == null)
{
throw new ExecutionException(string.Format("Kernal function {0} not found", functionName));
}
try
{
var ndobject = (Array)args.FirstOrDefault(x => (x.GetType().IsArray));
long length = ndobject != null ? ndobject.Length : 1;
var method = KernelFunctions.FirstOrDefault(x => (x.Name == functionName));
var buffers = BuildKernelArguments(method, args, kernel, length);
commands.Execute(kernel, null, new long[] { length }, null, null);
for (int i = 0; i < args.Length; i++)
{
if (!args[i].GetType().IsArray)
{
continue;
}
var ioMode = method.Parameters.ElementAt(i).Value.IOMode;
if (ioMode == IOMode.InOut || ioMode == IOMode.Out)
{
Array r = (Array)args[i];
commands.ReadFromMemory(buffers[i], ref r, true, 0, null);
}
buffers[i].Dispose();
}
}
catch (Exception ex)
{
throw new ExecutionException(ex.Message);
}
finally
{
commands.Finish();
commands.Dispose();
}
}
private static void ConductSearch(ComputeContext context, ComputeKernel kernel)
{
var todos = GetQueenTaskPartition(NumQueens, 4);
var done = new List<QueenTask>();
ComputeEventList eventList = new ComputeEventList();
var commands = new ComputeCommandQueue(context, context.Devices[1], ComputeCommandQueueFlags.None);
Console.WriteLine("Starting {0} tasks, and working {1} at a time.", todos.Count, Spread);
QueenTask[] inProgress = GetNextAssignment(new QueenTask[] {}, todos, done);
var sw = new Stopwatch();
sw.Start();
while (inProgress.Any())
{
var taskBuffer =
new ComputeBuffer<QueenTask>(context,
ComputeMemoryFlags.ReadWrite | ComputeMemoryFlags.CopyHostPointer,
inProgress);
kernel.SetMemoryArgument(0, taskBuffer);
commands.WriteToBuffer(inProgress, taskBuffer, false, null);
for (int i = 0; i < 12; i++)
commands.Execute(kernel, null, new long[] { inProgress.Length }, null, eventList);
commands.ReadFromBuffer(taskBuffer, ref inProgress, false, eventList);
commands.Finish();
inProgress = GetNextAssignment(inProgress, todos, done);
}
sw.Stop();
Console.WriteLine(sw.ElapsedMilliseconds / 1000.0);
ulong sum = done.Select(state => state.solutions)
.Aggregate((total, next) => total + next);
Console.WriteLine("Q({0})={1}", NumQueens, sum);
}
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 void CalculateConvolution(ComputeContext computeContext)
{
Stopwatch stopwatch = new Stopwatch();
stopwatch.Start();
float dx;
bool shiftXParse = float.TryParse(textBoxShiftX.Text, NumberStyles.Float, CultureInfo.InvariantCulture.NumberFormat, out dx);
if (!shiftXParse)
throw new SyntaxErrorException(", needs to be .");
float dy;
bool shiftYParse = float.TryParse(textBoxShiftX.Text, NumberStyles.Float, CultureInfo.InvariantCulture.NumberFormat, out dy);
if (!shiftYParse)
throw new SyntaxErrorException(", needs to be .");
float dz;
bool shiftZParse = float.TryParse(textBoxShiftX.Text, NumberStyles.Float, CultureInfo.InvariantCulture.NumberFormat, out dz);
if (!shiftZParse)
throw new SyntaxErrorException(", needs to be .");
int pixelCount = _imageDimensionX*_imageDimensionY*_imageDimensionZ;
Console.WriteLine("Computing...");
Console.WriteLine("Reading kernel...");
String kernelPath = Directory.GetParent(Directory.GetCurrentDirectory()).Parent.Parent.FullName;
String kernelString;
using (var sr = new StreamReader(kernelPath + "\\convolution.cl"))
kernelString = sr.ReadToEnd();
Console.WriteLine("Reading kernel... done");
float[] selectedTransformation = Transformations.GetTransformation((TransformationType)comboBoxTransform.SelectedItem, 1.0f / float.Parse(textBoxPixelSize.Text), 1.0f / float.Parse(textBoxPixelSize.Text), 1.0f / float.Parse(textBoxPixelSize.Text), dx, dy, dz);
//create openCL program
ComputeProgram computeProgram = new ComputeProgram(computeContext, kernelString);
computeProgram.Build(computeContext.Devices, null, null, IntPtr.Zero);
ComputeProgramBuildStatus computeProgramBuildStatus = computeProgram.GetBuildStatus(_selectedComputeDevice);
Console.WriteLine("computeProgramBuildStatus\n\t"+computeProgramBuildStatus);
String buildLog = computeProgram.GetBuildLog(_selectedComputeDevice);
Console.WriteLine("buildLog");
if (buildLog.Equals("\n"))
Console.WriteLine("\tbuildLog is empty...");
else
Console.WriteLine("\t" + buildLog);
float[] fluorophores = CsvData.ReadFluorophores(_sourceFilename);
/////////////////////////////////////////////
// Create a Command Queue & Event List
/////////////////////////////////////////////
ComputeCommandQueue computeCommandQueue = new ComputeCommandQueue(computeContext, _selectedComputeDevice, ComputeCommandQueueFlags.None);
////////////////////////////////////////////////////////////////
// Create Buffers Transform
////////////////////////////////////////////////////////////////
ComputeBuffer<float> fluorophoresCoords = new ComputeBuffer<float>(computeContext, ComputeMemoryFlags.ReadWrite, fluorophores.LongLength);
ComputeBuffer<float> transformationMatrix = new ComputeBuffer<float>(computeContext, ComputeMemoryFlags.ReadOnly, selectedTransformation.LongLength);
/////////////////////////////////////////////
// Create the transformFluorophoresKernel
///////////////////////////////////////////////////////////
ComputeKernel transformFluorophoresKernel = computeProgram.CreateKernel("transform_fluorophores");
/////////////////////////////////////////////
// Set the transformFluorophoresKernel arguments
/////////////////////////////////////////////
transformFluorophoresKernel.SetMemoryArgument(0, fluorophoresCoords);
transformFluorophoresKernel.SetMemoryArgument(1, transformationMatrix);
/////////////////////////////////////////////
// Configure the work-item structure
/////////////////////////////////////////////
long[] globalWorkOffsetTransformFluorophoresKernel = null;
long[] globalWorkSizeTransformFluorophoresKernel = new long[] { fluorophores.Length / 4 };
long[] localWorkSizeTransformFluorophoresKernel = null;
////////////////////////////////////////////////////////
// Enqueue the transformFluorophoresKernel for execution
////////////////////////////////////////////////////////
computeCommandQueue.WriteToBuffer(fluorophores, fluorophoresCoords, true, null);
computeCommandQueue.WriteToBuffer(selectedTransformation, transformationMatrix, true, null);
computeCommandQueue.Execute(transformFluorophoresKernel, globalWorkOffsetTransformFluorophoresKernel, globalWorkSizeTransformFluorophoresKernel, localWorkSizeTransformFluorophoresKernel, null);
// computeCommandQueue.ExecuteTask(transformFluorophoresKernel, transformFluorophoresEvents);
float[] transformedFluorophores = new float[fluorophores.Length];
computeCommandQueue.ReadFromBuffer(fluorophoresCoords, ref transformedFluorophores, true, null);
computeCommandQueue.Finish();
//TODO remove, only for testing
// for (int i = 0; i < transformedFluorophores.Length; i++)
// {
// Console.WriteLine(transformedFluorophores[i]);
// }
// /TODO remove, only for testing
stopwatch.Stop();
Console.WriteLine("Transform fluophores duration:\n\t" + stopwatch.Elapsed);
stopwatch.Reset();
stopwatch.Start();
// fluorophoresCoords are now transformed (done in place)
////////////////////////////////////////////////////////////////
// Create Buffers Convolve Fluorophores
////////////////////////////////////////////////////////////////
const int convolve_kernel_lwgs = 16;
int totalBuffer = (int) Math.Ceiling(pixelCount / (float)convolve_kernel_lwgs) * convolve_kernel_lwgs;
ComputeBuffer<float> resultImage = new ComputeBuffer<float>(computeContext, ComputeMemoryFlags.WriteOnly, totalBuffer);
/////////////////////////////////////////////
// Create the transformFluorophoresKernel
/////////////////////////////////////////////
ComputeKernel convolveFluorophoresKernel = computeProgram.CreateKernel("convolve_fluorophores");
/////////////////////////////////////////////
// Set the convolveFluorophoresKernel arguments
/////////////////////////////////////////////
convolveFluorophoresKernel.SetMemoryArgument(0, resultImage);
convolveFluorophoresKernel.SetValueArgument(1, _imageDimensionX);
convolveFluorophoresKernel.SetValueArgument(2, _imageDimensionY);
convolveFluorophoresKernel.SetMemoryArgument(3, fluorophoresCoords);
convolveFluorophoresKernel.SetLocalArgument(4, convolve_kernel_lwgs);
convolveFluorophoresKernel.SetValueArgument(5, fluorophores.Length / 4);
/////////////////////////////////////////////
// Configure the work-item structure
/////////////////////////////////////////////
long[] globalWorkOffsetTransformConvolveFluorophoresKernel = null;
long[] globalWorkSizeTransformConvolveFluorophoresKernel = new long[] { pixelCount };
long[] localWorkSizeTransformConvolveFluorophoresKernel = new long[] {convolve_kernel_lwgs};
////////////////////////////////////////////////////////
// Enqueue the convolveFluorophoresKernel for execution
////////////////////////////////////////////////////////
computeCommandQueue.Execute(convolveFluorophoresKernel, globalWorkOffsetTransformConvolveFluorophoresKernel, globalWorkSizeTransformConvolveFluorophoresKernel, localWorkSizeTransformConvolveFluorophoresKernel, null);
float[] resultImageData = new float[totalBuffer];
computeCommandQueue.ReadFromBuffer(resultImage, ref resultImageData, true, null);
computeCommandQueue.Finish();
for (int i = 0; i < pixelCount; i++)
{
Console.WriteLine(resultImageData[i]);
}
Console.WriteLine("Writing data to file...");
// CsvData.WriteToDisk("..\\..\\..\\output.csv", resultImageData);
TiffData.WriteToDisk(resultImageData, _saveFilename, _imageDimensionX, _imageDimensionY);
Bitmap bitmap = new Bitmap(_imageDimensionX, _imageDimensionY);
float max = resultImageData.Max();
float scale = 255/(float)max;
// for (int r = 0; r < _imageDimensionY; r++)
// {
// for (int c = 0; c < _imageDimensionX; c++)
// {
// float value = resultImageData[c*(r + 1)];
// Color newColor = Color.FromArgb((int)(value * scale), (int)(value * scale), (int)(value * scale));
// bitmap.SetPixel(c,r, newColor);
// }
// }
ushort[] ushortdata = new ushort[resultImageData.Length];
for (int i = 0; i < resultImageData.Length; i++)
{
ushortdata[i] = (ushort)resultImageData[i];
}
uint[] convertGray16ToRgb = ConvertGray16ToRGB(ushortdata, 16);
byte[] bytes = new byte[convertGray16ToRgb.Length * 4];
//
// int[] resultImageData2 = new int[resultImageData.Length];
//
for (int index = 0; index < convertGray16ToRgb.Length; index++)
{
// resultImageData2[index] = (int)(scale*resultImageData[index]);
byte[] bytes1 = BitConverter.GetBytes(convertGray16ToRgb[index]);
bytes[index] = bytes1[0];
bytes[4 * index + 1] = bytes1[1];
bytes[4 * index + 2] = bytes1[2];
bytes[4 * index + 3] = bytes1[3];
}
//
// for (int r = 0; r < _imageDimensionY; r++)
// {
// for (int c = 0; c < _imageDimensionX; c++)
// {
// float value = resultImageData2[c*(r + 1)];
// Color newColor = Color.FromArgb((int)(value), (int)(value), (int)(value));
// bitmap.SetPixel(c,r, newColor);
// }
// }
// bitmap.Save("c:\\temp.bmp");
using (MemoryStream ms = new MemoryStream(bytes))
{
Image image = Bitmap.FromStream(ms);
image.Save("c:\\temp.bmp");
}
Console.WriteLine("Writing data to file... done");
stopwatch.Stop();
Console.WriteLine("Convolve fluophores duration:\n\t" + stopwatch.Elapsed);
Console.WriteLine("Computing... done");
}
public static void Test()
{
string source = File.ReadAllText("MonteCarloSimulate.cl");
//Choose Device
ComputePlatform platform = ComputePlatform.Platforms[0];
ComputeDevice device = platform.QueryDevices()[0];
ComputeContextPropertyList properties =
new ComputeContextPropertyList(platform);
//Setup of stuff on our side
ComputeContext context = new ComputeContext(ComputeDeviceTypes.All,
properties, null, IntPtr.Zero);
//Build the program, which gets us the kernel
ComputeProgram program = new ComputeProgram(context, source);
program.Build(null, null, null, IntPtr.Zero);
//can use notify as the 3rd command... if you want this to be non-blocking
ComputeKernel kernel = program.CreateKernel("MonteCarloSimulate");
//Create arguments
int sideSize = 4096;
int[] inMatrixA = new int[sideSize * sideSize];
int[] inMatrixB = new int[sideSize * sideSize];
int[] outMatrixC = new int[sideSize * sideSize];
Random random = new Random((int)DateTime.Now.Ticks);
if (sideSize <= 32)
for (int y = 0; y < sideSize; y++)
for (int x = 0; x < sideSize; x++)
{
inMatrixA[y * sideSize + x] = random.Next(3);
inMatrixB[y * sideSize + x] = random.Next(3);
outMatrixC[y * sideSize + x] = 0;
}
ComputeBuffer<int> bufferMatrixA = new ComputeBuffer<int>(context,
ComputeMemoryFlags.UseHostPointer, inMatrixA);
ComputeBuffer<int> bufferMatrixB = new ComputeBuffer<int>(context,
ComputeMemoryFlags.UseHostPointer, inMatrixB);
ComputeBuffer<int> bufferMatrixC = new ComputeBuffer<int>(context,
ComputeMemoryFlags.UseHostPointer, outMatrixC);
long localWorkSize = Math.Min(device.MaxComputeUnits, sideSize);
//Sets arguments
kernel.SetMemoryArgument(0, bufferMatrixA);
kernel.SetMemoryArgument(1, bufferMatrixB);
kernel.SetMemoryArgument(2, bufferMatrixC);
kernel.SetLocalArgument(3, sideSize * 2);
kernel.SetValueArgument<int>(4, sideSize);
//kernel.SetLocalArgument(1, localWorkSize);
string offset = " ";
for (int x = 0; x < sideSize; x++)
offset += " ";
if (sideSize <= 32)
for (int y = 0; y < sideSize; y++)
{
Console.Write(offset);
for (int x = 0; x < sideSize; x++)
Console.Write(inMatrixA[y * sideSize + x] + " ");
Console.WriteLine();
}
//Runs commands
ComputeCommandQueue commands = new ComputeCommandQueue(context,
context.Devices[0], ComputeCommandQueueFlags.None);
long executionTime = DateTime.Now.Ticks;
//Execute kernel
//globalWorkSize in increments of localWorkSize (max of device.MaxComputeUnits or kernel.GetWorkGroupSize())
commands.Execute(kernel, null,
new long[] { Math.Min(sideSize, 16), Math.Min(sideSize, 16) },
new long[] { localWorkSize, 1 }, null);
//globalWorkSize can be any size
//localWorkSize product much not be greater than device.MaxComputeUnits
//and it must not be greater than kernel.GetWorkGroupSize()
//ESSENTIALLY, the program iterates through globalWorkSize
//in increments of localWorkSize. Both are multidimensional,
//but this just saves us the time of doing that
//(1 dimension can be put to multiple if the max dimension lengths
//are known very easily with remainder).
//Also, you should probably use this
//kernel.GetPreferredWorkGroupSizeMultiple(device);
commands.Finish();
commands.ReadFromBuffer(bufferMatrixC, ref outMatrixC, true, null);
commands.Finish();
executionTime = DateTime.Now.Ticks - executionTime;
GC.Collect();
program.Dispose();
Console.WriteLine();
if (sideSize <= 32)
for (int y = 0; y < sideSize; y++)
{
for (int x = 0; x < sideSize; x++)
Console.Write(inMatrixB[y * sideSize + x] + " ");
Console.Write(" ");
for (int x = 0; x < sideSize; x++)
Console.Write(outMatrixC[y * sideSize + x] + " ");
Console.WriteLine();
}
int testY = random.Next(sideSize);
int testX = random.Next(sideSize);
int sum = 0;
for (int q = 0; q < sideSize; q++)
sum += inMatrixA[q * sideSize + testX] *
inMatrixB[testY * sideSize + q];
Console.WriteLine(sum == outMatrixC[testY * sideSize + testX]);
Console.WriteLine(executionTime / 10000.0);
}
private static void CoreRender(ComputeMemory buffer, ComputeCommandQueue queue, IEnumerable<ComputeKernel> kernels, Vector4 position, Vector4 lookat, Vector4 up, int frame, float fov, int slowRenderCount, float focalDistance, int width, int height, long[] globalSize, long[] localSize)
{
foreach (var kernel in kernels)
{
kernel.SetMemoryArgument(0, buffer);
kernel.SetValueArgument(1, width);
kernel.SetValueArgument(2, height);
kernel.SetValueArgument(3, position);
kernel.SetValueArgument(4, lookat);
kernel.SetValueArgument(5, up);
kernel.SetValueArgument(6, frame);
kernel.SetValueArgument(7, fov);
kernel.SetValueArgument(8, slowRenderCount);
kernel.SetValueArgument(9, focalDistance);
queue.Execute(kernel, LaunchSize, globalSize, localSize, null);
}
}
static void Main(string[] args)
{
#region
const string programName = "Prime Number";
Stopwatch stopWatch = new Stopwatch();
string clProgramSource = KernelProgram();
Console.WriteLine("Environment OS:");
Console.WriteLine("-----------------------------------------");
Console.WriteLine(Environment.OSVersion);
#endregion
if (ComputePlatform.Platforms.Count == 0)
{
Console.WriteLine("No OpenCL Platforms are availble!");
}
else
{
#region 1
// step 1 choose the first available platform
ComputePlatform platform = ComputePlatform.Platforms[0];
// output the basic info
BasicInfo(platform);
Console.WriteLine("Program: " + programName);
Console.WriteLine("-----------------------------------------");
#endregion
//Cpu 10 seconds Gpu 28 seconds
int count = 64;
int[] output_Z = new int[count * count * count];
int[] input_X = new int[count * count * count];
for (int x = 0; x < count * count * count; x++)
{
input_X[x] = x;
}
#region 2
// step 2 create context for that platform and all devices
ComputeContextPropertyList properties = new ComputeContextPropertyList(platform);
ComputeContext context = new ComputeContext(platform.Devices, properties, null, IntPtr.Zero);
// step 3 create and build program
ComputeProgram program = new ComputeProgram(context, clProgramSource);
program.Build(platform.Devices, null, null, IntPtr.Zero);
#endregion
// step 4 create memory objects
ComputeBuffer<int> a = new ComputeBuffer<int>(context, ComputeMemoryFlags.ReadOnly | ComputeMemoryFlags.CopyHostPointer, input_X);
ComputeBuffer<int> z = new ComputeBuffer<int>(context, ComputeMemoryFlags.WriteOnly, output_Z.Length);
// step 5 create kernel object with same kernel programe name VectorAdd
ComputeKernel kernel = program.CreateKernel("PrimeNumber");
// step 6 set kernel arguments
//kernel.SetMemoryArgument(0, a);
kernel.SetMemoryArgument(0, a);
kernel.SetMemoryArgument(1, z);
ComputeEventList eventList = new ComputeEventList();
//for (int j = 0; j < context.Devices.Count; j++)
// query available devices n,...,1,0. cpu first then gpu
for (int j = context.Devices.Count-1; j > -1; j--)
{
#region 3
stopWatch.Start();
// step 7 create command queue on that context on that device
ComputeCommandQueue commands = new ComputeCommandQueue(context, context.Devices[j], ComputeCommandQueueFlags.None);
// step 8 run the kernel program
commands.Execute(kernel, null, new long[] { count, count, count }, null, eventList);
//Application.DoEvents();
#endregion
// step 9 read results
commands.ReadFromBuffer(z, ref output_Z, false, eventList);
#region 4
commands.Finish();
string fileName = "C:\\primenumber\\PrimeNumberGPU.txt";
StreamWriter file = new StreamWriter(fileName, true);
FileInfo info = new FileInfo(fileName);
long fs = info.Length;
// 1 MegaByte = 1.049e+6 Byte
int index = 1;
if (fs == 1.049e+6)
{
fileName = "C:\\primenumber\\PrimeNumberGPU" + index.ToString() + ".txt";
file = new System.IO.StreamWriter(fileName, true);
index++;
}
#endregion
for (uint xx = 0; xx < count * count * count; xx++)
{
if (output_Z[xx] != 0 && output_Z[xx] != 1)
{
Console.WriteLine(output_Z[xx]);
file.Write(output_Z[xx]);
file.Write("x");
}
}
#region 5
file.Close();
stopWatch.Stop();
ComputeCommandProfilingInfo start = ComputeCommandProfilingInfo.Started;
ComputeCommandProfilingInfo end = ComputeCommandProfilingInfo.Ended;
double time = 10e-9 * (end - start);
//Console.WriteLine("Nanosecond: " + time);
TimeSpan ts = stopWatch.Elapsed;
string elapsedTime = String.Format("{0:00}:{1:00}:{2:00}.{3:00}", ts.Hours, ts.Minutes, ts.Seconds, ts.Milliseconds);
Console.WriteLine(context.Devices[j].Name.Trim() + " Elapsed Time " + elapsedTime);
Console.WriteLine("-----------------------------------------");
#endregion
}
Console.ReadLine();
}
}
public static void CallOpenCL(int[,] libertyGroups,
int[,] groupNumbers, int x, int y,
int[] surroundingLibs, ref int emptySurroundings,
int ourSgn, ref int duplicateGroups)
{
//Create arguments
//Does not split yet
//int[,] libertyGroups,
//int[,] groupNumbers,
//int x,
//int y,
//int[] surroundingLibs,
//ref int emptySurroundings,
//ref int duplicateGroups,
//int ourSgn,
//We have to map 2 dimension to 1 dimension
//Set arguments
ComputeBuffer<int> libertyGroupsIn = new ComputeBuffer<int>(openCLContext, ComputeMemoryFlags.UseHostPointer, twoDtoOneD(libertyGroups));
openCLKernel.SetMemoryArgument(0, libertyGroupsIn);
ComputeBuffer<int> groupNumbersIn = new ComputeBuffer<int>(openCLContext, ComputeMemoryFlags.UseHostPointer, twoDtoOneD(groupNumbers));
openCLKernel.SetMemoryArgument(1, groupNumbersIn);
openCLKernel.SetValueArgument<int>(2, x);
openCLKernel.SetValueArgument<int>(3, y);
ComputeBuffer<int> surroundingLibsIn = new ComputeBuffer<int>(openCLContext, ComputeMemoryFlags.UseHostPointer, surroundingLibs);
openCLKernel.SetMemoryArgument(4, surroundingLibsIn);
int[] emptySurroundRef = new int[1];
ComputeBuffer<int> emptySurroundRefIn = new ComputeBuffer<int>(openCLContext, ComputeMemoryFlags.UseHostPointer, emptySurroundRef);
openCLKernel.SetMemoryArgument(5, emptySurroundRefIn);
int[] duplicateGroupsRef = new int[1];
ComputeBuffer<int> duplicateGroupsRefIn = new ComputeBuffer<int>(openCLContext, ComputeMemoryFlags.UseHostPointer, duplicateGroupsRef);
openCLKernel.SetMemoryArgument(6, duplicateGroupsRefIn);
openCLKernel.SetValueArgument<int>(7, ourSgn);
//long localWorkSize = Math.Min(openCLDevice.MaxComputeUnits, sideSize);
//Display input data
//Runs commands
ComputeCommandQueue commands = new ComputeCommandQueue(openCLContext,
openCLContext.Devices[0], ComputeCommandQueueFlags.None);
long executionTime = DateTime.Now.Ticks;
//Execute kernel
//globalWorkSize in increments of localWorkSize (max of device.MaxComputeUnits or kernel.GetWorkGroupSize())
commands.Execute(openCLKernel, null,
new long[] { 1 },
new long[] { 1 }, null);
//Also, you should probably use this
//kernel.GetPreferredWorkGroupSizeMultiple(device);
commands.Finish();
//int[] surroundingLibs,
//ref int emptySurroundings,
//ref int duplicateGroups,
//Read output data
commands.ReadFromBuffer(surroundingLibsIn, ref surroundingLibs, true, null);
commands.ReadFromBuffer(emptySurroundRefIn, ref emptySurroundRef, true, null); emptySurroundings = emptySurroundRef[0];
commands.ReadFromBuffer(duplicateGroupsRefIn, ref duplicateGroupsRef, true, null); duplicateGroups = duplicateGroupsRef[0];
//We could set blocking to false on reads and then read them all back in then, we could (possiblity) gain some performance
//by telling it that commands can be executed out of order and then by queuing them up and calling Finish
commands.Finish();
executionTime = DateTime.Now.Ticks - executionTime;
GC.Collect();
// openCLProgram.Dispose();
//display output data
//Test are done by our caller now
Console.WriteLine(executionTime / 10000.0);
}
public static void Calculate(List<Calculation> calculations)
{
Stopwatch s = new Stopwatch();
s.Start();
int count = calculations.Count;
IntVec2[] p_p = new IntVec2[count];
IntVec2[] p_a = new IntVec2[count];
IntVec2[] p_b = new IntVec2[count];
IntVec2[] p_c = new IntVec2[count];
FloatVec3[] c = new FloatVec3[count];
int[] c_valid = new int[count];
Parallel.For(0, count, i =>
{
var calc = calculations[i];
p_p[i] = new IntVec2(calc.P);
p_a[i] = new IntVec2(calc.A);
p_b[i] = new IntVec2(calc.B);
p_c[i] = new IntVec2(calc.C);
});
mark(s, "memory init");
ComputeBuffer<IntVec2> _p_p = new ComputeBuffer<IntVec2>(context, ComputeMemoryFlags.ReadOnly | ComputeMemoryFlags.CopyHostPointer, p_p);
ComputeBuffer<IntVec2> _p_a = new ComputeBuffer<IntVec2>(context, ComputeMemoryFlags.ReadOnly | ComputeMemoryFlags.CopyHostPointer, p_a);
ComputeBuffer<IntVec2> _p_b = new ComputeBuffer<IntVec2>(context, ComputeMemoryFlags.ReadOnly | ComputeMemoryFlags.CopyHostPointer, p_b);
ComputeBuffer<IntVec2> _p_c = new ComputeBuffer<IntVec2>(context, ComputeMemoryFlags.ReadOnly | ComputeMemoryFlags.CopyHostPointer, p_c);
ComputeBuffer<FloatVec3> _c = new ComputeBuffer<FloatVec3>(context, ComputeMemoryFlags.WriteOnly, c.Length);
ComputeBuffer<int> _c_valid = new ComputeBuffer<int>(context, ComputeMemoryFlags.WriteOnly, c_valid.Length);
mark(s, "memory buffer init");
ComputeKernel kernel = program.CreateKernel("Barycentric");
kernel.SetMemoryArgument(0, _p_p);
kernel.SetMemoryArgument(1, _p_a);
kernel.SetMemoryArgument(2, _p_b);
kernel.SetMemoryArgument(3, _p_c);
kernel.SetMemoryArgument(4, _c);
kernel.SetMemoryArgument(5, _c_valid);
mark(s, "memory init 2");
ComputeEventList eventList = new ComputeEventList();
ComputeCommandQueue commands = new ComputeCommandQueue(context, context.Devices[0], ComputeCommandQueueFlags.None);
commands.Execute(kernel, null, new long[] { count }, null, eventList);
mark(s, "execute");
commands.ReadFromBuffer(_c, ref c, false, eventList);
commands.ReadFromBuffer(_c_valid, ref c_valid, false, eventList);
commands.Finish();
mark(s, "read 1");
Parallel.For(0, count, i =>
{
var calc = calculations[i];
calc.Coords = new BarycentricCoordinates(c[i].U,c[i].V,c[i].W);
if (c_valid[i] == 1)
{
lock (calc.Tri)
calc.Tri.Points.Add(new DrawPoint(calc.Coords, calc.P));
}
});
mark(s, "read 2");
// cleanup commands
commands.Dispose();
// cleanup events
foreach (ComputeEventBase eventBase in eventList)
{
eventBase.Dispose();
}
eventList.Clear();
// cleanup kernel
kernel.Dispose();
_p_p.Dispose();
_p_a.Dispose();
_p_b.Dispose();
_p_c.Dispose();
_c.Dispose();
_c_valid.Dispose();
mark(s, "dispose");
}
public void Render(ComputeBuffer<Vector4> buffer, ComputeCommandQueue queue, IParameterSet parameters,
Size windowSize, int numBlocks, Size coordinates, int bufferWidth = 0)
{
lock (_kernelLock)
{
if (_kernel == null)
return;
var size = new long[] { windowSize.Width, windowSize.Height };
var localSize = Threadsize(queue);
var offset = new long[size.Length];
var offsetCoords = new long[] { coordinates.Width, coordinates.Height };
if (numBlocks > 0)
{
for (var i = 0; i < size.Length; i++)
size[i] = numBlocks * localSize[i];
for (var i = 0; i < size.Length; i++)
offset[i] = size[i] * offsetCoords[i];
}
var globalSize = GlobalLaunchsizeFor(localSize, size);
var kernelNumArgs = 0;
_kernel.SetMemoryArgument(kernelNumArgs++, buffer);
_kernel.SetValueArgument(kernelNumArgs++, bufferWidth);
_kernel.SetValueArgument(kernelNumArgs++, windowSize.Width);
_kernel.SetValueArgument(kernelNumArgs++, windowSize.Height);
parameters.ApplyToKernel(_kernel, _useDouble, ref kernelNumArgs);
queue.Execute(_kernel, offset, globalSize, localSize, null);
}
}
public void Run(ComputeContext context, TextWriter log)
{
try
{
// Create the arrays and fill them with random data.
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);
}
// Create the input buffers and fill them with data from the arrays.
// Access modifiers should match those in a kernel.
// CopyHostPointer means the buffer should be filled with the data provided in the last argument.
ComputeBuffer<float> a = new ComputeBuffer<float>(context, ComputeMemoryFlags.ReadOnly | ComputeMemoryFlags.CopyHostPointer, arrA);
ComputeBuffer<float> b = new ComputeBuffer<float>(context, ComputeMemoryFlags.ReadOnly | ComputeMemoryFlags.CopyHostPointer, arrB);
// The output buffer doesn't need any data from the host. Only its size is specified (arrC.Length).
ComputeBuffer<float> c = new ComputeBuffer<float>(context, ComputeMemoryFlags.WriteOnly, arrC.Length);
// Create and build the opencl program.
program = new ComputeProgram(context, clProgramSource);
program.Build(null, null, null, IntPtr.Zero);
// Create the kernel function and set its arguments.
ComputeKernel kernel = program.CreateKernel("VectorAdd");
kernel.SetMemoryArgument(0, a);
kernel.SetMemoryArgument(1, b);
kernel.SetMemoryArgument(2, c);
// Create the event wait list. An event list is not really needed for this example but it is important to see how it works.
// Note that events (like everything else) consume OpenCL resources and creating a lot of them may slow down execution.
// For this reason their use should be avoided if possible.
ComputeEventList eventList = new ComputeEventList();
// Create the command queue. This is used to control kernel execution and manage read/write/copy operations.
ComputeCommandQueue commands = new ComputeCommandQueue(context, context.Devices[0], ComputeCommandQueueFlags.None);
// Execute the kernel "count" times. After this call returns, "eventList" will contain an event associated with this command.
// If eventList == null or typeof(eventList) == ReadOnlyCollection<ComputeEventBase>, a new event will not be created.
commands.Execute(kernel, null, new long[] { count }, null, eventList);
// Read back the results. If the command-queue has out-of-order execution enabled (default is off), ReadFromBuffer
// will not execute until any previous events in eventList (in our case only eventList[0]) are marked as complete
// by OpenCL. By default the command-queue will execute the commands in the same order as they are issued from the host.
// eventList will contain two events after this method returns.
commands.ReadFromBuffer(c, ref arrC, false, eventList);
// A blocking "ReadFromBuffer" (if 3rd argument is true) will wait for itself and any previous commands
// in the command queue or eventList to finish execution. Otherwise an explicit wait for all the opencl commands
// to finish has to be issued before "arrC" can be used.
// This explicit synchronization can be achieved in two ways:
// 1) Wait for the events in the list to finish,
//eventList.Wait();
// 2) Or simply use
commands.Finish();
// Print the results to a log/console.
for (int i = 0; i < count; i++)
log.WriteLine("{0} + {1} = {2}", arrA[i], arrB[i], arrC[i]);
// cleanup commands
commands.Dispose();
// cleanup events
foreach (ComputeEventBase eventBase in eventList)
{
eventBase.Dispose();
}
eventList.Clear();
// cleanup kernel
kernel.Dispose();
// cleanup program
program.Dispose();
// cleanup buffers
a.Dispose();
b.Dispose();
c.Dispose();
}
catch (Exception e)
{
log.WriteLine(e.ToString());
}
}
public String SearchPassword (byte[] hash, HashType type, int maxLength, String[] keySpace)
{
if (type != HashType.MD5) {
throw new NotImplementedException ("sums other than MD5 not supported");
}
if (maxLength > 6) {
throw new NotImplementedException ("doesn't support longer passwords than 7");
}
var joinedKeySpace = new List<byte> ();
foreach (var k in keySpace) {
if (k.Length > 1) {
throw new NotImplementedException ("doesn't support longer keyspaces than 1");
}
joinedKeySpace.AddRange (Encoding.ASCII.GetBytes (k));
}
byte[] resultData = new byte[20];
byte[] keyspaceJoined = joinedKeySpace.ToArray ();
var resultBuffer = new ComputeBuffer<byte> (Context, ComputeMemoryFlags.WriteOnly | ComputeMemoryFlags.CopyHostPointer, resultData);
var hashBuffer = new ComputeBuffer<byte> (Context, ComputeMemoryFlags.ReadOnly | ComputeMemoryFlags.CopyHostPointer, hash);
var keyspaceBuffer = new ComputeBuffer<byte> (Context, ComputeMemoryFlags.ReadOnly | ComputeMemoryFlags.CopyHostPointer, keyspaceJoined);
var passLenBuffer = new ComputeBuffer<byte> (Context, ComputeMemoryFlags.WriteOnly, 1);
var flagBuffer = new ComputeBuffer<int> (Context, ComputeMemoryFlags.None, 1);
Kernel.SetMemoryArgument (0, hashBuffer);
Kernel.SetMemoryArgument (1, keyspaceBuffer);
Kernel.SetMemoryArgument (2, resultBuffer);
Kernel.SetMemoryArgument (3, passLenBuffer);
Kernel.SetMemoryArgument (4, flagBuffer);
// execute kernel
var queue = new ComputeCommandQueue (Context, Device, ComputeCommandQueueFlags.None);
long firstDim = joinedKeySpace.Count;
var globalWorksize = new long[] { firstDim, 57 * 57, 57 * 57 };
queue.Execute (Kernel, new long[] { 0, 0, 0 }, globalWorksize, null, null);
byte[] passLen = new byte[1];
queue.ReadFromBuffer (resultBuffer, ref resultData, true, null);
queue.ReadFromBuffer (passLenBuffer, ref passLen, true, null);
String password = null;
if (passLen [0] > 0) {
logger.Info ("pass len {0}", passLen [0]);
password = Encoding.ASCII.GetString (resultData, 0, passLen [0]);
logger.Info ("Found password: \"{0}\"", password);
} else {
logger.Info ("Password not found.");
}
queue.Finish ();
return password;
}
public void Run(ComputeContext context, TextWriter log)
{
try
{
// Create the arrays and fill them with random data.
int count = 640*480; //
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);
}
// Create the input buffers and fill them with data from the arrays.
// Access modifiers should match those in a kernel.
// CopyHostPointer means the buffer should be filled with the data provided in the last argument.
program = new ComputeProgram(context, clProgramSource);
program.Build(null, null, null, IntPtr.Zero);
ComputeBuffer<float> a = new ComputeBuffer<float>(context, ComputeMemoryFlags.ReadOnly | ComputeMemoryFlags.CopyHostPointer, arrA);
//ComputeBuffer<float> b = new ComputeBuffer<float>(context, ComputeMemoryFlags.ReadOnly | ComputeMemoryFlags.CopyHostPointer, arrB);
// The output buffer doesn't need any data from the host. Only its size is specified (arrC.Length).
ComputeBuffer<float> c = new ComputeBuffer<float>(context, ComputeMemoryFlags.WriteOnly, arrC.Length);
// Create and build the opencl program.
// Create the kernel function and set its arguments.
ComputeKernel kernel = program.CreateKernel("CompareGPUCPU");
DateTime ExecutionStartTime; //Var will hold Execution Starting Time
DateTime ExecutionStopTime;//Var will hold Execution Stopped Time
TimeSpan ExecutionTime;//Var will count Total Execution Time-Our Main Hero
ComputeCommandQueue commands = new ComputeCommandQueue(context, context.Devices[0], ComputeCommandQueueFlags.None);
ExecutionStartTime = DateTime.Now; //Gets the system Current date time expressed as local time
int repeatTimes = 100;
for (int repeatCounter = 0; repeatCounter < repeatTimes; repeatCounter++)
{
kernel.SetMemoryArgument(0, a);
//kernel.SetMemoryArgument(1, b);
//kernel.SetMemoryArgument(2, c);
kernel.SetMemoryArgument(1, c);
// Create the event wait list. An event list is not really needed for this example but it is important to see how it works.
// Note that events (like everything else) consume OpenCL resources and creating a lot of them may slow down execution.
// For this reason their use should be avoided if possible.
//ComputeEventList eventList = new ComputeEventList();
// Create the command queue. This is used to control kernel execution and manage read/write/copy operations.
// Execute the kernel "count" times. After this call returns, "eventList" will contain an event associated with this command.
// If eventList == null or typeof(eventList) == ReadOnlyCollection<ComputeEventBase>, a new event will not be created.
//commands.Execute(kernel, null, new long[] { count }, null, eventList);
commands.Execute(kernel, null, new long[] { count }, null, null);
// Read back the results. If the command-queue has out-of-order execution enabled (default is off), ReadFromBuffer
// will not execute until any previous events in eventList (in our case only eventList[0]) are marked as complete
// by OpenCL. By default the command-queue will execute the commands in the same order as they are issued from the host.
// eventList will contain two events after this method returns.
//commands.ReadFromBuffer(c, ref arrC, false, eventList);
commands.ReadFromBuffer(c, ref arrC, false, null);
// A blocking "ReadFromBuffer" (if 3rd argument is true) will wait for itself and any previous commands
// in the command queue or eventList to finish execution. Otherwise an explicit wait for all the opencl commands
// to finish has to be issued before "arrC" can be used.
// This explicit synchronization can be achieved in two ways:
// 1) Wait for the events in the list to finish,
//eventList.Wait();
// 2) Or simply use
commands.Finish();
}
ExecutionStopTime = DateTime.Now;
ExecutionTime = ExecutionStopTime - ExecutionStartTime;
double perTaskTime = ExecutionTime.TotalMilliseconds / repeatTimes;
log.WriteLine("Use {0} ms using GPU", perTaskTime);
// Do that using CPU
/*
ExecutionStartTime = DateTime.Now; //Gets the system Current date time expressed as local time
for (int repeatCounter = 0; repeatCounter < repeatTimes; repeatCounter++)
{
for (int i = 0; i < count; i++)
{
//arrC[i] = arrA[i] + arrB[i];
int j;
for (j = 0; j < 330 * 10; j++)
arrC[i] = arrA[i] + j;
}
}
ExecutionStopTime = DateTime.Now;
ExecutionTime = ExecutionStopTime - ExecutionStartTime;
perTaskTime = ExecutionTime.TotalMilliseconds / repeatTimes;
log.WriteLine("Use {0} ms using CPU", ExecutionTime.TotalMilliseconds.ToString());
*/
log.WriteLine("arrA[0]:{0}, arrC[0]:{1}", arrA[0], arrC[0]);
}
catch (Exception e)
{
log.WriteLine(e.ToString());
}
}
public unsafe void EndSend()
{
for (int i = 0; i < points.Count; i++)
{
inx[i].x = (float)points[i].Item3.Real;
inx[i].y = (float)points[i].Item3.Imaginary;
inc[i].x = (float)points[i].Item4.Real;
inc[i].y = (float)points[i].Item4.Imaginary;
}
_krnl.SetMemoryArgument(0, x);
_krnl.SetMemoryArgument(1, c);
for (int i = 0; i < _ld.Count; i++)
{
_krnl.SetMemoryArgument(2 + i, outp[i]);
}
ComputeCommandQueue command = new ComputeCommandQueue(_context, _context.Devices[0], ComputeCommandQueueFlags.None);
command.WriteToBuffer(inx, x, false, null);
command.WriteToBuffer(inc, c, false, null);
command.Execute(_krnl, null, new long[] { points.Count }, null, null);
for (int i = 0; i < _ld.Count; i++)
command.ReadFromBuffer(outp[i], ref opl[i], false, null);
command.Finish();
output = new Queue<Tuple<int, int, List<ProcessLayer>>>();
for (int i = 0; i < points.Count; i++)
{
List<ProcessLayer> pl = new List<ProcessLayer>();
for (int ii = 0; ii < _ld.Count; ii++)
{
ProcessLayer p = _ld[ii].Clone();
p.c_active = opl[ii][i].c_active != 0;
p.c_calc = opl[ii][i].c_calc;
p.c_cmean = opl[ii][i].c_cmean;
p.c_cvariance = opl[ii][i].c_cvariance;
p.c_cvarsx = opl[ii][i].c_cvarsx;
p.c_isin = opl[ii][i].c_isin != 0;
p.c_n = opl[ii][i].c_n;
p.c_old2x = new Complex(opl[ii][i].c_old2x.x,opl[ii][i].c_old2x.y);
p.c_oldx = new Complex(opl[ii][i].c_oldx.x,opl[ii][i].c_oldx.y);
p.c_resn = opl[ii][i].c_resn;
p.c_resx = new Complex(opl[ii][i].c_resx.x,opl[ii][i].c_resx.y);
p.c_x = new Complex(opl[ii][i].c_x.x,opl[ii][i].c_x.y);
pl.Add(p);
}
output.Enqueue(Tuple.Create(points[i].Item1, points[i].Item2, pl));
}
}
/// <summary>Execute this kernel</summary>
/// <param name="CQ">Command queue to use</param>
/// <param name="Arguments">Arguments of the kernel function</param>
/// <param name="GlobalWorkSize">Array of maximum index arrays. Total work-items = product(max[i],i+0..n-1), n=max.Length</param>
/// <param name="events">Event of this command</param>
public void Execute(ComputeCommandQueue CQ, CLCalc.Program.MemoryObject[] Arguments, int[] GlobalWorkSize, ICollection<ComputeEventBase> events)
{
SetArguments(Arguments);
long[] globWSize=new long[GlobalWorkSize.Length];
for (int i=0;i<globWSize.Length;i++) globWSize[i]=GlobalWorkSize[i];
CQ.Execute(kernel, null, globWSize, null, events);
}
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");
}
/// <summary>Execute this kernel</summary>
/// <param name="CQ">Command queue to use</param>
/// <param name="Arguments">Arguments of the kernel function</param>
/// <param name="GlobalWorkSize">Array of maximum index arrays. Total work-items = product(max[i],i+0..n-1), n=max.Length</param>
/// <param name="LocalWorkSize">Local work sizes</param>
/// <param name="events">Event of this command</param>
public void Execute(ComputeCommandQueue CQ, CLCalc.Program.MemoryObject[] Arguments, int[] GlobalWorkSize, int[] LocalWorkSize, ICollection<ComputeEventBase> events)
{
SetArguments(Arguments);
if (LocalWorkSize != null && GlobalWorkSize.Length != LocalWorkSize.Length) throw new Exception("Global and local work size must have same dimension");
long[] globWSize = new long[GlobalWorkSize.Length];
for (int i = 0; i < globWSize.Length; i++) globWSize[i] = GlobalWorkSize[i];
long[] locWSize = null;
if (LocalWorkSize != null)
{
locWSize = new long[LocalWorkSize.Length];
for (int i = 0; i < locWSize.Length; i++) locWSize[i] = LocalWorkSize[i];
}
CQ.Execute(kernel, null, globWSize, locWSize, events);
}
