public static void DummyComplexFloatOp(GThread thread, DummyComplexFloat[] result)
{
int x = thread.blockIdx.x;
result[x] = result[x].Add(result[x]);
DummyComplexFloat d = new DummyComplexFloat();
result[0] = d;
}
public static void Execute()
{
CudafyModule km = CudafyModule.TryDeserialize();
if (km == null || !km.TryVerifyChecksums())
{
km = CudafyTranslator.Cudafy(typeof(DummyComplexFloat), typeof(DummyFunctions));
km.Serialize();
}
GPGPU gpu = CudafyHost.GetDevice(CudafyModes.Target);
gpu.LoadModule(km);
bool pass = true;
int i = 0;
// 1D
Console.WriteLine("DummyFunction");
int[] host_array1D = new int[XSIZE];
int[] result_array1D = new int[XSIZE];
int[] dev_array1D = gpu.Allocate<int>(XSIZE);
i = 0;
for (int x = 0; x < XSIZE; x++)
host_array1D[x] = i++;
gpu.CopyToDevice(host_array1D, dev_array1D);
gpu.Launch(XSIZE, 1, "DummyFunction", dev_array1D);
gpu.CopyFromDevice(dev_array1D, result_array1D);
i = 0;
pass = true;
for (int x = 0; x < XSIZE && pass; x++)
{
pass = result_array1D[x] == host_array1D[x] * host_array1D[x] * result_array1D.Rank;
}
Console.WriteLine(pass ? "Pass" : "Fail");
// DummyComplexFloatOp
Console.WriteLine("DummyComplexFloatOp");
DummyComplexFloat[] host_array1DS = new DummyComplexFloat[XSIZE];
DummyComplexFloat[] result_array1DS = new DummyComplexFloat[XSIZE];
for (int x = 0; x < XSIZE; x++)
host_array1DS[x] = new DummyComplexFloat(x * 2, x);
DummyComplexFloat[] dev_array1DS = gpu.CopyToDevice(host_array1DS);
gpu.Launch(XSIZE, 1, "DummyComplexFloatOp", dev_array1DS);
gpu.CopyFromDevice(dev_array1DS, result_array1DS);
i = 0;
pass = true;
for (int x = 0; x < XSIZE && pass; x++)
{
DummyComplexFloat expected = host_array1DS[x].Add(host_array1DS[x]);
DummyComplexFloat res = result_array1DS[x];
pass = res.Real == expected.Real && res.Imag == expected.Imag;
}
Console.WriteLine(pass ? "Pass" : "Fail");
// DummyDummyComplexFloatOp
Console.WriteLine("DummyDummyComplexFloatFunction");
host_array1DS = new DummyComplexFloat[XSIZE];
result_array1DS = new DummyComplexFloat[XSIZE];
for (int x = 0; x < XSIZE; x++)
host_array1DS[x] = new DummyComplexFloat(x * 2, x);
dev_array1DS = gpu.CopyToDevice(host_array1DS);
gpu.Launch(XSIZE, 1, "DummyDummyComplexFloatFunction", dev_array1DS);
gpu.CopyFromDevice(dev_array1DS, result_array1DS);
i = 0;
pass = true;
for (int x = 0; x < XSIZE && pass; x++)
{
DummyComplexFloat expected = host_array1DS[x].Add(host_array1DS[x]);
DummyComplexFloat res = result_array1DS[x];
pass = res.Real == expected.Real && res.Imag == expected.Imag;
}
Console.WriteLine(pass ? "Pass" : "Fail");
gpu.FreeAll();
}
public DummyComplexFloat Add(DummyComplexFloat c)
{
return new DummyComplexFloat(Real + c.Real, Imag + c.Imag);
}
public static void DummyDummyComplexFloatFunction(DummyComplexFloat[] result)
{
for (int i = 0; i < XSIZE; i++)
{
result[i] = result[i].Add(result[i]);
}
}
public static void DummyComplexFloatOp(GThread thread, DummyComplexFloat[] result)
{
int x = thread.blockIdx.x;
result[x] = result[x].Add(result[x]);
DummyComplexFloat d = new DummyComplexFloat();
result[0] = d;
}
public static void Execute()
{
CudafyModule km = CudafyModule.TryDeserialize();
if (km == null || !km.TryVerifyChecksums())
{
km = CudafyTranslator.Cudafy(typeof(DummyComplexFloat), typeof(DummyFunctions));
km.Serialize();
}
GPGPU gpu = CudafyHost.GetDevice(CudafyModes.Target);
gpu.LoadModule(km);
bool pass = true;
int i = 0;
// 1D
Console.WriteLine("DummyFunction");
int[] host_array1D = new int[XSIZE];
int[] result_array1D = new int[XSIZE];
int[] dev_array1D = gpu.Allocate <int>(XSIZE);
i = 0;
for (int x = 0; x < XSIZE; x++)
{
host_array1D[x] = i++;
}
gpu.CopyToDevice(host_array1D, dev_array1D);
gpu.Launch(XSIZE, 1, "DummyFunction", dev_array1D);
gpu.CopyFromDevice(dev_array1D, result_array1D);
i = 0;
pass = true;
for (int x = 0; x < XSIZE && pass; x++)
{
pass = result_array1D[x] == host_array1D[x] * host_array1D[x] * result_array1D.Rank;
}
Console.WriteLine(pass ? "Pass" : "Fail");
// DummyComplexFloatOp
Console.WriteLine("DummyComplexFloatOp");
DummyComplexFloat[] host_array1DS = new DummyComplexFloat[XSIZE];
DummyComplexFloat[] result_array1DS = new DummyComplexFloat[XSIZE];
for (int x = 0; x < XSIZE; x++)
{
host_array1DS[x] = new DummyComplexFloat(x * 2, x);
}
DummyComplexFloat[] dev_array1DS = gpu.CopyToDevice(host_array1DS);
gpu.Launch(XSIZE, 1, "DummyComplexFloatOp", dev_array1DS);
gpu.CopyFromDevice(dev_array1DS, result_array1DS);
i = 0;
pass = true;
for (int x = 0; x < XSIZE && pass; x++)
{
DummyComplexFloat expected = host_array1DS[x].Add(host_array1DS[x]);
DummyComplexFloat res = result_array1DS[x];
pass = res.Real == expected.Real && res.Imag == expected.Imag;
}
Console.WriteLine(pass ? "Pass" : "Fail");
// DummyDummyComplexFloatOp
Console.WriteLine("DummyDummyComplexFloatFunction");
host_array1DS = new DummyComplexFloat[XSIZE];
result_array1DS = new DummyComplexFloat[XSIZE];
for (int x = 0; x < XSIZE; x++)
{
host_array1DS[x] = new DummyComplexFloat(x * 2, x);
}
dev_array1DS = gpu.CopyToDevice(host_array1DS);
gpu.Launch(XSIZE, 1, "DummyDummyComplexFloatFunction", dev_array1DS);
gpu.CopyFromDevice(dev_array1DS, result_array1DS);
i = 0;
pass = true;
for (int x = 0; x < XSIZE && pass; x++)
{
DummyComplexFloat expected = host_array1DS[x].Add(host_array1DS[x]);
DummyComplexFloat res = result_array1DS[x];
pass = res.Real == expected.Real && res.Imag == expected.Imag;
}
Console.WriteLine(pass ? "Pass" : "Fail");
gpu.FreeAll();
}
public DummyComplexFloat Add(DummyComplexFloat c)
{
return(new DummyComplexFloat(Real + c.Real, Imag + c.Imag));
}
