//[Test]
public void TestCGSolver()
{
Stopwatch sw = new Stopwatch();
float one = 1.0f;
float zero = 0.0f;
_hiMatrixMN = new float[N * N];
_hoVectorN = new float[N];
CreateDiagonalMatrix(_hiMatrixMN, N, 6);
_hiVectorN = new float[N];
_hiVectorN2 = new float[N];
FillBuffer(_hiVectorN2, 6);
_diMatrixMN = _gpu.CopyToDevice(_hiMatrixMN);
_diVectorN = _gpu.Allocate(_hiVectorN);
_diVectorN2 = _gpu.CopyToDevice(_hiVectorN2);
_diPerRow = _gpu.Allocate <int>(N);
_diVectorP = _gpu.Allocate <float>(N);
_diVectorAX = _gpu.Allocate <float>(N);
int nnz = _sparse.NNZ(N, N, _diMatrixMN, _diPerRow);
_diCSRVals = _gpu.Allocate <float>(nnz);
_diCSRCols = _gpu.Allocate <int>(nnz);
_diCSRRows = _gpu.Allocate <int>(N + 1);
_sparse.Dense2CSR(N, N, _diMatrixMN, _diPerRow, _diCSRVals, _diCSRRows, _diCSRCols);
sw.Start();
SolveResult result = _solver.CG(N, nnz, _diCSRVals, _diCSRRows, _diCSRCols, _diVectorN, _diVectorN2, _diVectorP, _diVectorAX, 0.01f, 1000);
long time = sw.ElapsedMilliseconds;
_sparse.CSRMV(N, N, nnz, ref one, _diCSRVals, _diCSRRows, _diCSRCols, _diVectorN, ref zero, _diVectorN2);
_gpu.CopyFromDevice(_diVectorN2, _hoVectorN);
float maxError = 0.0f;
for (int i = 0; i < N; i++)
{
float error = Math.Abs(_hoVectorN[i] - _hiVectorN2[i]);
if (error > maxError)
{
maxError = error;
}
}
Console.WriteLine("Time : {0} ms", time);
Console.WriteLine("Iterate Count : {0}", result.IterateCount);
Console.WriteLine("Residual : {0}", result.LastError);
Console.WriteLine("max error : {0}", maxError);
_gpu.FreeAll();
}
public void TestDENSE2CSR()
{
int[] cpunnzPerRow;
int cpuNNZ;
CreateDenseMatrixCSR(_hiMatrixMN, M, N, out cpunnzPerRow, out cpuNNZ);
CPUDense2CSR(_hiMatrixMN, M, N, cpuNNZ, out _hoCSRRowsCPU, out _hoCSRColsCPU, out _hoValsCPU);
_gpu.CopyToDevice(_hiMatrixMN, _diMatrixMN);
int nnz = _sparse.NNZ(M, N, _diMatrixMN, _diPerVector);
_hoVals = new double[nnz];
_hoCSRRows = new int[M + 1];
_hoCSRCols = new int[nnz];
_diVals = _gpu.Allocate(_hoVals);
_diCSRRows = _gpu.Allocate(_hoCSRRows);
_diCSRCols = _gpu.Allocate(_hoCSRCols);
_sparse.Dense2CSR(M, N, _diMatrixMN, _diPerVector, _diVals, _diCSRRows, _diCSRCols);
_gpu.CopyFromDevice(_diVals, _hoVals);
_gpu.CopyFromDevice(_diCSRRows, _hoCSRRows);
_gpu.CopyFromDevice(_diCSRCols, _hoCSRCols);
_gpu.Free(_diVals);
_gpu.Free(_diCSRRows);
_gpu.Free(_diCSRCols);
for (int i = 0; i < M + 1; i++)
{
Assert.AreEqual(_hoCSRRowsCPU[i], _hoCSRRows[i]);
}
for (int i = 0; i < nnz; i++)
{
Assert.AreEqual(_hoValsCPU[i], _hoVals[i]);
Assert.AreEqual(_hoCSRColsCPU[i], _hoCSRCols[i]);
}
}
public void Test_SPARSE2_CSRMV()
{
int nnz;
// No transpose
ClearBuffer(hiMatrixMN);
ClearBuffer(hiVectorXN);
ClearBuffer(hiVectorYM);
FillBufferSparse(hiMatrixMN);
FillBuffer(hiVectorXN);
FillBuffer(hiVectorYM);
diMatrixA = _gpu.CopyToDevice(hiMatrixMN);
diVectorXN = _gpu.CopyToDevice(hiVectorXN);
diVectorYM = _gpu.CopyToDevice(hiVectorYM);
diNNZRows = _gpu.Allocate <int>(M);
nnz = _sparse.NNZ(M, N, diMatrixA, diNNZRows);
diVals = _gpu.Allocate <double>(nnz);
diRows = _gpu.Allocate <int>(M + 1);
diCols = _gpu.Allocate <int>(nnz);
_sparse.Dense2CSR(M, N, diMatrixA, diNNZRows, diVals, diRows, diCols);
_sparse.CSRMV(M, N, nnz, ref Alpha, diVals, diRows, diCols, diVectorXN, ref Beta, diVectorYM);
_gpu.CopyFromDevice(diVectorYM, gpuResultM);
for (int i = 0; i < M; i++)
{
double cpuResult = 0.0;
for (int j = 0; j < N; j++)
{
cpuResult += Alpha * hiMatrixMN[GetIndexColumnMajor(i, j, M)] * hiVectorXN[j];
}
cpuResult += Beta * hiVectorYM[i];
Assert.AreEqual(cpuResult, gpuResultM[i]);
}
_gpu.FreeAll();
// Transpose
ClearBuffer(hiMatrixMN);
ClearBuffer(hiVectorXM);
ClearBuffer(hiVectorYN);
FillBufferSparse(hiMatrixMN);
FillBuffer(hiVectorXM);
FillBuffer(hiVectorYN);
diMatrixA = _gpu.CopyToDevice(hiMatrixMN);
diVectorXM = _gpu.CopyToDevice(hiVectorXM);
diVectorYN = _gpu.CopyToDevice(hiVectorYN);
diNNZRows = _gpu.Allocate <int>(M);
nnz = _sparse.NNZ(M, N, diMatrixA, diNNZRows);
diVals = _gpu.Allocate <double>(nnz);
diRows = _gpu.Allocate <int>(M + 1);
diCols = _gpu.Allocate <int>(nnz);
_sparse.Dense2CSR(M, N, diMatrixA, diNNZRows, diVals, diRows, diCols);
_sparse.CSRMV(M, N, nnz, ref Alpha, diVals, diRows, diCols, diVectorXM, ref Beta, diVectorYN, SPARSE.cusparseOperation.Transpose);
_gpu.CopyFromDevice(diVectorYN, gpuResultN);
for (int j = 0; j < N; j++)
{
double cpuResult = 0.0;
for (int i = 0; i < M; i++)
{
cpuResult += Alpha * hiMatrixMN[GetIndexColumnMajor(i, j, M)] * hiVectorXM[i];
}
cpuResult += Beta * hiVectorYN[j];
Assert.AreEqual(cpuResult, gpuResultN[j]);
}
_gpu.FreeAll();
}
